search
Search
Login
Unlock 100+ guides
menu
menu
web
search toc
close
Outline
Comments
Log in or sign up
Cancel
Post
account_circle
Profile
exit_to_app
Sign out
What does this mean?
Why is this true?
Give me some examples!
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

Pandas DataFrame | shape property

schedule Aug 12, 2023
Last updated
local_offer
PythonPandas
Tags
tocTable of Contents
expand_more
mode_heat
Master the mathematics behind data science with 100+ top-tier guides
Start your free 7-days trial now!

Pandas DataFrame.shape property returns the number of rows and columns in the DataFrame as a tuple.

Examples

Consider the following DataFrame:

df = pd.DataFrame({"A":[4,5],"B":[6,7],"C":[8,9]})
df
   A  B  C
0  4  6  8
1  5  7  9

Here's its shape property:

df.shape
(2, 3)

This means that our DataFrame has 2 rows and 3 columns.

To access the individual values, simply use [~] as you would for any tuple:

print("Rows:", df.shape[0])
print("Columns:", df.shape[1])
Rows: 2
Columns: 3
robocat
Published by Isshin Inada
Edited by 0 others
Did you find this page useful?
thumb_up
thumb_down
Comment
Citation
Ask a question or leave a feedback...
thumb_up
0
thumb_down
0
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!