In gabrielburcea/cvindia: Analysis of symptoms
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
echo = FALSE,
warning = FALSE,
message = FALSE
)
library(magrittr)
library(tidyverse)
data <- read_csv("/Users/gabrielburcea/rprojects/data/your.md/cleaned_data_22092020.csv")
world_map_plot <- cvindia::count_map_world(data = data, item = "world", start_date = "2020-04-09", end_date = "2020-09-01", plot_chart = TRUE, title = "World Map")
world_map_plot
world_map_numbers <- cvindia::count_map_world(data = data, item = "world", start_date = "2020-04-09", end_date = "2020-09-01", plot_chart = FALSE, title = "World Map")
world_map_n <- world_map_numbers %>%
arrange(desc(percentage)) %>% top_n(10) %>%
rename(Country = country, Count = count, Percentage = percentage)
knitr::kable(world_map_n)
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
sympt_pos_age_band
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"),
plot_chart = FALSE )
sympt_pos_age_band <- sympt_pos_age_band %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(sympt_pos_age_band)
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_plot <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
comorb_age_band_plot
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_numbers <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
comorb_age_band_numbers
comorb_age_band_numbers <- comorb_age_band_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(comorb_age_band_numbers)
Gender and age band 20-39
age_band_gender_plot <-cvindia::gender_age_band(data = data, age_category = "20-39", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 20-39
age_band_gender_numbers <- cvindia::gender_age_band(data = data, age_category = "20-39", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Gender and age band 40-59
age_band_gender_plot <-cvindia::gender_age_band(data = data, age_category = "40-59", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 40-59
age_band_gender_numbers <- cvindia::gender_age_band(data = data, age_category = "40-59", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Gender and age band 60+
age_band_gender_plot <-cvindia::gender_age_band(data = data, age_category = "60+", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 60+
age_band_gender_numbers <- cvindia::gender_age_band(data = data, age_category = "60+", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Covid status across symptoms
covid_status_symptoms_plo <- cvindia::covid_status_symptoms(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
covid_status_symptoms_plo
covid_status_symptoms_numbers <- cvindia::covid_status_symptoms(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
covid_status_symptoms_n <- covid_status_symptoms_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
covid_status_symptoms_n
covid_status_comorbidities_plot <- cvindia::comorbidities_covid_status(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
covid_status_comorbidities_plot
covid_status_comorbidities_numbers <- cvindia::comorbidities_covid_status(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
covid_st_no <- covid_status_comorbidities_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(covid_st_no)
Covid status and gender
gender_positive_plot <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = TRUE)
gender_positive_plot
gender_positive_numbers <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = FALSE)
knitr::kable(gender_positive_numbers)
gender_showsympt_plot <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = TRUE)
gender_showsympt_plot
gender_showsympt_numbers <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = FALSE)
knitr::kable(gender_showsympt_numbers)
gender_negative_plot <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = TRUE)
gender_negative_plot
gender_negative_numbers <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = FALSE)
knitr::kable(gender_negative_numbers)
Countries under analysis
United Kingdom - analysis
uk_data <- read_csv("/Users/gabrielburcea/rprojects/data/your.md/uk_data_22092020.csv")
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
sympt_pos_age_band
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"),
plot_chart = FALSE )
sympt_pos_age_band <- sympt_pos_age_band %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(sympt_pos_age_band)
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_plot <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
comorb_age_band_plot
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_numbers <- cvindia::comorbidities_age_band(uk_data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
comorb_age_band_numbers
comorb_age_band_numbers <- comorb_age_band_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(comorb_age_band_numbers)
Gender and age band 20-39
age_band_gender_plot <-cvindia::gender_age_band(data = uk_data, age_category = "20-39", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 20-39
age_band_gender_numbers <- cvindia::gender_age_band(data = uk_data, age_category = "20-39", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Gender and age band 40-59
