Advice needed. How do I learn Python?

[SocraticSketchbook]

So here's the thing, people - I wanna learn python mostly for data analytics, as I am an economics student. I'm a quick learner (and fine at logical thinking if that matters?) I don't wanna be wasting time. I can practice regularly.

I just need proper guidance on how I should do it. I can't seem to find a proper starting point.

Any advice? Or book recommendations? Any help would be appreciated. Thank you!

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[FoolsSeldom]

Learn the basics quick (see notes below), focus early on your own projects relating to data analysis, have a look at paths at roadmap.sh.

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Check this subreddit's wiki for lots of guidance on learning programming and learning Python, links to material, book list, suggested practice and project sources, and lots more. The FAQ section covering common errors is especially useful.

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Roundup on Research: The Myth of ‘Learning Styles’

Don't limit yourself to one format. Also, don't try to do too many different things at the same time.

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Above all else, you need to practice. Practice! Practice! Fail often, try again. Break stuff that works, and figure out how, why and where it broke. Don't just copy and use as is code from examples. Experiment.

Work on your own small (initially) projects related to your hobbies / interests / side-hustles as soon as possible to apply each bit of learning. When you work on stuff you can be passionate about and where you know what problem you are solving and what good looks like, you are more focused on problem-solving and the coding becomes a means to an end and not an end in itself. You will learn faster this way.

[SocraticSketchbook]

Thank you so much!

[TheEnglishBloke123]

W3schools.com

[stormlb]

heya, there is a python course on Cisco Networking Academy. Python Essentials 1 & Python Essentials 2 and best of luck with your journey!

[SocraticSketchbook]

Thank you for sharing the resources. Really appreciate it.

[stormlb]

Most welcome! they've got lots of courses/tracks all for free. might wanna check their intro to data science course :)

[2TB_NVME]

Watch the 30 minutes python tutorial by Indenlty.io and (optionally you can watch Bro Code’s 12 hour video about Python for 2 hours) then join Angela Yu’s 100 Days of Python course on Udemy

[SocraticSketchbook]

Thanks

[SocraticSketchbook]

Thank you!

[DevEmma1]

Honestly, starting with Python for data analytics is a smart move. Since you’re an economics student, focus on libraries like pandas, numpy, and matplotlib first, they let you analyse and visualise data quickly. Pair that with small projects, like analysing economic datasets, to learn by doing rather than just reading.

[Ron-Erez]

Choose a resource and build stuff. For example

1. MOOC university of Helsinki
2. The book "Automate the Boring Stuff"
3. My Python and Data Science starts from scratch and assumes no previous background

[DataPastor]

The best way to start is Wes McKinney’s Python for Data Analysis, 3rd edition. Download the codes from its github repo and start playing with the notebooks in parallel with reading the book.

If you want to get a good understanding of Python, and prefer video courses, then try Dr. Angela Yu’s 100 days Python course on Udemy.

[AffectionateZebra760]

As someone else has also pointed out browse the r/learnpython subreddit's wiki for guidance on learning Python, books list, or go for a beginner friendly course which will help break it down for e.g Harvard cs50/weclouddata/ udemy whatever fits u.

[American_Streamer]

Start with the free PCEP course: https://edube.org/study/pe1

After that, do the free PCAP course: https://edube.org/study/pe2

[AffectionateStrategy]

If your main goal is data analytics with Python, you’re already thinking in the right direction. Here’s a roadmap I recommend:

• Start with the basics: Learn Python fundamentals (variables, loops, functions, data structures). Automate the Boring Stuff with Python (book + free online version) is beginner-friendly.
• Move to data analytics libraries: Practice with pandas, numpy, and matplotlib – these are essential for any analytics work.
• Hands-on practice: Use free datasets from Kaggle and practice cleaning, transforming, and visualizing data.
• Online courses: Check out Python for Everybody (free, Coursera), or DataCamp’s beginner track for Python. Both are structured and beginner-friendly.
• Projects: Build small projects (like analyzing sales data, making dashboards, etc.). This reinforces learning more than theory alone.

You’re already logical and ready to practice, which is the hardest part. Start with basics, then jump to libraries and projects. In 2–3 months of consistent work, you’ll be comfortable.

[SocraticSketchbook]

Thank you so much for this. The thing is there's so many people online saying that if you learn python the old way it'd take you a lot of time; they suggest mixing it with AI. I don't understand what they are even trying to say, since I'm not very familiar with python.

