The NaN values in pandas are semantically NULL; when you write them as NaN they are no longer considered to be NULL by other systems. So pd.isnull(value) will yield different results from ISNULL(value) in Spark/Hive/Impala/Presto/Drill/etc. Member martindurant commented Apr 7, 2017 "T...
Setting values on a copy of a slice from a dataframe Removing newlines from messy strings in pandas dataframe cells pd.NA vs np.nan for pandas Pandas rank by column value Pandas: selecting rows whose column value is null / None / nan ...
By taking a look at our test data set, we can assume that row 11 and 12 are duplicates.To discover duplicates, we can use the duplicated() method.The duplicated() method returns a Boolean values for each row:ExampleGet your own Python Server Returns True for every row that is a ...