replace part of the string in pandas data frame [duplicate]

Answer 1

It seems you need Series.replace:

print (df)
              val
0  HF - Antartica
1    HF - America
2       HF - Asia

print (df.val.replace({'HF -':'Hi'}, regex=True))
0    Hi Antartica
1      Hi America
2         Hi Asia
Name: val, dtype: object

Similar solution with str.replace:

print (df.val.str.replace('HF -', 'Hi'))
0    Hi Antartica
1      Hi America
2         Hi Asia
Name: val, dtype: object

Answer 2

I would like to share one more thing that is very much important, you can replace full stop with space ". " with "." normal full stop

df['label']=df.label.replace({"\. ": "."},regex=True)

Answer 3

To add to @jezrael's answer, you need to include regex=True otherwise it would match directly. Also, here it replaces the values across all columns in the data frame. If you don't intend this, you could filter to a column and then replace. For replacing across all values in the data frame, try:

df.replace('HF', 'Hi Funny', regex=True)

You could also provide a list based patterns and replacement values. The complete set of options are provided in the documentation here.

So if the data frame is:

>df = pd.DataFrame({'Column': ['HF - Antartica', 'HF - America', 'HF - Asia']})
>df.replace('HF', 'Hi Funny', regex=True)

should print:

                 Column
0  Hi Funny - Antartica
1    Hi Funny - America
2       Hi Funny - Asia