I try to replace everywhere the symbols " -
in the start line and end line:
dtnew.applymap(lambda x: x.replace('^-', ''))
dtnew.applymap(lambda x: x.replace('^"', ''))
But the output dataframe has these symbols
well, if performance is NOT an issue you can iterate over columns and rows and use a simple replace (see below). Again, I would only use this if the dataframe is not enormous and you have no concern for performance.
for column in df.columns:
for i in df.index:
df[column][i] = df[column][i].replace('-','').replace('"','')
Assuming this example and that you only want to replace the leading character(s):
df = pd.DataFrame([['- abc', 'def -'], ['" ghi-', '--jkl']])
0 1
0 - abc def -
1 " ghi- --jkl
Use str.lstrip
.
df2 = df.apply(lambda c: c.str.lstrip('- "'))
output:
0 1
0 abc def -
1 ghi- jkl
# as list: [['abc', 'def -'], ['ghi-', 'jkl']]
For only the first character, use str.replace
:
df2 = df.apply(lambda c: c.str.replace('^[- "]', '', regex=True))
output:
0 1
0 abc def -
1 ghi- -jkl
# as list: [[' abc', 'def -'], [' ghi-', '-jkl']]
to strip both start and end, use str.strip
to remove all characters (anywhere): df.apply(lambda c: c.str.replace('[- "]', '', regex=True))
to remove first or last matching character: df.apply(lambda c: c.str.replace('(^[- "]|[- "]$)', '', regex=True))
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