Python Pandas Tutorial for beginners: Python for data analytics
In this video we’re going to learn about Python’s data analytics library called Pandas. This is a beginner tutorial that aspires to teach you some fundamental principles so that you’re inspired to continue exploring Python.
Python is a programming language. You can implement Python in various environments including script files, notebooks, and terminal or command line. My preference is to code in a script file; my editor of choice is PyCharm. Another popular editor is VS Code.
This lesson will take place in a notebook. I wanted to craft a tutorial that minimizes the barrier to entry so that you can overcome the friction that comes from learning something new. So I decided to use Google Colab, which is Google’s version of a Jupyter notebook. You will need a Google Account in order to access Colab but it’s completely free and easy to install.
Pandas is a data analytics library. It’s called Pandas bc it stands for Panel Data, which means that it formats values in a row and column format similar to a spreadsheet. However, it is much more powerful than a spreadsheet and it will fundamentally change the way you approach data work.
This lesson will cover:
2:45 How to install Colab
3:49: Pandas explanation
4:40: How Python notebooks work
6:49: Declaring variables + Data Types
11:23: How to lists work in Python
20:17: How dictionaries work in Python
24:45: How to import Pandas in Python
26:35: How to build DataFrames
30:00: How to build DataFrames with Lists
35:12: How to sort DataFrames in a DataFrame
39:33: How to replace Values in a DataFrame
50:00 How to drop columns in a DataFrame
54:30: How to add columns in a DataFrame with Merge
1:01:00: How to add rows in a DataFrame
1:04:36: How to query data in a DataFrame
1:08:40: How to use sum, average, and median in a DataFrame
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