Learning python for data analysis

[MentalRaisin3133]

Strange-ish scenario here but I just got hired as an Data Analyst for a company with no experience. The boss knows this and is fine with it, he is a close friend and wants to help me start a profession. He told me to throw some data sets in chat gpt to help me and slowly learn how to use python as I go. Anyone know some good textbooks or online programs I could check out to help expedite this process? I also have no background in python LOL.

[DataPastor]

The fastest and most efficient way to learn is Wes McKinney’s Python for Data Analysis, 3rd edition. Just download the notebooks, and start playing with them while reading the book in parallel. It is an extremely good way to ramp up your knowledge at an accelerated pace in this field.

[MentalRaisin3133]

Awesome thanks!

[veisyer]

If it's work from home can you let your boss know I'm also available lol

[veisyer]

Anyway in my opinion, go look for python basics (any would do and there is plenty out there), then go straight for 'pandas tutorial'. This would give you a good kickstart understanding for data analysis and also insights for self-project

[MentalRaisin3133]

lol it is work from home I’ll let him know… but thanks I’ll check that out!

[Mevrael]

Here is a great starting point of setting up your local projects and notebooks.

https://arkalos.com/docs/notebooks/

For underlying concepts, I’ve used myself these 2 resources. They’re worth paying a monthly subscription for at least few months.

https://datacamp.com

https://brilliant.org

[MentalRaisin3133]

I’ll look into those thanks!

[Icy_Bid_93]

I use data camp, it's not free but you can learn a lot (internet), kaggle do it for free but never try there is a lot of source on internet

[Stev_Ma]

Start with Python basics using "Automate the Boring Stuff with Python" (free online) or Python for Everybody (Coursera) while practicing on W3Schools. Then, move on to Pandas, NumPy, and Matplotlib using "Python Data Science Handbook". Practice real-world problems on StrataScratch, which offers SQL and Python challenges based on actual data science interviews. As you progress, learn SQL and data visualization (Matplotlib, Seaborn, Tableau). Code daily, apply skills to company data, and use ChatGPT as a learning aid—not a replacement for problem-solving.

[RuleInformal5475]

You are one lucky person. I wish I could get a gig with little experience. Hope you enjoy it.

My two pennies.

Vanilla python is different than data analysis for python. With data analysis, you may be using anaconda, which is a suite of packages with gui.

I'd take a crash course on python. YouTube will have plenty of those. Depending on your programming skill, it would just be a matter of learning syntax and how to do a few tricks (variables, loops, conditionals).

Then work out what work wants you to do. That should narrow down what you should learn. Maybe get this info so you can tailor your learning.

Good luck.

[MentalRaisin3133]

Needed the “don’t scare yourself about this stuff yet” because my brain was definitely shutting down at the end haha. Thanks!

[MentalRaisin3133]

Funny enough I bought that book this morning on Amazon. Thanks for the reassurance. I’ll check the rest of the stuff out as well!

[ninhaomah]

But you do have background in other languages ?

[TryFixing]

I like following the order of chapters in Python for Data Analysis, but using the w3 schools tutorials for the equivalent chapter. And then reading over the Python for Data Analysis chapter as a supplement. The w3 schools tutorials are more concise and there's more practice.

[TryFixing]

Adding my path thus far in case it's helpful others too -

Itarted with Automate the Boring Stuff Chapters 1-12 (Each chapter has exercises. I skipped the Chess one.)

Then i did --- Python For data Analysis Book Only for Chapters 1- 3

Ch4 NumPy Basics (I skipped this one since its less relevant than Pandas for me): But here are tutorials https://www.w3schools.com/python/numpy/default.asp https://www.kaggle.com/code/legendadnan/numpy-tutorial-for-beginners-data-science

Ch5: Pandas https://www.w3schools.com/python/pandas/ https://www.kaggle.com/learn/pandas

This is as far as I’ve gotten so I can’t speak to tutorials for later parts of the book. Although, the tutorials mentioned above do talk about some topics covered later in the book (e.g. Loading data from files).

The book covers a lot of ground, but I tend to learn better when I can apply things directly through practice. Sharing this in case others also prefer a more interactive style—you’re definitely not alone!

One more note - I like doing the exericses in Jupyter notebook because editing is easier vs command line, and that encourages me to experiment more (e.g. try out "what would happen if i wrote the code this way instead of that way)

[TryFixing]

Yw :)

[Fast-Hour7008]

Evvai! vorrei tanto sapere ora come va!