Pandas Fundamentals | Series & DataFrames
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In this video, you’ll learn the fundamentals of working with Pandas and NumPy, two essential Python libraries for data manipulation and analysis. We cover how to create and work with Pandas Series and DataFrames, exploring various methods and use cases. You’ll also see examples of creating Series from lists, dictionaries, and NumPy arrays, as well as how to combine Series into DataFrames. Additionally, we demonstrate adding and removing columns, accessing rows and columns, and much more. This is a must-watch if you’re diving into Python for data analysis!
To start learning without installing Python locally, use Google Colab.
Introduction to Google Colab: • Google Colab Basics
Create a new Google Colab Notebook: https://colab.research.google.com/#cr...
Table of Contents:
0:00 Introduction to Pandas and NumPy
0:08 Overview of Series and DataFrames
0:26 Importing Libraries (Pandas, NumPy)
0:57 Pandas Series: Basics and Examples
1:13 Creating Series from Lists, Dictionaries, and NumPy Arrays
2:43 Custom Indices in Series
4:04 Creating Series from a Dictionary
5:51 Random Numbers to Series
7:02 Introduction to DataFrames
7:25 Creating DataFrames from Dictionaries and Lists
12:02 DataFrames from NumPy Arrays
14:38 Combining Series into DataFrames
16:50 Adding and Removing Columns
19:17 Accessing Columns and Rows (loc and iloc)
21:41 Join AI Learning Hub
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