CODEWITHSUNDEEP
rdataframeggplot2bar-chartmutate
Katlego Motsatsing
Katlego Motsatsing

Reputation: 21

Plotting a bar chart in R

# A tibble: 6 × 7
  No    Region     District `Name of School`  Male Female Total
  <chr> <fct>      <fct>    <chr>            <dbl>  <dbl> <dbl>
1 1     South East Gaborone Bokamoso CJSS      545    516  1061
2 2     South East Gaborone Marang CJSS        550    567  1117
3 3     South East Gaborone Nanogang CJSS      493    558  1051
4 4     South East Gaborone Maikano CJSS       440    388   828
5 5     South East Gaborone Motswedi CJSS      443    475   918
6 6     South East Gaborone Gaborone West      415    401   816

i want to declare and add a new categorical variable Gender to my data. the gender variable should depend on the values of males and females already provided in the dataset. The point is to plot a grouped bar chart where Region is divided into gender categories in the x axis

# A tibble: 6 × 7
  No    Region     District `Name of School`  Male Female Total
  <chr> <fct>      <fct>    <chr>            <dbl>  <dbl> <dbl>
1 1     South East Gaborone Bokamoso CJSS      545    516  1061
2 2     South East Gaborone Marang CJSS        550    567  1117
3 3     South East Gaborone Nanogang CJSS      493    558  1051
4 4     South East Gaborone Maikano CJSS       440    388   828
5 5     South East Gaborone Motswedi CJSS      443    475   918
6 6     South East Gaborone Gaborone West      415    401   816

Upvotes: 2

Views: 62

Answers (2)

Friede
Friede

Reputation: 7979

Adding a basic approach in base R:

X = df[, c("Name.of.School", "Male", "Female")] 
X[-1] |>
  t() |> 
  `colnames<-`(X$Name.of.School) |>
  barplot(beside = TRUE, col = c("lightblue", "red2"), legend = c("M", "F"))

enter image description here

Data

df = data.frame(
  No = c("1", "2", "3", "4", "5", "6"),
  Region = factor(rep("South East", 6)), District = factor(rep("Gaborone", 6)),
  `Name of School` = c("Bokamoso CJSS", "Marang CJSS", "Nanogang CJSS", 
                       "Maikano CJSS", "Motswedi CJSS", "Gaborone West"),
  Male = c(545, 550, 493, 440, 443, 415), Female = c(516, 567, 558, 388, 475, 401),
  Total = c(1061, 1117, 1051, 828, 918, 816))

Upvotes: 1

AnilGoyal
AnilGoyal

Reputation: 26238

You need to learn tidy data principles first

library(tidyverse)

# Create the dataframe df
df <- tibble(
  No = c("1", "2", "3", "4", "5", "6"),
  Region = factor(rep("South East", 6)),
  District = factor(rep("Gaborone", 6)),
  `Name of School` = c("Bokamoso CJSS", "Marang CJSS", "Nanogang CJSS", "Maikano CJSS", "Motswedi CJSS", "Gaborone West"),
  Male = c(545, 550, 493, 440, 443, 415),
  Female = c(516, 567, 558, 388, 475, 401),
  Total = c(1061, 1117, 1051, 828, 918, 816)
)

df %>% 
  select(-Total) %>% 
  pivot_longer(c(Male, Female), names_to = "gender", values_to = "schools") %>% 
  ggplot(aes(`Name of School`, y = schools, fill = gender)) +
  geom_col(position = "dodge")

Created on 2024-03-07 with reprex v2.0.2

Upvotes: 0

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