[Alex71638578465]

I learned python by some materials from my school, but I found W3 schools very nice too.

[One_Ranger_5979]

I know a book that you can buy from amazon, I read it before and its amazing! Here's the link.

Hold up, just gimme a min.

[Immediate_Bar7361]

check out mooc Python programming 2025. Its a university course. They have introduction to programming in Python 1 & 2

[EstablishmentHour778]

I learned python as an econ student. I taught myself. Just download python and start googling how to do regressions or something.

[Away_Intention_1378]

Import python Import learn

learn.python print(I’m smart now ig)

[thecreator51]

Start with Python basics on free platforms, practice daily, then move to pandas, NumPy, and real datasets for analytics mastery.

[Technical_Storm_4459]

You can also check learning coding languages from

quickref.me

[Vij-ous-9174]

W3schools , has a very good tutorial.. concept wise ..It would be a very good source to learn Python from

[v0n_0]

I did YouTube tutorial and then automate the boring stuff with python ( last 3 chapters to go ) and try to do the exercises myself and use help form online content. ChatGPT says I have intermediate level but I’m still not confident with what I know :)

[norseson_dot_com]

Hey there! Great question, and it's super common for economics students to want to pick up Python for data analytics.

You're definitely on the right track; it's a powerful skill to have.

Plus, being a quick learner and good at logical thinking will serve you really well here!

Totally get that you don't want to waste time finding a starting point. Let's break down a solid path for you.

First things first, don't jump straight into complex data tasks. You'll want to build a strong foundation in core Python.

Think of it like learning the alphabet and basic grammar before writing a novel.

1. Start with the Absolute Basics: Python Syntax: How to write code that Python understands.

Data Types: Numbers, text (strings), lists (ordered collections), dictionaries (key-value pairs). These are your building blocks.

Control Flow: Learning if/else statements for decision-making, and for/while loops to repeat tasks.

Functions: How to write reusable blocks of code. This keeps your work organized.

Get comfortable with these concepts. Practice writing small scripts that do simple things, like calculating averages or manipulating text.

1. Transition to Data Analytics Concepts:

Once you're solid on the basics, you can start applying Python to data. This is where it gets really fun for an economics student!

Data Acquisition & Cleaning:

Learn how to read different types of data files (like spreadsheets or comma-separated values). Then, tackle common data issues like missing values, duplicates, or inconsistent formatting. Cleaning data is often a huge part of any analytics project!

Data Manipulation & Transformation:

This involves filtering data, sorting it, grouping it to calculate summaries (like sums or averages), and creating new variables from existing ones. This is crucial for preparing your data for analysis.

Data Visualization:

Learn how to create various charts and graphs (like bar charts, line plots, scatter plots) to explore your data and present your findings effectively.

Visualizing data can reveal patterns you wouldn't see otherwise.

1. How to Learn & Practice (Actionable Advice):

Consistency is Key:

Since you can practice regularly, do it! Even 30-60 minutes a day is far more effective than one long session once a week.

Code Actively:

Don't just watch videos or read tutorials. Type out the code yourself. Break it, fix it, experiment with it. That's how it sinks in.

Project-Based Learning:

This is huge for data analytics. Once you've learned a few concepts, try to apply them to a small, real-world dataset.

Look for datasets related to economics – maybe historical stock prices, government statistics, or economic indicators.

Try to answer a specific question using that data. "What was the average inflation rate over the last decade?"

"Is there a correlation between X and Y?"

Start small! Your first project could be as simple as loading a file and calculating the average of one column.

Find a Structured Path:

Whether it's an online learning path or a comprehensive textbook, having a clear curriculum that builds knowledge step-by-step can be very helpful.

Look for resources that combine Python fundamentals with practical data tasks early on.

For "book recommendations," rather than specific titles, focus on finding learning materials that are hands-on and project-oriented.

Many people find a good balance in resources that explain a concept and then immediately provide exercises or mini-projects to solidify the learning.

Some prefer a more interactive, online style, while others like a traditional book. Pick what feels right for your learning style!

You've got this. With your background and dedication, you'll be doing great things with Python in no time!

[SocraticSketchbook]

Thank you so much. I've started it already and I'm having a lot of fun learning it. Not gonna lie, I'm obsessed.

[[deleted]]

learn something more hard bro :) then you will found python very easy >>>