In YuanchenZhu2020/antgreens: Automatic Generation of Vegetable Report

蔬菜产品中农药（兽药）残留风险分析

  

总体残留风险

full_sample <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product")

  r year_range[1]-r year_range[2] 年共抽取样本 r nrow(treated_data) 例，总体合格率为 r full_sample[["qualification_rate_percent"]]%。

各年份残留风险

year <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", year) |>
  factor_dims(year)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year"))

(ref:year) 各年份样本量与合格率

sp_dable(
  year, ref_text = "(ref:year)",
  order = list(list("qualification_rate_percent", "desc"))
)

  表 \@ref(tab:year) 给出了 r year_range[1] - r year_range[2] 年蔬菜类产品年抽检样本量及其合格率，其图形展示见图 \@ref(fig:year-bar-line-echart)。可以看出，r year_range[1] - r year_range[2] 年蔬菜类产品年抽检样本量在 r text_range(year, "sample_size") 之间，合格率稳定在 r text_range(year, "qualification_rate_percent") 之间。

bar_line_echart(year, x_var = "year")

各季度残留风险

quarter <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", quarter) |>
  factor_dims(quarter)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter"))

(ref:quarter) 各季度样本量与合格率

sp_dable(
  quarter, ref_text = "(ref:quarter)",
  order = list(list("qualification_rate_percent", "desc"))
)

  表 \@ref(tab:quarter) 给出了 r year_range[2] - year_range[1] + 1 年内四个季度蔬菜类产品的抽检样本量及其合格率，其图形展示见图 \@ref(fig:quarter-bar-line-echart)。可以看出，四个季度的蔬菜类产品抽检样本量在 r text_range(quarter, "sample_size") 之间，合格率稳定在 r text_range(quarter, "qualification_rate_percent") 之间。

bar_line_echart(quarter, x_var = "quarter")

各省份残留风险

province <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", province)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("province"))

(ref:province) 各省份样本量与合格率

sp_dable(
  province, ref_text = "(ref:province)",
  order = list(list("qualification_rate_percent", "desc"))
)

  表 \@ref(tab:province) 给出了全国 r nrow(province) 个省市自治区蔬菜类产品的抽检样本量及其合格率，各省蔬菜中农药残留超标率的展示见图 \@ref(fig:province-map-echart)。可以看出，r nrow(province) 个省市自治区的蔬菜类产品抽检样本量在 r text_range(province, "sample_size") 之间，合格率稳定在 r text_range(province, "qualification_rate_percent") 之间。

map_echart(
  province |> change_to_defective() |> shorten_province_name(), 
  map_json = cn_province_map_json_2015
)

各蔬菜类别残留风险

category <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", category) |>
  factor_dims(category)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("category"))

(ref:category) 各蔬菜类别样本量与合格率

sp_dable(
  category, ref_text = "(ref:category)",
  order = list(list("qualification_rate_percent", "desc"))
)

  表 \@ref(tab:category) 给出了 r nrow(category) 个蔬菜类别的抽检样本量及其合格率，其图形展示见图 \@ref(fig:category-bar-line-echart) - 图 \@ref(fig:category-scatter-echart)。可以看出，r nrow(category) 个蔬菜类别的抽检样本量在 r text_range(category, "sample_size") 之间，合格率稳定在 r text_range(category, "qualification_rate_percent") 之间。

bar_line_echart(category, x_var = "category", long_x_label = TRUE, x_name_gap = 40, x_label_width = 50)

category |> 
  e_charts(category) |> 
  e_pie(sample_size, roseType = "radius", center = c("25%", "50%"), radius = "45%") |> 
  e_pie(
    qualification_rate_percent, roseType = "radius", center = c("75%", "50%"), radius = "45%"
  ) |> 
  e_tooltip(trigger = "item")

bar_group_echart(
  category, x_var = "category", bar_var = c("qualification_rate_percent", "sample_size"),
  sec_y_axis = TRUE, show_labels = TRUE
)

scatter_echart(
  category, 
  x_var = "sample_size", y_var = "qualification_rate_percent", label_var = "category"
)

各品种残留风险

product <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", product) |>
  factor_dims(product)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("product"))

(ref:product) 各品种样本量与合格率

sp_dable(
  product, ref_text = "(ref:product)",
  order = list(list("qualification_rate_percent", "desc"))
)

  表 \@ref(tab:product) 给出了 r nrow(product) 个蔬菜品种的抽检样本量及其合格率，其图形展示见图 \@ref(fig:product-rose-eplot) - 图 \@ref(fig:product-scatter-echart)。可以看出，r nrow(product) 个蔬菜品种的抽检样本量在 r text_range(product, "sample_size") 之间，合格率稳定在 r text_range(product, "qualification_rate_percent") 之间。

product |> 
  e_charts(product) |> 
  e_pie(sample_size, roseType = "radius", center = c("25%", "50%"), radius = "45%") |>
  e_pie(
    qualification_rate_percent, roseType = "radius", center = c("75%", "50%"), radius = "45%"
  ) |> 
  e_tooltip(trigger = "item")

bar_group_echart(
  product, x_var = "product", bar_var = c("qualification_rate_percent", "sample_size"),
  sec_y_axis = T
)

scatter_echart(
  product, 
  x_var = "sample_size", y_var = "qualification_rate_percent", label_var = "product"
)

“年份-季度”残留风险

year_quarter <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", year, quarter)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter"))

(ref:year-quarter) 各年份各季度样本量与合格率

sp_dable(year_quarter |> factor_dims(year, quarter), ref_text = "(ref:year-quarter)")

  表 \@ref(tab:year-quarter) 给出了 r year_range[1] - r year_range[2] 年每年四个季度的抽检样本量及其合格率，其图形展示见图 \@ref(fig:year-quarter-bar-line-echart)。可以看出，r year_range[2] - year_range[1] + 1 年共 r 4 * (year_range[2] - year_range[1] + 1 ) 个季度的抽检样本量在 r text_range(year_quarter, "sample_size") 之间，合格率稳定在 r text_range(year_quarter, "qualification_rate_percent") 之间。

bar_line_echart(
  year_quarter |> combine_year_quarter() |> factor_dims(timeline), 
  x_var = "timeline",
  x_axis_name = "时间", x_name_gap = 40,
  long_x_label = TRUE, x_label_width = 30
) |> e_labels(fontWeight = "bold", fontSize = 11)

“年份-省份”残留风险

year_province <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", year, province)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "province"))

(ref:year-province) 各年份各省份样本量与合格率

sp_dable(year_province |> factor_dims(year, province), ref_text = "(ref:year-province)")

  表 \@ref(tab:year-province) 给出了全国 r nrow(province) 个省市自治区在 r year_range[1] - r year_range[2] 年的抽检样本量及其合格率，各省各年蔬菜中农药残留超标率的展示见图 \@ref(fig:year-province-map-echart)。可以看出，r nrow(province) 个省市自治区每年的抽检样本量在 r text_range(year_province, "sample_size") 之间，合格率在 r text_range(year_province, "qualification_rate_percent") 之间。

map_echart(
  year_province |> change_to_defective() |> shorten_province_name(), 
  map_json = cn_province_map_json_2015,
  timeline_var = "year"
)

“年份-蔬菜类别”残留风险

year_category <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", year, category) |>
  factor_dims(year, category)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "category"))

(ref:year-category) 各年份各蔬菜类别样本量与合格率

sp_dable(year_category, ref_text = "(ref:year-category)")

  表 \@ref(tab:year-category) 给出了 r nrow(category) 个蔬菜类别在 r year_range[1] - r year_range[2] 年的抽检样本量及其合格率，其图形展示见图 \@ref(fig:year-category-bar-line-echart) - 图 \@ref(fig:year-category-bar-echart)。可以看出，r nrow(category) 个蔬菜类别每年的抽检样本量在 r text_range(year_category, "sample_size") 之间，合格率在 r text_range(year_category, "qualification_rate_percent") 之间。

bar_line_echart(year_category, timeline_var = "year", x_var = "category")

scatter_timeline_echart(
  year_category, timeline_var = "year", 
  x_var = "category", y_var = "qualification_rate_percent", size_var = "sample_size",
  symbol_size = c(1,50)
)

bar_line_echart(
  year_category, timeline_var = "category", x_var = "year",
) |>
  e_timeline_opts(
    label = list(interval = 0, width = 50, overflow = "break"),
    padding = 0
  )

bar_group_echart(
  year_category, timeline_var = "year", 
  x_var = "category", bar_var = c("qualification_rate_percent", "sample_size"), 
  sec_y_axis = TRUE, show_labels = TRUE
)

“年份-品种”残留风险

year_product <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", year, product) |>
  factor_dims(year, product)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "product"))

(ref:year-product) 各年份各品种样本量与合格率

sp_dable(year_product, ref_text = "(ref:year-product)")

  表 \@ref(tab:year-product) 给出了 r nrow(product) 个蔬菜品种在 r year_range[1] - r year_range[2] 年的抽检样本量及其合格率，其图形展示见图 \@ref(fig:year-product-scatter-echart) - 图 \@ref(fig:year-product-bar-echart)。可以看出，r nrow(product) 个蔬菜品种每年的抽检样本量在 r text_range(year_product, "sample_size") 之间，合格率在 r text_range(year_product, "qualification_rate_percent") 之间。

scatter_timeline_echart(
  year_product, timeline_var = "year", 
  x_var = "product", y_var = "qualification_rate_percent", size_var = "sample_size",
  x_label_width = 1
)

bar_group_echart(
  year_product, timeline_var = "year", 
  x_var = "product", bar_var = c("qualification_rate_percent", "sample_size"), 
  sec_y_axis = T
)

“季度-省份”残留风险

quarter_province <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", quarter, province) |>
  factor_dims(quarter, province)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "province"))

(ref:quarter-province) 各季度各省份样本量与合格率

sp_dable(quarter_province, ref_text = "(ref:quarter-province)")

  表 \@ref(tab:quarter-province) 给出了 r nrow(province) 个省市自治区在四个季度的抽检样本量及其合格率，其图形展示见图 \@ref(fig:quarter-province-map-echart)。可以看出，r nrow(province) 个省市自治区每个季度的抽检样本量在 r text_range(quarter_province, "sample_size") 之间，合格率在 r text_range(quarter_province, "qualification_rate_percent") 之间。

map_echart(
  quarter_province |> change_to_defective() |> shorten_province_name(), 
  map_json = cn_province_map_json_2015,
  timeline_var = "quarter"
)

“季度-蔬菜类别”残留风险

quarter_category <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", quarter, category) |>
  factor_dims(quarter, category)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "category"))

(ref:quarter-category) 各季度各蔬菜类别样本量与合格率

sp_dable(quarter_category, ref_text = "(ref:quarter-category)")

  表 \@ref(tab:quarter-category) 给出了 r nrow(category) 个蔬菜类别在四个季度的抽检样本量及其合格率，其图形展示见图 \@ref(fig:quarter-category-bar-line-echart) - 图 \@ref(fig:quarter-category-bar-echart)。可以看出，r nrow(category) 个蔬菜类别每个季度的抽检样本量在 r text_range(quarter_category, "sample_size") 之间，合格率在 r text_range(quarter_category, "qualification_rate_percent") 之间。

bar_line_echart(quarter_category, timeline_var = "quarter", x_var = "category")

scatter_timeline_echart(
  quarter_category, timeline_var = "quarter",
  x_var = "category", y_var = "qualification_rate_percent", size_var = "sample_size",
  symbol_size = c(1, 50)
)

bar_line_echart(
  quarter_category, timeline_var = "category",
  x_var = "quarter"
) |>
  e_timeline_opts(
    label = list(interval = 0, width = 50, overflow = "break"),
    padding = 0
  )

bar_group_echart(
  quarter_category, timeline_var = "quarter",
  x_var = "category", bar_var = c("qualification_rate_percent", "sample_size"),
  sec_y_axis = TRUE, show_labels = TRUE
)

“季度-品种”残留风险

quarter_product <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", quarter, product) |>
  factor_dims(quarter, product)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "product"))

(ref:quarter-product) 各季度各品种样本量与合格率

sp_dable(quarter_product, ref_text = "(ref:quarter-product)")

  表 \@ref(tab:quarter-product) 给出了 r nrow(product) 个蔬菜品种在四个季度的抽检样本量及其合格率，其图形展示见图 \@ref(fig:quarter-product-scatter-echart) - 图 \@ref(fig:quarter-product-bar-echart)。可以看出，r nrow(product) 个蔬菜品种每个季度的抽检样本量在 r text_range(quarter_product, "sample_size") 之间，合格率在 r text_range(quarter_product, "qualification_rate_percent") 之间。

scatter_timeline_echart(
  quarter_product, timeline_var = "quarter", 
  x_var = "product", y_var = "qualification_rate_percent", size_var = "sample_size",
  x_label_width = 1
)

bar_group_echart(
  quarter_product, timeline_var = "quarter",
  x_var = "product", bar_var = c("qualification_rate_percent", "sample_size"),
  sec_y_axis = TRUE
)

“省份-蔬菜类别”残留风险

province_category <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", province, category) |>
  factor_dims(province, category)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("province", "category"))

(ref:province-category) 各省份各蔬菜类别样本量与合格率

sp_dable(province_category, ref_text = "(ref:province-category)")

  表 \@ref(tab:province-category) 给出了 r nrow(province) 个省市自治区分别在 r nrow(category) 个蔬菜类别上的抽检样本量及其合格率，各省份各蔬菜类别的农药残留超标率展示见图 \@ref(fig:province-category-map-echart)。可以看出，各省份各蔬菜类别的抽检样本量在 r text_range(province_category, "sample_size") 之间，合格率在 r text_range(province_category, "qualification_rate_percent") 之间。

map_echart(
  province_category |> change_to_defective() |> shorten_province_name(), 
  map_json = cn_province_map_json_2015,
  timeline_var = "category"
) |> e_timeline_opts(controlStyle = list(showPlayBtn = FALSE))

“省份-品种”残留风险

province_product <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product", province, product) |>
  factor_dims(province, product)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("province", "product"))

(ref:province-product) 各省份各品种样本量与合格率

sp_dable(province_product, ref_text = "(ref:province-product)")

  表 \@ref(tab:province-product) 给出了 r nrow(province) 个省市自治区分别在 r nrow(product) 个蔬菜类别上的抽检样本量及其合格率，各省份各蔬菜类别的农药残留超标率展示见图 \@ref(fig:province-product-eheatmap)。可以看出，各省份各蔬菜类别的抽检样本量在 r text_range(province_product, "sample_size") 之间，合格率在 r text_range(province_product, "qualification_rate_percent") 之间。

heatmap_echart(
  province_product |> change_to_defective() |> shorten_province_name(), 
  x_var = "product", y_var = "province", value_var = "defective_rate_percent"
)

“年份-季度-省份”残留风险

year_quarter_province <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product", 
  year, quarter, province
)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter", "province"))

(ref:year-quarter-province) 各年份各季度各省份样本量与合格率

sp_dable(
  year_quarter_province |>
    factor_dims(year, quarter, province), 
  ref_text = "(ref:year-quarter-province)"
)

