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

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.

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

Replace all commas with underscore in the column names

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