pandas filter if string in row A contains row b element

Question

Let's say we have this df

d = pd.DataFrame({'year': [2010, 2020, 2010], 'colors': ['red', 'white', 'blue'], "shirt" : ["red shirt", "green and red shirt", "yellow shirt"] })

like this:

    year    colors  shirt
0   2010    red     red shirt
1   2020    white   green and red shirt
2   2010    blue    yellow shirt

I want to filter out rows in which the "shirt" column contains the "colors" column also considering the "year" column

desired output:

year    colors  shirt
    0   2010    red     red shirt

I tried this d[(d.year == 2010) & (d.shirt.str.contains(d.colors))] but I am getting this error:

'Series' objects are mutable, thus they cannot be hashed

It is a big df that I am working on. How can I solve with some pandas function?

do a join by pipe on the string contains: d[(d.year == 2010) & (d.shirt.str.contains('|'.join(d.colors)))]..? — anky
– anky, Commented Sep 24, 2020 at 17:16
Actually looking at your example the answer by Rakesh should be more apt, as str contains with a pattern for all rows will even match something not in the current row — anky
– anky, Commented Sep 24, 2020 at 18:07

Rakesh · Accepted Answer · 2020-09-24 17:22:53Z

2

I believe you need df.apply

Ex:

df = pd.DataFrame({'year': [2010, 2020, 2010], 'colors': ['red', 'white', 'blue'], "shirt" : ["red shirt", "green and red shirt", "yellow shirt"] })
print(df[(df.year == 2010) & df.apply(lambda x: x.colors in x.shirt, axis=1)])

Output:

   year colors      shirt
0  2010    red  red shirt

answered Sep 24, 2020 at 17:22

Rakesh

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3 Comments

JaySabir Over a year ago

I thought about it, I was hoping for some pandas function but this works too!

Rakesh Over a year ago

@anky sorry i am not able to think on how to use a list comprehension here.

anky Over a year ago

No Problem , i meant something like: d[d['year'].eq(2010) & [a in b for a,b in zip(d['colors'],d['shirt'])]]

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