Copy text between parentheses in pandas DataFrame column into another column
Question:
I am trying to copy text that appears between parentheses in a pandas DataFrame column into another column. I have come across this solution to parse strings accordingly: Regular expression to return text between parenthesis
I would like to assign the result element-by-element to the same row in a new column.
However, this doesn’t carry over directly to pandas Series. I seems that map/apply/lambda seems the way to go. I’ve arrived at this piece of code, but getting an invalid syntax error.
dataSources.dataUnits = dataSources.dataDescription.map(str.find("(")+1:str.find(")"))
Obviously, I’m not yet fluent enough there – help much appreciated.
Answers:
You can just use an apply with the same method suggested there:
In [11]: s = pd.Series(['hi(pandas)there'])
In [12]: s
Out[12]:
0 hi(pandas)there
dtype: object
In [13]: s.apply(lambda st: st[st.find("(")+1:st.find(")")])
Out[13]:
0 pandas
dtype: object
Or perhaps you could use one of the Series string methods e.g. replace
:
In [14]: s.str.replace(r'[^(]*(|)[^)]*', '')
Out[14]:
0 pandas
dtype: object
throw away all the stuff before the (
and all the stuff after )
inclusive.
From 0.13 you can use the extract method:
In [15]: s.str.extract('.*((.*)).*')
Out[15]:
0 pandas
dtype: object
I am trying to copy text that appears between parentheses in a pandas DataFrame column into another column. I have come across this solution to parse strings accordingly: Regular expression to return text between parenthesis
I would like to assign the result element-by-element to the same row in a new column.
However, this doesn’t carry over directly to pandas Series. I seems that map/apply/lambda seems the way to go. I’ve arrived at this piece of code, but getting an invalid syntax error.
dataSources.dataUnits = dataSources.dataDescription.map(str.find("(")+1:str.find(")"))
Obviously, I’m not yet fluent enough there – help much appreciated.
You can just use an apply with the same method suggested there:
In [11]: s = pd.Series(['hi(pandas)there'])
In [12]: s
Out[12]:
0 hi(pandas)there
dtype: object
In [13]: s.apply(lambda st: st[st.find("(")+1:st.find(")")])
Out[13]:
0 pandas
dtype: object
Or perhaps you could use one of the Series string methods e.g. replace
:
In [14]: s.str.replace(r'[^(]*(|)[^)]*', '')
Out[14]:
0 pandas
dtype: object
throw away all the stuff before the (
and all the stuff after )
inclusive.
From 0.13 you can use the extract method:
In [15]: s.str.extract('.*((.*)).*')
Out[15]:
0 pandas
dtype: object