  表 \@ref(tab:year-quarter-province) 给出了 r nrow(province) 个省市自治区在 r year_range[1] 年第一季度到 r year_range[2] 年第四季度的抽检样本量及其合格率，各年份各季度各省份的农药残留超标率展示见图 \@ref(fig:province-product-eheatmap) 和图 \@ref(fig:year-quarter-province-eheatmap)。可以看出，各年份各季度各省份的抽检样本量在 r text_range(year_quarter_province, "sample_size") 之间，合格率在 r text_range(year_quarter_province, "qualification_rate_percent") 之间。

map_echart(
  year_quarter_province |> 
    combine_year_quarter() |>
    change_to_defective() |>
    shorten_province_name() |> 
    factor_dims(timeline), 
  map_json = cn_province_map_json_2015,
  timeline_var = "timeline", 
  interval = 3, timeline_label_width = 60
)

heatmap_echart(
  year_quarter_province |> 
    combine_year_quarter() |>
    change_to_defective() |>
    shorten_province_name() |>
    factor_dims(timeline),
  x_var = "province", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度"
)

“年份-季度-蔬菜类别”残留风险

year_quarter_category <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product", 
  year, quarter, category
)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter", "category"))

(ref:year-quarter-category) 各年份各季度各蔬菜类别样本量与合格率

sp_dable(
  year_quarter_category |> factor_dims(year, quarter, category), 
  ref_text = "(ref:year-quarter-category)"
)

  表 \@ref(tab:year-quarter-category) 给出了 r nrow(category) 个蔬菜类别在 r year_range[1] 年第一季度到 r year_range[2] 年第四季度的抽检样本量及其合格率，其图形展示见图 \@ref(fig:year-quarter-category-bar-line-echart) - 图 \@ref(fig:year-quarter-category-bar-echart)。可以看出，各年份各季度各蔬菜类别的抽检样本量在 r text_range(year_quarter_category, "sample_size") 之间，合格率在 r text_range(year_quarter_category, "qualification_rate_percent") 之间。

bar_line_echart(
  year_quarter_category |> combine_year_quarter() |> factor_dims(timeline, category), 
  timeline_var = "timeline", x_var = "category"
)

scatter_timeline_echart(
  year_quarter_category |> combine_year_quarter() |> factor_dims(timeline, category), 
  timeline_var = "timeline", 
  x_var = "category", y_var = "qualification_rate_percent", size_var = "sample_size",
  symbol_size = c(1,50), interval = 3, timeline_label_width = 60
)

bar_line_echart(
  year_quarter_category |> combine_year_quarter() |> factor_dims(timeline, category), 
  timeline_var = "category",
  x_var = "timeline", show_label = FALSE,
  long_x_label = TRUE, x_label_width = 30
) |>
  e_timeline_opts(
    label = list(interval = 0, width = 60, overflow = "break"),
    padding = 0
  )

heatmap_echart(
  year_quarter_category |> 
    combine_year_quarter() |> 
    change_to_defective() |> 
    factor_dims(timeline, category), 
  x_var = "category", y_var = "timeline", value_var = "defective_rate_percent",
  width = "100%", height = "600%",
  y_axis_name = "年份-季度", x_label_width = 50
)

bar_group_echart(
  year_quarter_category |> combine_year_quarter() |> factor_dims(timeline, category), 
  timeline_var = "timeline", 
  x_var = "category", bar_var = c("qualification_rate_percent", "sample_size"),
  sec_y_axis = TRUE, show_labels = TRUE
)

“年份-季度-品种”残留风险

year_quarter_product <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product", 
  year, quarter, product
)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter", "product"))

(ref:year-quarter-product) 各年份各季度各品种样本量与合格率

sp_dable(
  year_quarter_product |>
    factor_dims(year, quarter, product), 
  ref_text = "(ref:year-quarter-product)"
)

  表 \@ref(tab:year-quarter-product) 给出了 r nrow(product) 个蔬菜品种在 r year_range[1] 年第一季度到 r year_range[2] 年第四季度的抽检样本量及其合格率，其图形展示见图 \@ref(fig:year-quarter-product-eheatmap) 和图 \@ref(fig:year-quarter-product-bar-echart)。可以看出，各年份各季度各蔬菜品种的抽检样本量在 r text_range(year_quarter_product, "sample_size") 之间，合格率在 r text_range(year_quarter_product, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_product |> 
    combine_year_quarter() |>
    change_to_defective() |>
    factor_dims(timeline, product),
  x_var = "product", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度"
)

bar_group_echart(
  year_quarter_product |> combine_year_quarter() |> factor_dims(timeline, product), 
  timeline_var = "timeline", 
  x_var = "product", bar_var = c("qualification_rate_percent", "sample_size"),
  sec_y_axis = TRUE
)

“年份-省份-蔬菜类别”残留风险

带时间轴的热力图无法展示部分数据。这部分数据在热力图的时间轴、X轴和Y轴均有较大程度的缺失，因此无法被选中进行可视化。

year_province_category <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product", 
  year, province, category
)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "province", "category"))

(ref:year-province-category) 各年份各省份各蔬菜类别样本量与合格率

sp_dable(
  year_province_category |> factor_dims(year, province, category), 
  ref_text = "(ref:year-province-category)"
)

  表 \@ref(tab:year-province-category) 给出了 r year_range[1] - r year_range[2] 年 r nrow(province) 个省市自治区的 r nrow(category) 个蔬菜类别的抽检样本量及其合格率，其图形展示见图 \@ref(fig:year-province-category-eheatmap) 和图 \@ref(fig:year-province-category-2020-eheatmap)。可以看出，各年份各省份各蔬菜类别的抽检样本量在 r text_range(year_province_category, "sample_size") 之间，合格率在 r text_range(year_province_category, "qualification_rate_percent") 之间。

heatmap_echart(
  year_province_category |> change_to_defective() |> shorten_province_name(),
  timeline_var = "year",
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60, width = "100%", height = "400%"
)

heatmap_echart(
  year_province_category |> change_to_defective() |> shorten_province_name() |> filter(year == 2016),
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60, width = "100%", height = "400%"
)

heatmap_echart(
  year_province_category |> change_to_defective() |> shorten_province_name() |> filter(year == 2017),
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60, width = "100%", height = "400%"
)

heatmap_echart(
  year_province_category |> change_to_defective() |> shorten_province_name() |> filter(year == 2018),
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60, width = "100%", height = "400%"
)

heatmap_echart(
  year_province_category |> change_to_defective() |> shorten_province_name() |> filter(year == 2019),
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60, width = "100%", height = "400%"
)

heatmap_echart(
  year_province_category |> change_to_defective() |> shorten_province_name() |> filter(year == 2020),
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60, width = "100%", height = "400%"
)

“年份-省份-品种”残留风险

带时间轴的热力图无法展示部分数据。这部分数据在热力图的时间轴、X轴和Y轴均有较大程度的缺失，因此无法被选中进行可视化。

year_province_product <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product", 
  year, province, product
) |>
  factor_dims(year, province, product)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "province", "product"))

(ref:year-province-product) 各年份各省份各品种样本量与合格率

sp_dable(year_province_product, ref_text = "(ref:year-province-product)")

  表 \@ref(tab:year-province-product) 给出了 r year_range[1] - r year_range[2] 年 r nrow(province) 个省市自治区的 r nrow(product) 个蔬菜品种的抽检样本量及其合格率，其图形展示见图 \@ref(fig:year-province-product-eheatmap) 和图 \@ref(fig:year-province-product-2020-eheatmap)。可以看出，各年份各省份各蔬菜品种的抽检样本量在 r text_range(year_province_product, "sample_size") 之间，合格率在 r text_range(year_province_product, "qualification_rate_percent") 之间。

heatmap_echart(
  year_province_product |> change_to_defective() |> shorten_province_name(),
  timeline_var = "year",
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "200%"
)

heatmap_echart(
  year_province_product |> change_to_defective() |> shorten_province_name() |> filter(year == 2016),
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "200%"
)

heatmap_echart(
  year_province_product |> change_to_defective() |> shorten_province_name() |> filter(year == 2017),
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "200%"
)

heatmap_echart(
  year_province_product |> change_to_defective() |> shorten_province_name() |> filter(year == 2018),
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "200%"
)

heatmap_echart(
  year_province_product |> change_to_defective() |> shorten_province_name() |> filter(year == 2019),
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "200%"
)

heatmap_echart(
  year_province_product |> change_to_defective() |> shorten_province_name() |> filter(year == 2020),
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "200%"
)

“季度-省份-蔬菜类别”残留风险

带时间轴的热力图无法展示部分数据。这部分数据在热力图的时间轴、X轴和Y轴均有较大程度的缺失，因此无法被选中进行可视化。

quarter_province_category <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product", 
  quarter, province, category
) |>
  factor_dims(quarter, province, category)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "province", "category"))

(ref:quarter-province-category) 各季度各省份各蔬菜类别样本量与合格率

sp_dable(quarter_province_category, ref_text = "(ref:quarter-province-category)")

  表 \@ref(tab:quarter-province-category) 给出了第一季度到第四季度 r nrow(province) 个省市自治区的 r nrow(category) 个蔬菜类别的抽检样本量及其合格率，其图形展示见图 \@ref(fig:quarter-province-category-eheatmap) 和图 \@ref(fig:quarter-province-category-Q4-eheatmap)。可以看出，各季度各省份各蔬菜类别的抽检样本量在 r text_range(quarter_province_category, "sample_size") 之间，合格率在 r text_range(quarter_province_category, "qualification_rate_percent") 之间。

heatmap_echart(
  quarter_province_category |> change_to_defective() |> shorten_province_name(),
  timeline_var = "quarter",
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "400%"
)

heatmap_echart(
  quarter_province_category |> change_to_defective() |> shorten_province_name() |> filter(quarter == "第一季度"),
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "550%"
)

heatmap_echart(
  quarter_province_category |> change_to_defective() |> shorten_province_name() |> filter(quarter == "第二季度"),
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "550%"
)

heatmap_echart(
  quarter_province_category |> change_to_defective() |> shorten_province_name() |> filter(quarter == "第三季度"),
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "550%"
)

heatmap_echart(
  quarter_province_category |> change_to_defective() |> shorten_province_name() |> filter(quarter == "第四季度"),
  x_var = "category", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "550%"
)

“季度-省份-品种”残留风险

quarter_province_product <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product", 
  quarter, province, product
) |>
  factor_dims(quarter, province, product)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "province", "product"))

(ref:quarter-province-product) 各季度各省份各品种样本量与合格率

sp_dable(quarter_province_product, ref_text = "(ref:quarter-province-product)")

  表 \@ref(tab:quarter-province-product) 给出了第一季度到第四季度 r nrow(province) 个省市自治区的 r nrow(product) 个蔬菜品种的抽检样本量及其合格率，其图形展示见图 \@ref(fig:quarter-province-product-eheatmap) 和图 \@ref(fig:quarter-province-product-Q4-eheatmap)。可以看出，各季度各省份各蔬菜品种的抽检样本量在 r text_range(quarter_province_product, "sample_size") 之间，合格率在 r text_range(quarter_province_product, "qualification_rate_percent") 之间。

heatmap_echart(
  quarter_province_product |> change_to_defective() |> shorten_province_name(),
  timeline_var = "quarter",
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "200%"
)

heatmap_echart(
  quarter_province_product |> change_to_defective() |> shorten_province_name() |> filter(quarter == "第一季度"),
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "300%"
)

heatmap_echart(
  quarter_province_product |> change_to_defective() |> shorten_province_name() |> filter(quarter == "第二季度"),
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "300%"
)

heatmap_echart(
  quarter_province_product |> change_to_defective() |> shorten_province_name() |> filter(quarter == "第三季度"),
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "300%"
)

heatmap_echart(
  quarter_province_product |> change_to_defective() |> shorten_province_name() |> filter(quarter == "第四季度"),
  x_var = "product", y_var = "province", value_var = "defective_rate_percent",
  x_label_width = 60,
  width = "100%", height = "300%"
)

“年份-季度-省份-产品类别”残留风险

year_quarter_province_category <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product", 
  year, quarter, province, category
)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter", "province", "category"))

(ref:year-quarter-province-category) 各年份各季度各省份各蔬菜类别样本量与合格率

sp_dable(
  year_quarter_province_category |>
    factor_dims(year, quarter, province, category), 
  ref_text = "(ref:year-quarter-province-category)"
)

  表 \@ref(tab:year-quarter-province-category) 给出了 r year_range[1] - r year_range[2] 年第一季度到第四季度 r nrow(province) 个省市自治区的 r nrow(category) 个蔬菜品种的抽检样本量及其合格率。可以看出，各季度各省份各蔬菜品种的抽检样本量在 r text_range(year_quarter_province_category, "sample_size") 之间，合格率在 r text_range(year_quarter_province_category, "qualification_rate_percent") 之间。

`r if (FALSE) '

“年份-季度-省份-品种”残留风险（不分析）

'`

year_quarter_province_product <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product", 
  year, quarter, province, product
) |>
  factor_dims(year, quarter, province, product)

r if (FALSE) text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter", "province", "product"))

(ref:year-quarter-province-product) 各年份各季度各省份各品种样本量与合格率

sp_dable(year_quarter_province_product, ref_text = "(ref:year-quarter-province-product)")

各农药残留风险

drug <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product_drug", drug) |>
  factor_dims(drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("drug"))

(ref:drug) 各农药总体检出率与合格率

sp_dable(drug, ref_text = "(ref:drug)")

  表 \@ref(tab:drug) 给出了 r nrow(drug) 种农药的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:drug-scatter-echart)。可以看出，r nrow(drug) 种农药抽检样本量在 r text_range(drug, "sample_size") 之间，检出率稳定在 r text_range(drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(drug, "qualification_rate_percent") 之间。

scatter_echart(
  drug |> change_to_defective(), 
  x_var = "detection_rate_percent", y_var = "defective_rate_percent", label_var = "drug",
  increment = 1
)

“年份-药品”残留风险

year_drug <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product_drug", year, drug) |>
  factor_dims(year, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "drug"))

(ref:year-drug) 各年份各农药检出率与合格率

sp_dable(year_drug, ref_text = "(ref:year-drug)")

  表 \@ref(tab:year-drug) 给出了 r year_range[1] - r year_range[2] 年 r nrow(drug) 种农药每年的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-drug-det-eheatmap) 和图 \@ref(fig:year-drug-def-eheatmap)。可以看出，r nrow(drug) 种农药每年的抽检样本量在 r text_range(year_drug, "sample_size") 之间，检出率稳定在 r text_range(year_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_drug,
  x_var = "drug", y_var = "year", value_var = "detection_rate_percent",
  height = "300%", x_label_fontsize = 11, shrink_height = "35%"
)

heatmap_echart(
  year_drug |> change_to_defective(),
  x_var = "drug", y_var = "year", value_var = "defective_rate_percent",
  height = "300%", x_label_fontsize = 11, shrink_height = "35%"
)

“季度-药品”残留风险

quarter_drug <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product_drug", quarter, drug) |>
  factor_dims(quarter, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "drug"))

(ref:quarter-drug) 各季度各农药检出率与合格率

sp_dable(quarter_drug, ref_text = "(ref:quarter-drug)")

  表 \@ref(tab:quarter-drug) 给出了 r nrow(drug) 种农药每季度的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:quarter-drug-det-eheatmap) 和图 \@ref(fig:quarter-drug-def-eheatmap)。可以看出，r nrow(drug) 种农药每季度的抽检样本量在 r text_range(quarter_drug, "sample_size") 之间，检出率稳定在 r text_range(quarter_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(quarter_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  quarter_drug,
  x_var = "drug", y_var = "quarter", value_var = "detection_rate_percent",
  height = "300%", x_label_fontsize = 11, shrink_height = "35%"
)

heatmap_echart(
  quarter_drug |> change_to_defective(),
  x_var = "drug", y_var = "quarter", value_var = "defective_rate_percent",
  height = "300%", x_label_fontsize = 11, shrink_height = "35%"
)

