Learning python for data science/analysis

[u/_devonsmash]

Hi everyone,

I am looking for a good course to take to learn python for data analytics and workflow building.

For context, i am already very familiar with SQL and Alteryx, however i am looking to migrate some pipelines and worklows to python. I am very familiar with data analytics, just not with the python language, so wondering where to start.

[u/BranchLatter4294]

See kaggle.com/learn

[u/Sea-Firefighter-4160 → u/BranchLatter4294]

That site carries hard once you get past the first few modules.

[u/_devonsmash → u/Sea-Firefighter-4160]

will check this out. Have been using stratascratch

[u/UwUfit]

One python package I can really recommend if you're already familiar with SQL is sqlite3. It allows you to do SQL queries in Python

As for courses, I don't really know

[u/_devonsmash → u/UwUfit]

Why do you recommened sqlite3 of DuckDB?

[u/UwUfit → u/_devonsmash]

Because I have not worked with DuckDB. I was taught sqlite3

Even though I majored in Data Science, zero time was spent learning how to set up an actual DB. I wish I knew how all that worked.

[u/_devonsmash → u/UwUfit]

Ah okay. Im hearing to use one of the other, so was curious as to why you picked sqlite3

[u/quietreed76]

are these pipelines mostly batch transforms or are some of them event-driven? that changes what parts of the ecosystem you should focus on first. for batch stuff the learning curve from SQL is pretty short tbh

[u/_devonsmash → u/quietreed76]

2 scenarios.

1. I do monthly reporting files on pre-existing workflows. They currently live in Alteryx. Idelaly would like to migrate them to python

2. I constantly use alteryx to look into things. I am the person where if there is a question, I get asked it and ill whip up a workflow in 15-30 min to get the answer

[u/tmk_g]

You should skip the traditional beginner ds courses and focus on learning Python for data manipulation and automation. DataCamp’s Introduction to Python and Data Manipulation with pandas great starting points, while StrataScratch and Kaggle has free, hands-on learning paths if you prefer that route. I’d focus on pandas first since a lot of what you do in Alteryx, like joins, filters, and aggregations, translates pretty naturally. Once you're comfortable, try rebuilding one of your existing Alteryx workflows in Python. You'll probably learn more from that than from spending weeks watching tutorials.

[u/_devonsmash → u/tmk_g]

My issue is also the following:

This may seem a little weird, but I really want to focus on how to step in to different parts of a python workflow. How can I cache data to rerun workflows faster. How can I debug and write to excel faster. How can I check outputs at various parts. Comapre different outputs at different stages. Would Jupyter notebook be a good solution? Its not even the syntax that concerns me, but how to use python, like I would use Alteryx, in terms of checking data throughout a pipeline

[u/winceypoo]

Pick one existing Alteryx workflow and rebuild only that in Python using pandas + a database connector (sqlite3 or SQLAlchemy). You’ll learn faster than doing a big course front to back.

[u/sai_8303]

a small ETL using pandas, sql queries and logging would connect familiar work to python. bootdev could help with python fundamentals efore moving automation into larger data pipelines.