CODEWITHSUNDEEP
pythonpandas
scott martin
scott martin

Reputation: 1293

Comparing Pandas Dataframe to a set in Python

I have a Dataframe with some sales data as below:

df = pd.DataFrame({'bill_id': ['1001','1002','1006']})

I have another set with a list of bill_id:

{'1002', '10006', '1009'}

I am trying to find bill_id common in the Dataframe and the set and tried the below:

issues = list(l in set(df['bill_id']))

I get an error TypeError: 'bool' object is not iterable, wondering if I am checking it incorrectly. Expecting the output to be a list.

Expected output of set as below: 

{'1002'}

Upvotes: 1

Views: 840

Answers (4)

AlCorreia
AlCorreia

Reputation: 552

You can also use isin to get the rows in your dataframe that match your other list of ids. 

In [1]: df = pd.DataFrame({'bill_id': ['1001','1002','1006']})
        other_bill_ids = set({'1002', '10006', '1009'})
        df[df['bill_id'].isin(other_bill_ids)]
Out[1]:   bill_id
        1    1002

If all you want is a list or a set, you can do 

In [2]: df['bill_id'][df['bill_id'].isin(other_bill_ids)].tolist()
Out[2]: {'1002'}

or

In [3]: df['bill_id'][df['bill_id'].isin(other_bill_ids)].tolist()
Out[3]: ['1002']

Upvotes: 1

tawab_shakeel
tawab_shakeel

Reputation: 3739

1.Convert the dict into list
2.Fetch list of unique bill_id from dataframe
3.Use set and intersection method to get common elements

df = pd.DataFrame({'bill_id': ['1001','1002','1006']})
bill_id = list({'1002', '10006', '1009'})

bill_df = list(df['bill_id'].unique())
final_res = list(set(bill_df).intersection(bill_id))

print(final_res)

I hope it would solve your problem

Upvotes: 1

Shir
Shir

Reputation: 1207

Try something like that:

issues = set(df['bill_id']).intersection(other_bill_id_set)

Upvotes: 1

mujjiga
mujjiga

Reputation: 16886

df = pd.DataFrame({'bill_id': ['1001','1002','1006']})
bill_id = ('1002', '10006', '1009')
set(df.bill_id.values).intersection(bill_id)

Upvotes: 2

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