Pandas df.replace() replacing all rows

Asked Feb 04 '22 at 11:11

Active Feb 04 '22 at 11:11

Viewed 15 times

I have a program to look through rows, and reformat/replace incorrect sizes.

For instance:

Option2 Value	Shirt Color	Actual Size
L	Yellow	XL
XL	Black	2XL
2XL	Green	3XL

So I'm using some code to go through the dataframe from a CSV and replace the documented size with the actual size.

for index, row in df.iterrows():
   if df.loc[index, 'Documented Size''] == 'L':
       df['Documented Size'].replace(to_replace=['L'], value='XL', inplace=True)
   elif df.loc[index, 'Documented Size''] == 'XL':
       df['Documented Size'].replace(to_replace=['XL'], value='2XL', inplace=True)

However, it just seems to replace ALL entries of 'Documented Size' with the first 'if,' like so:

Option2 Value	Shirt Color	Actual Size
XL	Yellow	XL
XL	Black	2XL
XL	Green	3XL

asked Feb 04 '22 at 11:11

Jeremy Gorden

Everytime you want to use `iterrows`, stop and avoid. This is not the right to work with `dataframe`. – Aryerez Feb 04 '22 at 11:14
1

I think create dictionary and then use `replace`, no loops necessary. – jezrael Feb 04 '22 at 11:16

Pandas df.replace() replacing all rows

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