“省份-药品”残留风险

province_drug <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product_drug", province, drug) |>
  factor_dims(province, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("province", "drug"))

(ref:province-drug) 各省份各农药检出率与合格率

sp_dable(province_drug, ref_text = "(ref:province-drug)")

  表 \@ref(tab:province-drug) 给出了 r nrow(province) 个省市自治区对 r nrow(drug) 种农药的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:province-drug-det-eheatmap) 和图 \@ref(fig:province-drug-def-eheatmap)。可以看出，各省份各农药的抽检样本量在 r text_range(province_drug, "sample_size") 之间，检出率稳定在 r text_range(province_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(province_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  province_drug |> shorten_province_name(),
  x_var = "drug", y_var = "province", value_var = "detection_rate_percent",
  x_label_fontsize = 11, shrink_height = "73%"
)

heatmap_echart(
  province_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "province", value_var = "defective_rate_percent",
  x_label_fontsize = 11, shrink_height = "73%"
)

“蔬菜类别-药品”残留风险

category_drug <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product_drug", category, drug) |>
  factor_dims(category, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("category", "drug"))

(ref:category-drug) 各蔬菜类别各农药检出率与合格率

sp_dable(category_drug, ref_text = "(ref:category-drug)")

  表 \@ref(tab:category-drug) 给出了 r nrow(drug) 种农药在 r nrow(category) 个蔬菜类别上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:category-drug-det-eheatmap) 和图 \@ref(fig:category-drug-def-eheatmap)。可以看出，各蔬菜类别各农药的抽检样本量在 r text_range(category_drug, "sample_size") 之间，检出率稳定在 r text_range(category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  category_drug,
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%", shrink_height = "50%"
)

heatmap_echart(
  category_drug |> change_to_defective(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%", shrink_height = "50%"
)

“品种-药品”残留风险

product_drug <- spec_dataset(dims_comb_data, ana_dims, ana_threshold, "product_drug", product, drug) |>
  factor_dims(product, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("product", "drug"))

(ref:product-drug) 各品种各农药检出率与合格率

sp_dable(product_drug, ref_text = "(ref:product-drug)")

  表 \@ref(tab:product-drug) 给出了 r nrow(drug) 种农药在 r nrow(product) 个蔬菜品种上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:product-drug-det-eheatmap) 和图 \@ref(fig:product-drug-def-eheatmap)。可以看出，各品种各农药的抽检样本量在 r text_range(product_drug, "sample_size") 之间，检出率稳定在 r text_range(product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "800%", shrink_height = "75%"
)

heatmap_echart(
  product_drug |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "800%", shrink_height = "75%"
)

“年份-季度-药品”残留风险

year_quarter_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, quarter, drug
)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter", "drug"))

(ref:year-quarter-drug) 各年份各季度各农药检出率与合格率

sp_dable(
  year_quarter_drug |> factor_dims(year, quarter, drug), 
  ref_text = "(ref:year-quarter-drug)"
)

  表 \@ref(tab:year-quarter-drug) 给出了 r year_range[1] - r year_range[2] 年第一季度到第四季度 r nrow(drug) 种农药的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-drug-det-eheatmap) 和图 \@ref(fig:year-quarter-drug-def-eheatmap)。可以看出，各年份各季度各农药的抽检样本量在 r text_range(year_quarter_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_drug |> combine_year_quarter(),
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度",
  x_label_fontsize = 11, height = "600%", shrink_height = "65%"
)

heatmap_echart(
  year_quarter_drug |> combine_year_quarter() |> change_to_defective(),
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "600%", shrink_height = "65%"
)

“年份-省份-药品”残留风险

year_province_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, province, drug
) |>
  factor_dims(year, province, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "province", "drug"))

(ref:year-province-drug) 各年份各省份各农药检出率与合格率

sp_dable(year_province_drug, ref_text = "(ref:year-province-drug)")

  表 \@ref(tab:year-province-drug) 给出了 r year_range[1] - r year_range[2] 年 r nrow(province) 个省市自治区的 r nrow(drug) 种农药的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-province-drug-det-eheatmap) 和图 \@ref(fig:year-province-drug-def-eheatmap)。可以看出，各年份各省份各农药的抽检样本量在 r text_range(year_province_drug, "sample_size") 之间，检出率稳定在 r text_range(year_province_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_province_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_province_drug |> shorten_province_name(), timeline_var = "year",
  x_var = "drug", y_var = "province", value_var = "detection_rate_percent",
  x_label_fontsize = 11, shrink_height = "70%"
)

heatmap_echart(
  year_province_drug |> change_to_defective() |> shorten_province_name(), 
  timeline_var = "year",
  x_var = "drug", y_var = "province", value_var = "defective_rate_percent",
  x_label_fontsize = 11, shrink_height = "70%"
)

“年份-蔬菜类别-药品”残留风险

year_category_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, category, drug
) |>
  factor_dims(year, category, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "category", "drug"))

(ref:year-category-drug) 各年份各蔬菜类别各农药检出率与合格率

sp_dable(year_category_drug, ref_text = "(ref:year-category-drug)")

  表 \@ref(tab:year-category-drug) 给出了 r year_range[1] - r year_range[2] 年 r nrow(category) 个蔬菜类别的 r nrow(drug) 种农药的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-category-drug-det-eheatmap) 和图 \@ref(fig:year-category-drug-def-eheatmap)。可以看出，各年份各蔬菜类别各农药的抽检样本量在 r text_range(year_category_drug, "sample_size") 之间，检出率稳定在 r text_range(year_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_category_drug, timeline_var = "year",
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  height = "400%", x_label_fontsize = 11
)

heatmap_echart(
  year_category_drug |> change_to_defective(), timeline_var = "year",
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  height = "400%", x_label_fontsize = 11
)

“年份-品种-药品”残留风险

热力图缺少黑木耳与茶树菇（2019年）的数据

year_product_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, product, drug
) |>
  factor_dims(year, product, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "product", "drug"))

(ref:year-product-drug) 各年份各品种各农药检出率与合格率

sp_dable(year_product_drug, ref_text = "(ref:year-product-drug)")

  表 \@ref(tab:year-product-drug) 给出了 r year_range[1] - r year_range[2] 年 r nrow(product) 个蔬菜品种的 r nrow(drug) 种农药的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-product-drug-det-eheatmap) 和图 \@ref(fig:year-product-drug-def-eheatmap)。可以看出，各年份各蔬菜品种各农药的抽检样本量在 r text_range(year_product_drug, "sample_size") 之间，检出率稳定在 r text_range(year_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_product_drug, timeline_var = "year",
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11
)

heatmap_echart(
  year_product_drug |> change_to_defective(), timeline_var = "year",
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11
)

“季度-省份-药品”残留风险

quarter_province_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  quarter, province, drug
) |>
  factor_dims(quarter, province, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "province", "drug"))

(ref:quarter-province-drug) 各季度各省份各农药检出率与合格率

sp_dable(quarter_province_drug, ref_text = "(ref:quarter-province-drug)")

  表 \@ref(tab:quarter-province-drug) 给出了 r nrow(province) 个省市自治区在四个季度的 r nrow(drug) 种农药的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:quarter-province-drug-det-eheatmap) 和图 \@ref(fig:quarter-province-drug-def-eheatmap)。可以看出，各季度各省份各农药的抽检样本量在 r text_range(quarter_province_drug, "sample_size") 之间，检出率稳定在 r text_range(quarter_province_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(quarter_province_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  quarter_province_drug |> shorten_province_name(), timeline_var = "quarter",
  x_var = "drug", y_var = "province", value_var = "detection_rate_percent",
  x_label_fontsize = 11
)

heatmap_echart(
  quarter_province_drug |> change_to_defective() |> shorten_province_name(), 
  timeline_var = "quarter",
  x_var = "drug", y_var = "province", value_var = "defective_rate_percent"
)

“季度-蔬菜类别-药品”残留风险

quarter_category_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  quarter, category, drug
) |>
  factor_dims(quarter, category, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "category", "drug"))

(ref:quarter-category-drug) 各季度各蔬菜类别各农药检出率与合格率

sp_dable(quarter_category_drug, ref_text = "(ref:quarter-category-drug)")

  表 \@ref(tab:quarter-category-drug) 给出了 r nrow(category) 个蔬菜类别在四个季度的 r nrow(drug) 种农药的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:quarter-category-drug-det-eheatmap) 和图 \@ref(fig:quarter-category-drug-def-eheatmap)。可以看出，各季度各蔬菜类别各农药的抽检样本量在 r text_range(quarter_category_drug, "sample_size") 之间，检出率稳定在 r text_range(quarter_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(quarter_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  quarter_category_drug, timeline_var = "quarter",
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  quarter_category_drug |> change_to_defective(), timeline_var = "quarter",
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

“季度-品种-药品”残留风险

quarter_product_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  quarter, product, drug
) |>
  factor_dims(quarter, product, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "product", "drug"))

(ref:quarter-product-drug) 各季度各品种各农药检出率与合格率

sp_dable(quarter_product_drug, ref_text = "(ref:quarter-product-drug)")

  表 \@ref(tab:quarter-product-drug) 给出了四个季度种 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率。可以看出，各季度各蔬菜品种各农药的抽检样本量在 r text_range(quarter_product_drug, "sample_size") 之间，检出率稳定在 r text_range(quarter_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(quarter_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  quarter_product_drug |> filter(quarter == "第一季度"),
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent", 
  x_label_fontsize = 11
)

heatmap_echart(
  quarter_product_drug |> filter(quarter == "第二季度"),
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent", 
  x_label_fontsize = 11
)

heatmap_echart(
  quarter_product_drug |> filter(quarter == "第三季度"),
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent", 
  x_label_fontsize = 11
)

heatmap_echart(
  quarter_product_drug |> filter(quarter == "第四季度"),
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent", 
  x_label_fontsize = 11
)

heatmap_echart(
  quarter_product_drug |> filter(quarter == "第一季度") |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11
)

heatmap_echart(
  quarter_product_drug |> filter(quarter == "第二季度") |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11
)

heatmap_echart(
  quarter_product_drug |> filter(quarter == "第三季度") |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11
)

heatmap_echart(
  quarter_product_drug |> filter(quarter == "第四季度") |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11
)

“省份-蔬菜类别-药品”残留风险

province_category_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  province, category, drug
) |>
  factor_dims(province, category, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("province", "category", "drug"))

(ref:province-category-drug) 各省份各蔬菜类别各农药检出率与合格率

sp_dable(province_category_drug, ref_text = "(ref:province-category-drug)")

  表 \@ref(tab:anhui-category-drug) - 表 \@ref(tab:chongqing-category-drug) 给出了 r nrow(province) 个省市自治区的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:anhui-category-drug-det-eheatmap) - 图 \@ref(fig:chongqing-category-drug-def-eheatmap)。可以看出，各省市自治区各蔬菜类别各农药的抽检样本量在 r text_range(province_category_drug, "sample_size") 之间，检出率稳定在 r text_range(province_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(province_category_drug, "qualification_rate_percent") 之间。

安徽省

anhui_category_drug <- province_category_drug |>
  filter(province == "安徽省")

(ref:anhui-category-drug) 安徽省各蔬菜类别各农药检出率与合格率

sp_dable(anhui_category_drug, ref_text = "(ref:anhui-category-drug)")

  表 \@ref(tab:anhui-category-drug) 给出了安徽省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:anhui-category-drug-det-eheatmap) - 图 \@ref(fig:anhui-category-drug-def-eheatmap)。可以看出，安徽省各蔬菜类别各农药的抽检样本量在 r text_range(anhui_category_drug, "sample_size") 之间，检出率稳定在 r text_range(anhui_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(anhui_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  anhui_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  anhui_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

北京市

beijing_category_drug <- province_category_drug |>
  filter(province == "北京市")

(ref:beijing-category-drug) 北京市各蔬菜类别各农药检出率与合格率

sp_dable(beijing_category_drug, ref_text = "(ref:beijing-category-drug)")

  表 \@ref(tab:beijing-category-drug) 给出了北京市的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:beijing-category-drug-det-eheatmap) - 图 \@ref(fig:beijing-category-drug-def-eheatmap)。可以看出，北京市各蔬菜类别各农药的抽检样本量在 r text_range(beijing_category_drug, "sample_size") 之间，检出率稳定在 r text_range(beijing_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(beijing_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  beijing_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  beijing_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

福建省

fujian_category_drug <- province_category_drug |>
  filter(province == "福建省")

(ref:fujian-category-drug) 福建省各蔬菜类别各农药检出率与合格率

sp_dable(fujian_category_drug, ref_text = "(ref:fujian-category-drug)")

  表 \@ref(tab:fujian-category-drug) 给出了福建省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:fujian-category-drug-det-eheatmap) - 图 \@ref(fig:fujian-category-drug-def-eheatmap)。可以看出，福建省各蔬菜类别各农药的抽检样本量在 r text_range(fujian_category_drug, "sample_size") 之间，检出率稳定在 r text_range(fujian_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(fujian_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  fujian_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  fujian_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

甘肃省

gansu_category_drug <- province_category_drug |>
  filter(province == "甘肃省")

(ref:gansu-category-drug) 甘肃省各蔬菜类别各农药检出率与合格率

sp_dable(gansu_category_drug, ref_text = "(ref:gansu-category-drug)")

  表 \@ref(tab:gansu-category-drug) 给出了甘肃省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:gansu-category-drug-det-eheatmap) - 图 \@ref(fig:gansu-category-drug-def-eheatmap)。可以看出，甘肃省各蔬菜类别各农药的抽检样本量在 r text_range(gansu_category_drug, "sample_size") 之间，检出率稳定在 r text_range(gansu_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(gansu_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  gansu_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  gansu_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

广东省

guangdong_category_drug <- province_category_drug |>
  filter(province == "广东省")

(ref:guangdong-category-drug) 广东省各蔬菜类别各农药检出率与合格率

sp_dable(guangdong_category_drug, ref_text = "(ref:guangdong-category-drug)")

  表 \@ref(tab:guangdong-category-drug) 给出了广东省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:guangdong-category-drug-det-eheatmap) - 图 \@ref(fig:guangdong-category-drug-def-eheatmap)。可以看出，广东省各蔬菜类别各农药的抽检样本量在 r text_range(guangdong_category_drug, "sample_size") 之间，检出率稳定在 r text_range(guangdong_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(guangdong_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  guangdong_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  guangdong_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

广西壮族自治区

guangxi_category_drug <- province_category_drug |>
  filter(province == "广西壮族自治区")

(ref:guangxi-category-drug) 广西壮族自治区各蔬菜类别各农药检出率与合格率

sp_dable(guangxi_category_drug, ref_text = "(ref:guangxi-category-drug)")

  表 \@ref(tab:guangxi-category-drug) 给出了广西壮族自治区的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:guangxi-category-drug-det-eheatmap) - 图 \@ref(fig:guangxi-category-drug-def-eheatmap)。可以看出，广西壮族自治区各蔬菜类别各农药的抽检样本量在 r text_range(guangxi_category_drug, "sample_size") 之间，检出率稳定在 r text_range(guangxi_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(guangxi_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  guangxi_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  guangxi_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

贵州省

guizhou_category_drug <- province_category_drug |>
  filter(province == "贵州省")