age_band_gender_plot <-cvindia::gender_age_band(data = uk_data, age_category = "40-59", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 40-59
age_band_gender_numbers <- cvindia::gender_age_band(data = uk_data, age_category = "40-59", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Gender and age band 60+
age_band_gender_plot <-cvindia::gender_age_band(data = uk_data, age_category = "60+", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 60+
age_band_gender_numbers <- cvindia::gender_age_band(data = uk_data, age_category = "60+", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Covid status across symptoms
covid_status_symptoms_plo <- cvindia::covid_status_symptoms(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
covid_status_symptoms_plo
covid_status_symptoms_numbers <- cvindia::covid_status_symptoms(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
covid_status_symptoms_n <- covid_status_symptoms_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(covid_status_symptoms_n)
covid_status_comorbidities_plot <- cvindia::comorbidities_covid_status(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
covid_status_comorbidities_plot
covid_status_comorbidities_numbers <- cvindia::comorbidities_covid_status(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
covid_st_no <- covid_status_comorbidities_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(covid_st_no)
Covid status and gender
gender_positive_plot <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = TRUE)
gender_positive_plot
gender_positive_numbers <- cvindia::gender_covid_status(uk_data, covid_status = "positive", plot_chart = FALSE)
knitr::kable(gender_positive_numbers)
gender_showsympt_plot <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = TRUE)
gender_showsympt_plot
gender_showsympt_numbers <- cvindia::gender_covid_status(uk_data, covid_status = "showing symptoms", plot_chart = FALSE)
knitr::kable(gender_showsympt_numbers)
gender_negative_plot <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = TRUE)
gender_negative_plot
gender_negative_numbers <- cvindia::gender_covid_status(uk_data, covid_status = "negative", plot_chart = FALSE)
knitr::kable(gender_negative_numbers)
India analysis
indian_data <- read_csv("/Users/gabrielburcea/rprojects/data/your.md/indian_data_22092020.csv")
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
sympt_pos_age_band
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"),
plot_chart = FALSE )
sympt_pos_age_band <- sympt_pos_age_band %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(sympt_pos_age_band)
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_plot <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
comorb_age_band_plot
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_numbers <- cvindia::comorbidities_age_band(indian_data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
comorb_age_band_numbers
comorb_age_band_numbers <- comorb_age_band_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(comorb_age_band_numbers)
Gender and age band 20-39
age_band_gender_plot <-cvindia::gender_age_band(data = indian_data, age_category = "20-39", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 20-39
age_band_gender_numbers <- cvindia::gender_age_band(data = indian_data, age_category = "20-39", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Gender and age band 40-59
age_band_gender_plot <-cvindia::gender_age_band(data = indian_data, age_category = "40-59", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 40-59
age_band_gender_numbers <- cvindia::gender_age_band(data = indian_data, age_category = "40-59", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Gender and age band 60+
age_band_gender_plot <-cvindia::gender_age_band(data = indian_data, age_category = "60+", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 60+
age_band_gender_numbers <- cvindia::gender_age_band(data = indian_data, age_category = "60+", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Covid status across symptoms
covid_status_symptoms_plo <- cvindia::covid_status_symptoms(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
covid_status_symptoms_plo
covid_status_symptoms_numbers <- cvindia::covid_status_symptoms(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
covid_status_symptoms_n <- covid_status_symptoms_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(covid_status_symptoms_n)
covid_status_comorbidities_plot <- cvindia::comorbidities_covid_status(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
covid_status_comorbidities_plot
covid_status_comorbidities_numbers <- cvindia::comorbidities_covid_status(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
covid_st_no <- covid_status_comorbidities_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(covid_st_no)
Covid status and gender
gender_positive_plot <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = TRUE)
gender_positive_plot
gender_positive_numbers <- cvindia::gender_covid_status(indian_data, covid_status = "positive", plot_chart = FALSE)
knitr::kable(gender_positive_numbers)
