Pandas DataFrame all() Method
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 |
Optional, Which axis to check, default 0. |
| bool_only | None |
Optional. Specify whether to only check Boolean columns or not. Default None |
| skip_na | True |
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.
