CODEWITHSUNDEEP
pythonpandaslistdataframeseries
INGl0R1AM0R1
INGl0R1AM0R1

Reputation: 1628

Pandas map, check if any values in a list is inside another

I have the following list

x  = [1,2,3]

And the following df

Sample df

pd.DataFrame({'UserId':[1,1,1,2,2,2,3,3,3,4,4,4],'Origins':[1,2,3,2,2,3,7,8,9,10,11,12]})

Lets say I want to return, the userid who contains any of the values in the list, in his groupby origins list.

Wanted result

pd.Series({'UserId':[1,2]})

What would be the best approach? To do this, maybe a groupby with a lambda, but I am having a little trouble formulating the condition.

Upvotes: 0

Views: 313

Answers (2)

Gonçalo Peres
Gonçalo Peres

Reputation: 13582

IIUC, OP wants, for each Origin, the UserId whose number appears in list x. If that is the case, the following, using pandas.Series.isin and pandas.unique will do the work

df_new = df[df['Origins'].isin(x)]['UserId'].unique()

[Out]:
[1 2]

Assuming one wants a series, one can convert the dataframe to a series as follows

df_new = pd.Series(df_new)

[Out]:
0    1
1    2
dtype: int64

If one wants to return a Series, and do it all in one step, instead of pandas.unique, one can use pandas.DataFrame.drop_duplicates (see Steven Rumbaliski answer).

Upvotes: 1

Steven Rumbalski
Steven Rumbalski

Reputation: 45542

df['UserId'][df['Origins'].isin(x)].drop_duplicates()

I had considered using unique(), but that returns a numpy array. Since you wanted a series, I went with drop_duplicates().

Upvotes: 1

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