Iterate through dataframe and select null values

Question

I am trying to iterate through a dataframe that has null values for the column = [myCol]. I am able to iterate through the dataframe fine, however when I specify I only want to see null values I get an error.

End goal is that I want to force a value into the fields that are Null which is why I am iterating to identify which are first.

for index,row in df.iterrows():
    if(row['myCol'].isnull()):
        print('true')

AttributeError: 'str' object has no attribute 'isnull'

I tried specifying the column = 'None' since that is the value I see when I print the iteration of the dataframe. Still no luck:

for index,row in df.iterrows():
    if(row['myCol']=='None'):
        print('true')

No returned rows

Any help greatly appreciated!

Answer 1

You can use pd.isnull() to check if a value is null or not:

for index, row in df.iterrows():
    if(pd.isnull(row['myCol'])):
        print('true')

But seems like you need df.fillna(myValue) where myValue is the value you want to force into fields that are NULL. And also to check the NULL fields in a data frame you can invoke df.myCol.isnull() instead of looping through rows and check individually.

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If the columns are of string type, you might also want check if it is empty string:

for index, row in df.iterrows():
    if(row['myCol'] == ""):
        print('true')