Pandas Fundamentals | Indexing & Filtering
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In this video, you’ll learn how to perform data indexing and selection in Python using Pandas. We cover fundamental operations that allow you to access and manipulate subsets of your data efficiently. This tutorial includes practical examples to help you build a strong foundation in data analysis with Pandas.
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 Data Indexing and Selection
0:18 Creating a DataFrame with Sample Data
0:18 Defining the data dictionary
2:24 Setting custom indexes
3:30 Accessing Data in a DataFrame
3:35 Accessing column data (single column)
4:03 Accessing column data using dot notation
4:47 Accessing multiple columns
5:18 Selecting Rows in a DataFrame
5:30 Using slicing for row selection
6:28 Using loc for label-based row selection
9:09 Using iloc for position-based row selection
10:20 Selecting Specific Rows and Columns
13:39 Conditional Selection
13:39 Filtering data with conditions
15:32 Combining multiple conditions (and, or)
17:18 Using is in method for element existence
18:22 Replacing Values in DataFrame
18:22 Using where with default replacement (NaN)
19:05 Using where with custom replacement
19:24 Join AI Learning Hub
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