47
$\begingroup$

I have been using pandas for quite some time. But, I don't understood what's the difference between isna() and isnull() in pandas. And, more importantly, which one to use for identifying missing values in the dataframe.

What is the basic underlying difference of how a value is detected as either na or null?

$\endgroup$
  • 1
    $\begingroup$ The two functions are same. Both give the missing values. $\endgroup$ – Ankit Seth Sep 6 '18 at 11:37
63
$\begingroup$

Pandas isna() vs isnull().

I'm assuming you are referring to pandas.DataFrame.isna() vs pandas.DataFrame.isnull(). Not to confuse with pandas.isnull(), which in contrast to the two above isn't a method of the DataFrame class.

These two DataFrame methods do exactly the same thing! Even their docs are identical. You can even confirm this in pandas' code.

But why have two methods with different names do the same thing?

This is because pandas' DataFrames are based on R's DataFrames. In R na and null are two separate things. Read this post for more information.

However, in python, pandas is built on top of numpy, which has neither na nor null values. Instead numpy has NaN values (which stands for "Not a Number"). Consequently, pandas also uses NaN values.

In short

  • To detect NaN values numpy uses np.isnan().

  • To detect NaN values pandas uses either .isna() or .isnull().
    The NaN values are inherited from the fact that pandas is built on top of numpy, while the two functions' names originate from R's DataFrames, whose structure and functionality pandas tried to mimic.

$\endgroup$
  • 2
    $\begingroup$ This explains everything and yes i wanted to infer 'pandas.DataFrame.isna()' vs 'pandas.DataFrame.isnull()' . Thanks for such a detailed explanation. $\endgroup$ – Vaibhav Thakur Sep 7 '18 at 6:45

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.