Check if All Elements of DataFrame are True in Pandas

Check if All Elements of DataFrame are True

To check if all elements of a DataFrame are True in Pandas, along an axis: index or columns, call all() method on this DataFrame, with required values for parameters.

In this tutorial, we will learn the syntax of DataFrame.all() method and how to use this method to check if all the elements of given DataFrame are True over an axis, with examples.

Syntax

The syntax of pandas DataFrame.all() method is

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DataFrame.all(axis=0, bool_only=None, skipna=True, level=None, **kwargs)

where

Parameter	Value	Description
axis	{0 or ‘index’, 1 or ‘columns’, None}. default is 0.	Indicate which axis or axes should be reduced. 0 / ‘index’ : reduce the index, return a Series whose index is the original column labels. 1 / ‘columns’ : reduce the columns, return a Series whose index is the original index. None : reduce all axes, return a scalar.
bool_only	bool. default is None.	Include only boolean columns. If None, will attempt to use everything, then use only boolean data. Not implemented for Series.
skipna	bool. default is True.	Exclude NA/null values. If the entire row/column is NA and skipna is True, then the result will be True, as for an empty row/column. If skipna is False, then NA are treated as True, because these are not equal to zero.
level	int or level name. default is None.	If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series.
**kwargs	any. default is None.	Additional keywords have no effect but might be accepted for compatibility with NumPy.

Return Value

This method returns

Series : If level is not specified.
DataFrame: If level is specified.

Examples

Check if Column-wise Values are All True

By default, axis=’index’ for all() method. So, call all() method on DataFrame with default values for parameters to check if column-wise values are all True.

Example.py

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import pandas as pd

df = pd.DataFrame(
    {'col_1': [True, True, True], 'col_2': [True, True, False]})

result = df.all()
print(result)

Output

col_1     True
col_2    False
dtype: bool

Check if Row-wise Values are All True

Pass axis=’columns’ to check if DataFrame has elements all True row-wise.

Example.py

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import pandas as pd

df = pd.DataFrame(
    {'col_1': [True, True, True], 'col_2': [True, True, False]})

result = df.all(axis='columns')
print(result)

Output

0     True
1     True
2    False
dtype: bool

Conclusion

In this Pandas Tutorial, we learned how to check if all the elements of given DataFrame are True along an axis, using pandas DataFrame.all() method.

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Check if All Elements of DataFrame are True in Pandas