在数据框中查找和替换半常见字符串？

Question

I am attempting to find a semi-common occurring string and remove all other data in the column. Pandas and Re have been imported. For instance, I have dataframe...

>>>df
COLUMN COUNT   DATA
           1   this row RA-123: data 8b43a
           2   here RA-5372: data 94h63c

I need to keep just the RA-'number that follows' and remove everything before and after. The numbers that follow are not always the same length and the 'RA-' string does not always occur in the same position. There is a colon after every instance that can be used as a delimiter.

I tried this (a friend wrote the regex search piece for me because I am not familiar with it).

df.assign(DATA= df['DATA'].str.extract(re.search('RA[^:]+')))

But python returned

TypeError: search() missing 1 required positional argument: 'string'

What am I missing here? Thanks in advance!

Answer 1

You should use acapturing group with extract:

df['DATA'].str.extract(r'(RA-\d+)')

Here, (RA-\\d+) is a capturing group matching RA , then a hyphen and then one or more digits.

You may use your own pattern, but you still need to wrap it with capturing parentheses, r'(RA[^:]+)' .

Answer 2

Looking at the docs , you don't need the re.search method. You just call df[DATA] = df['DATA'].str.extract(r'RA[^:]+'))

Answer 3

As I mentioned earlier, no need for re here.

Other answers addressed well how to use extract directly. However, to answer your specificly, if you really want to use re , the way to go is to use re.compile instead of re.search .

df.assign(DATA= df['DATA'].str.extract(re.compile(regex_str)))