Question

How can I reduce data set by deleting any rows that have all FALSE values for every column in
that row using pandas. Example: The table data below the pandas code should drop/reduce the data to remove the second & fifth row. Treat The Dtype for the True and False values as object.

id	Test1	value1	value2	value3	value4
0.1	1	False	False	False	False
0.2	2	False	True	True	False
0.3	3	True	False	False	False
0.4	4	False	False	False	False

Answer 1

Assuming the name of the pandas Dataframe is df we first get all the indexes of the rows for which every column has value False.After this we simply delete the required indexes using inplace = True so that it gets permanently deleted from the dataset not just the dataframe.

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# Get indexes where value1,value2,value3,value4 column has False value

indexNames = df[ (df['value1'] == 'False') & (df['value2'] == 'False') & (df['value3'] == 'False') & (df['value4'] == 'False') ].index

df.drop(indexNames , inplace=True)

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