Python Pandas: Get number of NaN before first non NaN value

Question

I have the following DataFrame:

y
NaN
NaN
5
NaN
7

I would like to write a function that will return the number of NaN values before the first non-NaN value. Given the above example, the function should return the value 2.

I tried to solve my problem using this question , but it did not help me much.

Edit: The values always start with a NaN. If the column is all NaN, the function should return the column length.

Answer 1

You could use isna to get True/1 on the NaN values and cumprod to get rid of all values that follow a non-NaN. Then sum :

df['y'].isna().cumprod().sum()

output: 2

Answer 2

Use Series.isna with Series.cummin and count True s by sum :

s = df['y'].isna().cummin().sum()
print (s)
2

Answer 3

You can use first_valid_index .

df.y.first_valid_index()
> 2

This grabs the index of the first non-NaN value. By default we don't need to sum if the index starts from NaN .