(ref:guizhou-category-drug) 贵州省各蔬菜类别各农药检出率与合格率

sp_dable(guizhou_category_drug, ref_text = "(ref:guizhou-category-drug)")

  表 \@ref(tab:guizhou-category-drug) 给出了贵州省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:guizhou-category-drug-det-eheatmap) - 图 \@ref(fig:guizhou-category-drug-def-eheatmap)。可以看出，贵州省各蔬菜类别各农药的抽检样本量在 r text_range(guizhou_category_drug, "sample_size") 之间，检出率稳定在 r text_range(guizhou_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(guizhou_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  guizhou_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  guizhou_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

海南省

hainan_category_drug <- province_category_drug |>
  filter(province == "海南省")

(ref:hainan-category-drug) 海南省各蔬菜类别各农药检出率与合格率

sp_dable(hainan_category_drug, ref_text = "(ref:hainan-category-drug)")

  表 \@ref(tab:hainan-category-drug) 给出了海南省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:hainan-category-drug-det-eheatmap) - 图 \@ref(fig:hainan-category-drug-def-eheatmap)。可以看出，海南省各蔬菜类别各农药的抽检样本量在 r text_range(hainan_category_drug, "sample_size") 之间，检出率稳定在 r text_range(hainan_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(hainan_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  hainan_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  hainan_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

河北省

hebei_category_drug <- province_category_drug |>
  filter(province == "河北省")

(ref:hebei-category-drug) 河北省各蔬菜类别各农药检出率与合格率

sp_dable(hebei_category_drug, ref_text = "(ref:hebei-category-drug)")

  表 \@ref(tab:hebei-category-drug) 给出了河北省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:hebei-category-drug-det-eheatmap) - 图 \@ref(fig:hebei-category-drug-def-eheatmap)。可以看出，河北省各蔬菜类别各农药的抽检样本量在 r text_range(hebei_category_drug, "sample_size") 之间，检出率稳定在 r text_range(hebei_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(hebei_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  hebei_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  hebei_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

河南省

henan_category_drug <- province_category_drug |>
  filter(province == "河南省")

(ref:henan-category-drug) 河南省各蔬菜类别各农药检出率与合格率

sp_dable(henan_category_drug, ref_text = "(ref:henan-category-drug)")

  表 \@ref(tab:henan-category-drug) 给出了河南省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:henan-category-drug-det-eheatmap) - 图 \@ref(fig:henan-category-drug-def-eheatmap)。可以看出，河南省各蔬菜类别各农药的抽检样本量在 r text_range(henan_category_drug, "sample_size") 之间，检出率稳定在 r text_range(henan_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(henan_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  henan_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  henan_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

黑龙江省

heilongjiang_category_drug <- province_category_drug |>
  filter(province == "黑龙江省")

(ref:heilongjiang-category-drug) 黑龙江省各蔬菜类别各农药检出率与合格率

sp_dable(heilongjiang_category_drug, ref_text = "(ref:heilongjiang-category-drug)")

  表 \@ref(tab:heilongjiang-category-drug) 给出了黑龙江省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:heilongjiang-category-drug-det-eheatmap) - 图 \@ref(fig:heilongjiang-category-drug-def-eheatmap)。可以看出，黑龙江省各蔬菜类别各农药的抽检样本量在 r text_range(heilongjiang_category_drug, "sample_size") 之间，检出率稳定在 r text_range(heilongjiang_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(heilongjiang_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  heilongjiang_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  heilongjiang_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

湖北省

hubei_category_drug <- province_category_drug |>
  filter(province == "湖北省")

(ref:hubei-category-drug) 湖北省各蔬菜类别各农药检出率与合格率

sp_dable(hubei_category_drug, ref_text = "(ref:hubei-category-drug)")

  表 \@ref(tab:hubei-category-drug) 给出了湖北省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:hubei-category-drug-det-eheatmap) - 图 \@ref(fig:hubei-category-drug-def-eheatmap)。可以看出，湖北省各蔬菜类别各农药的抽检样本量在 r text_range(hubei_category_drug, "sample_size") 之间，检出率稳定在 r text_range(hubei_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(hubei_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  hubei_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  hubei_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

湖南省

hunan_category_drug <- province_category_drug |>
  filter(province == "湖南省")

(ref:hunan-category-drug) 湖南省各蔬菜类别各农药检出率与合格率

sp_dable(hunan_category_drug, ref_text = "(ref:hunan-category-drug)")

  表 \@ref(tab:hunan-category-drug) 给出了湖南省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:hunan-category-drug-det-eheatmap) - 图 \@ref(fig:hunan-category-drug-def-eheatmap)。可以看出，湖南省各蔬菜类别各农药的抽检样本量在 r text_range(hunan_category_drug, "sample_size") 之间，检出率稳定在 r text_range(hunan_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(hunan_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  hunan_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  hunan_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

吉林省

jiling_category_drug <- province_category_drug |>
  filter(province == "吉林省")

(ref:jiling-category-drug) 吉林省各蔬菜类别各农药检出率与合格率

sp_dable(jiling_category_drug, ref_text = "(ref:jiling-category-drug)")

  表 \@ref(tab:jiling-category-drug) 给出了吉林省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:jiling-category-drug-det-eheatmap) - 图 \@ref(fig:jiling-category-drug-def-eheatmap)。可以看出，吉林省各蔬菜类别各农药的抽检样本量在 r text_range(jiling_category_drug, "sample_size") 之间，检出率稳定在 r text_range(jiling_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(jiling_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  jiling_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  jiling_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

江苏省

jiangsu_category_drug <- province_category_drug |>
  filter(province == "江苏省")

(ref:jiangsu-category-drug) 江苏省各蔬菜类别各农药检出率与合格率

sp_dable(jiangsu_category_drug, ref_text = "(ref:jiangsu-category-drug)")

  表 \@ref(tab:jiangsu-category-drug) 给出了江苏省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:jiangsu-category-drug-det-eheatmap) - 图 \@ref(fig:jiangsu-category-drug-def-eheatmap)。可以看出，江苏省各蔬菜类别各农药的抽检样本量在 r text_range(jiangsu_category_drug, "sample_size") 之间，检出率稳定在 r text_range(jiangsu_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(jiangsu_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  jiangsu_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  jiangsu_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

江西省

jiangxi_category_drug <- province_category_drug |>
  filter(province == "江西省")

(ref:jiangxi-category-drug) 江西省各蔬菜类别各农药检出率与合格率

sp_dable(jiangxi_category_drug, ref_text = "(ref:jiangxi-category-drug)")

  表 \@ref(tab:jiangxi-category-drug) 给出了江西省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:jiangxi-category-drug-det-eheatmap) - 图 \@ref(fig:jiangxi-category-drug-def-eheatmap)。可以看出，江西省各蔬菜类别各农药的抽检样本量在 r text_range(jiangxi_category_drug, "sample_size") 之间，检出率稳定在 r text_range(jiangxi_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(jiangxi_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  jiangxi_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  jiangxi_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

辽宁省

liaoning_category_drug <- province_category_drug |>
  filter(province == "辽宁省")

(ref:liaoning-category-drug) 辽宁省各蔬菜类别各农药检出率与合格率

sp_dable(liaoning_category_drug, ref_text = "(ref:liaoning-category-drug)")

  表 \@ref(tab:liaoning-category-drug) 给出了辽宁省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:liaoning-category-drug-det-eheatmap) - 图 \@ref(fig:liaoning-category-drug-def-eheatmap)。可以看出，辽宁省各蔬菜类别各农药的抽检样本量在 r text_range(liaoning_category_drug, "sample_size") 之间，检出率稳定在 r text_range(liaoning_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(liaoning_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  liaoning_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  liaoning_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

内蒙古自治区

neimenggu_category_drug <- province_category_drug |>
  filter(province == "内蒙古自治区")

(ref:neimenggu-category-drug) 内蒙古自治区各蔬菜类别各农药检出率与合格率

sp_dable(neimenggu_category_drug, ref_text = "(ref:neimenggu-category-drug)")

  表 \@ref(tab:neimenggu-category-drug) 给出了内蒙古自治区的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:neimenggu-category-drug-det-eheatmap) - 图 \@ref(fig:neimenggu-category-drug-def-eheatmap)。可以看出，内蒙古自治区各蔬菜类别各农药的抽检样本量在 r text_range(neimenggu_category_drug, "sample_size") 之间，检出率稳定在 r text_range(neimenggu_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(neimenggu_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  neimenggu_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  neimenggu_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

宁夏回族自治区

ningxia_category_drug <- province_category_drug |>
  filter(province == "宁夏回族自治区")

(ref:ningxia-category-drug) 宁夏回族自治区各蔬菜类别各农药检出率与合格率

sp_dable(ningxia_category_drug, ref_text = "(ref:ningxia-category-drug)")

  表 \@ref(tab:ningxia-category-drug) 给出了宁夏回族自治区的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:ningxia-category-drug-det-eheatmap) - 图 \@ref(fig:ningxia-category-drug-def-eheatmap)。可以看出，宁夏回族自治区各蔬菜类别各农药的抽检样本量在 r text_range(ningxia_category_drug, "sample_size") 之间，检出率稳定在 r text_range(ningxia_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(ningxia_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  ningxia_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  ningxia_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

青海省

qinghai_category_drug <- province_category_drug |>
  filter(province == "青海省")

(ref:qinghai-category-drug) 青海省各蔬菜类别各农药检出率与合格率

sp_dable(qinghai_category_drug, ref_text = "(ref:qinghai-category-drug)")

  表 \@ref(tab:qinghai-category-drug) 给出了青海省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:qinghai-category-drug-det-eheatmap) - 图 \@ref(fig:qinghai-category-drug-def-eheatmap)。可以看出，青海省各蔬菜类别各农药的抽检样本量在 r text_range(qinghai_category_drug, "sample_size") 之间，检出率稳定在 r text_range(qinghai_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(qinghai_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  qinghai_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  qinghai_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

山东省

shandong_category_drug <- province_category_drug |>
  filter(province == "山东省")

(ref:shandong-category-drug) 山东省各蔬菜类别各农药检出率与合格率

sp_dable(shandong_category_drug, ref_text = "(ref:shandong-category-drug)")

  表 \@ref(tab:shandong-category-drug) 给出了山东省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:shandong-category-drug-det-eheatmap) - 图 \@ref(fig:shandong-category-drug-def-eheatmap)。可以看出，山东省各蔬菜类别各农药的抽检样本量在 r text_range(shandong_category_drug, "sample_size") 之间，检出率稳定在 r text_range(shandong_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(shandong_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  shandong_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  shandong_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

山西省

shan1xi_category_drug <- province_category_drug |>
  filter(province == "山西省")

(ref:shan1xi-category-drug) 山西省各蔬菜类别各农药检出率与合格率

sp_dable(shan1xi_category_drug, ref_text = "(ref:shan1xi-category-drug)")

  表 \@ref(tab:shan1xi-category-drug) 给出了山西省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:shan1xi-category-drug-det-eheatmap) - 图 \@ref(fig:shan1xi-category-drug-def-eheatmap)。可以看出，山西省各蔬菜类别各农药的抽检样本量在 r text_range(shan1xi_category_drug, "sample_size") 之间，检出率稳定在 r text_range(shan1xi_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(shan1xi_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  shan1xi_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  shan1xi_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

陕西省

shan3xi_category_drug <- province_category_drug |>
  filter(province == "陕西省")

(ref:shan3xi-category-drug) 陕西省各蔬菜类别各农药检出率与合格率

sp_dable(shan3xi_category_drug, ref_text = "(ref:shan3xi-category-drug)")

  表 \@ref(tab:shan3xi-category-drug) 给出了陕西省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:shan3xi-category-drug-det-eheatmap) - 图 \@ref(fig:shan3xi-category-drug-def-eheatmap)。可以看出，陕西省各蔬菜类别各农药的抽检样本量在 r text_range(shan3xi_category_drug, "sample_size") 之间，检出率稳定在 r text_range(shan3xi_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(shan3xi_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  shan3xi_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  shan3xi_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

上海市

shanghai_category_drug <- province_category_drug |>
  filter(province == "上海市")

(ref:shanghai-category-drug) 上海市各蔬菜类别各农药检出率与合格率

sp_dable(shanghai_category_drug, ref_text = "(ref:shanghai-category-drug)")

  表 \@ref(tab:shanghai-category-drug) 给出了上海市的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:shanghai-category-drug-det-eheatmap) - 图 \@ref(fig:shanghai-category-drug-def-eheatmap)。可以看出，上海市各蔬菜类别各农药的抽检样本量在 r text_range(shanghai_category_drug, "sample_size") 之间，检出率稳定在 r text_range(shanghai_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(shanghai_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  shanghai_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  shanghai_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

四川省

sichuan_category_drug <- province_category_drug |>
  filter(province == "四川省")

(ref:sichuan-category-drug) 四川省各蔬菜类别各农药检出率与合格率

sp_dable(sichuan_category_drug, ref_text = "(ref:sichuan-category-drug)")

  表 \@ref(tab:sichuan-category-drug) 给出了四川省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:sichuan-category-drug-det-eheatmap) - 图 \@ref(fig:sichuan-category-drug-def-eheatmap)。可以看出，四川省各蔬菜类别各农药的抽检样本量在 r text_range(sichuan_category_drug, "sample_size") 之间，检出率稳定在 r text_range(sichuan_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(sichuan_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  sichuan_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  sichuan_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

天津市

tianjin_category_drug <- province_category_drug |>
  filter(province == "天津市")

(ref:tianjin-category-drug) 天津市各蔬菜类别各农药检出率与合格率

sp_dable(tianjin_category_drug, ref_text = "(ref:tianjin-category-drug)")

  表 \@ref(tab:tianjin-category-drug) 给出了天津市的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:tianjin-category-drug-det-eheatmap) - 图 \@ref(fig:tianjin-category-drug-def-eheatmap)。可以看出，天津市各蔬菜类别各农药的抽检样本量在 r text_range(tianjin_category_drug, "sample_size") 之间，检出率稳定在 r text_range(tianjin_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(tianjin_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  tianjin_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  tianjin_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

西藏自治区

xizang_category_drug <- province_category_drug |>
  filter(province == "西藏自治区")

(ref:xizang-category-drug) 西藏自治区各蔬菜类别各农药检出率与合格率

sp_dable(xizang_category_drug, ref_text = "(ref:xizang-category-drug)")

  表 \@ref(tab:xizang-category-drug) 给出了西藏自治区的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:xizang-category-drug-det-eheatmap) - 图 \@ref(fig:xizang-category-drug-def-eheatmap)。可以看出，西藏自治区各蔬菜类别各农药的抽检样本量在 r text_range(xizang_category_drug, "sample_size") 之间，检出率稳定在 r text_range(xizang_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(xizang_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  xizang_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  xizang_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

新疆维吾尔自治区

xinjiang_category_drug <- province_category_drug |>
  filter(province == "新疆维吾尔自治区")

(ref:xinjiang-category-drug) 新疆维吾尔自治区各蔬菜类别各农药检出率与合格率

sp_dable(xinjiang_category_drug, ref_text = "(ref:xinjiang-category-drug)")

  表 \@ref(tab:xinjiang-category-drug) 给出了新疆维吾尔自治区的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:xinjiang-category-drug-det-eheatmap) - 图 \@ref(fig:xinjiang-category-drug-def-eheatmap)。可以看出，新疆维吾尔自治区各蔬菜类别各农药的抽检样本量在 r text_range(xinjiang_category_drug, "sample_size") 之间，检出率稳定在 r text_range(xinjiang_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(xinjiang_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  xinjiang_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  xinjiang_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

