Understanding Map, Replace, and Apply Functions for Effective Data Transformation in Pandas

Описание: Learn how to transform your data efficiently using Pandas map, replace, and apply methods. This tutorial covers practical techniques for cleaning, encoding, and customizing your data frames with real-world business examples using the popular tips dataset. You will see step-by-step demonstrations of mapping categorical values, replacing text, and applying custom functions for feature engineering and analysis.

By the end of this lesson, you will understand when to use each method and how to combine them for flexible data preparation. Whether you are preparing data for machine learning or improving reporting clarity, these skills will help you streamline your workflow and produce cleaner, more insightful results.

00:00 Introduction and lesson overview
00:23 Preparing the environment and loading data
01:12 Exploring the dataset structure
01:50 Why use map, replace, and apply
02:19 Mapping categorical values to numbers
02:52 Mapping smoker status
03:17 Mapping days of the week
04:07 When to use map
05:27 Using replace for value substitution
05:48 Replacing multiple values across the data frame
06:15 Introduction to apply for custom logic
07:35 Calculating tip percentage with apply
08:26 Creating a big spender flag
09:26 Applying functions column-wise
10:12 Interactive mapping challenge
11:13 Combining replace and apply
11:37 Flagging generous tippers
12:28 Making flags more readable
13:26 Recap and next steps
14:05 Final tips and encouragement

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