I have the below series:

my_series = pd.Series([np.nan, np.nan, ['A', 'B']])

I have to loop through my_series and evaluate whether the value is NaN or not and then do something (actions defined as 'do A' and 'do B' for the sake of simplicity).

1st try:

for element in my_series: if element.isna(): print('do A') else: print('do B')

When running it, I've got the error: "'float' object has no attribute 'isna'"

2nd try from the question: Error: float object has no attribute notnull

for element in my_series: np.where(element.isnull(), 'do A', 'do B')

When running it, I've got the error: "AttributeError: 'float' object has no attribute 'isnull'"

I haven't found any other similar question here at StackOverflow, I don't know what else to try.

2 Answers

Change your code to:

for element in my_series: if type(element) == float and pd.isna(element): print('do A') else: print('do B')

Edit following the comment by Peter

I on purpose didn't change the original concept of processing the source Series in a loop. It looks like both print instructions are rather "placeholders", to be replaced with one piece of code for NaN values and another for other values.

No need for explicit for loops. Based on your second attempt:

# Setup
my_series = pd.Series([np.nan, np.nan, ['A', 'B']])
# Solution
np.where(my_series.isnull(), 'do A', 'do B')
# Output
array(['do A', 'do A', 'do B'], dtype='<U4')