how to check if string in column matches another column, regardless of row

Asked Sep 10 '18 at 15:52

Active Sep 10 '18 at 16:09

Viewed 460 times

I am trying to compare two columns to see if strings in one column exist in another even if the row numbers don't match.

The columns look like this:

A              B

Classic        Classic
Classic Rock   Rock
Kpop           Pop
Jpop           Hip-Hop
Rock           Classic Rock
Jazz           Jazz

I want to be able to create a new table with B that looks like the following:

B              C

Classic        True
Rock           True
Pop            False
Hip-Hop        False
Classic Rock   True
Jazz           True

I tried using

df['C'] = df.apply(lambda x: x.A in x.B, axis=1)

But this only provided whether the strings in the row matched, and I'm looking for a way so that row placement does not matter.

asked Sep 10 '18 at 15:52

user_seaweed

4

`df.B.isin(df.A)` – user3483203 Sep 10 '18 at 15:54
Here's a post on how to do a [Cartesian Products](https://stackoverflow.com/questions/45426843/cartesian-product-of-a-pandas-dataframe-with-itself) for pandas DataFrames. – pault Sep 10 '18 at 15:55
Use a free variable `row` to iterate through column A; apply `any`, such as `any(df.B == row.A)`. Is that enough of a hint? – Prune Sep 10 '18 at 15:59
Thanks guys! `isin` did it :) – user_seaweed Sep 10 '18 at 16:06

0 Answers0