Need to delete some specific column and rows(by index) of multiple csv files, without creating new files.
For the code below, it is giving output with new blank rows after each row.
import csv
with open('file.csv') as fd:
reader = csv.reader(fd)
valid_rows = [row for idx, row in enumerate(reader) if idx != 0]
with open('file.csv', 'w') as out:
csv.writer(out).writerows(valid_rows)
What is the simpler way to do this(might be by other python libraries)?
Since you wish not to generate any new csv files and would like the data to perform operations, I would suggest you to make use of Pandas Framework. Make use of drop function in this framework.
Consider the following example:
Sample.csv:
col1,col2,col3,col4
1,2,3,4
5,6,7,8
9,10,11,12
13,14,15,16
17,18,19,20
Code:
import pandas as pd
df = pd.read_csv('./Sample.csv')
To delete columns:
df.drop('col3', axis = 1, inplace = True)
df contents:
col1 col2 col4
0 1 2 4
1 5 6 8
2 9 10 12
3 13 14 16
4 17 18 20
To delete rows:
df.drop(df.index[[1,4]], inplace = True)
df contents:
col1 col2 col4
0 1 2 4
2 9 10 12
3 13 14 16
Finally to save the edited csv file:
df.to_csv('new_sample.csv', index = False)
inplace option for that. I have edited the code. Check it out