gender_showsympt_plot <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = TRUE)
gender_showsympt_plot
gender_showsympt_numbers <- cvindia::gender_covid_status(indian_data, covid_status = "showing symptoms", plot_chart = FALSE)
knitr::kable(gender_showsympt_numbers)
gender_negative_plot <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = TRUE)
gender_negative_plot
gender_negative_numbers <- cvindia::gender_covid_status(indian_data, covid_status = "negative", plot_chart = FALSE)
knitr::kable(gender_negative_numbers)
mexico_data <- read_csv("/Users/gabrielburcea/rprojects/data/your.md/mexico_data_22092020.csv")
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
sympt_pos_age_band
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"),
plot_chart = FALSE )
sympt_pos_age_band <- sympt_pos_age_band %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(sympt_pos_age_band)
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_plot <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
comorb_age_band_plot
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_numbers <- cvindia::comorbidities_age_band(mexico_data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
comorb_age_band_numbers
comorb_age_band_numbers <- comorb_age_band_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(comorb_age_band_numbers)
Gender and age band 20-39
age_band_gender_plot <-cvindia::gender_age_band(data = mexico_data, age_category = "20-39", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 20-39
age_band_gender_numbers <- cvindia::gender_age_band(data = mexico_data, age_category = "20-39", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Gender and age band 40-59
age_band_gender_plot <-cvindia::gender_age_band(data = mexico_data, age_category = "40-59", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 40-59
age_band_gender_numbers <- cvindia::gender_age_band(data = mexico_data, age_category = "40-59", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Gender and age band 60+
age_band_gender_plot <-cvindia::gender_age_band(data = mexico_data, age_category = "60+", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 60+
age_band_gender_numbers <- cvindia::gender_age_band(data = mexico_data, age_category = "60+", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Covid status across symptoms
covid_status_symptoms_plo <- cvindia::covid_status_symptoms(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
covid_status_symptoms_plo
covid_status_symptoms_numbers <- cvindia::covid_status_symptoms(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
covid_status_symptoms_n <- covid_status_symptoms_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(covid_status_symptoms_n)
covid_status_comorbidities_plot <- cvindia::comorbidities_covid_status(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
covid_status_comorbidities_plot
covid_status_comorbidities_numbers <- cvindia::comorbidities_covid_status(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
covid_st_no <- covid_status_comorbidities_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(covid_st_no)
Covid status and gender
gender_positive_plot <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = TRUE)
gender_positive_plot
gender_positive_numbers <- cvindia::gender_covid_status(mexico_data, covid_status = "positive", plot_chart = FALSE)
knitr::kable(gender_positive_numbers)
gender_showsympt_plot <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = TRUE)
gender_showsympt_plot
gender_showsympt_numbers <- cvindia::gender_covid_status(mexico_data, covid_status = "showing symptoms", plot_chart = FALSE)
knitr::kable(gender_showsympt_numbers)
gender_negative_plot <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = TRUE)
gender_negative_plot
gender_negative_numbers <- cvindia::gender_covid_status(mexico_data, covid_status = "negative", plot_chart = FALSE)
knitr::kable(gender_negative_numbers)
Phillipines analysis
phillipines_data <- read_csv("/Users/gabrielburcea/rprojects/data/your.md/phillipines_data.csv")
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
sympt_pos_age_band
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"),
plot_chart = FALSE )
sympt_pos_age_band <- sympt_pos_age_band %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(sympt_pos_age_band)
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_plot <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
comorb_age_band_plot
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_numbers <- cvindia::comorbidities_age_band(phillipines_data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
comorb_age_band_numbers
comorb_age_band_numbers <- comorb_age_band_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(comorb_age_band_numbers)
Gender and age band 20-39
age_band_gender_plot <-cvindia::gender_age_band(data = phillipines_data, age_category = "20-39", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 20-39
age_band_gender_numbers <- cvindia::gender_age_band(data = phillipines_data, age_category = "20-39", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Gender and age band 40-59
