CODEWITHSUNDEEP
pythonpandasdataframe
SRJCoding
SRJCoding

Reputation: 473

How to list values from column A where column B is NaN?

I have a dataframe (let's call it df) that looks a bit like this:

Offer | Cancelled | Restriction
------|-----------|------------
1     | N         | A
2     | Y         | B
3     | N         | NaN
4     | Y         | NaN

I have the following bit of code, which creates a list of all offers that have been cancelled:

cancelled = list('000'+df.loc[(df['Cancelled']=='Y'),'Offer'].astype(str))

What I now want to do is to adapt this to create a list of all offers where the 'Restriction' column is not NaN. So my desired result would look like this:

['0001','0002']

Does anyone know how to do this please?

Upvotes: 0

Views: 55

Answers (1)

chatax
chatax

Reputation: 998

You were almost there. Just add the extra condition that the Restriction column may not be NaN.

list('000'+df.loc[(df['Restriction'].notna()) & (df['Cancelled'] == 'Y'), 'Offer'].astype(str))

If you just want to filter on not NaN in Restriction column, the answer is commented by @Henry Ecker

Upvotes: 1

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