1. SQL Server and Python Pandas Indexes are two different worlds and should not be mixed.
2. SQL Server uses Index primarily for DML operations and to keep data ACID.
3. Python Pandas uses Index and MultiIndex for keeping data dimensionality when performing data wrangling and statistical analysis.
4. SQL Server Index and Python Pandas Index don’t know about each other’s existence, meaning if user want to propagate the T-SQL index to Python Pandas (in order to minimize the impact of duplicates, missing values or to impose the relational model), it needs to be introduced and created, once data enters “in the python world”.
Read on for additional conclusions and the demos which bring us here.