I have a pandas data frame in which I need to replace one part of the string value with another string value:
For example, I have:
HF - Antartica
HF - America
HF - Asia
Out of which I'd like to replace ony the HF - part,
thus the result should be:
Hi Funny Antartica
Hi Funny America
Hi Funny Asia
I have tried pd.replace() but it doesn't work as I need only one part of the string replaced, rather than the entire string.
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
series.replace solution did not make the replacement in my dataframe with either regex=True or with regex=False. I don't know why, but when I used str.replace, it worked
str.replace(..., regex=True) is significantly faster than Series.replace(..., regex=True)
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
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)
