How to Count NaN in a pandas DataFrame

TLDR solution

# grouped by column
df.isna().sum() 
# total
df.isna().sum().sum()

Step-by-Step Example

Let's say, you have the following DataFrame:

      a    b
0  10.0  1.0
1   3.0  NaN
2   5.0  4.0
3 -20.0  0.0
4   NaN  NaN

You can then use the isna() and sum() methods to count the NaN values:

print(f"NaNs by column: {df.isna().sum()}")
print(f"Total number of NaNs: {df.isna().sum().sum()}")

The result:

NaNs by column: 
a    1
b    2
dtype: int64
Total number of NaNs: 3

That's it! You just learned how to count NaN values in a pandas DataFrame.