# Histograms

This lesson is called Histograms, part of the Fundamentals of R course. This lesson is called Histograms, part of the Fundamentals of R course.

### Transcript

Click on the transcript to go to that point in the video. Please note that transcripts are auto generated and may contain minor inaccuracies.

## View code shown in video

```
# Load Packages -----------------------------------------------------------
library(tidyverse)
# Import Data -------------------------------------------------------------
penguins <- read_csv("penguins.csv")
# Histograms --------------------------------------------------------------
# We use geom_histogram() to make a histogram.
ggplot(data = penguins,
mapping = aes(x = bill_length_mm)) +
geom_histogram()
# How does ggplot know what to plot on the y axis?
# It's using the default statistical transformation for geom_histogram,
# which is stat = "bin".
# If we add stat = "bin" we get the same thing.
# Each geom has a default stat.
ggplot(data = penguins,
mapping = aes(x = bill_length_mm)) +
geom_histogram(stat = "bin")
# We can adjust the number of bins using the bins argument.
ggplot(data = penguins,
mapping = aes(x = bill_length_mm)) +
geom_histogram(bins = 100)
```

## Your Turn

```
# Load Packages -----------------------------------------------------------
library(tidyverse)
# Import Data -------------------------------------------------------------
penguins <- read_csv("penguins.csv")
# Histograms --------------------------------------------------------------
# Make a histogram that shows the distribution of the body_mass_g variable.
# YOUR CODE HERE
# Adjust your histogram so it has 50 bins.
# YOUR CODE HERE
```

## Learn More

You can find examples of code to make histograms on the Data to Viz website , the R Graph Gallery website , and in Chapter 6 of the R Graphics Cookbook , and Chapter 7 of the Fundamentals of Data Visualization.

To learn about more statistical transformations, Chapter 9 of R for Data Science has a discussion of them.

## Have any questions? Put them below and we will help you out!

## Course Content

34 Lessons

1

The Grammar of Graphics

04:39

2

Scatterplots

03:46

3

Histograms

05:47

4

Bar Charts

06:37

5

Setting color and fill Aesthetic Properties

02:39

6

Setting color and fill Scales

05:40

7

Setting x and y Scales

03:09

8

Adding Text to Plots

07:32

9

Plot Labels

03:57

10

Themes

02:19

11

Facets

03:12

12

Save Plots

02:57

13

Bring it All Together (Data Visualization)

06:42

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