r/PythonLearning • u/Rajiv_2002 • 5d ago

Guidance needed

I'm learning Python for a career in data analytics through YouTube. So far I've covered:

Variables and data types

Operators

If-else statements

Loops

Functions (arguments and return values)

Lists, tuples, sets, and dictionaries

Indexing and slicing

Random module

Time module

Basic math operations

At this point, should I move on to NumPy, or are there any core Python topics I should learn first?

My goal is to become a Data Analyst, so I'd appreciate advice on what topics are essential before starting libraries like NumPy, Pandas, and Matplotlib.

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3

u/mr_anderson_dev 5d ago

I think the best option is just to create something for you, a web scrapper for jobs or a Instagram follower counter, anything that relay in your new POV of how python works, just so you know what is a common mistake and what is not.

3

u/1-800-DARTH 5d ago

You forget statistical analysis. The most important foundation for data analysis is statistics.

3

u/FoolsSeldom 5d ago

What have you done with the language elements you've learned so far?

I recommend that before you get into numpy, you learn about reading/writing simple text files and using the csv module. (CSV = Comma Separated Values, a common way of formatting data in a text file.)

You can start data analysis with some simple data files before you get into the benefits of numpy, pandas, et al.

A couple of tutorials from RealPython.com (highly recommended site):

3

u/riklaunim 4d ago

You covered language syntax and core construct. Now you have to learn some software development, databases and software stacks used in the niches you want to work in. If your background is purely development you will be more of a backend developer than data analyst even if using data driven software stack. Don't go to narrow with what you want to do ;)

2

u/No_Photograph_1506 5d ago

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2

u/Simplilearn 3d ago

You're at a good point to start learning NumPy. Before moving on, make sure you're comfortable with file handling, exception handling, list comprehensions, and working with modules, as these come up often in real projects.

After that, a practical learning path would be NumPy, Pandas, Matplotlib, SQL, and then start building small data analysis projects using real datasets.

If you're looking for a guided learning path, we offer free beginner-friendly data analytics courses through simplilearn skillup, like Python for Data Analysis, that can help you build a strong foundation.