age_band_gender_plot <-cvindia::gender_age_band(data = phillipines_data, age_category = "40-59", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 40-59
age_band_gender_numbers <- cvindia::gender_age_band(data = phillipines_data, age_category = "40-59", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Gender and age band 60+
age_band_gender_plot <-cvindia::gender_age_band(data = phillipines_data, age_category = "60+", plot_chart = TRUE)
age_band_gender_plot
Gender and age band 60+
age_band_gender_numbers <- cvindia::gender_age_band(data = phillipines_data, age_category = "60+", plot_chart = FALSE)
knitr::kable(age_band_gender_numbers)
Covid status across symptoms
covid_status_symptoms_plo <- cvindia::covid_status_symptoms(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
covid_status_symptoms_plo
covid_status_symptoms_numbers <- cvindia::covid_status_symptoms(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
covid_status_symptoms_n <- covid_status_symptoms_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(covid_status_symptoms_n)
covid_status_comorbidities_plot <- cvindia::comorbidities_covid_status(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE)
covid_status_comorbidities_plot
covid_status_comorbidities_numbers <- cvindia::comorbidities_covid_status(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE)
covid_st_no <- covid_status_comorbidities_numbers %>%
arrange(desc(percentage)) %>% top_n(5)
knitr::kable(covid_st_no)
Covid status and gender
gender_positive_plot <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = TRUE)
gender_positive_plot
gender_positive_numbers <- cvindia::gender_covid_status(phillipines_data, covid_status = "positive", plot_chart = FALSE)
knitr::kable(gender_positive_numbers)
gender_showsympt_plot <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = TRUE)
gender_showsympt_plot
gender_showsympt_numbers <- cvindia::gender_covid_status(phillipines_data, covid_status = "showing symptoms", plot_chart = FALSE)
knitr::kable(gender_showsympt_numbers)
gender_negative_plot <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = TRUE)
gender_negative_plot
gender_negative_numbers <- cvindia::gender_covid_status(phillipines_data, covid_status = "negative", plot_chart = FALSE)
knitr::kable(gender_negative_numbers)
gabrielburcea/cvindia documentation built on Feb. 17, 2021, 3:31 a.m.
R Package Documentation
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knitr::opts_chunk$set( collapse = TRUE, comment = "#>", echo = FALSE, warning = FALSE, message = FALSE ) library(magrittr) library(tidyverse)
data <- read_csv("/Users/gabrielburcea/rprojects/data/your.md/cleaned_data_22092020.csv")
world_map_plot <- cvindia::count_map_world(data = data, item = "world", start_date = "2020-04-09", end_date = "2020-09-01", plot_chart = TRUE, title = "World Map") world_map_plot
world_map_numbers <- cvindia::count_map_world(data = data, item = "world", start_date = "2020-04-09", end_date = "2020-09-01", plot_chart = FALSE, title = "World Map") world_map_n <- world_map_numbers %>% arrange(desc(percentage)) %>% top_n(10) %>% rename(Country = country, Count = count, Percentage = percentage) knitr::kable(world_map_n)
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) sympt_pos_age_band
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE ) sympt_pos_age_band <- sympt_pos_age_band %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(sympt_pos_age_band)
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_plot <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) comorb_age_band_plot
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_numbers <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) comorb_age_band_numbers comorb_age_band_numbers <- comorb_age_band_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(comorb_age_band_numbers)
Gender and age band 20-39
age_band_gender_plot <-cvindia::gender_age_band(data = data, age_category = "20-39", plot_chart = TRUE) age_band_gender_plot
Gender and age band 20-39
age_band_gender_numbers <- cvindia::gender_age_band(data = data, age_category = "20-39", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Gender and age band 40-59
age_band_gender_plot <-cvindia::gender_age_band(data = data, age_category = "40-59", plot_chart = TRUE) age_band_gender_plot
Gender and age band 40-59
age_band_gender_numbers <- cvindia::gender_age_band(data = data, age_category = "40-59", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Gender and age band 60+
age_band_gender_plot <-cvindia::gender_age_band(data = data, age_category = "60+", plot_chart = TRUE) age_band_gender_plot
Gender and age band 60+
age_band_gender_numbers <- cvindia::gender_age_band(data = data, age_category = "60+", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Covid status across symptoms
covid_status_symptoms_plo <- cvindia::covid_status_symptoms(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) covid_status_symptoms_plo
covid_status_symptoms_numbers <- cvindia::covid_status_symptoms(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) covid_status_symptoms_n <- covid_status_symptoms_numbers %>% arrange(desc(percentage)) %>% top_n(5) covid_status_symptoms_n
