I have a pandas Dataframe with one column a list of files
import pandas as pd
df = pd.read_csv(\'fname.csv\')
df.head()
filename A B C
fn1.txt 2
I think you can use str.replace with regex .txt$'
( $
- matches the end of the string):
import pandas as pd
df = pd.DataFrame({'A': {0: 2, 1: 1},
'C': {0: 5, 1: 1},
'B': {0: 4, 1: 2},
'filename': {0: "txt.txt", 1: "x.txt"}},
columns=['filename','A','B', 'C'])
print df
filename A B C
0 txt.txt 2 4 5
1 x.txt 1 2 1
df['filename'] = df['filename'].str.replace(r'.txt$', '')
print df
filename A B C
0 txt 2 4 5
1 x 1 2 1
df['filename'] = df['filename'].map(lambda x: str(x)[:-4])
print df
filename A B C
0 txt 2 4 5
1 x 1 2 1
df['filename'] = df['filename'].str[:-4]
print df
filename A B C
0 txt 2 4 5
1 x 1 2 1
EDIT:
rstrip
can remove more characters, if the end of strings contains some characters of striped string (in this case .
, t
, x
):
Example:
print df
filename A B C
0 txt.txt 2 4 5
1 x.txt 1 2 1
df['filename'] = df['filename'].str.rstrip('.txt')
print df
filename A B C
0 2 4 5
1 1 2 1
You may want:
df['filename'] = df.apply(lambda x: x['filename'][:-4], axis = 1)
You can use str.rstrip to remove the endings:
df['filename'] = df['filename'].str.rstrip('.txt')
should work
use list comprehension
df['filename'] = [x[:-4] for x in df['filename']]