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
check_circle
Mark as learned
thumb_up
2
thumb_down
2
chat_bubble_outline
0
Comment
auto_stories Bi-column layout
settings

Extracting numbers from column in Pandas DataFrame

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!

Consider the following DataFrame:

import pandas as pd
import numpy as np
df = pd.DataFrame({'A':['a10','a 10','09','0',np.nan]})
df
A
0 a10
1 a 10
2 09
3 0
4 NaN

To extract numbers from column A:

df['A'].str.extract('(\d+)') # returns a DataFrame
0
0 10
1 10
2 09
3 0
4 NaN

Here, the argument string is a regex:

  • \d+ represents a number

  • () indicates the group you want to extract

If you wanted a Series instead of a DataFrame:

df['A'].str.extract('(\d+)', expand=False) # returns a Series
0 10
1 10
2 09
3 0
4 NaN
Name: A, dtype: object
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
2
thumb_down
2
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!