I have a directory with several csvs.
files = glob('C:/Users/jj/Desktop/Bulk_Wav/*.csv')
Each csv has the same below columns. Reprex below-
yes no maybe ofcourse
1 2 3 4
I want my script to iterate through all csvs in the folder and delete the columns maybe and ofcourse.
Do you mean by:
files = glob('C:/Users/jj/Desktop/Bulk_Wav/*.csv')
for filename in files:
df = pd.read_csv(filename)
df = df.drop(['maybe ', 'ofcourse'], axis=1)
df.to_csv(filename)
This code will remove the maybe
and ofcourse
columns and save it back to the csv.
If glob
provides you with file paths, you can do the following with pandas
:
import pandas as pd
files = glob('C:/Users/jj/Desktop/Bulk_Wav/*.csv')
drop = ['maybe ', 'ofcourse']
for file in files:
df = pd.read_csv(file)
for col in drop:
if col in df:
df = df.drop(col, axis=1)
df.to_csv(file)
Alternatively if you want a cleaner way to not get KeyError
s from drop you can do this:
import pandas as pd
files = glob('C:/Users/jj/Desktop/Bulk_Wav/*.csv')
drop = ['maybe ', 'ofcourse']
for file in files:
df = pd.read_csv(file)
df = df.drop([c for c in drop if c in df], axis=1)
df.to_csv(file)
You can use panda to read csv file to a dataframe then use drop() to drop specific columns. something like below:
df = pd.read_csv(csv_filename)
df.drop(['maybe', 'ofcourse'], axis=1)
import pandas as pd
from glob import glob
files = glob(r'C:/Users/jj/Desktop/Bulk_Wav/*.csv')
for filename in files:
df = pd.read_csv(filename, sep='\t')
df.drop(['maybe', 'ofcourse'], axis=1, inplace=True)
df.to_csv(filename, sep='\t', index=False)
If the files look exactly like what you have there, then maybe something like this
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