search
Search
Join our weekly DS/ML newsletter layers DS/ML Guides
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
brightness_medium
share
arrow_backShare
Twitter
Facebook

Pandas DataFrame | rmod method

Programming
chevron_right
Python
chevron_right
Pandas
chevron_right
Documentation
chevron_right
DataFrame
chevron_right
Binary Operators
schedule Jul 1, 2022
Last updated
local_offer PythonPandas
Tags

Pandas DataFrame.rmod(~) method computes the modulo of the values in the source DataFrame and another scalar, sequence, Series or DataFrame, that is:

other % DataFrame

Note that this is just the reverse of DataFrame.mod(~), which does:

DataFrame % other
NOTE

Unless you use the parameters axis, level and fill_value, rmod(~) is equivalent to computing the modulo using the % operator.

Parameters

1. otherlink | scalar or sequence or Series or DataFrame

The resulting DataFrame will be the modulo of other to the source DataFrame.

2. axislink | int or string | optional

Whether to broadcast other for each column or row of the source DataFrame:

Axis

Description

other is broadcasted for each column.

"index" or 0

other is broadcasted for each row.

"columns" or 1

This is only relevant if the shape of the source DataFrame and that of other does not match up. By default, axis=1.

3. level | int or string | optional

The name or the integer index of the level to consider. This is relevant only if your DataFrame is Multi-index.

4. fill_valuelink | float or None | optional

The value to replace NaN before the computation of the modulo. If both pair of entries are NaN, then its result would also be NaN. By default, fill_value=None.

Return Value

A new DataFrame computed by the modulo.

Examples

Basic usage

Consider the following DataFrames:

df = pd.DataFrame({"A":[2,3], "B":[4,5]})
df_other = pd.DataFrame({"A":[9,8], "B":[7,6]})
A B | A B
0 2 4 | 0 9 7
1 3 5 | 1 8 6

Computing the modulo:

df.rmod(df_other)
A B
0 1 3
1 2 1

Here, we're computing the following element-wise modulo:

9%2 7%4
8%3 6%5

Note that this is equivalent to:

df_other % df
A B
0 1 3
1 2 1

Broadcasting

Consider the following DataFrame:

df = pd.DataFrame({"A":[3,4], "B":[5,6]})
df
A B
0 3 5
1 4 6

Row-wise modulo

By default, axis=1, which means that other will be broadcasted for each row in df:

df.rmod([8,9]) # axis=1
A B
0 2 4
1 0 3

Here, we're computing the following element-wise modulo:

8%3 9%5
8%4 9%6

Column-wise modulo

To broadcast other for each column in df, set axis=0 like so:

df.rmod([8,9], axis=0)
A B
0 2 3
1 1 3

Here, we're computing the following element-wise modulo:

8%3 8%5
9%4 9%6

Specifying fill_value

Consider the following DataFrame:

df = pd.DataFrame({"A":[2,np.NaN], "B":[np.NaN,3]})
df_other = pd.DataFrame({"A":[8,9],"B":[np.NaN,np.NaN]})
A B | A B
0 2.0 NaN | 0 8 NaN
1 NaN 3.0 | 1 9 NaN

By default, when we compute the modulo using rmod(~), any operation with NaN results in NaN:

df.rmod(df_other)
A B
0 0.0 NaN
1 NaN NaN

We can fill the NaN values before we compute the modulo by using the fill_value parameter:

df.rmod(df_other, fill_value=5)
A B
0 0.0 NaN
1 4.0 2.0

Here, notice how when the operation involves two NaN, then the resulting modulo would still be NaN, regardless of fill_value.

mail
Join our newsletter for updates on new DS/ML comprehensive guides (spam-free)
robocat
Published by Isshin Inada
Edited by 0 others
Did you find this page useful?
Ask a question or leave a feedback...
0
thumb_down
0
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!