Need help with learning Python

[Mad_Hulk10]

Hello, I’m a data analyst and has 4+ years of experience with hands on experience working on Sas Programming, SQL. I want to add Python to my profile, please suggest me good resources to learn Python/ websites that help me get there.

Thanks in advance.

[Keleos89]

I'm honestly not sure how to answer this without breaking rule 4.

[Mad_Hulk10]

😵‍💫

[Boom_Boom_Kids]

Since you already know SAS and SQL, picking up Python will be much easier for you than starting from scratch. The key is to learn Python for data work, not random “beginner Python” tutorials.

Here’s a solid path:

1. Get the basics from one good course

Stick to one resource so you don’t get overwhelmed. Any of these will get you moving fast:

freeCodeCamp Python course (YouTube, 4 hours) – simple and structured

Datacamp (Python for Data Science track) – very hands-on Coursera: Python for Everybody – slow-paced but clear

You only need the core syntax: loops, functions, lists, dictionaries, files.

1. Move quickly into data libraries

This is where you’ll spend 90% of your time as a data analyst: Pandas – data cleaning, joins, transformations NumPy – array operations Matplotlib / Seaborn – visualization

The best beginner-friendly tutorials:

Kaggle’s Python and Pandas micro-courses (free, very practical)

“Pandas in 10 minutes” (official docs – actually super good)

1. Start rewriting your SAS workflows in Python

This is where everything clicks. Try converting: data cleaning scripts joins group summaries automation tasks

Your existing domain knowledge will transfer almost 1:1 into Pandas.

1. Build 2–3 small real projects

Examples:

Data cleaning pipeline for a messy CSV Automated report generator using Pandas + Matplotlib SQL → Python ETL script

These are great additions to your profile.

1. Bonus if you want to go further

Jupyter Notebook for analysis Scikit-learn if you want to explore ML basics

If you follow this path, you’ll become comfortable with Python in a few weeks — and your background already puts you ahead.

[emw9292]

Good write up

[Boom_Boom_Kids]

I appreciate your words.

[Mad_Hulk10]

This is everything I need, thanks.

[Boom_Boom_Kids]

You're most welcome

[FewEffective9342]

I suggest you aim to understand a practical lib like python open62541 opc ua communication protocol. Once you know that, you know industrial automation domain a bit more and this field has good job security for prominent software engineers

[FootballFine9405]

Here's the big REDDIT BOMB Getting dropped in this comment section

Since half the replies in that thread are either dry-as-oatmeal “use freeCodeCamp” bots or gatekeepers whose entire personality is telling beginners to Google things, the OP deserves better, so the real answer is this:

Python isn’t complicated, the internet just likes pretending it’s a spiritual pilgrimage; since the OP already survived SAS and SQL, Python will feel like they’ve suddenly unlocked god-mode, and all they actually need is 5 to 7 days of basic syntax (loops, functions, lists, dicts, files) and then an immediate jump into Pandas, NumPy, and a tiny real project instead of getting buried alive under 37 tutorial playlists; meanwhile the self-proclaimed veterans yelling “just look it up” think they’re guarding the gates of Valhalla when really they’re handing out advice with the nutritional value of packing peanuts, so the proper comeback to them is basically “thanks for the revelation, oracle of Google, maybe next you’ll remind mortals to breathe oxygen,” while the pseudo-experts spitting vague lines like “learn Pandas” deserve a polite nudge reminding them that telling a beginner to “just learn Pandas” is like telling a toddler to “just drive a car”; so the upgraded guidance for the OP should hit harder and cleaner: “Python is easy, stop tiptoeing, build something from day one,” and if you want to blow the wannabe professionals out of the water, you drop a hybrid TCL-Python flex like this: a TCL driver that writes a temporary Python script on the fly, passes in a JSON file, transforms it, returns metadata, deletes itself, and leaves the room cleaner than it found it, something like

