How to use SQL with Pandas?

Some Pandas Magic with SQL

Pandas is one of the best data manipulation libraries in recent times. It lets you slice and dice, groupby, join and do any arbitrary data transformation. You can take a look at this post , which talks about handling most of the data manipulation cases using a straightforward, simple, and matter of fact way using Pandas.

But even with how awesome pandas generally is, there sometimes are moments when you would like to have just a bit more. Say you come from a SQL background in which the same operation was too easy. Or you wanted to have more readable code. Or you just wanted to run an ad-hoc SQL query on your data frame. Or, maybe you come from R and want a replacement for sqldf.

For example, one of the operations that Pandas doesn’t have an alternative for is non-equi joins, which are quite trivial in SQL.

In this series of posts named Python Shorts , I will explain some simple but very useful constructs provided by Python, some essential tips, and some use cases I come up with regularly…