covid_status_comorbidities_plot <- cvindia::comorbidities_covid_status(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) covid_status_comorbidities_plot
covid_status_comorbidities_numbers <- cvindia::comorbidities_covid_status(data = data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) covid_st_no <- covid_status_comorbidities_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(covid_st_no)
Covid status and gender
gender_positive_plot <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = TRUE) gender_positive_plot
gender_positive_numbers <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = FALSE) knitr::kable(gender_positive_numbers)
gender_showsympt_plot <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = TRUE) gender_showsympt_plot
gender_showsympt_numbers <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = FALSE) knitr::kable(gender_showsympt_numbers)
gender_negative_plot <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = TRUE) gender_negative_plot
gender_negative_numbers <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = FALSE) knitr::kable(gender_negative_numbers)
Countries under analysis
United Kingdom - analysis
uk_data <- read_csv("/Users/gabrielburcea/rprojects/data/your.md/uk_data_22092020.csv")
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) sympt_pos_age_band
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE ) sympt_pos_age_band <- sympt_pos_age_band %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(sympt_pos_age_band)
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_plot <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) comorb_age_band_plot
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_numbers <- cvindia::comorbidities_age_band(uk_data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) comorb_age_band_numbers comorb_age_band_numbers <- comorb_age_band_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(comorb_age_band_numbers)
Gender and age band 20-39
age_band_gender_plot <-cvindia::gender_age_band(data = uk_data, age_category = "20-39", plot_chart = TRUE) age_band_gender_plot
Gender and age band 20-39
age_band_gender_numbers <- cvindia::gender_age_band(data = uk_data, age_category = "20-39", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Gender and age band 40-59
age_band_gender_plot <-cvindia::gender_age_band(data = uk_data, age_category = "40-59", plot_chart = TRUE) age_band_gender_plot
Gender and age band 40-59
age_band_gender_numbers <- cvindia::gender_age_band(data = uk_data, age_category = "40-59", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Gender and age band 60+
age_band_gender_plot <-cvindia::gender_age_band(data = uk_data, age_category = "60+", plot_chart = TRUE) age_band_gender_plot
Gender and age band 60+
age_band_gender_numbers <- cvindia::gender_age_band(data = uk_data, age_category = "60+", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Covid status across symptoms
covid_status_symptoms_plo <- cvindia::covid_status_symptoms(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) covid_status_symptoms_plo
covid_status_symptoms_numbers <- cvindia::covid_status_symptoms(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) covid_status_symptoms_n <- covid_status_symptoms_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(covid_status_symptoms_n)
covid_status_comorbidities_plot <- cvindia::comorbidities_covid_status(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) covid_status_comorbidities_plot
covid_status_comorbidities_numbers <- cvindia::comorbidities_covid_status(data = uk_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) covid_st_no <- covid_status_comorbidities_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(covid_st_no)
Covid status and gender
gender_positive_plot <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = TRUE) gender_positive_plot
gender_positive_numbers <- cvindia::gender_covid_status(uk_data, covid_status = "positive", plot_chart = FALSE) knitr::kable(gender_positive_numbers)
gender_showsympt_plot <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = TRUE) gender_showsympt_plot
gender_showsympt_numbers <- cvindia::gender_covid_status(uk_data, covid_status = "showing symptoms", plot_chart = FALSE) knitr::kable(gender_showsympt_numbers)
gender_negative_plot <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = TRUE) gender_negative_plot
gender_negative_numbers <- cvindia::gender_covid_status(uk_data, covid_status = "negative", plot_chart = FALSE) knitr::kable(gender_negative_numbers)
India analysis
indian_data <- read_csv("/Users/gabrielburcea/rprojects/data/your.md/indian_data_22092020.csv")
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) sympt_pos_age_band
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE ) sympt_pos_age_band <- sympt_pos_age_band %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(sympt_pos_age_band)
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_plot <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) comorb_age_band_plot
