Python How to Select to List All DataFrame Rows where Column has a NaN Entry

Question

I have a DataFrame (20k rows) with 2 columns I would like to update if the first column (latitude) row entry is NaN. I wanted to use the code below as it might be a fast way of doing it, but I'm not sure how to update this line msk = [isinstance(row, float) for row in df['latitude'].tolist()] to get the rows that are NaN only. The latitude column I am doing the check on is float, so this line of code returns all rows.

def boolean_mask_loop(df):

    msk = [isinstance(row, float) for row in df['latitude'].tolist()]

    out = []
    for target in df.loc[msk, 'address'].tolist():
        dict_temp = geocoding(target)
        out.append([dict_temp['lat'], dict_temp['long']])

    df.loc[msk, ['latitude', 'longitude']] = out
    
    return df

id	address	latitude	longitude
1	addr1	NaN	NaN
2	addr2	NaN	NaN
3	addr3	40.7526	-74.0016

This question is similar to: How to find which columns contain any NaN value in Pandas dataframe. If you believe it’s different, please edit the question, make it clear how it’s different and/or how the answers on that question are not helpful for your problem. — Anerdw
– Anerdw, Commented Oct 26, 2024 at 19:42
Thank you. Would that work through the code in relation to this line: msk = [isinstance(row, float) for row in df['latitude'].tolist()] — CGarden
– CGarden, Commented Oct 26, 2024 at 20:09

CGarden · Accepted Answer · 2024-10-28 12:10:20Z

0

I amended this line of code msk = [isinstance(row, float) for row in df['latitude'].tolist()] to msk = df['latitude'].isnull().tolist() which essentially identifies those rows that have NaN values in the latitude column that I wanted to update. Thank you for the advice from @Anerdw.

answered Oct 28, 2024 at 12:10

CGarden

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2 Comments

Anerdw Over a year ago

If the duplicate target solved your problem, I would rather you accept the duplicate than self-answer. But glad you found a solution!

CGarden Over a year ago

I'm not sure it really did, but maybe it helped a little. Just wanted to give some credit.

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