Pulling Specifics Words/Numbers from String

[bigpapa]

Hi There,

I know this may seem like a silly question because there might be 1000s of tutorials but I just can't quite figure it out.

I have a data frame and it has a column (columnA) where its an Object but its just a string of text like this:

'columnA': ['680 PACKAGES FOR SOAP NET WEIGHT: 17, 000. 00 KGS']


I want to extract NET WEIGHT: 17, 000. 00 KGS

This is what I've tried thus far:

df['Net Weight'] = df['columnA'].str.extract('NET WEIGHT: (\d+ KGS)')
df['Net Weight'] = df['columnA'].str.extract('NET WEIGHT:? (\d+ KGS)')
df['Net Weight'] = df['columnA'].str.extract('NET\sWEIGHT:\s?(\d+\.?\d*\sKGS)')

df['Net Weight'] = df['columnA'].apply(lambda x: re.search(r'NET\sWEIGHT:\s([\d,]+\.\d+\sKGS)', x).group(1) if re.search(r'NET\sWEIGHT:\s([\d,]+\.\d+\sKGS)', x) else None)

-- Nothing works. It still shows NaN Values - I'm reading the API for re and other pandas.Series.str. doc. and I can't find something to suit my needs.


Also! Sometimes Net Weight comes In other forms like N.W.: or Net Weight; or Net Weight or Net WT: and the endings vary like KGS, KG,

I'm really not sure how further explore this.

[deanhystad]

Is net weight always the first number following the colon? Your number, "17, 000. 00" contains extra spaces. Are they really there, or is that a typo?

This works if net weight starts with the first digit after the colon and goes to the end of the string.

df["Net Weight"] = df["columnA"].str.extract(r":.*?(\d.*)")

[bigpapa]

Is net weight always the first number following the colon? Your number, "17, 000. 00" contains extra spaces. Are they really there, or is that a typo?

This works if net weight starts with the first digit after the colon and goes to the end of the string.

df["Net Weight"] = df["columnA"].str.extract(r":.*?(\d.*)")

Ah! Yes this is one of my issues, sometimes there are spaces, the formatting is all messed up and varies between each case.

The above with the spaces is correct.

Thanks for your help!