search
Search
Publish
menu
menu search toc more_vert
Robocat
Guest 0reps
Thanks for the thanks!
close
Outline
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

Using previous row to create new columns in Pandas DataFrame

Programming
chevron_right
Python
chevron_right
Pandas
chevron_right
Cookbooks
chevron_right
DataFrame Cookbooks
chevron_right
Data Manipulation Cookbook
schedule Jul 1, 2022
Last updated
local_offer PythonPandas
Tags
tocTable of Contents
expand_more

Consider the following DataFrame:

df = pd.DataFrame({'A':[3,4,5]})
df
A
0 3
1 4
2 5

Suppose we wanted to create a new column B from column A where each row is computed using the current row and the previous row. To do so, we first make a new Series that is shifted by one:

series_shifted = df['A'].shift()
series_shifted
0 NaN
1 3.0
2 4.0
Name: A, dtype: float64

We then perform row-wise addition with this shifted series:

df['B'] = df['A'] + series_shifted
df
A B
0 3 NaN
1 4 7.0
2 5 9.0
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...
thumb_up
0
thumb_down
0
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!