prep_q44b_meeting_attendance_alt <- function(.data){
.data <- .data[,c("submissionid","maa",
"12a_fishing_men", "12b_fishing_women",
"12c_fishing_children", "44_meeting_attendance")] %>%
tidyr::unnest(cols = `44_meeting_attendance`)
hhs_fishers <- .data[,c("submissionid","maa",
"12a_fishing_men", "12b_fishing_women",
"12c_fishing_children")] %>%
dplyr::filter(`12a_fishing_men` > 0 |
`12b_fishing_women` > 0 |
`12c_fishing_children` > 0) %>%
droplevels()
hhs_Q44f <-
dplyr::left_join(
hhs_fishers[, c("submissionid")],
.data[,c("submissionid",
"maa",
"44_meeting_attendance")],
by = "submissionid") %>%
dplyr::filter(`44_meeting_attendance` != "") %>%
dplyr::filter(`44_meeting_attendance` != "na") %>%
droplevels()
# replace no respond and no management with NO
#hhs_Q44f$`44_meeting_attendance`[hhs_Q44f$`44_meeting_attendance` == ""] <- "No"
#hhs_Q44f$`44_meeting_attendance`[hhs_Q44f$`44_meeting_attendance` == "No management"] <- "No"
Q44f_summary <- proportion(hhs_Q44f[[3]],
hhs_Q44f[[2]],
3,
length(unique(hhs_Q44f[[3]])))
Q44f_summary_long <-
Q44f_summary %>% tidyr::pivot_longer(
cols = names(Q44f_summary[-c(1:2)]),
names_to = "key",
values_to = "Proportion (%)"
)
Q44f_summary_long$key <- stringr::str_replace (Q44f_summary_long$key, "[.]", " ")
Q44f <- clean_plot_data(Q44f_summary_long)
Q44f
}
plot_q44b_meeting_attendance_alt <- function(.data, ...){
.data_plot <- prep_q44b_meeting_attendance_alt(.data)
p <- plot_horiz_bar(
.data_plot,
title = "Proportion of fishers who \nattend management body meetings regularly",
facet_var = key
)
result <- list(
plot = p,
data = .data_plot
)
}
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