Native SQL on Pandas, Numpy Objects

Anant Gupta (~anant79)


The adoption of Python is increasing at a very fast pace which is good for the community. However, there are many users who are not from an active coding background, yet they would like to perform operations on Python. Most of the users are adept in getting data to be read into a pandas dataframe and numpy array, but after that there is a bit of programming that needs to be done

The advantages are huge if we look at the community who are good with SQL and are trying Python for some of their use cases. This will allow easy communication w.r.t native data processing in pandas ( similar to SQL ). R which is another programming language and used heavily in the industry, has something similar, but it is missing in Python

Through this talk, I will be explaining how this has been implemented. The following will be the outline of the talk


  • How does Pandas work
  • Looking at some Pandas equivalent code for SQL operations
  • Quick understanding of grammars ( Lexers and Parsers )
  • Reading free form SQL text and passing it through ANTLR grammar
  • Creating a tree structure of the commands
  • Converting the commands to native pandas/numpy code

Target Audience

  • People from the Computer Science Background ( including freshers )
  • Individuals/Organizations who are in the process of adopting Python for data processing
  • Individuals who know SQL


  1. Data
  2. SQL
  3. Python ( Beginner )

Content URLs:

  1. The code will be hosted on a website very soon, where people can play around
  2. It will also be available as a installer

Speaker Info:

Anant is currently working as a senior data scientist at Ericsson with over 8+ years of experience in Data Engineering and Machine Learning. He has come up with creative solutions for solving the problems faced by organizations. His favorite language is currently Python, but he has worked extensively on C#, R, VBA and Shell Scripting He had given a talk last year at the Fifth Elephant conference

Id: 1214
Section: Developer tools and automation
Type: Talks
Target Audience: Intermediate
Last Updated: