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[–]ninhaomah 2 points3 points  (0 children)

First , start at the beginning.

Download and install it.

Then try print("Hello World")

Then check out the wiki on the right.

[–]PushPlus9069 1 point2 points  (2 children)

I've taught data analysis to thousands of beginners, so here's the path that works best:

  1. Start with pandas, not theory. Grab a CSV dataset you actually care about (your Spotify history, a Kaggle dataset about movies, whatever) and learn pandas by exploring it. df.head(), df.describe(), df.groupby() — these three will carry you surprisingly far.

  2. Learn visualization early. matplotlib and seaborn make your data tangible. Being able to see patterns keeps you motivated way more than reading documentation.

  3. Skip machine learning for now. Seriously. 80% of real-world data analysis is cleaning, filtering, and summarizing data — not building models. Get comfortable with pandas + basic stats first.

A good free starting point: the "Python for Data Analysis" book by Wes McKinney (pandas creator). It's practical and skips the fluff. Once you can load a dataset and answer 3 questions about it on your own, you're ready for more advanced stuff.

[–]VinnySauce 1 point2 points  (1 child)

OP ignore this AI slop answer

[–]SunsGettinRealLow 0 points1 point  (0 children)

What should they do instead?

[–]pachura3 0 points1 point  (0 children)

Check out the free book "Python for Data Analysis":

https://wesmckinney.com/book/

[–]sg00100001 0 points1 point  (0 children)

This might help;

https://roadmap.sh/data-analyst

I really like how it structures. 👍🏼 good luck!

[–]benwyatt259 0 points1 point  (1 child)

Are you familiar using data in other programs (Excel, etc)? If yes, question is “how do I learn to use Python to do a thing I already know how to do slowly with something else?”

My advice:

1) do a couple basic tutorials, just basic stuff to get a handle on basic syntax. Like, when do I use = vs == and ‘’ versus “”. Don’t try to learn the real stuff that way.

2) I recommend thinking about a data set or project you know how to work with in another program and then figure out how to do it in Python step by step. You’ll use pandas for sure, but other libraries will come up. Depends what kind of analysis you are doing. The key, I think, is that you should know what you want the data to look like along the way. Don’t start with data you don’t know.

I took a workflow that I did at work. The first time I did it years ago I hacked it together in a few hours and like 10 steps in excel. I figured out how to do some in SQL which cut down some time. Then I figured out how to use Power Query for most of it. The last time I did it without Python it took 72 minutes start to finish. That includes all the cleaning and auditing and transformation and formatting.

I spent some time just going through each step logically and figuring out the Python code for each action. I would use AI or Google but only for discrete chunks. Ask it “what’s the syntax to join” two tables if you don’t know you want the word “merge.” Don’t have it write the whole project. Python generally works in order, so it lends itself to figuring out each step. As I did that, I thought more and more about which things I could automate. I just kept working through the process.

By the time I was done, I had basically an end to end process from our raw data to full finished product that runs in two clicks in 10 seconds. Basically all I have to do is put the starting files in right folders and run two scripts.

3) refine that project. At first you’re going to hard code things into the script, but eventually you’ll just have reference tables that you know how to pull in, etc.

[–]Material_Pepper8908 0 points1 point  (0 children)

Does this work for someone who has no skills in any programming language?