pandas.DataFrame.any() function with example in python

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pandas.DataFrame.any(): This function return whether any element is True, potentially over an axis.
Syntax: DataFrame.any(axis=0, bool_only=None, skipna=True, level=None, **kwargs)[source]
Returns False unless there at least one element within a series or along a Dataframe axis that is True or equivalent (e.g. non-zero or non-empty).

axis : {0 or ‘index’, 1 or ‘columns’, None}, default 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 None
Include only boolean columns. If None, will attempt to use everything, then use only boolean data. Not implemented for Series.

skipna : bool, default True
Exclude NA/null values. If the entire row/column is NA and skipna is True, then the result will be False, 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 None
If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series.

**kwargs : any, default None
Additional keywords have no effect but might be accepted for compatibility with NumPy.

Series or DataFrame
If level is specified, then, DataFrame is returned; otherwise, Series is returned.

#Example program on dataframe.any()

import pandas as pd import numpy as np df = pd.DataFrame({'x': [1, 2, 2,3,np.nan,0], 'y': [10,20,30,40,50,60]}) print(df.any())


x    True
y    True
dtype: bool




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