How do I put another "value" to look for into a.loc in dataframe?

Question

I'd like to look for info 'months_in_service" that could be 1, 2 or 3. Instead of put the code three times, what I can do instead?

axx = clean_df.loc[(clean_df['service_part_number'] == pn_list[3]) & (clean_df['months_in_service'] == 1), 'service_technician_comment']

Check out this post for more info: [How to select rows from a DataFrame based on column values](https://stackoverflow.com/questions/17071871/how-to-select-rows-from-a-dataframe-based-on-column-values) — perl, Mar 09 '21 at 16:35

score 1 · Answer 1 · answered Mar 09 '21 at 16:40

1

You can use .isin([<list of items>])

axx = clean_df.loc[(clean_df['service_part_number'] == pn_list[3]) & (clean_df['months_in_service'].isin([1, 2, 3]), 'service_technician_comment']

answered Mar 09 '21 at 16:40

Niels Henkens

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score 0 · Accepted Answer · edited Mar 09 '21 at 17:06

You may want to give the isin method a shot.

axx = clean_df.loc[(clean_df['service_part_number'] == pn_list[3]) & (clean_df['months_in_service'].isin([1,2,3])), 'service_technician_comment']

If you use the dictionary implementation of isin, you should be able to get the same results while placing whatever equal predicates you may have:

axx = clean_df[clean_df.isin({"service_part_number": [pn_list[3]], "months_in_service", [1,2,3]})]["service_technician_comment"]

Just keep in mind, you cannot use loc when using isin like this, as it will raise: ValueError: Cannot index with multidimensional key.

How do I put another "value" to look for into a.loc in dataframe?

2 Answers2