云南省

yunnan_category_drug <- province_category_drug |>
  filter(province == "云南省")

(ref:yunnan-category-drug) 云南省各蔬菜类别各农药检出率与合格率

sp_dable(yunnan_category_drug, ref_text = "(ref:yunnan-category-drug)")

  表 \@ref(tab:yunnan-category-drug) 给出了云南省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:yunnan-category-drug-det-eheatmap) - 图 \@ref(fig:yunnan-category-drug-def-eheatmap)。可以看出，云南省各蔬菜类别各农药的抽检样本量在 r text_range(yunnan_category_drug, "sample_size") 之间，检出率稳定在 r text_range(yunnan_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(yunnan_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  yunnan_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  yunnan_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

浙江省

zhejiang_category_drug <- province_category_drug |>
  filter(province == "浙江省")

(ref:zhejiang-category-drug) 浙江省各蔬菜类别各农药检出率与合格率

sp_dable(zhejiang_category_drug, ref_text = "(ref:zhejiang-category-drug)")

  表 \@ref(tab:zhejiang-category-drug) 给出了浙江省的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:zhejiang-category-drug-det-eheatmap) - 图 \@ref(fig:zhejiang-category-drug-def-eheatmap)。可以看出，浙江省各蔬菜类别各农药的抽检样本量在 r text_range(zhejiang_category_drug, "sample_size") 之间，检出率稳定在 r text_range(zhejiang_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(zhejiang_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  zhejiang_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  zhejiang_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

重庆市

chongqing_category_drug <- province_category_drug |>
  filter(province == "重庆市")

(ref:chongqing-category-drug) 重庆市各蔬菜类别各农药检出率与合格率

sp_dable(chongqing_category_drug, ref_text = "(ref:chongqing-category-drug)")

  表 \@ref(tab:chongqing-category-drug) 给出了重庆市的 r nrow(category) 种蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:chongqing-category-drug-det-eheatmap) - 图 \@ref(fig:chongqing-category-drug-def-eheatmap)。可以看出，重庆市各蔬菜类别各农药的抽检样本量在 r text_range(chongqing_category_drug, "sample_size") 之间，检出率稳定在 r text_range(chongqing_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(chongqing_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  chongqing_category_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  chongqing_category_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

“省份-品种-药品”残留风险

province_product_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  province, product, drug
) |>
  factor_dims(province, product, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("province", "product", "drug"))

(ref:province-product-drug) 各省份各品种各农药检出率与合格率

sp_dable(province_product_drug, ref_text = "(ref:province-product-drug)")

  表 \@ref(tab:anhui-product-drug) - 表 \@ref(tab:chongqing-product-drug) 给出了 r nrow(province) 个省市自治区的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:anhui-product-drug-det-eheatmap) - 图 \@ref(fig:chongqing-product-drug-def-eheatmap)。可以看出，各省市自治区各蔬菜品种各农药的抽检样本量在 r text_range(province_product_drug, "sample_size") 之间，检出率稳定在 r text_range(province_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(province_product_drug, "qualification_rate_percent") 之间。

安徽省

anhui_product_drug <- province_product_drug |>
  filter(province == "安徽省")

(ref:anhui-product-drug) 安徽省各品种各农药检出率与合格率

sp_dable(anhui_product_drug, ref_text = "(ref:anhui-product-drug)")

  表 \@ref(tab:anhui-product-drug) 给出了安徽省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:anhui-product-drug-det-eheatmap) - 图 \@ref(fig:anhui-product-drug-def-eheatmap)。可以看出，安徽省各蔬菜品种各农药的抽检样本量在 r text_range(anhui_product_drug, "sample_size") 之间，检出率稳定在 r text_range(anhui_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(anhui_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  anhui_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  anhui_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

北京市

beijing_product_drug <- province_product_drug |>
  filter(province == "北京市")

(ref:beijing-product-drug) 北京市各品种各农药检出率与合格率

sp_dable(beijing_product_drug, ref_text = "(ref:beijing-product-drug)")

  表 \@ref(tab:beijing-product-drug) 给出了北京市的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:beijing-product-drug-det-eheatmap) - 图 \@ref(fig:beijing-product-drug-def-eheatmap)。可以看出，北京市各蔬菜品种各农药的抽检样本量在 r text_range(beijing_product_drug, "sample_size") 之间，检出率稳定在 r text_range(beijing_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(beijing_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  beijing_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  beijing_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

福建省

fujian_product_drug <- province_product_drug |>
  filter(province == "福建省")

(ref:fujian-product-drug) 福建省各品种各农药检出率与合格率

sp_dable(fujian_product_drug, ref_text = "(ref:fujian-product-drug)")

  表 \@ref(tab:fujian-product-drug) 给出了福建省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:fujian-product-drug-det-eheatmap) - 图 \@ref(fig:fujian-product-drug-def-eheatmap)。可以看出，福建省各蔬菜品种各农药的抽检样本量在 r text_range(fujian_product_drug, "sample_size") 之间，检出率稳定在 r text_range(fujian_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(fujian_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  fujian_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  fujian_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

甘肃省

gansu_product_drug <- province_product_drug |>
  filter(province == "甘肃省")

(ref:gansu-product-drug) 甘肃省各品种各农药检出率与合格率

sp_dable(gansu_product_drug, ref_text = "(ref:gansu-product-drug)")

  表 \@ref(tab:gansu-product-drug) 给出了甘肃省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:gansu-product-drug-det-eheatmap) - 图 \@ref(fig:gansu-product-drug-def-eheatmap)。可以看出，甘肃省各蔬菜品种各农药的抽检样本量在 r text_range(gansu_product_drug, "sample_size") 之间，检出率稳定在 r text_range(gansu_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(gansu_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  gansu_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  gansu_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

广东省

guangdong_product_drug <- province_product_drug |>
  filter(province == "广东省")

(ref:guangdong-product-drug) 广东省各品种各农药检出率与合格率

sp_dable(guangdong_product_drug, ref_text = "(ref:guangdong-product-drug)")

  表 \@ref(tab:guangdong-product-drug) 给出了广东省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:guangdong-product-drug-det-eheatmap) - 图 \@ref(fig:guangdong-product-drug-def-eheatmap)。可以看出，广东省各蔬菜品种各农药的抽检样本量在 r text_range(guangdong_product_drug, "sample_size") 之间，检出率稳定在 r text_range(guangdong_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(guangdong_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  guangdong_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  guangdong_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

广西壮族自治区

guangxi_product_drug <- province_product_drug |>
  filter(province == "广西壮族自治区")

(ref:guangxi-product-drug) 广西壮族自治区各品种各农药检出率与合格率

sp_dable(guangxi_product_drug, ref_text = "(ref:guangxi-product-drug)")

  表 \@ref(tab:guangxi-product-drug) 给出了广西壮族自治区的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:guangxi-product-drug-det-eheatmap) - 图 \@ref(fig:guangxi-product-drug-def-eheatmap)。可以看出，广西壮族自治区各蔬菜品种各农药的抽检样本量在 r text_range(guangxi_product_drug, "sample_size") 之间，检出率稳定在 r text_range(guangxi_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(guangxi_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  guangxi_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  guangxi_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

贵州省

guizhou_product_drug <- province_product_drug |>
  filter(province == "贵州省")

(ref:guizhou-product-drug) 贵州省各品种各农药检出率与合格率

sp_dable(guizhou_product_drug, ref_text = "(ref:guizhou-product-drug)")

  表 \@ref(tab:guizhou-product-drug) 给出了贵州省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:guizhou-product-drug-det-eheatmap) - 图 \@ref(fig:guizhou-product-drug-def-eheatmap)。可以看出，贵州省各蔬菜品种各农药的抽检样本量在 r text_range(guizhou_product_drug, "sample_size") 之间，检出率稳定在 r text_range(guizhou_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(guizhou_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  guizhou_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  guizhou_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

海南省

hainan_product_drug <- province_product_drug |>
  filter(province == "海南省")

(ref:hainan-product-drug) 海南省各品种各农药检出率与合格率

sp_dable(hainan_product_drug, ref_text = "(ref:hainan-product-drug)")

  表 \@ref(tab:hainan-product-drug) 给出了海南省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:hainan-product-drug-det-eheatmap) - 图 \@ref(fig:hainan-product-drug-def-eheatmap)。可以看出，海南省各蔬菜品种各农药的抽检样本量在 r text_range(hainan_product_drug, "sample_size") 之间，检出率稳定在 r text_range(hainan_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(hainan_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  hainan_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  hainan_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

河北省

hebei_product_drug <- province_product_drug |>
  filter(province == "河北省")

(ref:hebei-product-drug) 河北省各品种各农药检出率与合格率

sp_dable(hebei_product_drug, ref_text = "(ref:hebei-product-drug)")

  表 \@ref(tab:hebei-product-drug) 给出了河北省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:hebei-product-drug-det-eheatmap) - 图 \@ref(fig:hebei-product-drug-def-eheatmap)。可以看出，河北省各蔬菜品种各农药的抽检样本量在 r text_range(hebei_product_drug, "sample_size") 之间，检出率稳定在 r text_range(hebei_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(hebei_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  hebei_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  hebei_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

河南省

henan_product_drug <- province_product_drug |>
  filter(province == "河南省")

(ref:henan-product-drug) 河南省各品种各农药检出率与合格率

sp_dable(henan_product_drug, ref_text = "(ref:henan-product-drug)")

  表 \@ref(tab:henan-product-drug) 给出了河南省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:henan-product-drug-det-eheatmap) - 图 \@ref(fig:henan-product-drug-def-eheatmap)。可以看出，河南省各蔬菜品种各农药的抽检样本量在 r text_range(henan_product_drug, "sample_size") 之间，检出率稳定在 r text_range(henan_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(henan_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  henan_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  henan_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

黑龙江省

heilongjiang_product_drug <- province_product_drug |>
  filter(province == "黑龙江省")

(ref:heilongjiang-product-drug) 黑龙江省各品种各农药检出率与合格率

sp_dable(heilongjiang_product_drug, ref_text = "(ref:heilongjiang-product-drug)")

  表 \@ref(tab:heilongjiang-product-drug) 给出了黑龙江省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:heilongjiang-product-drug-det-eheatmap) - 图 \@ref(fig:heilongjiang-product-drug-def-eheatmap)。可以看出，黑龙江省各蔬菜品种各农药的抽检样本量在 r text_range(heilongjiang_product_drug, "sample_size") 之间，检出率稳定在 r text_range(heilongjiang_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(heilongjiang_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  heilongjiang_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  heilongjiang_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

湖北省

hubei_product_drug <- province_product_drug |>
  filter(province == "湖北省")

(ref:hubei-product-drug) 湖北省各品种各农药检出率与合格率

sp_dable(hubei_product_drug, ref_text = "(ref:hubei-product-drug)")

  表 \@ref(tab:hubei-product-drug) 给出了湖北省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:hubei-product-drug-det-eheatmap) - 图 \@ref(fig:hubei-product-drug-def-eheatmap)。可以看出，湖北省各蔬菜品种各农药的抽检样本量在 r text_range(hubei_product_drug, "sample_size") 之间，检出率稳定在 r text_range(hubei_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(hubei_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  hubei_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  hubei_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

湖南省

hunan_product_drug <- province_product_drug |>
  filter(province == "湖南省")

(ref:hunan-product-drug) 湖南省各品种各农药检出率与合格率

sp_dable(hunan_product_drug, ref_text = "(ref:hunan-product-drug)")

  表 \@ref(tab:hunan-product-drug) 给出了湖南省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:hunan-product-drug-det-eheatmap) - 图 \@ref(fig:hunan-product-drug-def-eheatmap)。可以看出，湖南省各蔬菜品种各农药的抽检样本量在 r text_range(hunan_product_drug, "sample_size") 之间，检出率稳定在 r text_range(hunan_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(hunan_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  hunan_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  hunan_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

吉林省

jiling_product_drug <- province_product_drug |>
  filter(province == "吉林省")

(ref:jiling-product-drug) 吉林省各品种各农药检出率与合格率

sp_dable(jiling_product_drug, ref_text = "(ref:jiling-product-drug)")

  表 \@ref(tab:jiling-product-drug) 给出了吉林省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:jiling-product-drug-det-eheatmap) - 图 \@ref(fig:jiling-product-drug-def-eheatmap)。可以看出，吉林省各蔬菜品种各农药的抽检样本量在 r text_range(jiling_product_drug, "sample_size") 之间，检出率稳定在 r text_range(jiling_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(jiling_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  jiling_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  jiling_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

江苏省

jiangsu_product_drug <- province_product_drug |>
  filter(province == "江苏省")

(ref:jiangsu-product-drug) 江苏省各品种各农药检出率与合格率

sp_dable(jiangsu_product_drug, ref_text = "(ref:jiangsu-product-drug)")

  表 \@ref(tab:jiangsu-product-drug) 给出了江苏省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:jiangsu-product-drug-det-eheatmap) - 图 \@ref(fig:jiangsu-product-drug-def-eheatmap)。可以看出，江苏省各蔬菜品种各农药的抽检样本量在 r text_range(jiangsu_product_drug, "sample_size") 之间，检出率稳定在 r text_range(jiangsu_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(jiangsu_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  jiangsu_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  jiangsu_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

江西省

jiangxi_product_drug <- province_product_drug |>
  filter(province == "江西省")

(ref:jiangxi-product-drug) 江西省各品种各农药检出率与合格率

sp_dable(jiangxi_product_drug, ref_text = "(ref:jiangxi-product-drug)")

  表 \@ref(tab:jiangxi-product-drug) 给出了江西省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:jiangxi-product-drug-det-eheatmap) - 图 \@ref(fig:jiangxi-product-drug-def-eheatmap)。可以看出，江西省各蔬菜品种各农药的抽检样本量在 r text_range(jiangxi_product_drug, "sample_size") 之间，检出率稳定在 r text_range(jiangxi_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(jiangxi_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  jiangxi_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  jiangxi_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

辽宁省

liaoning_product_drug <- province_product_drug |>
  filter(province == "辽宁省")

(ref:liaoning-product-drug) 辽宁省各品种各农药检出率与合格率

sp_dable(liaoning_product_drug, ref_text = "(ref:liaoning-product-drug)")

  表 \@ref(tab:liaoning-product-drug) 给出了辽宁省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:liaoning-product-drug-det-eheatmap) - 图 \@ref(fig:liaoning-product-drug-def-eheatmap)。可以看出，辽宁省各蔬菜品种各农药的抽检样本量在 r text_range(liaoning_product_drug, "sample_size") 之间，检出率稳定在 r text_range(liaoning_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(liaoning_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  liaoning_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  liaoning_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

内蒙古自治区

neimenggu_product_drug <- province_product_drug |>
  filter(province == "内蒙古自治区")

(ref:neimenggu-product-drug) 内蒙古自治区各品种各农药检出率与合格率

sp_dable(neimenggu_product_drug, ref_text = "(ref:neimenggu-product-drug)")

  表 \@ref(tab:neimenggu-product-drug) 给出了内蒙古自治区的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:neimenggu-product-drug-det-eheatmap) - 图 \@ref(fig:neimenggu-product-drug-def-eheatmap)。可以看出，内蒙古自治区各蔬菜品种各农药的抽检样本量在 r text_range(neimenggu_product_drug, "sample_size") 之间，检出率稳定在 r text_range(neimenggu_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(neimenggu_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  neimenggu_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  neimenggu_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

