Needed a guide to progress further

[u/Typical_Succotash126]

So i started learning python a little while ago, I have learnt the basics such as loops and functions etc then I moved onto libraries such as pandas, numpy and matplotlib as I am data analytics student

Most of the tutorials I found cover the basics. What should I be doing to progress further, I wanna master python for now. I would like to know what other important and useful libraries and functions should I be learning. I am thinking of learning about automations next, let me know if there is anything else

A guide and resource material would be helpful as well

[u/Goodswimkarma]

There is a Wiki to the right in Bookmarks that has all of these things ------>

[u/DemonicHorseman19]

Saw your post and just wanted to say you're at the exact point where tutorial hopping stops being useful. The jump from "I know the syntax" to "I can actually build things" is mostly just picking a project you care about and suffering through making it work.

For data analytics specifically I'd focus on SQL integration (sqlite3 or SQLAlchemy) since real-world data lives in databases 90% of the time, and get comfortable with requests/BeautifulSoup for pulling data from web sources when CSV files aren't handed to you. Automation is a solid direction but I'd suggest scraping and cleaning a dataset end-to-end as a bridge project before diving into scheduled scripts, it's the same skill set with a clearer deliverable.

[u/mc_pm]

How much actual programming -- fingers on keyboard -- have you been doing?

[u/Typical_Succotash126 → u/mc_pm]

I practice everything i learn until I get comfortable then try to advance further by combining everything I learnt

[u/Ok-Scientist-1367]

You've got the foundation. Stop chasing tutorials and start building actual projects.

For data analytics, learn SQL next not optional. Every analytics job needs it. Then databases like PostgreSQL or SQLite. After that, either go deep into statistical analysis (scipy, statsmodels) or better visualization (plotly, seaborn). Pick based on what you want like dashboards or predictive modeling. Don't mix automation in yet. Learn it after you're solid on data. Build something real. That teaches you what actually matters. Projects expose gaps. Tutorials give false confidence. Stop consuming. Start building.

[u/Typical_Succotash126 → u/Ok-Scientist-1367]

Yes I learnt basics of sql during my semester break and did an internship at a software company

[u/datadriven_io]

matplotlib, seaborn, or ggplot2 would probably be more useful. pandas interview questions on datadriven.io are worth working through once you're comfortable with the library basics. If your company doesn't use Tableau, you won't be able to easily talk them into getting a license. But, with python or R there's nothing to request - you can just do whatever you need in a more useful format.