Pandas Fundamentals | Data Analysis Functions
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In this video, you’ll learn advanced and useful functions in Pandas for efficient data manipulation and analysis. We explore how to create a DataFrame, retrieve essential information, find unique values, apply custom functions, sort data, and much more. This tutorial is packed with practical examples to help you understand and use Pandas effectively.
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 its advanced functions
0:19 Creating a Pandas DataFrame: Employee data example
0:48 Exploring the created DataFrame: Structure and basic analysis
2:36 Using the info method: DataFrame summary and details
3:56 Retrieving column names with columns and keys methods
5:41 Using head and tail methods to preview DataFrame rows
6:14 Converting DataFrame to NumPy array with the values attribute
7:05 Determining size and dimensions of a DataFrame with size and shape
8:19 Finding unique values and their counts in DataFrame columns
9:55 Using apply to perform row-wise calculations: Adding a bonus column
11:14 Using lambda functions for on-the-fly transformations
13:08 Applying transformations to entire DataFrame with applymap
14:47 Sorting data with sort_values method: Single and multiple column sorting
17:15 Resetting index after sorting for a clean DataFrame
19:02 Final index adjustments and review
19:28 Join AI Learning Hub for resources and mentorship
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