3 Different ways to make bar plots with ggplot2

Creating effective bar plots in ggplot2 requires knowing which function to use for your data structure. This comprehensive guide demonstrates three essential approaches—geom_bar() for raw data, geom_col() for summarized values, and stat_count() for explicit control—with practical R code examples you can immediately apply to your own datasets.”

library(tidyverse)
theme_set(theme_bw(16))

mpg |> head()

# A tibble: 6 × 11
  manufacturer model displ  year   cyl trans      drv     cty   hwy fl    class 
  <chr>        <chr> <dbl> <int> <int> <chr>      <chr> <int> <int> <chr> <chr> 
1 audi         a4      1.8  1999     4 auto(l5)   f        18    29 p     compa…
2 audi         a4      1.8  1999     4 manual(m5) f        21    29 p     compa…
3 audi         a4      2    2008     4 manual(m6) f        20    31 p     compa…
4 audi         a4      2    2008     4 auto(av)   f        21    30 p     compa…
5 audi         a4      2.8  1999     6 auto(l5)   f        16    26 p     compa…
6 audi         a4      2.8  1999     6 manual(m5) f        18    26 p     compa…

Bar plot with geom_bar()

mpg |>
  ggplot(aes(x=class))+
  geom_bar()

Bar plot with stat_count()

mpg |>
  ggplot(aes(x=class))+
  stat_count(geom="bar")

Bar plot with geom_col()

mpg |>
  count(class) |>
  ggplot(aes(x=class, y =n))+
  geom_col()

When to Use Each ggplot2 Bar Plot Function

geom_bar()

Raw Data

Use when: You have individual observations and want ggplot2 to automatically count occurrences.

Perfect for: Survey responses, categorical data like car types, exploring frequency distributions

Data example: A column with “SUV”, “compact”, “SUV”, “midsize” → automatically counts each type

geom_col()

Pre-calculated Data

Use when: Your data already contains the values you want to plot (heights of bars).

Perfect for: Sales by region, population by country, any pre-summarized data

Data example: Region A = 100 sales, Region B = 150 sales → plot these exact values

stat_count()

Same as geom_bar()

Use when: You want the same result as geom_bar() but prefer explicit control over the statistical transformation.

Perfect for: When teaching R code, documenting statistical transformations explicitly

Note: Functionally identical to geom_bar() – use whichever you prefer

Quick Reference

📊 Have individual data points? → Use geom_bar()

📈 Have calculated totals/averages? → Use geom_col()

🎯 Want explicit statistical control? → Use stat_count()

🤔 Not Sure Which to Use?

Start with geom_bar() for raw data or geom_col() for summary data

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