DuckDB and SQL - for Data Analysis and Processing

☕️ 𝗕𝘂𝘆 𝗺𝗲 𝗮 𝗰𝗼𝗳𝗳𝗲𝗲:
To support the channel and encourage new videos, please consider buying me a coffee here:

In this video, we'll look at the DuckDB database for rapid analytical querying across datasets. We'll explore the basics of the package, and how it can be used to read in data and perform analytical queries.

📌 𝗖𝗵𝗮𝗽𝘁𝗲𝗿𝘀:
00:00 Intro
00:43 Introduction to DuckDB
02:27 Installing DuckDB
05:25 Importing CSV data into DuckDB database
09:42 Writing analytical queries with DuckDB

𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮:

📚 𝗙𝘂𝗿𝘁𝗵𝗲𝗿 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 𝗮𝗻𝗱 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻:

#python #datascience #data

[as_wani]

Great stuff!
Appreciate the effort you have put in to make this wonderful tutorial!
Thank you

[thepigol]

Great video - concise and informative. Thank you, mate!

[davidtindell]

thank you. "And Now for something completely (or, 'a bit') different !

[zb]

Great stuff Lyle! I've been hearing a lot of good things about DuckDB, would love a follow up episode on this for more advanced use cases to demonstrate the performance benefits of DuckDB over Postgres for example. I'd love to see an example with 100x the data and the performance differences there

[jhncnnr-sec]

This guy should be paid as much as a professor

[tmb]

For my money the expression syntax and method chaining of Polars is less cognitively demanding for analytical queries like this, but I do like the fact they’re interoperable with little overhead so you could potentially leverage the strengths of both in the same workflow if it made sense to do that. Cheers!

[michwilhelmi]

Really good highlights. Thanks. I will be moving on to your HTMX session again soon .. I would like to try to work on a HTMX + Python + DuckDB combo soon with CRUD included.

[zulhishamtan]

Please consider to make a video for using geospatial function in duckdb. Thank you very much.

[MOaz-hwqy]

What if the Data is too big to fit into the memory
I work on a project where I deal with punch of a CSV's Files where each is 2.5 GB, What Should I Do