4.48 out of 5
4.48
245 reviews on Udemy

Data Analysis with Polars

Transform your data analysis with Polars - the powerful new dataframe library
Instructor:
Liam Brannigan
1,758 students enrolled
English [Auto]
Taking advantage of parallel and optimised analysis with Polars
Working with larger-than-memory data
Using Polars expressions for analysis that is easy to read and write
Loading data from a wide variety of data sources
Combining data from different datasets using fast joins operations
Grouping and parallel aggregations
Deriving insight from time series
Preparing data for machine learning pipelines
Visualising data with Matplotlib, Seaborn, Altair & Plotly

In this course I show you how to take advantage of Polars – the fast-growing open source dataframe library that is becoming the go-to dataframe library for data scientists in python. I am a Polars contributor with a focus on making Polars accessible to new users.

“A thorough introduction to Polars” – Ritchie Vink, creator of Polars

“Thank you for your great work with this course – I’ve optimized some code thanks to it already!” Maiia Bocharova

The course is for data scientists who have some familiarity with a dataframe library like Pandas but who want to move to Polars because it is easier to write and faster to run. The core materials are Jupyter notebooks that examine each topic in depth. Each notebook comes with a set of exercises to help you develop your understanding of the core concepts. For many key topics this course is the only source of documentation for learners and comes from my time examining the Polars source code.

An important note about videos: this is a notebook course and not a video course. Only half of the lectures have videos and some of the videos may have components that are not up-to-date. The Polars API has changed too often to allow me to keep videos up-to-date. I have instead backed the notebooks by an automated testing system that alerts me when they need to be updated. I release an updated version of the course every couple of weeks in response to changes in Polars.

The course introduces the syntax of Polars and shows you the many ways that Polars allows you to produce queries that are easy to read and write. However, the course also delves deeper to help you understand and exploit the algorithms that drive the outstanding performance of Polars.

By the end of the course you will have optimised ways to:

  • load and transform your data from CSV, Excel, Parquet, cloud storage or a database

  • run your analysis in parallel

  • work with larger-than-memory datasets

  • carry out aggregations on your data

  • combine your datasets

  • visualise your outputs with Matplotlib, Seaborn, Plotly & Altair and

  • prepare your data for machine learning pipelines

Filtering rows

Data types and missing values

Statistics, counts and grouping

Combining dataframes

Time series analysis

Input/Output

Nested dtypes

You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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Includes

3 hours on-demand video
38 articles
Certificate of Completion

Archive

Working hours

Monday 9:30 am - 6.00 pm
Tuesday 9:30 am - 6.00 pm
Wednesday 9:30 am - 6.00 pm
Thursday 9:30 am - 6.00 pm
Friday 9:30 am - 5.00 pm
Saturday Closed
Sunday Closed

Archive

Working hours

Monday 9:30 am - 6.00 pm
Tuesday 9:30 am - 6.00 pm
Wednesday 9:30 am - 6.00 pm
Thursday 9:30 am - 6.00 pm
Friday 9:30 am - 5.00 pm
Saturday Closed
Sunday Closed

Archive

Working hours

Monday 9:30 am - 6.00 pm
Tuesday 9:30 am - 6.00 pm
Wednesday 9:30 am - 6.00 pm
Thursday 9:30 am - 6.00 pm
Friday 9:30 am - 5.00 pm
Saturday Closed
Sunday Closed