宁夏回族自治区

ningxia_product_drug <- province_product_drug |>
  filter(province == "宁夏回族自治区")

(ref:ningxia-product-drug) 宁夏回族自治区各品种各农药检出率与合格率

sp_dable(ningxia_product_drug, ref_text = "(ref:ningxia-product-drug)")

  表 \@ref(tab:ningxia-product-drug) 给出了宁夏回族自治区的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:ningxia-product-drug-det-eheatmap) - 图 \@ref(fig:ningxia-product-drug-def-eheatmap)。可以看出，宁夏回族自治区各蔬菜品种各农药的抽检样本量在 r text_range(ningxia_product_drug, "sample_size") 之间，检出率稳定在 r text_range(ningxia_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(ningxia_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  ningxia_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  ningxia_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

青海省

qinghai_product_drug <- province_product_drug |>
  filter(province == "青海省")

(ref:qinghai-product-drug) 青海省各品种各农药检出率与合格率

sp_dable(qinghai_product_drug, ref_text = "(ref:qinghai-product-drug)")

  表 \@ref(tab:qinghai-product-drug) 给出了青海省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:qinghai-product-drug-det-eheatmap) - 图 \@ref(fig:qinghai-product-drug-def-eheatmap)。可以看出，青海省各蔬菜品种各农药的抽检样本量在 r text_range(qinghai_product_drug, "sample_size") 之间，检出率稳定在 r text_range(qinghai_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(qinghai_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  qinghai_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  qinghai_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

山东省

shandong_product_drug <- province_product_drug |>
  filter(province == "山东省")

(ref:shandong-product-drug) 山东省各品种各农药检出率与合格率

sp_dable(shandong_product_drug, ref_text = "(ref:shandong-product-drug)")

  表 \@ref(tab:shandong-product-drug) 给出了山东省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:shandong-product-drug-det-eheatmap) - 图 \@ref(fig:shandong-product-drug-def-eheatmap)。可以看出，山东省各蔬菜品种各农药的抽检样本量在 r text_range(shandong_product_drug, "sample_size") 之间，检出率稳定在 r text_range(shandong_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(shandong_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  shandong_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  shandong_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

山西省

shan1xi_product_drug <- province_product_drug |>
  filter(province == "山西省")

(ref:shan1xi-product-drug) 山西省各品种各农药检出率与合格率

sp_dable(shan1xi_product_drug, ref_text = "(ref:shan1xi-product-drug)")

  表 \@ref(tab:shan1xi-product-drug) 给出了山西省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:shan1xi-product-drug-det-eheatmap) - 图 \@ref(fig:shan1xi-product-drug-def-eheatmap)。可以看出，山西省各蔬菜品种各农药的抽检样本量在 r text_range(shan1xi_product_drug, "sample_size") 之间，检出率稳定在 r text_range(shan1xi_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(shan1xi_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  shan1xi_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  shan1xi_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

陕西省

shan3xi_product_drug <- province_product_drug |>
  filter(province == "陕西省")

(ref:shan3xi-product-drug) 陕西省各品种各农药检出率与合格率

sp_dable(shan3xi_product_drug, ref_text = "(ref:shan3xi-product-drug)")

  表 \@ref(tab:shan3xi-product-drug) 给出了陕西省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:shan3xi-product-drug-det-eheatmap) - 图 \@ref(fig:shan3xi-product-drug-def-eheatmap)。可以看出，陕西省各蔬菜品种各农药的抽检样本量在 r text_range(shan3xi_product_drug, "sample_size") 之间，检出率稳定在 r text_range(shan3xi_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(shan3xi_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  shan3xi_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  shan3xi_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

上海市

shanghai_product_drug <- province_product_drug |>
  filter(province == "上海市")

(ref:shanghai-product-drug) 上海市各品种各农药检出率与合格率

sp_dable(shanghai_product_drug, ref_text = "(ref:shanghai-product-drug)")

  表 \@ref(tab:shanghai-product-drug) 给出了上海市的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:shanghai-product-drug-det-eheatmap) - 图 \@ref(fig:shanghai-product-drug-def-eheatmap)。可以看出，上海市各蔬菜品种各农药的抽检样本量在 r text_range(shanghai_product_drug, "sample_size") 之间，检出率稳定在 r text_range(shanghai_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(shanghai_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  shanghai_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  shanghai_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

四川省

sichuan_product_drug <- province_product_drug |>
  filter(province == "四川省")

(ref:sichuan-product-drug) 四川省各品种各农药检出率与合格率

sp_dable(sichuan_product_drug, ref_text = "(ref:sichuan-product-drug)")

  表 \@ref(tab:sichuan-product-drug) 给出了四川省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:sichuan-product-drug-det-eheatmap) - 图 \@ref(fig:sichuan-product-drug-def-eheatmap)。可以看出，四川省各蔬菜品种各农药的抽检样本量在 r text_range(sichuan_product_drug, "sample_size") 之间，检出率稳定在 r text_range(sichuan_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(sichuan_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  sichuan_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  sichuan_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

天津市

tianjin_product_drug <- province_product_drug |>
  filter(province == "天津市")

(ref:tianjin-product-drug) 天津市各品种各农药检出率与合格率

sp_dable(tianjin_product_drug, ref_text = "(ref:tianjin-product-drug)")

  表 \@ref(tab:tianjin-product-drug) 给出了天津市的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:tianjin-product-drug-det-eheatmap) - 图 \@ref(fig:tianjin-product-drug-def-eheatmap)。可以看出，天津市各蔬菜品种各农药的抽检样本量在 r text_range(tianjin_product_drug, "sample_size") 之间，检出率稳定在 r text_range(tianjin_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(tianjin_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  tianjin_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  tianjin_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

西藏自治区

xizang_product_drug <- province_product_drug |>
  filter(province == "西藏自治区")

(ref:xizang-product-drug) 西藏自治区各品种各农药检出率与合格率

sp_dable(xizang_product_drug, ref_text = "(ref:xizang-product-drug)")

  表 \@ref(tab:xizang-product-drug) 给出了西藏自治区的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:xizang-product-drug-det-eheatmap) - 图 \@ref(fig:xizang-product-drug-def-eheatmap)。可以看出，西藏自治区各蔬菜品种各农药的抽检样本量在 r text_range(xizang_product_drug, "sample_size") 之间，检出率稳定在 r text_range(xizang_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(xizang_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  xizang_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  xizang_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

新疆维吾尔自治区

xinjiang_product_drug <- province_product_drug |>
  filter(province == "新疆维吾尔自治区")

(ref:xinjiang-product-drug) 新疆维吾尔自治区各品种各农药检出率与合格率

sp_dable(xinjiang_product_drug, ref_text = "(ref:xinjiang-product-drug)")

  表 \@ref(tab:xinjiang-product-drug) 给出了新疆维吾尔自治区的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:xinjiang-product-drug-det-eheatmap) - 图 \@ref(fig:xinjiang-product-drug-def-eheatmap)。可以看出，新疆维吾尔自治区各蔬菜品种各农药的抽检样本量在 r text_range(xinjiang_product_drug, "sample_size") 之间，检出率稳定在 r text_range(xinjiang_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(xinjiang_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  xinjiang_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  xinjiang_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

云南省

yunnan_product_drug <- province_product_drug |>
  filter(province == "云南省")

(ref:yunnan-product-drug) 云南省各品种各农药检出率与合格率

sp_dable(yunnan_product_drug, ref_text = "(ref:yunnan-product-drug)")

  表 \@ref(tab:yunnan-product-drug) 给出了云南省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:yunnan-product-drug-det-eheatmap) - 图 \@ref(fig:yunnan-product-drug-def-eheatmap)。可以看出，云南省各蔬菜品种各农药的抽检样本量在 r text_range(yunnan_product_drug, "sample_size") 之间，检出率稳定在 r text_range(yunnan_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(yunnan_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  yunnan_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  yunnan_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

浙江省

zhejiang_product_drug <- province_product_drug |>
  filter(province == "浙江省")

(ref:zhejiang-product-drug) 浙江省各品种各农药检出率与合格率

sp_dable(zhejiang_product_drug, ref_text = "(ref:zhejiang-product-drug)")

  表 \@ref(tab:zhejiang-product-drug) 给出了浙江省的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:zhejiang-product-drug-det-eheatmap) - 图 \@ref(fig:zhejiang-product-drug-def-eheatmap)。可以看出，浙江省各蔬菜品种各农药的抽检样本量在 r text_range(zhejiang_product_drug, "sample_size") 之间，检出率稳定在 r text_range(zhejiang_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(zhejiang_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  zhejiang_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  zhejiang_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

重庆市

chongqing_product_drug <- province_product_drug |>
  filter(province == "重庆市")

(ref:chongqing-product-drug) 重庆市各品种各农药检出率与合格率

sp_dable(chongqing_product_drug, ref_text = "(ref:chongqing-product-drug)")

  表 \@ref(tab:chongqing-product-drug) 给出了重庆市的 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:chongqing-product-drug-det-eheatmap) - 图 \@ref(fig:chongqing-product-drug-def-eheatmap)。可以看出，重庆市各蔬菜品种各农药的抽检样本量在 r text_range(chongqing_product_drug, "sample_size") 之间，检出率稳定在 r text_range(chongqing_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(chongqing_product_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  chongqing_product_drug |> shorten_province_name(), 
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  chongqing_product_drug |> change_to_defective() |> shorten_province_name(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

“年份-季度-省份-药品”残留风险

year_quarter_province_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, quarter, province, drug
)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter", "province", "drug"))

(ref:year-quarter-province-drug) 各年份各季度各省份各农药检出率与合格率

sp_dable(
  year_quarter_province_drug |>
    factor_dims(year, quarter, province, drug), 
  ref_text = "(ref:year-quarter-province-drug)"
)

  表 \@ref(tab:year-quarter-anhui-drug) - 表 \@ref(tab:year-quarter-chongqing-drug) 给出了 r year_range[1] 年第一季度 r year_range[2] 年第四季度 r nrow(province) 个省市自治区在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率。可以看出，各年份各季度各省市自治区各农药的抽检样本量在 r text_range(year_quarter_province_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_province_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_province_drug, "qualification_rate_percent") 之间。

安徽省

year_quarter_anhui_drug <- year_quarter_province_drug |>
  filter(province == "安徽省")

(ref:year-quarter-anhui-drug) 安徽省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_anhui_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-anhui-drug)")

  表 \@ref(tab:year-quarter-anhui-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度安徽省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-anhui-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-anhui-drug-def-eheatmap)。可以看出，安徽省各年各季度各农药的抽检样本量在 r text_range(year_quarter_anhui_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_anhui_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_anhui_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_anhui_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_anhui_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

北京市

year_quarter_beijing_drug <- year_quarter_province_drug |>
  filter(province == "北京市")

(ref:year-quarter-beijing-drug) 北京市各年份各季度各农药检出率与合格率

sp_dable(year_quarter_beijing_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-beijing-drug)")

  表 \@ref(tab:year-quarter-beijing-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度北京市在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-beijing-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-beijing-drug-def-eheatmap)。可以看出，北京市各年各季度各农药的抽检样本量在 r text_range(year_quarter_beijing_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_beijing_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_beijing_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_beijing_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_beijing_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

福建省

year_quarter_fujian_drug <- year_quarter_province_drug |>
  filter(province == "福建省")

(ref:year-quarter-fujian-drug) 福建省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_fujian_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-fujian-drug)")

  表 \@ref(tab:year-quarter-fujian-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度福建省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-fujian-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-fujian-drug-def-eheatmap)。可以看出，福建省各年各季度各农药的抽检样本量在 r text_range(year_quarter_fujian_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_fujian_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_fujian_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_fujian_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_fujian_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

甘肃省

year_quarter_gansu_drug <- year_quarter_province_drug |>
  filter(province == "甘肃省")

(ref:year-quarter-gansu-drug) 甘肃省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_gansu_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-gansu-drug)")

  表 \@ref(tab:year-quarter-gansu-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度甘肃省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-gansu-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-gansu-drug-def-eheatmap)。可以看出，甘肃省各年各季度各农药的抽检样本量在 r text_range(year_quarter_gansu_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_gansu_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_gansu_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_gansu_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_gansu_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

广东省

year_quarter_guangdong_drug <- year_quarter_province_drug |>
  filter(province == "广东省")

(ref:year-quarter-guangdong-drug) 广东省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_guangdong_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-guangdong-drug)")

  表 \@ref(tab:year-quarter-guangdong-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度广东省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-guangdong-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-guangdong-drug-def-eheatmap)。可以看出，广东省各年各季度各农药的抽检样本量在 r text_range(year_quarter_guangdong_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_guangdong_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_guangdong_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_guangdong_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_guangdong_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

广西壮族自治区

year_quarter_guangxi_drug <- year_quarter_province_drug |>
  filter(province == "广西壮族自治区")

(ref:year-quarter-guangxi-drug) 广西壮族自治区各年份各季度各农药检出率与合格率

sp_dable(year_quarter_guangxi_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-guangxi-drug)")

  表 \@ref(tab:year-quarter-guangxi-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度广西壮族自治区在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-guangxi-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-guangxi-drug-def-eheatmap)。可以看出，广西壮族自治区各年各季度各农药的抽检样本量在 r text_range(year_quarter_guangxi_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_guangxi_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_guangxi_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_guangxi_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_guangxi_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

贵州省

year_quarter_guizhou_drug <- year_quarter_province_drug |>
  filter(province == "贵州省")

(ref:year-quarter-guizhou-drug) 贵州省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_guizhou_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-guizhou-drug)")

  表 \@ref(tab:year-quarter-guizhou-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度贵州省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-guizhou-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-guizhou-drug-def-eheatmap)。可以看出，贵州省各年各季度各农药的抽检样本量在 r text_range(year_quarter_guizhou_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_guizhou_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_guizhou_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_guizhou_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_guizhou_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

海南省

year_quarter_hainan_drug <- year_quarter_province_drug |>
  filter(province == "海南省")

(ref:year-quarter-hainan-drug) 海南省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_hainan_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-hainan-drug)")

  表 \@ref(tab:year-quarter-hainan-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度海南省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-hainan-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-hainan-drug-def-eheatmap)。可以看出，海南省各年各季度各农药的抽检样本量在 r text_range(year_quarter_hainan_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_hainan_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_hainan_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_hainan_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_hainan_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

河北省

year_quarter_hebei_drug <- year_quarter_province_drug |>
  filter(province == "河北省")

(ref:year-quarter-hebei-drug) 河北省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_hebei_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-hebei-drug)")

  表 \@ref(tab:year-quarter-hebei-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度河北省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-hebei-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-hebei-drug-def-eheatmap)。可以看出，河北省各年各季度各农药的抽检样本量在 r text_range(year_quarter_hebei_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_hebei_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_hebei_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_hebei_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_hebei_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

河南省

year_quarter_henan_drug <- year_quarter_province_drug |>
  filter(province == "河南省")

(ref:year-quarter-henan-drug) 河南省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_henan_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-henan-drug)")

  表 \@ref(tab:year-quarter-henan-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度河南省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-henan-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-henan-drug-def-eheatmap)。可以看出，河南省各年各季度各农药的抽检样本量在 r text_range(year_quarter_henan_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_henan_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_henan_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_henan_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_henan_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

