search
Search
Publish
menu
menu search toc more_vert
Robocat
Guest 0reps
Thanks for the thanks!
close
Comments
Log in or sign up
Cancel
Post
account_circle
Profile
exit_to_app
Sign out
help Ask a question
Share on Twitter
search
keyboard_voice
close
Searching Tips
Search for a recipe: "Creating a table in MySQL"
Search for an API documentation: "@append"
Search for code: "!dataframe"
Apply a tag filter: "#python"
Useful Shortcuts
/ to open search panel
Esc to close search panel
to navigate between search results
d to clear all current filters
Enter to expand content preview
icon_star
Doc Search
icon_star
Code Search Beta
SORRY NOTHING FOUND!
mic
Start speaking...
Voice search is only supported in Safari and Chrome.
Navigate to
A
A
share
thumb_up_alt
bookmark
arrow_backShare
Twitter
Facebook

Drawing a histogram in Matplotlib

Programming
chevron_right
Python
chevron_right
Matplotlib
chevron_right
Cookbooks
chevron_right
Graphs Cookbook
schedule Mar 9, 2022
Last updated
local_offer PythonMatplotlib
Tags

We can use the ax.hist(~) method to draw a basic histogram in Matplotlib.

Drawing a basic histogram

Object Oriented Interface

To plot a histogram showing the distribution of some numbers:

nums = [1,1,2,3,3,3,3,3,4,5,6,6,6,7,8,8,9,10,12,12,12,12,14,18]
fig,ax = plt.subplots()
ax.hist(nums)
ax.set_xlabel('Number')
ax.set_ylabel('Frequency')
plt.show()

This produces the following output:

Pyplot Interface

To plot the same histogram as above, but using Pyplot Interface:

nums = [1,1,2,3,3,3,3,3,4,5,6,6,6,7,8,8,9,10,12,12,12,12,14,18]
_ = plt.hist(nums)
_ = plt.xlabel('Number')
_ = plt.ylabel('Frequency')
plt.show()

It is good practice to assign the various plotting statements to a dummy variable _ so that we do not display any unnecessary output.

Setting the number of bins

By default the number of bins is 10, however, we can customize this using the bins argument:

nums = [1,1,2,3,3,3,3,3,4,5,6,6,6,7,8,8,9,10,12,12,12,12,14,18]
fig,ax = plt.subplots()
ax.hist(nums, bins=5)
plt.show()

Now the output histogram only has 5 bins:

Multiple variables on the same histogram

We can plot multiple variables on the same histogram:

nums1 = [1,1,2,3,3,3,3,3,4,5,6,6,6,7,8,8,9,10,12,12,12,12,14,18]
nums2= [10,12,13,13,14,14,15,15,15,16,17,18,20,22,23]
fig,ax = plt.subplots()
ax.hist(nums1, label="nums1", histtype="step")
ax.hist(nums2, label="nums2", histtype="step")
plt.legend()
plt.show()

The histtype="step" means we only see the outlines of each histogram. This enables us to easily see the distribution for each variable when there is overlap between the two.

Visualizing the distribution of random numbers

We want to visualize the distribution of random numbers that we generate.

We generate 100 random integers between 0 (inclusive) and 200 (exclusive):

x = np.random.randint(low=0, high=200, size=100)
x
array([122, 76, 147, 160, 100, 173, 62, 21, 50, 150, 75, 19, 87,
...
83, 43, 184, 153, 148, 198, 88, 8, 196])

We then draw a histogram showing the distribution of the data-points:

plt.hist(x, range=(0,200), bins=10, rwidth=0.9)

Here,

  • range is a tuple indicating the lower and upper bound

  • bins is number of bars you want

  • rwidth is the width of each bin. If we set rwidth=1, then there will be no gap between the bins.

The output is as follows:

robocat
Published by Isshin Inada
Edited by 0 others
Did you find this page useful?
thumb_up
thumb_down
Ask a question or leave a feedback...