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_numbers <- cvindia::comorbidities_age_band(indian_data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) comorb_age_band_numbers comorb_age_band_numbers <- comorb_age_band_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(comorb_age_band_numbers)
Gender and age band 20-39
age_band_gender_plot <-cvindia::gender_age_band(data = indian_data, age_category = "20-39", plot_chart = TRUE) age_band_gender_plot
Gender and age band 20-39
age_band_gender_numbers <- cvindia::gender_age_band(data = indian_data, age_category = "20-39", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Gender and age band 40-59
age_band_gender_plot <-cvindia::gender_age_band(data = indian_data, age_category = "40-59", plot_chart = TRUE) age_band_gender_plot
Gender and age band 40-59
age_band_gender_numbers <- cvindia::gender_age_band(data = indian_data, age_category = "40-59", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Gender and age band 60+
age_band_gender_plot <-cvindia::gender_age_band(data = indian_data, age_category = "60+", plot_chart = TRUE) age_band_gender_plot
Gender and age band 60+
age_band_gender_numbers <- cvindia::gender_age_band(data = indian_data, age_category = "60+", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Covid status across symptoms
covid_status_symptoms_plo <- cvindia::covid_status_symptoms(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) covid_status_symptoms_plo
covid_status_symptoms_numbers <- cvindia::covid_status_symptoms(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) covid_status_symptoms_n <- covid_status_symptoms_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(covid_status_symptoms_n)
covid_status_comorbidities_plot <- cvindia::comorbidities_covid_status(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) covid_status_comorbidities_plot
covid_status_comorbidities_numbers <- cvindia::comorbidities_covid_status(data = indian_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) covid_st_no <- covid_status_comorbidities_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(covid_st_no)
Covid status and gender
gender_positive_plot <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = TRUE) gender_positive_plot
gender_positive_numbers <- cvindia::gender_covid_status(indian_data, covid_status = "positive", plot_chart = FALSE) knitr::kable(gender_positive_numbers)
gender_showsympt_plot <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = TRUE) gender_showsympt_plot
gender_showsympt_numbers <- cvindia::gender_covid_status(indian_data, covid_status = "showing symptoms", plot_chart = FALSE) knitr::kable(gender_showsympt_numbers)
gender_negative_plot <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = TRUE) gender_negative_plot
gender_negative_numbers <- cvindia::gender_covid_status(indian_data, covid_status = "negative", plot_chart = FALSE) knitr::kable(gender_negative_numbers)
mexico_data <- read_csv("/Users/gabrielburcea/rprojects/data/your.md/mexico_data_22092020.csv")
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) sympt_pos_age_band
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE ) sympt_pos_age_band <- sympt_pos_age_band %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(sympt_pos_age_band)
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_plot <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) comorb_age_band_plot
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_numbers <- cvindia::comorbidities_age_band(mexico_data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) comorb_age_band_numbers comorb_age_band_numbers <- comorb_age_band_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(comorb_age_band_numbers)
Gender and age band 20-39
age_band_gender_plot <-cvindia::gender_age_band(data = mexico_data, age_category = "20-39", plot_chart = TRUE) age_band_gender_plot
Gender and age band 20-39
age_band_gender_numbers <- cvindia::gender_age_band(data = mexico_data, age_category = "20-39", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Gender and age band 40-59
age_band_gender_plot <-cvindia::gender_age_band(data = mexico_data, age_category = "40-59", plot_chart = TRUE) age_band_gender_plot
Gender and age band 40-59
age_band_gender_numbers <- cvindia::gender_age_band(data = mexico_data, age_category = "40-59", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Gender and age band 60+
age_band_gender_plot <-cvindia::gender_age_band(data = mexico_data, age_category = "60+", plot_chart = TRUE) age_band_gender_plot
Gender and age band 60+
age_band_gender_numbers <- cvindia::gender_age_band(data = mexico_data, age_category = "60+", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Covid status across symptoms
covid_status_symptoms_plo <- cvindia::covid_status_symptoms(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) covid_status_symptoms_plo
covid_status_symptoms_numbers <- cvindia::covid_status_symptoms(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) covid_status_symptoms_n <- covid_status_symptoms_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(covid_status_symptoms_n)
