pandas query rows by list

Question

I have a pandas data frame and want to return the rows from the data frame corresponding to the customer ids that appear in a list of target ids.

For example, if my data frame looks like this:

id    Name    ...    ...
-------------------------
1     Bob     ...    ...
2     Dave    ...    ...
2     Dave    ...    ...
3     Phil    ...    ...
4     Rick    ...    ...
4     Rick    ...    ...

Basically I want to return the rows for customers who appear more than once in this data frame. So I want to return all the ids that occur more than once.

id    Name    ...    ...
-------------------------
2     Dave    ...    ...
2     Dave    ...    ...
4     Rick    ...    ...
4     Rick    ...    ...

I can get a list of the ids by doing the following

grouped_ids = df.groupby('id').size()
id_list = grouped_ids[grouped_ids>1].index.tolist()

And now I'd like to go back to the data frame and return all the rows corresponding to those ids in the list.

Is this possible?

Thanks for the help.

Could you please show some sample data?

Ankur Ankan
– Ankur Ankan

2014-06-16 05:44:42 +00:00
Commented Jun 16, 2014 at 5:44 — Ankur Ankan
– Ankur Ankan, Commented Jun 16, 2014 at 5:44

Nic · Accepted Answer · 2014-06-16 05:56:03Z

3

I guess you are looking for isin():

In [1]: import pandas as pd

In [2]: df = pd.DataFrame({'customer_id':range(5), 'A':('a', 'b', 'c', 'd', 'e')})

In [3]: df
Out[3]: 
   A  customer_id
0  a            0
1  b            1
2  c            2
3  d            3
4  e            4

In [4]: df[df.customer_id.isin((1,3))]
Out[4]: 
   A  customer_id
1  b            1
3  d            3

[edit] To match a given target list, just use it as argument for the isin() method:

In [5]: mylist = (1,3)

In [6]: df[df.customer_id.isin(mylist)]
Out[6]: 
       A  customer_id
1  abcde            1
3  abcde            3

answered Jun 16, 2014 at 5:56

Nic

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