Both the pandas.crosstab and the Pandas pivot table seem to provide the exact same functionality. Are there any differences?
The main difference between the two is the pivot_table
expects your input data to already be a DataFrame; you pass a DataFrame to pivot_table
and specify the index
/columns
/values
by passing the column names as strings. With cross_tab
, you don't necessarily need to have a DataFrame going in, as you just pass array-like objects for index
/columns
/values
.
Looking at the source code for crosstab
, it essentially takes the array-like objects you pass, creates a DataFrame, then calls pivot_table
as appropriate.
In general, use pivot_table
if you already have a DataFrame, so you don't have the additional overhead of creating the same DataFrame again. If you're starting from array-like objects and are only concerned with the pivoted data, use crosstab
. In most cases, I don't think it will really make a difference which function you decide to use.