Question

How can I reduce data set by deleting any rows that have all FALSE values for every column in
that row using pandas. Assuming there are 20+ columns/rows to loop through. 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 Bool.

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

Code:

import pandas as pd
df = pd.read_csv('test.csv')
a = []
for i, row in df.iterrows():
if(int(row['value1'])==0 and int(row['value2'])==0 and int(row['value3'])==0 and int(row['value4'])==0):
a.append(i)
df = df.drop(a)

Dataframe Before deleting:

Dataframe after deleting:

Hope this helps.