Index.isna() detects missing values. It returns a boolean of the same size indicating whether the values are NA. NA values such as None, numpy.NaN, or pd.NaT map to True. Everything else is matched against false values. Characters such as empty strings & # 39; & # 39; or numpy.inf are not considered NA values (unless you set pandas.options.mode.use_inf_as_na = True).
Syntax: Index.isna () p>
Parameters: Doesn`t take any parameter.
Returns: A boolean array of whether my values are NA p >
Example # 1: Use
Index.isna () to check if any value in the index is
Now we will check the missing values in the index .
Function returned an array object of the same size as the index.
True means there was no index mark, and
False means there was an index mark.
Example # 2: strong > Use
Index.isna () to check if missing Datetime indexes count as
NaN values or not.
Now we check if there are tags in the Datetime index .
As we can see from the output, the function returned an array object whose size matches with the size of the Datetime index.
True means there is no index mark, and
False means no index mark is missing.