Overview:
- Pandas DataFrame has methods all() and any() to check whether all or any of the elements across an axis(i.e., row-wise or column-wise) is True.
- all() does a logical AND operation on a row or column of a DataFrame and returns the resultant Boolean value.
- any() does a logical OR operation on a row or column of a DataFrame and returns the resultant Boolean value.
Example – For DataFrame.all() method:
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import pandas as pd
dataDict = {"v1":[True, True], "v2":[True, False], "v3":[True, True]}; dataFrame = pd.DataFrame(data=dataDict); results = dataFrame.all(axis=0);
print("DataFrame:") print(dataFrame)
print("Results:Computed column-wise") print(results)
results = dataFrame.all(axis=1); print("Results:Computed row-wise") print(results) |
Output:
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DataFrame: v1 v2 v3 0 True True True 1 True False True Results:Computed column-wise v1 True v2 False v3 True dtype: bool Results:Computed row-wise 0 True 1 False dtype: bool
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Example – For DataFrame.any() method:
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import pandas as pd
dataValues = {"Column1":[True, False, True], "Column2":[True, True, True], "Column3":[False, False, False]}; dataFrame = pd.DataFrame(data=dataValues); resultData = dataFrame.any();
print("DataFrame"); print(dataFrame);
print("DataFrame:Computed column-wise"); print(resultData);
resultData = dataFrame.any(axis=1); print("Result:Computed row-wise"); print(resultData); |
Output:
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DataFrame: Column1 Column2 Column3 0 True True False 1 False True False 2 True True False DataFrame:Computed column-wise Column1 True Column2 True Column3 False dtype: bool Result:Computed row-wise 0 True 1 True 2 True dtype: bool |