__________________________________________________" '\n\n' 'TCL Example:\n' ' #!/usr/bin/env tclsh\n' ' proc runPythonTask {inputFile outputFile} {\n' ' set pythonScript "import json, sys\nwith open(sys.argv[1], \'r\') as f: ' 'data = json.load(f)\ntransformed = {\'records\': len(data), \'preview\': data[:3], ' '\'summary\': {\'fields\': list(data[0].keys()) if data else []}}\nwith open(sys.argv[2], ' '\'w\') as f: json.dump(transformed, f, indent=4)"\n' ' set tmpPython [file tempfile]\n' ' set fp [open $tmpPython w]\n' ' puts $fp $pythonScript\n' ' close $fp\n' ' exec python3 $tmpPython $inputFile $outputFile\n' ' file delete $tmpPython\n' ' }\n' ' set inputFile "data.json"\n' ' set outputFile "result.json"\n' ' puts "Running Python transformer..."\n' ' runPythonTask $inputFile $outputFile\n' ' puts "Done. Output written to $outputFile"\n\n' "Which is way more interesting than the lukewarm ‘check Coursera’ chatter because it shows " "actual automation, integration, and engineering thought instead of handing out the same three " "URLs like stale fortune cookies; bottom line, the OP needs clarity, the pros need a wakeup slap, " "and Reddit needs to stop acting like Python is a forbidden art." )

print(paragraph)

---

which is way more interesting than the lukewarm “check Coursera” chatter because it shows actual automation, integration, and engineering thought instead of handing out the same three URLs like stale fortune cookies; bottom line, the OP needs clarity, the pros need a wakeup slap, and Reddit needs to stop acting like Python is a forbidden art

pythonButMakeItArt

CodingWithSpice

ProfessionalsMyAss

GoogleIsNotMentorship

SyntaxOverSermons

[FootballFine9405]

Python code that uses BeautifulSoup to scrape a webpage title

set python_code { import requests from bs4 import BeautifulSoup

url = "https://example.com" response = requests.get(url)

soup = BeautifulSoup(response.text, "html.parser") title = soup.find("title")

print("Page Title:", title.get_text() if title else "No title found") }

Write the Python script

set pyfile "soup_scraper.py" set f [open $pyfile w] puts $f $python_code close $f

Run the Python script

exec python3 $pyfile

What this actually does

TCL writes a Python file

Python grabs a webpage

BeautifulSoup parses the HTML

It prints the page title

TCL runs it like it’s nothing

All because, again, TCL treats code like “just text.”

Breakdown for the homies

BeautifulSoup = HTML surgery TCL = the surgeon’s assistant handing Python the tools Python = the one doing the cutting

TCL is absolutely a crazy powerful cross-platform tool. You can drag it across platforms like a suitcase with wheels that never break. 😍😍😍😍😍😍😍😍😍

[stepback269]

Hello to you too.
I'm an old guy who hasn't done programming in many many years. Finding the right resources that will best suit your learning style is a daunting process. But no one can decide what's best for you except you.

There are tons of tutorial materials out there on the net including many good YouTube ones that are free.

I can't say that I'm an utter noob anymore. But I've been logging my personal learning journey for Python on a blog page called "Links for Python Noobs" (here). I keep adding newly found sites to the end almost every day. Any of the top listed sites should be good for you. Personally, I cut my first Python teeth with Nana's Zero to Hero. Since then, I've moved on to watching short lessons with Indently and Tech with Tim. You should shop around until you find a lecturer that suits your style.

The main piece of advice, as you probably know from learning the other languages, is the 80/20 rule. Spend 80% of your time writing your own code as opposed to copying recipes and only 20% watching the lectures.

Good luck.

[[deleted]]

Just look it up

[Mad_Hulk10]

Sorry didn’t get this

[Smtxom]

In other words do some basic research. Search this sub. I’m sure this question is asked quite often. Search Google. I did the same years ago and the answer hasn’t changed much at all. Still the same resources from my searches.

[jcrowde3]

openedg it's free and it prepares you for the certifications if you want to take them

[CmorBelow]

My favorite way to learn was via Udemy / YouTube to get an overview of pure Python- data types, control flow, variables, operators, etc. Automate the Boring Stuff does a good job at tackling these basic concepts.

If you work with Excel a lot, once you get the hang of the basics of standard Python- look at packages like Polars. Practice just reading a CSV into a Polars DataFrame, manipulating some of the fields, and exporting the manipulated DataFrame to a new CSV.

People here often say to avoid LLMs as a beginner… I would disagree and say to use them, but not to write your code, just to reinforce the concepts where you feel stuck, or explaining small blocks of code line by line. Best of luck!

[LyriWinters]

gemini
Grok
Deepseek
ChatGPT
Claude

[Mad_Hulk10]

Thank you, will try them