covid_status_comorbidities_plot <- cvindia::comorbidities_covid_status(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) covid_status_comorbidities_plot
covid_status_comorbidities_numbers <- cvindia::comorbidities_covid_status(data = mexico_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) covid_st_no <- covid_status_comorbidities_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(covid_st_no)
Covid status and gender
gender_positive_plot <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = TRUE) gender_positive_plot
gender_positive_numbers <- cvindia::gender_covid_status(mexico_data, covid_status = "positive", plot_chart = FALSE) knitr::kable(gender_positive_numbers)
gender_showsympt_plot <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = TRUE) gender_showsympt_plot
gender_showsympt_numbers <- cvindia::gender_covid_status(mexico_data, covid_status = "showing symptoms", plot_chart = FALSE) knitr::kable(gender_showsympt_numbers)
gender_negative_plot <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = TRUE) gender_negative_plot
gender_negative_numbers <- cvindia::gender_covid_status(mexico_data, covid_status = "negative", plot_chart = FALSE) knitr::kable(gender_negative_numbers)
Phillipines analysis
phillipines_data <- read_csv("/Users/gabrielburcea/rprojects/data/your.md/phillipines_data.csv")
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) sympt_pos_age_band
Symptoms across age band (20-39; 40-59, 60+)
sympt_pos_age_band <- cvindia::sympt_positive_age_band(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE ) sympt_pos_age_band <- sympt_pos_age_band %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(sympt_pos_age_band)
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_plot <- cvindia::comorbidities_age_band(data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) comorb_age_band_plot
Comorbidities across age band (20-39; 40-59, 60+)
comorb_age_band_numbers <- cvindia::comorbidities_age_band(phillipines_data, start_date = as.Date("2020-04-19"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) comorb_age_band_numbers comorb_age_band_numbers <- comorb_age_band_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(comorb_age_band_numbers)
Gender and age band 20-39
age_band_gender_plot <-cvindia::gender_age_band(data = phillipines_data, age_category = "20-39", plot_chart = TRUE) age_band_gender_plot
Gender and age band 20-39
age_band_gender_numbers <- cvindia::gender_age_band(data = phillipines_data, age_category = "20-39", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Gender and age band 40-59
age_band_gender_plot <-cvindia::gender_age_band(data = phillipines_data, age_category = "40-59", plot_chart = TRUE) age_band_gender_plot
Gender and age band 40-59
age_band_gender_numbers <- cvindia::gender_age_band(data = phillipines_data, age_category = "40-59", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Gender and age band 60+
age_band_gender_plot <-cvindia::gender_age_band(data = phillipines_data, age_category = "60+", plot_chart = TRUE) age_band_gender_plot
Gender and age band 60+
age_band_gender_numbers <- cvindia::gender_age_band(data = phillipines_data, age_category = "60+", plot_chart = FALSE) knitr::kable(age_band_gender_numbers)
Covid status across symptoms
covid_status_symptoms_plo <- cvindia::covid_status_symptoms(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) covid_status_symptoms_plo
covid_status_symptoms_numbers <- cvindia::covid_status_symptoms(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) covid_status_symptoms_n <- covid_status_symptoms_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(covid_status_symptoms_n)
covid_status_comorbidities_plot <- cvindia::comorbidities_covid_status(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = TRUE) covid_status_comorbidities_plot
covid_status_comorbidities_numbers <- cvindia::comorbidities_covid_status(data = phillipines_data, start_date= as.Date("2020-04-09"), end_date = as.Date("2020-09-01"), plot_chart = FALSE) covid_st_no <- covid_status_comorbidities_numbers %>% arrange(desc(percentage)) %>% top_n(5) knitr::kable(covid_st_no)
Covid status and gender
gender_positive_plot <- cvindia::gender_covid_status(data, covid_status = "positive", plot_chart = TRUE) gender_positive_plot
gender_positive_numbers <- cvindia::gender_covid_status(phillipines_data, covid_status = "positive", plot_chart = FALSE) knitr::kable(gender_positive_numbers)
gender_showsympt_plot <- cvindia::gender_covid_status(data, covid_status = "showing symptoms", plot_chart = TRUE) gender_showsympt_plot
gender_showsympt_numbers <- cvindia::gender_covid_status(phillipines_data, covid_status = "showing symptoms", plot_chart = FALSE) knitr::kable(gender_showsympt_numbers)
gender_negative_plot <- cvindia::gender_covid_status(data, covid_status = "negative", plot_chart = TRUE) gender_negative_plot
gender_negative_numbers <- cvindia::gender_covid_status(phillipines_data, covid_status = "negative", plot_chart = FALSE) knitr::kable(gender_negative_numbers)
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