python - How to replace text in a column of a Pandas dataframe?

Question

I have a column in my dataframe like this:

range
"(2,30)"
"(50,290)"
"(400,1000)"
... 

and I want to replace the , comma with - dash. I'm currently using this method but nothing is changed.

org_info_exc['range'].replace(',', '-', inplace=True)

Can anybody help?

Answer 1

Use the vectorised str method replace:

In [30]:

df['range'] = df['range'].str.replace(',','-')
df
Out[30]:
      range
0    (2-30)
1  (50-290)

EDIT

So if we look at what you tried and why it didn't work:

df['range'].replace(',','-',inplace=True)

from the docs we see this desc:

str or regex: str: string exactly matching to_replace will be replaced with value

So because the str values do not match, no replacement occurs, compare with the following:

In [43]:

df = pd.DataFrame({'range':['(2,30)',',']})
df['range'].replace(',','-', inplace=True)
df['range']
Out[43]:
0    (2,30)
1         -
Name: range, dtype: object

here we get an exact match on the second row and the replacement occurs.

Answer 2

For anyone else arriving here from Google search on how to do a string replacement on all columns (for example, if one has multiple columns like the OP's 'range' column): Pandas has a built in replace method available on a dataframe object.

df.replace(',', '-', regex=True)

Source: Docs

Answer 3

Replace all commas with underscore in the column names

data.columns= data.columns.str.replace(' ','_',regex=True)

Answer 4

In addition, for those looking to replace more than one character in a column, you can do it using regular expressions:

import re
chars_to_remove = ['.', '-', '(', ')', '']
regular_expression = '[' + re.escape (''. join (chars_to_remove)) + ']'

df['string_col'].str.replace(regular_expression, '', regex=True)

Answer 5

If you only need to replace characters in one specific column, somehow regex=True and in place=True all failed, I think this way will work:

data["column_name"] = data["column_name"].apply(lambda x: x.replace("characters_need_to_replace", "new_characters"))

lambda is more like a function that works like a for loop in this scenario. x here represents every one of the entries in the current column.

The only thing you need to do is to change the "column_name", "characters_need_to_replace" and "new_characters".