How to replace text in a string column of a Pandas dataframe?

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?

Answers:

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Method 1

Use the vectorised str method replace:

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

df
      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 description:

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:

df = pd.DataFrame({'range':['(2,30)',',']})
df['range'].replace(',','-', inplace=True)

df['range']

0    (2,30)
1         -
Name: range, dtype: object

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

Method 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

Method 3

Replace all commas with underscore in the column names

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

Method 4

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”.

Method 5

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)

Method 6

Almost similar to the answer by Nancy K, this works for me:

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

Method 7

If you want to remove two or more elements from a string, example the characters ‘$’ and ‘,’ :

Column_Name
===========
$100,000
$1,100,000

… then use:

data.Column_Name.str.replace("[$,]", "", regex=True)

=> [ 100000, 1100000 ]

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0