黑龙江省

year_quarter_heilongjiang_drug <- year_quarter_province_drug |>
  filter(province == "黑龙江省")

(ref:year-quarter-heilongjiang-drug) 黑龙江省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_heilongjiang_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-heilongjiang-drug)")

  表 \@ref(tab:year-quarter-heilongjiang-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度黑龙江省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-heilongjiang-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-heilongjiang-drug-def-eheatmap)。可以看出，黑龙江省各年各季度各农药的抽检样本量在 r text_range(year_quarter_heilongjiang_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_heilongjiang_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_heilongjiang_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_heilongjiang_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_heilongjiang_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

湖北省

year_quarter_hubei_drug <- year_quarter_province_drug |>
  filter(province == "湖北省")

(ref:year-quarter-hubei-drug) 湖北省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_hubei_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-hubei-drug)")

  表 \@ref(tab:year-quarter-hubei-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度湖北省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-hubei-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-hubei-drug-def-eheatmap)。可以看出，湖北省各年各季度各农药的抽检样本量在 r text_range(year_quarter_hubei_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_hubei_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_hubei_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_hubei_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_hubei_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

湖南省

year_quarter_hunan_drug <- year_quarter_province_drug |>
  filter(province == "湖南省")

(ref:year-quarter-hunan-drug) 湖南省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_hunan_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-hunan-drug)")

  表 \@ref(tab:year-quarter-hunan-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度湖南省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-hunan-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-hunan-drug-def-eheatmap)。可以看出，湖南省各年各季度各农药的抽检样本量在 r text_range(year_quarter_hunan_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_hunan_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_hunan_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_hunan_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_hunan_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

吉林省

year_quarter_jiling_drug <- year_quarter_province_drug |>
  filter(province == "吉林省")

(ref:year-quarter-jiling-drug) 吉林省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_jiling_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-jiling-drug)")

  表 \@ref(tab:year-quarter-jiling-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度吉林省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-jiling-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-jiling-drug-def-eheatmap)。可以看出，吉林省各年各季度各农药的抽检样本量在 r text_range(year_quarter_jiling_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_jiling_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_jiling_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_jiling_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_jiling_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

江苏省

year_quarter_jiangsu_drug <- year_quarter_province_drug |>
  filter(province == "江苏省")

(ref:year-quarter-jiangsu-drug) 江苏省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_jiangsu_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-jiangsu-drug)")

  表 \@ref(tab:year-quarter-jiangsu-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度江苏省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-jiangsu-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-jiangsu-drug-def-eheatmap)。可以看出，江苏省各年各季度各农药的抽检样本量在 r text_range(year_quarter_jiangsu_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_jiangsu_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_jiangsu_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_jiangsu_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_jiangsu_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

江西省

year_quarter_jiangxi_drug <- year_quarter_province_drug |>
  filter(province == "江西省")

(ref:year-quarter-jiangxi-drug) 江西省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_jiangxi_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-jiangxi-drug)")

  表 \@ref(tab:year-quarter-jiangxi-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度江西省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-jiangxi-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-jiangxi-drug-def-eheatmap)。可以看出，江西省各年各季度各农药的抽检样本量在 r text_range(year_quarter_jiangxi_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_jiangxi_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_jiangxi_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_jiangxi_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_jiangxi_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

辽宁省

year_quarter_liaoning_drug <- year_quarter_province_drug |>
  filter(province == "辽宁省")

(ref:year-quarter-liaoning-drug) 辽宁省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_liaoning_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-liaoning-drug)")

  表 \@ref(tab:year-quarter-liaoning-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度辽宁省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-liaoning-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-liaoning-drug-def-eheatmap)。可以看出，辽宁省各年各季度各农药的抽检样本量在 r text_range(year_quarter_liaoning_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_liaoning_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_liaoning_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_liaoning_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_liaoning_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

内蒙古自治区

year_quarter_neimenggu_drug <- year_quarter_province_drug |>
  filter(province == "内蒙古自治区")

(ref:year-quarter-neimenggu-drug) 内蒙古自治区各年份各季度各农药检出率与合格率

sp_dable(year_quarter_neimenggu_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-neimenggu-drug)")

  表 \@ref(tab:year-quarter-neimenggu-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度内蒙古自治区在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-neimenggu-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-neimenggu-drug-def-eheatmap)。可以看出，内蒙古自治区各年各季度各农药的抽检样本量在 r text_range(year_quarter_neimenggu_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_neimenggu_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_neimenggu_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_neimenggu_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_neimenggu_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

宁夏回族自治区

year_quarter_ningxia_drug <- year_quarter_province_drug |>
  filter(province == "宁夏回族自治区")

(ref:year-quarter-ningxia-drug) 宁夏回族自治区各年份各季度各农药检出率与合格率

sp_dable(year_quarter_ningxia_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-ningxia-drug)")

  表 \@ref(tab:year-quarter-ningxia-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度宁夏回族自治区在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-ningxia-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-ningxia-drug-def-eheatmap)。可以看出，宁夏回族自治区各年各季度各农药的抽检样本量在 r text_range(year_quarter_ningxia_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_ningxia_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_ningxia_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_ningxia_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_ningxia_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

青海省

year_quarter_qinghai_drug <- year_quarter_province_drug |>
  filter(province == "青海省")

(ref:year-quarter-qinghai-drug) 青海省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_qinghai_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-qinghai-drug)")

  表 \@ref(tab:year-quarter-qinghai-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度青海省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-qinghai-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-qinghai-drug-def-eheatmap)。可以看出，青海省各年各季度各农药的抽检样本量在 r text_range(year_quarter_qinghai_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_qinghai_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_qinghai_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_qinghai_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_qinghai_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

山东省

year_quarter_shandong_drug <- year_quarter_province_drug |>
  filter(province == "山东省")

(ref:year-quarter-shandong-drug) 山东省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_shandong_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-shandong-drug)")

  表 \@ref(tab:year-quarter-shandong-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度山东省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-shandong-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-shandong-drug-def-eheatmap)。可以看出，山东省各年各季度各农药的抽检样本量在 r text_range(year_quarter_shandong_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_shandong_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_shandong_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_shandong_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_shandong_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

山西省

year_quarter_shan1xi_drug <- year_quarter_province_drug |>
  filter(province == "山西省")

(ref:year-quarter-shan1xi-drug) 山西省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_shan1xi_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-shan1xi-drug)")

  表 \@ref(tab:year-quarter-shan1xi-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度山西省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-shan1xi-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-shan1xi-drug-def-eheatmap)。可以看出，山西省各年各季度各农药的抽检样本量在 r text_range(year_quarter_shan1xi_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_shan1xi_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_shan1xi_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_shan1xi_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_shan1xi_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

陕西省

year_quarter_shan3xi_drug <- year_quarter_province_drug |>
  filter(province == "陕西省")

(ref:year-quarter-shan3xi-drug) 陕西省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_shan3xi_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-shan3xi-drug)")

  表 \@ref(tab:year-quarter-shan3xi-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度陕西省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-shan3xi-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-shan3xi-drug-def-eheatmap)。可以看出，陕西省各年各季度各农药的抽检样本量在 r text_range(year_quarter_shan3xi_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_shan3xi_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_shan3xi_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_shan3xi_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_shan3xi_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

上海市

year_quarter_shanghai_drug <- year_quarter_province_drug |>
  filter(province == "上海市")

(ref:year-quarter-shanghai-drug) 上海市各年份各季度各农药检出率与合格率

sp_dable(year_quarter_shanghai_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-shanghai-drug)")

  表 \@ref(tab:year-quarter-shanghai-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度上海市在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-shanghai-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-shanghai-drug-def-eheatmap)。可以看出，上海市各年各季度各农药的抽检样本量在 r text_range(year_quarter_shanghai_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_shanghai_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_shanghai_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_shanghai_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_shanghai_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

四川省

year_quarter_sichuan_drug <- year_quarter_province_drug |>
  filter(province == "四川省")

(ref:year-quarter-sichuan-drug) 四川省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_sichuan_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-sichuan-drug)")

  表 \@ref(tab:year-quarter-sichuan-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度四川省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-sichuan-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-sichuan-drug-def-eheatmap)。可以看出，四川省各年各季度各农药的抽检样本量在 r text_range(year_quarter_sichuan_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_sichuan_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_sichuan_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_sichuan_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_sichuan_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

天津市

year_quarter_tianjin_drug <- year_quarter_province_drug |>
  filter(province == "天津市")

(ref:year-quarter-tianjin-drug) 天津市各年份各季度各农药检出率与合格率

sp_dable(year_quarter_tianjin_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-tianjin-drug)")

  表 \@ref(tab:year-quarter-tianjin-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度天津市在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-tianjin-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-tianjin-drug-def-eheatmap)。可以看出，天津市各年各季度各农药的抽检样本量在 r text_range(year_quarter_tianjin_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_tianjin_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_tianjin_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_tianjin_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_tianjin_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

西藏自治区

year_quarter_xizang_drug <- year_quarter_province_drug |>
  filter(province == "西藏自治区")

(ref:year-quarter-xizang-drug) 西藏自治区各年份各季度各农药检出率与合格率

sp_dable(year_quarter_xizang_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-xizang-drug)")

  表 \@ref(tab:year-quarter-xizang-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度西藏自治区在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-xizang-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-xizang-drug-def-eheatmap)。可以看出，西藏自治区各年各季度各农药的抽检样本量在 r text_range(year_quarter_xizang_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_xizang_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_xizang_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_xizang_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_xizang_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

新疆维吾尔自治区

year_quarter_xinjiang_drug <- year_quarter_province_drug |>
  filter(province == "新疆维吾尔自治区")

(ref:year-quarter-xinjiang-drug) 新疆维吾尔自治区各年份各季度各农药检出率与合格率

sp_dable(year_quarter_xinjiang_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-xinjiang-drug)")

  表 \@ref(tab:year-quarter-xinjiang-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度新疆维吾尔自治区在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-xinjiang-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-xinjiang-drug-def-eheatmap)。可以看出，新疆维吾尔自治区各年各季度各农药的抽检样本量在 r text_range(year_quarter_xinjiang_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_xinjiang_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_xinjiang_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_xinjiang_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_xinjiang_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

云南省

year_quarter_yunnan_drug <- year_quarter_province_drug |>
  filter(province == "云南省")

(ref:year-quarter-yunnan-drug) 云南省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_yunnan_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-yunnan-drug)")

  表 \@ref(tab:year-quarter-yunnan-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度云南省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-yunnan-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-yunnan-drug-def-eheatmap)。可以看出，云南省各年各季度各农药的抽检样本量在 r text_range(year_quarter_yunnan_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_yunnan_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_yunnan_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_yunnan_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_yunnan_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

浙江省

year_quarter_zhejiang_drug <- year_quarter_province_drug |>
  filter(province == "浙江省")

(ref:year-quarter-zhejiang-drug) 浙江省各年份各季度各农药检出率与合格率

sp_dable(year_quarter_zhejiang_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-zhejiang-drug)")

  表 \@ref(tab:year-quarter-zhejiang-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度浙江省在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-zhejiang-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-zhejiang-drug-def-eheatmap)。可以看出，浙江省各年各季度各农药的抽检样本量在 r text_range(year_quarter_zhejiang_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_zhejiang_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_zhejiang_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_zhejiang_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_zhejiang_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

重庆市

year_quarter_chongqing_drug <- year_quarter_province_drug |>
  filter(province == "重庆市")

(ref:year-quarter-chongqing-drug) 重庆市各年份各季度各农药检出率与合格率

sp_dable(year_quarter_chongqing_drug |> factor_dims(year, quarter, drug), ref_text = "(ref:year-quarter-chongqing-drug)")

  表 \@ref(tab:year-quarter-chongqing-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度重庆市在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-chongqing-drug-det-eheatmap) - 图 \@ref(fig:year-quarter-chongqing-drug-def-eheatmap)。可以看出，重庆市各年各季度各农药的抽检样本量在 r text_range(year_quarter_chongqing_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_chongqing_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_chongqing_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_chongqing_drug |> combine_year_quarter() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "detection_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_chongqing_drug |> combine_year_quarter() |> change_to_defective() |> shorten_province_name(), 
  x_var = "drug", y_var = "timeline", value_var = "defective_rate_percent",
  y_axis_name = "年份-季度", x_label_fontsize = 11, height = "400%"
)

“年份-季度-蔬菜类别-药品”残留风险

year_quarter_category_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, quarter, category, drug
)

(ref:year-quarter-category-drug) 各年份各季度各蔬菜类别各农药检出率与合格率

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter", "category", "drug"))

sp_dable(
  year_quarter_category_drug |> 
    factor_dims(year, quarter, category, drug), 
  ref_text = "(ref:year-quarter-category-drug)"
)

  表 \@ref(tab:year-quarter-category-drug) 给出了 r year_range[1] 年第一季度 r year_range[2] 年第四季度 r nrow(category) 个蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:year-quarter-category-drug-det-eheatmap) 和图 \@ref(fig:year-quarter-category-drug-def-eheatmap)。可以看出，各年份各季度各蔬菜类别各农药的抽检样本量在 r text_range(year_quarter_category_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_category_drug, "qualification_rate_percent") 之间。

heatmap_echart(
  year_quarter_category_drug |> combine_year_quarter() |> factor_dims(category, drug),
  timeline_var = "timeline", 
  x_var = "drug", y_var = "category", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  year_quarter_category_drug |> combine_year_quarter() |> change_to_defective() |> factor_dims(category, drug),
  timeline_var = "timeline", 
  x_var = "drug", y_var = "category", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

“年份-季度-品种-药品”残留风险

year_quarter_product_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, quarter, product, drug
)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter", "product", "drug"))

(ref:year-quarter-product-drug) 各年份各季度各品种各农药检出率与合格率

sp_dable(
  year_quarter_product_drug |> 
    factor_dims(year, quarter, product, drug), 
  ref_text = "(ref:year-quarter-product-drug)"
)

  表 \@ref(tab:2016-1-product-drug) - 表 \@ref(tab:2020-4-product-drug) 给出了 r year_range[1] 年第一季度 r year_range[2] 年第四季度 r nrow(product) 个蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2016-1-product-drug-det-eheatmap) - 图 \@ref(fig:2020-4-product-drug-def-eheatmap)。可以看出，各年份各季度各蔬菜品种各农药的抽检样本量在 r text_range(year_quarter_product_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_product_drug, "qualification_rate_percent") 之间。

2016 年第一季度

product_drug_2016_1 <- year_quarter_product_drug |>
  filter(year == 2016, quarter == 1)

(ref:2016-1-product-drug) 2016年第一季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2016_1 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2016-1-product-drug)"
)

  表 \@ref(tab:2016-1-product-drug) 给出了 2016 年第一季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2016-1-product-drug-det-eheatmap) - 图 \@ref(fig:2016-1-product-drug-def-eheatmap)。可以看出，2016 年第一季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2016_1, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2016_1, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2016_1, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2016_1,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2016_1 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2016 年第二季度

product_drug_2016_2 <- year_quarter_product_drug |>
  filter(year == 2016, quarter == 2)

(ref:2016-2-product-drug) 2016年第二季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2016_2 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2016-2-product-drug)"
)

  表 \@ref(tab:2016-2-product-drug) 给出了 2016 年第二季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2016-2-product-drug-det-eheatmap) - 图 \@ref(fig:2016-2-product-drug-def-eheatmap)。可以看出，2016 年第二季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2016_2, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2016_2, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2016_2, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2016_2,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2016_2 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2016 年第三季度

product_drug_2016_3 <- year_quarter_product_drug |>
  filter(year == 2016, quarter == 3)

