search
Search
Login
Math ML Join our weekly DS/ML newsletter
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 | reset_index method

Pandas
chevron_right
Documentation
chevron_right
DataFrame
chevron_right
Data Selection and Renaming
schedule Jul 1, 2022
Last updated
local_offer PythonPandas
Tags

Pandas's DataFrame.reset_index(~) resets the index to the default integer index.

Parameters

1. level | int or string or tuple or list | optional

The levels to reset. This is only relevant if your DataFrame is multi-index. By default, level=None.

2. drop | boolean | optional

  • If True, then the current index will not be added to the DataFrame.

  • If False, then current index will be added to the DataFrame.

By default, drop=False.

3. inplace | boolean | optional

  • If True, then the source DataFrame will be modified directly.

  • If False, then a new DataFrame will be returned.

By default, inplace=False.

4. col_level | int or string | optional

The column levels to place the resetted index. This is only relevant if DataFrame has multi-index columns. By default, col_level=None.

5. col_fill | scalar | optional

The name assigned to the other column levels in the same hierarchy. This is only relevant if DataFrame has multi-index columns. By default, col_fill="".

Return Value

A DataFrame with the index reset to the default integer index.

Examples

Consider the following DataFrame:

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

Reseting the index

Single-index DataFrames

To reset the index of df:

df.reset_index()
index A B
0 a 3 5
1 b 4 6

Note the following:

  • the default integer indices ([0,1]) is the new index

  • the label of the new column is "index"

Multi-index DataFrames

Consider the following multi-index DataFrame:

index = [("A", "alice"), ("A", "bob"),("A", "cathy"), ("B", "david"),("B", "eric")]
multi_index = pd.MultiIndex.from_tuples(index)
df = pd.DataFrame({"a":[2,3,4,5,6]}, index=multi_index)
df
a
A alice 2
bob 3
cathy 4
B david 5
eric 6

By default, level=None, which means that all levels will be reset:

df.reset_index()
level_0 level_1 a
0 A alice 2
1 A bob 3
2 A cathy 4
3 B david 5
4 B eric 6

Notice how the new columns are labelled as level_0 and level_1.

To reset a particular level, pass in level like so:

df.reset_index(level=0)
level_0 a
alice A 2
bob A 3
cathy A 4
david B 5
eric B 6

Dropping the index

Consider the following DataFrame:

df
A B
a 3 5
b 4 6

The default behaviour is to prepend the index to the DataFrame as a column. To prevent this, set drop=True:

df.reset_index(drop=True)
A B
0 3 5
1 4 6

Notice how no new column was added to the DataFrame.

Reseting the index in-place

To reset the index in-place, set inplace=True:

df.reset_index(inplace=True)
df
index A B
0 a 3 5
1 b 4 6

Notice how the original df has been directly modified.

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?
thumb_up
thumb_down
thumb_up
0
thumb_down
0
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!