Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Leer Creating Histograms | Data Visualization
Data Analysis with R

bookCreating Histograms

Why Use Histograms?

Histograms are used to visualize the distribution of continuous (numerical) data. They show how data is spread across ranges (bins) and help us:

  • Detect skewness, outliers, or gaps;

  • Understand frequency distribution;

  • Quickly assess if the data is normally distributed or not.

They are best used for variables like price, mileage, or age.

Basic Histogram Syntax in ggplot2

ggplot(data = df, aes(x = variable)) +
  geom_histogram()

The x variable must be numeric.

Customize using bins, fill, color, theme, etc.

Example: Distribution of Selling Prices

ggplot(data = df, aes(x = selling_price)) +  
  geom_histogram(fill = "steelblue", color = "black") +  
  labs(title = "Distribution of Selling Prices", 
       x = "Selling Price (in PKR)", 
       y = "Count") +
  theme_minimal()

This plot shows how car prices are distributed. It can highlight if most cars fall in a certain price range.

question mark

What does the bins argument in geom_histogram() control?

Select the correct answer

Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 2. Hoofdstuk 3

Vraag AI

expand

Vraag AI

ChatGPT

Vraag wat u wilt of probeer een van de voorgestelde vragen om onze chat te starten.

Suggested prompts:

Can you explain the difference between a histogram and a bar plot?

How do I choose the right number of bins for my histogram?

What does it mean if my histogram is skewed to the right or left?

Awesome!

Completion rate improved to 4

bookCreating Histograms

Veeg om het menu te tonen

Why Use Histograms?

Histograms are used to visualize the distribution of continuous (numerical) data. They show how data is spread across ranges (bins) and help us:

  • Detect skewness, outliers, or gaps;

  • Understand frequency distribution;

  • Quickly assess if the data is normally distributed or not.

They are best used for variables like price, mileage, or age.

Basic Histogram Syntax in ggplot2

ggplot(data = df, aes(x = variable)) +
  geom_histogram()

The x variable must be numeric.

Customize using bins, fill, color, theme, etc.

Example: Distribution of Selling Prices

ggplot(data = df, aes(x = selling_price)) +  
  geom_histogram(fill = "steelblue", color = "black") +  
  labs(title = "Distribution of Selling Prices", 
       x = "Selling Price (in PKR)", 
       y = "Count") +
  theme_minimal()

This plot shows how car prices are distributed. It can highlight if most cars fall in a certain price range.

question mark

What does the bins argument in geom_histogram() control?

Select the correct answer

Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 2. Hoofdstuk 3
some-alt