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I have a dataframe that has an array as one of its values

   Alg    iMap_x
0  Max()  [12,34]
1  Min()  [43,11,84,33]
2  Sum()  [93,15,3,99,37]

I want to filter my dataframe based on iMap_x value

I have i = [43,11,84,33]

when i try this code it does not work

df[df["iMap_x"] == i]["Alg"]

this gives error

ValueError: ('Lengths must match to compare', (4,), (2,))

I also tried

df[df["iMap_x"].isin(i)]["Alg"]

but gave no values (empty dataframe)

I tried

df["iMap_x"].isin(i)

but gave all false

0    False
1    False
2    False
3    False

any idea how to do that?

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  • One possibility from the dupe: df[df.iMap_x.map(tuple).isin([tuple(i)])] Commented May 30, 2022 at 1:30

1 Answer 1

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Here's a way to do what your question asks:

df2 = df['iMap_x'].apply(lambda x: x == i)

Full test code:

import pandas as pd
df = pd.DataFrame({'Alg':['Max()','Min()','Sum()'], 'iMap_x':[[12,34],[43,11,84,33],[93,15,3,99,37]]})
print('df:',df,sep='\n')

i = [43,11,84,33]
df2 = df['iMap_x'].apply(lambda x: x == i)
print('df2:',df2,sep='\n')

Input:

df:
     Alg               iMap_x
0  Max()             [12, 34]
1  Min()     [43, 11, 84, 33]
2  Sum()  [93, 15, 3, 99, 37]

Output:

df2:
0    False
1     True
2    False

If you want to use this criteria to filter rows then select the Alg column, you can do this:

df3 = df[df['iMap_x'].apply(lambda x: x == i)]['Alg']
print(df3)

Output:

1    Min()
Name: Alg, dtype: object
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