I'm just learning python/pandas and like how powerful and concise it is.
During data cleaning I want to use replace on a column in a dataframe with regex but I want to reinsert parts of the match (groups).
Simple Example: lastname, firstname -> firstname lastname
I tried something like the following (actual case is more complex so excuse the simple regex):
df['Col1'].replace({'([A-Za-z])+, ([A-Za-z]+)' : '\2 \1'}, inplace=True, regex=True)
However, this results in empty values. The match part works as expected, but the value part doesn't. I guess this could be achieved by some splitting and merging, but I am looking for a general answer as to whether the regex group can be used in replace.
I think you have a few issues with the RegEx's.
As @Abdou just said use either '\\2 \\1' or better r'\2 \1', as '\1' is a symbol with ASCII code 1
Your solution should work if you will use correct RegEx's:
In [193]: df
Out[193]:
name
0 John, Doe
1 Max, Mustermann
In [194]: df.name.replace({r'(\w+),\s+(\w+)' : r'\2 \1'}, regex=True)
Out[194]:
0 Doe John
1 Mustermann Max
Name: name, dtype: object
In [195]: df.name.replace({r'(\w+),\s+(\w+)' : r'\2 \1', 'Max':'Fritz'}, regex=True)
Out[195]:
0 Doe John
1 Mustermann Fritz
Name: name, dtype: object