pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

Modin: Scale your Pandas workflows by changing a single line of code

A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner

Lightweight and extensible compatibility layer between dataframe libraries!

Python and Pandas are known to have issues around scalability and efficiency. You will learn how to use libraries such as Modin, Dask, Ray, Vaex etc to overcome the problems faced by Pandas.

Distributed XGBoost on Ray

A low-level execution library for analytic data processing.

Open Data Profiling, Quality and Analysis on NYC OpenData dataset with semantic profiling using fuzzy ratio, Levenshtein distance and regex

oneAPI Hackathon: The LLM Challenge

A Kedro plugin that provides pandas dropin replacements for the pandas datasets (e.g modin and cuDF)

Simple example on how Modin can peed up your Pandas workflows by changing a single line of code

Unlimited Data-Science Benchmarks for Numeric, Tabular and Graph Workloads

A transformation pipeline for Delta Lake using AWS SDK for Pandas

Global Markets Options Pricing

Recommendation system approaches

Build a machine model to predict whether the freshwater is safe to drink or not.Based on the measures like pH, TDS, etc.

AI Starter Kit to generate structured synthetic data using Intel® Distribution of Modin

Delve deeper into data manipulation using Python's prominent libraries. Explore the functionalities of Pandas and get a glimpse of alternatives like Polars, Dask, and Modin.

HHA507 / Data Science / Assignment 2 / Data Manipulation