Odtnhj

I have a csv file with these values:

0,0,0,0,October 29 2018 16:35:04
0,1,2,0,October 30 2018 11:40:04
0,0,0,0,November 25 2018 04:20:13

I wanted to remove the rows with zero values on the first 4 columns:

0,0,0,0,October 29 2018 16:35:04 #remove this
0,1,2,0,October 30 2018 11:40:04 #this should stay
0,0,0,0,November 25 2018 04:20:13 #remove this

IIUC use df[...]:

print(df[~(df[df.columns[:4]]==0).all(1)])

Slightly better (thanks to @jpp), use iloc:

print((df.iloc[:, :4] == 0).all(1))

Both Output:

 0 1 2 3 4
1 0 1 2 0 October 30 2018 11:40:04

Columns for output maybe incorrect, because i don't know the actual ones.

There's many ways to do what you're asking, but you have a couple of tasks:

• read a .csv, you can do this with csv.reader
  


• go over all its contents, you can do this with a simple for loop


• check some conditions, you'll need to check if the integer value is 0, int(row[col]) == 0
  


• write lines that meet the conditions to a new .csv, you can do this with csv.writer

Here's a working script that does these things, without requiring external libraries, other than the standard csv one:

from csv import reader, writer

with open('input.csv', 'r') as input_file:
 with open('output.csv', 'w', newline='') as output_file:
 csv_in = reader(input_file)
 csv_out = writer(output_file)
 for row in csv_in:
 if not all([int(row[col]) == 0 for col in range(0, 4)]):
 csv_out.writerow(row)