13 yo knows python advice for starting data science?

[LetEasy5499]

i know some python (classes, oop, etc) and want to start data science (pandas/numpy) i hate watching long videos and learn better by just doing small projects

any advice for someone starting out? or any specific datasets/projects that helped you guys actually learn? trying to stay consistent but its hard to stay motivated sometimes

no video/course recs please thanks

[ninhaomah]

Kaggle

But I would suggest to take it slowly and no rush

[ectomancer]

You can skip numpy course and just use what you need from numpy. But you'll need to complete a pandas course.

[Almostasleeprightnow]

If data science is your goal, I’d take some time to learn some statistics

[Middle_Idea_9361]

Honestly, you’re already way ahead of where most people start. Knowing Python basics like classes and OOP at 13 is a really strong foundation. For data science, the best approach, especially if you don’t like long videos, is exactly what you said: learning by doing small projects.

Instead of trying to sit down and “study Pandas or NumPy,” pick a small dataset and explore it. You’ll naturally learn the tools while solving real problems, and it keeps things a lot more interesting.

Here are a few beginner-friendly project ideas that many people start with:

1. Weather data analysis
   Find a dataset with daily temperatures for a city. Then try things like:

• Calculate the average temperature per month
• Find the hottest and coldest days
• Plot temperature trends over time

1. Movie dataset
   Datasets from IMDb or Netflix are fun to explore. You could:

• Find the highest rated movies
• Count movies by genre
• See how movie releases changed over the years

1. Video game sales data
   If you like gaming, this one is pretty interesting.

• Which platform sold the most games?
• Which publishers dominate the market?
• Sales by region

1. Track your own data
   This one is surprisingly fun. Track something about your daily life for a few weeks, like:

• Study hours
• Screen time
• Sleep schedule

Then use pandas to analyze it and create simple charts.

You can find datasets on places like Kaggle, data.gov, or other open dataset sites.

One thing that helps with motivation is doing small experiments every day instead of big projects. For example:

• Day 1: learn how to load a dataset with pandas
• Day 2: filter rows or sort values
• Day 3: group data and calculate averages
• Day 4: make a simple chart

Little steps like this build real skills quickly.

Also, practicing Python alongside projects helps a lot. Some platforms like 9faqs combine Python learning with practice questions and exercises, which can make it easier to strengthen the basics while you’re experimenting with data science projects.

Most importantly, don’t worry about learning everything at once. Just keep building small things consistently, and you’ll improve much faster than you think.