如何删除字符串值列表中的“nan”值？

Question

I have a list, made of values from various rows, those values have to be converted into strings. The problem is when a row is empty there is a value called 'nan' displayed, which I would like to remove.

My code:

import pandas as pd

test = []
for index, row in df.iterrows():
x = str(row['Date']) + ' | ' + str(row['Time'])
test.append(x)

print(test)

I tried multiple things :

import numpy as np

list_clean = test[np.logical_not(np.isnan(test))]
print(res_backend_nan)

Which says

TypeError: only integer scalar arrays can be converted to a scalar index

I tried:

import math
from numpy import nan

list_clean = [item for item in test if not(math.isnan(item) == False)]

And it says:

TypeError: must be real number, not P

I tried:

list_clean = [item for item in list if not(pd.isnull(item) == True)]

The result is the list is still displayed with nan values:

06/07/35 | nan

Some help would be very welcome please, thank you.

Answer 1

Try something like the following:

import pandas as pd

def remove_nan(row):
    return [str(x) for x in row if not pd.isnull(x)]