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Pandas DataFrame all() Method

❮ DataFrame Reference


Example

Check if all values in each row (index) are True:

import pandas as pd

data = [[True, False, True], [True, True, True]]
df = pd.DataFrame(data)

print(df.all())
Try it Yourself »

Definition and Usage

The all() method returns one value for each column, True if ALL values in that column are True, otherwise False.

By specifying the column axis (axis='columns'), the all() method returns True if ALL values in that axis are True.


Syntax

dataframe.all(axis, bool_only, skipna, level, kwargs)

Parameters

The axis, bool_only, skipna, level parameters are keyword arguments.

Parameter Value Description
axis 0
1
'index'
'columns'
Optional, Which axis to check, default 0.
bool_only None
True
False
Optional. Specify whether to only check Boolean columns or not. Default None
skip_na True
False
Optional, default True. Set to False if the result should NOT skip NULL values
level Number
level name
Optional, default None. Specifies which level ( in a hierarchical multi index) to count along
kwargs   Optional, keyword arguments. These arguments has no effect, but could be accepted by a NumPy function

 Return Value

A Series of True and False values.

If the level argument is specified, this method will return a DataFrame object.

This function does NOT make changes to the original DataFrame object.


❮ DataFrame Reference