in R, how to automatically plots based on lists?

Question

I\'ve got a survey results for two products categories, here is the data

surveyresults<-data.frame(\"Name\"=c(\"Adam\",\"John\"),
\"Gender\"=c(\"m\",\"m\         


        

Answer 1

Here, we could reshape into 'long' format and then use ggplot to plot

library(dplyr)
library(tidyr)
library(ggplot2)
library(plotly)
p1 <- surveyresults %>%
      type.convert(as.is = TRUE) %>%
      pivot_longer(cols = fash_pay_cash:elc_DlvTime_afternoon, 
        names_to = c("group", ".value"), names_pattern = "^(\\w+_\\w+)_(\\w+)$") %>% 
      pivot_longer(cols = cash:afternoon, values_drop_na = TRUE) %>% 
      group_by(group, name) %>%
      summarise(value = sum(value)) %>%
      ggplot(aes(x = name, y = value, fill = group)) + 
        geom_col(position = 'dodge') +
        facet_wrap(vars(group))

ggplotly(p1)

-output

---

Or we can use facet_wrap_paginate from ggforce

library(ggforce)
p1 <- surveyresults %>%
       type.convert(as.is = TRUE) %>%
       pivot_longer(cols = fash_pay_cash:elc_DlvTime_afternoon, 
         names_to = c("group", ".value"),
               names_pattern = "^(\\w+_\\w+)_(\\w+)$") %>% 
       pivot_longer(cols = cash:afternoon, values_drop_na = TRUE) %>% 
       group_by(group, name) %>%
       summarise(value = sum(value)) %>%
       ggplot(aes(x = name, y = value, fill = group)) + 
         geom_col(position = 'dodge') +
         facet_wrap_paginate(~ group, ncol = 1, nrow = 2, page = 2)

n <- n_pages(p1)
pdf('surveyout.pdf')
for(i in seq_len(n)) print(p1 + 
           facet_wrap_paginate(~ group, ncol = 1, nrow = 2, page = i))
dev.off()

---

Or it can be split into smaller subsets, create ggplot in each and then apply the plotly on it separately

library(purrr)
lstOut <- surveyresults %>%
           type.convert(as.is = TRUE) %>%
           pivot_longer(cols = fash_pay_cash:elc_DlvTime_afternoon, 
              names_to = c("group", ".value"),
                names_pattern = "^(\\w+_\\w+)_(\\w+)$") %>% 
           pivot_longer(cols = cash:afternoon, values_drop_na = TRUE) %>% 
           group_by(group, name) %>%
           summarise(value = sum(value)) %>%
           ungroup %>%
           group_split(grp =(as.integer(factor(group, 
               levels = unique(group)))%/% 3) + 1) %>%
           map(~ 
             ggplot(.x, aes(x = name, y = value, fill = group)) + 
             geom_col(position = 'dodge') +
             facet_wrap(vars(group)) -> p)

ggplotly(lstOut[[1]])
ggplotly(lstOut[[2]])