Pandas: Difference between pivot and pivot_table. Why is only pivot_table working?

For anyone who is still interested in the difference between pivot and pivot_table, there are mainly two differences:

• pivot_table is a generalization of pivot that can handle duplicate values for one pivoted index/column pair. Specifically, you can give pivot_table a list of aggregation functions using keyword argument aggfunc. The default aggfunc of pivot_table is numpy.mean.
• pivot_table also supports using multiple columns for the index and column of the pivoted table. A hierarchical index will be automatically generated for you.

REF: pivot and pivot_table

Another caveat:

pivot_table will only allow numerical types as "values=", whereas pivot will take string types as "values=".

I debugged it a little bit.

• The DataFrame.pivot() and DataFrame.pivot_table() are different.
• pivot() doesn't accept a list for index.
• pivot_table() accepts.

Internally, both of them are using reset_index()/stack()/unstack() to do the job.

pivot() is just a short cut for simple usage, I think.