Question

How can I reduce data set by deleting any rows that have all FALSE bool 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. True and False in the table are dtype 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

Below is a screen shot of the python program to check indentation. Comments are given on every line explaining the code.


Below is the output of the program:
Contents of del.csv:

Console output:

Below is the code to copy:
#CODE STARTS HERE----------------

import pandas as pd
#reading sample csv from a file
df = pd.read_csv("del.csv", delimiter="\t")
print("ORIGINAL DATAFRAME:")
print(df) #prints original dataframe
print("\nMODIFIED DATAFRAME:")
#df.iloc[:,2:] => selects all rows with columns from 2 to end. This removes 'test1' and 'id'
#.any(axis=1) => returns true if there is atleast 1 'True' in the column
#df[~df.iloc[:,2:].any(axis=1)] => prints rows where all values are 'False'
print(df[~df.iloc[:,2:].any(axis=1)]) #Prints modified df
#CODE ENDS HERE-----------------