print value if it is not nan

Question

I have a df with a column containing floats (transaction values). I would liek to iterate trough the column and only print the value if it is not nan. Right now i have the following condition.

if j > 0:
  print(j)
  i += 1
else: i += 1

where i is my iteration number.

I do this because I know that in my dataset there are no negative values and that is my workaound, but I would like to know how it would be done correctly if I would have nagative values. so what would be the if condition ?

I have tried j != None and j != np.nan but it still prints all nan.

Tip: Both branches have `i += 1` so no `else` is needed, just move that out of the loop. — tadman, Dec 27 '22 at 14:09
Does this answer your question? [How can I check for NaN values?](https://stackoverflow.com/questions/944700/how-can-i-check-for-nan-values) — tadman, Dec 27 '22 at 14:10

score 1 · Answer 1 · answered Dec 27 '22 at 14:16

Why not use built-in pandas functionality?

Given some dataframe:

import pandas as pd
import numpy as np
df = pd.DataFrame({
    'a': [-1, -2, 0, np.nan, 5, 6, np.nan]
})

You can filter out all nans:

df[df['a'].notna()]
>>> a
0   -1.0
1   -2.0
2   0.0
4   5.0
5   6.0

or only positive numbers:

df[df['a']> 0]
>>> a
4   5.0
5   6.0

Thiru17 · Answer 2 · 2022-12-27T15:06:54.630

0

Suppose let's assume here the datatype is int64 for the filled values in column

for i in range(0,10):
    if(type(array[i])!= int):
        print(array[i])

edited Dec 27 '22 at 15:06

answered Dec 27 '22 at 15:05

Thiru17

9
4

print value if it is not nan

2 Answers2