(ref:2016-3-product-drug) 2016年第三季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2016_3 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2016-3-product-drug)"
)

  表 \@ref(tab:2016-3-product-drug) 给出了 2016 年第三季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2016-3-product-drug-det-eheatmap) - 图 \@ref(fig:2016-3-product-drug-def-eheatmap)。可以看出，2016 年第三季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2016_3, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2016_3, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2016_3, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2016_3,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2016_3 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2016 年第四季度

product_drug_2016_4 <- year_quarter_product_drug |>
  filter(year == 2016, quarter == 4)

(ref:2016-4-product-drug) 2016年第四季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2016_4 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2016-4-product-drug)"
)

  表 \@ref(tab:2016-4-product-drug) 给出了 2016 年第四季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2016-4-product-drug-det-eheatmap) - 图 \@ref(fig:2016-4-product-drug-def-eheatmap)。可以看出，2016 年第四季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2016_4, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2016_4, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2016_4, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2016_4,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2016_4 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2017 年第一季度

product_drug_2017_1 <- year_quarter_product_drug |>
  filter(year == 2017, quarter == 1)

(ref:2017-1-product-drug) 2017年第一季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2017_1 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2017-1-product-drug)"
)

  表 \@ref(tab:2017-1-product-drug) 给出了 2017 年第一季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2017-1-product-drug-det-eheatmap) - 图 \@ref(fig:2017-1-product-drug-def-eheatmap)。可以看出，2017 年第一季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2017_1, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2017_1, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2017_1, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2017_1,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2017_1 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2017 年第二季度

product_drug_2017_2 <- year_quarter_product_drug |>
  filter(year == 2017, quarter == 2)

(ref:2017-2-product-drug) 2017年第二季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2017_2 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2017-2-product-drug)"
)

  表 \@ref(tab:2017-2-product-drug) 给出了 2017 年第二季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2017-2-product-drug-det-eheatmap) - 图 \@ref(fig:2017-2-product-drug-def-eheatmap)。可以看出，2017 年第二季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2017_2, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2017_2, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2017_2, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2017_2,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2017_2 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2017 年第三季度

product_drug_2017_3 <- year_quarter_product_drug |>
  filter(year == 2017, quarter == 3)

(ref:2017-3-product-drug) 2017年第三季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2017_3 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2017-3-product-drug)"
)

  表 \@ref(tab:2017-3-product-drug) 给出了 2017 年第三季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2017-3-product-drug-det-eheatmap) - 图 \@ref(fig:2017-3-product-drug-def-eheatmap)。可以看出，2017 年第三季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2017_3, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2017_3, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2017_3, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2017_3,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2017_3 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2017 年第四季度

product_drug_2017_4 <- year_quarter_product_drug |>
  filter(year == 2017, quarter == 4)

(ref:2017-4-product-drug) 2017年第四季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2017_4 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2017-4-product-drug)"
)

  表 \@ref(tab:2017-4-product-drug) 给出了 2017 年第四季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2017-4-product-drug-det-eheatmap) - 图 \@ref(fig:2017-4-product-drug-def-eheatmap)。可以看出，2017 年第四季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2017_4, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2017_4, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2017_4, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2017_4,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2017_4 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2018 年第一季度

product_drug_2018_1 <- year_quarter_product_drug |>
  filter(year == 2018, quarter == 1)

(ref:2018-1-product-drug) 2018年第一季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2018_1 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2018-1-product-drug)"
)

  表 \@ref(tab:2018-1-product-drug) 给出了 2018 年第一季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2018-1-product-drug-det-eheatmap) - 图 \@ref(fig:2018-1-product-drug-def-eheatmap)。可以看出，2018 年第一季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2018_1, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2018_1, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2018_1, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2018_1,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2018_1 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2018 年第二季度

product_drug_2018_2 <- year_quarter_product_drug |>
  filter(year == 2018, quarter == 2)

(ref:2018-2-product-drug) 2018年第二季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2018_2 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2018-2-product-drug)"
)

  表 \@ref(tab:2018-2-product-drug) 给出了 2018 年第二季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2018-2-product-drug-det-eheatmap) - 图 \@ref(fig:2018-2-product-drug-def-eheatmap)。可以看出，2018 年第二季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2018_2, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2018_2, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2018_2, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2018_2,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2018_2 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2018 年第三季度

product_drug_2018_3 <- year_quarter_product_drug |>
  filter(year == 2018, quarter == 3)

(ref:2018-3-product-drug) 2018年第三季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2018_3 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2018-3-product-drug)"
)

  表 \@ref(tab:2018-3-product-drug) 给出了 2018 年第三季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2018-3-product-drug-det-eheatmap) - 图 \@ref(fig:2018-3-product-drug-def-eheatmap)。可以看出，2018 年第三季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2018_3, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2018_3, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2018_3, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2018_3,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2018_3 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2018 年第四季度

product_drug_2018_4 <- year_quarter_product_drug |>
  filter(year == 2018, quarter == 4)

(ref:2018-4-product-drug) 2018年第四季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2018_4 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2018-4-product-drug)"
)

  表 \@ref(tab:2018-4-product-drug) 给出了 2018 年第四季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2018-4-product-drug-det-eheatmap) - 图 \@ref(fig:2018-4-product-drug-def-eheatmap)。可以看出，2018 年第四季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2018_4, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2018_4, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2018_4, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2018_4,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2018_4 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2019 年第一季度

product_drug_2019_1 <- year_quarter_product_drug |>
  filter(year == 2019, quarter == 1)

(ref:2019-1-product-drug) 2019年第一季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2019_1 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2019-1-product-drug)"
)

  表 \@ref(tab:2019-1-product-drug) 给出了 2019 年第一季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2019-1-product-drug-det-eheatmap) - 图 \@ref(fig:2019-1-product-drug-def-eheatmap)。可以看出，2019 年第一季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2019_1, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2019_1, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2019_1, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2019_1,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2019_1 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2019 年第二季度

product_drug_2019_2 <- year_quarter_product_drug |>
  filter(year == 2019, quarter == 2)

(ref:2019-2-product-drug) 2019年第二季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2019_2 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2019-2-product-drug)"
)

  表 \@ref(tab:2019-2-product-drug) 给出了 2019 年第二季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2019-2-product-drug-det-eheatmap) - 图 \@ref(fig:2019-2-product-drug-def-eheatmap)。可以看出，2019 年第二季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2019_2, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2019_2, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2019_2, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2019_2,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2019_2 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2019 年第三季度

product_drug_2019_3 <- year_quarter_product_drug |>
  filter(year == 2019, quarter == 3)

(ref:2019-3-product-drug) 2019年第三季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2019_3 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2019-3-product-drug)"
)

  表 \@ref(tab:2019-3-product-drug) 给出了 2019 年第三季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2019-3-product-drug-det-eheatmap) - 图 \@ref(fig:2019-3-product-drug-def-eheatmap)。可以看出，2019 年第三季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2019_3, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2019_3, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2019_3, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2019_3,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2019_3 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2019 年第四季度

product_drug_2019_4 <- year_quarter_product_drug |>
  filter(year == 2019, quarter == 4)

(ref:2019-4-product-drug) 2019年第四季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2019_4 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2019-4-product-drug)"
)

  表 \@ref(tab:2019-4-product-drug) 给出了 2019 年第四季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2019-4-product-drug-det-eheatmap) - 图 \@ref(fig:2019-4-product-drug-def-eheatmap)。可以看出，2019 年第四季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2019_4, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2019_4, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2019_4, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2019_4,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2019_4 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2020 年第一季度

product_drug_2020_1 <- year_quarter_product_drug |>
  filter(year == 2020, quarter == 1)

(ref:2020-1-product-drug) 2020年第一季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2020_1 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2020-1-product-drug)"
)

  表 \@ref(tab:2020-1-product-drug) 给出了 2020 年第一季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2020-1-product-drug-det-eheatmap) - 图 \@ref(fig:2020-1-product-drug-def-eheatmap)。可以看出，2020 年第一季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2020_1, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2020_1, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2020_1, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2020_1,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2020_1 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2020 年第二季度

product_drug_2020_2 <- year_quarter_product_drug |>
  filter(year == 2020, quarter == 2)

(ref:2020-2-product-drug) 2020年第二季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2020_2 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2020-2-product-drug)"
)

  表 \@ref(tab:2020-2-product-drug) 给出了 2020 年第二季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2020-2-product-drug-det-eheatmap) - 图 \@ref(fig:2020-2-product-drug-def-eheatmap)。可以看出，2020 年第二季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2020_2, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2020_2, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2020_2, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2020_2,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2020_2 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2020 年第三季度

product_drug_2020_3 <- year_quarter_product_drug |>
  filter(year == 2020, quarter == 3)

(ref:2020-3-product-drug) 2020年第三季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2020_3 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2020-3-product-drug)"
)

  表 \@ref(tab:2020-3-product-drug) 给出了 2020 年第三季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2020-3-product-drug-det-eheatmap) - 图 \@ref(fig:2020-3-product-drug-def-eheatmap)。可以看出，2020 年第三季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2020_3, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2020_3, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2020_3, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2020_3,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2020_3 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

2020 年第四季度

product_drug_2020_4 <- year_quarter_product_drug |>
  filter(year == 2020, quarter == 4)

(ref:2020-4-product-drug) 2020年第四季度各品种各农药检出率与合格率

sp_dable(
  product_drug_2020_4 |> factor_dims(year, quarter, product, drug),
  ref_text = "(ref:2020-4-product-drug)"
)

  表 \@ref(tab:2020-4-product-drug) 给出了 2020 年第四季度 r nrow(product) 种蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率，其图形展示见图 \@ref(fig:2020-4-product-drug-det-eheatmap) - 图 \@ref(fig:2020-4-product-drug-def-eheatmap)。可以看出，2020 年第四季度各蔬菜品种各农药的抽检样本量在 r text_range(product_drug_2020_4, "sample_size") 之间，检出率稳定在 r text_range(product_drug_2020_4, "detection_rate_percent") 之间，合格率稳定在 r text_range(product_drug_2020_4, "qualification_rate_percent") 之间。

heatmap_echart(
  product_drug_2020_4,
  x_var = "drug", y_var = "product", value_var = "detection_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

heatmap_echart(
  product_drug_2020_4 |> change_to_defective(),
  x_var = "drug", y_var = "product", value_var = "defective_rate_percent",
  x_label_fontsize = 11, height = "400%"
)

“年份-省份-蔬菜类别-药品”残留风险

year_province_category_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, province, category, drug
) |>
  factor_dims(year, province, category, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "province", "category", "drug"))

(ref:year-province-category-drug) 各年份各省份各蔬菜类别各农药检出率与合格率

sp_dable(year_province_category_drug, ref_text = "(ref:year-province-category-drug)")

  表 \@ref(tab:year-province-category-drug) 给出了 r year_range[1] - r year_range[2] 年 r nrow(province) 个省市自治区 r nrow(category) 个蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率。可以看出，各年份各省市自治区各蔬菜类别各农药的抽检样本量在 r text_range(year_province_category_drug, "sample_size") 之间，检出率稳定在 r text_range(year_province_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_province_category_drug, "qualification_rate_percent") 之间。

“年份-省份-品种-药品”残留风险

year_province_product_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, province, product, drug
) |>
  factor_dims(year, province, product, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "province", "product", "drug"))

(ref:year-province-product-drug) 各年份各省份各品种各农药检出率与合格率

sp_dable(year_province_product_drug, ref_text = "(ref:year-province-product-drug)")

  表 \@ref(tab:year-province-product-drug) 给出了 r year_range[1] - r year_range[2] 年 r nrow(province) 个省市自治区 r nrow(product) 个蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率。可以看出，各年份各省市自治区各蔬菜品种各农药的抽检样本量在 r text_range(year_province_product_drug, "sample_size") 之间，检出率稳定在 r text_range(year_province_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_province_product_drug, "qualification_rate_percent") 之间。

“季度-省份-蔬菜类别-药品”残留风险

quarter_province_category_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  quarter, province, category, drug
) |>
  factor_dims(quarter, province, category, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "province", "category", "drug"))

(ref:quarter-province-category-drug) 各季度各省份各蔬菜类别各农药检出率与合格率

sp_dable(
  quarter_province_category_drug, 
  ref_text = "(ref:quarter-province-category-drug)"
)

  表 \@ref(tab:quarter-province-category-drug) 给出了 r nrow(province) 个省市自治区 r nrow(category) 个蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率。可以看出，各季度各省市自治区各蔬菜类别各农药的抽检样本量在 r text_range(quarter_province_category_drug, "sample_size") 之间，检出率稳定在 r text_range(quarter_province_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(quarter_province_category_drug, "qualification_rate_percent") 之间。

“季度-省份-品种-药品”残留风险

quarter_province_product_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  quarter, province, product, drug
) |>
  factor_dims(quarter, province, product, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("quarter", "province", "product", "drug"))

(ref:quarter-province-product-drug) 各季度各省份各品种各农药检出率与合格率

sp_dable(quarter_province_product_drug, ref_text = "(ref:quarter-province-product-drug)")

  表 \@ref(tab:quarter-province-product-drug) 给出了 r nrow(province) 个省市自治区 r nrow(product) 个蔬菜品种在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率。可以看出，各季度各省市自治区各蔬菜品种各农药的抽检样本量在 r text_range(quarter_province_product_drug, "sample_size") 之间，检出率稳定在 r text_range(quarter_province_product_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(quarter_province_product_drug, "qualification_rate_percent") 之间。

“年份-季度-省份-产品类别-药品”残留风险

year_quarter_province_category_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, quarter, province, category, drug
) |>
  factor_dims(year, quarter, province, category, drug)

r text_threshold(threshold_data = ana_threshold, dims = ana_dims, ana_dims = c("year", "quarter", "province", "category", "drug"))

(ref:year-quarter-province-category-drug) 各年份各季度各省份各蔬菜类别各农药检出率与合格率

sp_dable(
  year_quarter_province_category_drug, 
  ref_text = "(ref:year-quarter-province-category-drug)"
)

  表 \@ref(tab:year-quarter-province-category-drug) 给出了 r year_range[1] 年第一季度到 r year_range[2] 年第四季度 r nrow(province) 个省市自治区 r nrow(category) 个蔬菜类别在 r nrow(drug) 种农药上的抽检样本量、检出率及合格率。可以看出，各年份各季度各省市自治区各蔬菜类别各农药的抽检样本量在 r text_range(year_quarter_province_category_drug, "sample_size") 之间，检出率稳定在 r text_range(year_quarter_province_category_drug, "detection_rate_percent") 之间，合格率稳定在 r text_range(year_quarter_province_category_drug, "qualification_rate_percent") 之间。

`r if (FALSE) '

“年份-季度-省份-品种-药品”残留风险（不分析）

'`

year_quarter_province_product_drug <- spec_dataset(
  dims_comb_data, ana_dims, ana_threshold, "product_drug", 
  year, quarter, province, product, drug
) |>
  factor_dims(year, quarter, province, product, drug)

(ref:year-quarter-province-product-drug) 各年份各季度各省份各品种各农药检出率与合格率

sp_dable(
  year_quarter_province_product_drug, 
  ref_text = "(ref:year-quarter-province-product-drug)"
)

YuanchenZhu2020/antgreens documentation built on Dec. 18, 2021, 8:20 p.m.