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NaN value would be a placeholder for missing values in this case, which is what the Pandas package does. Many methods lose the first several rows of data to computation and currently the returned object simply omits them. By providing a option inside methods along the lines of includeNaN = false, users could opt to include the NaN values that convey that there was an original value inside the specified timestamp, but it was lost to computation.
The text was updated successfully, but these errors were encountered:
Perhaps better is to provide a padNaN method that allows users to pad the returned object with the number of rows that were used to calculate the series. It should default to side=top with a bottom alternative. Though the specific dates that were consumed by calculations would need to be accounted for correctly.
NaN
value would be a placeholder for missing values in this case, which is what the Pandas package does. Many methods lose the first several rows of data to computation and currently the returned object simply omits them. By providing a option inside methods along the lines ofincludeNaN = false
, users could opt to include theNaN
values that convey that there was an original value inside the specified timestamp, but it was lost to computation.The text was updated successfully, but these errors were encountered: