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1
Introduction
2
Agenda
3
EDA Introduction
4
Data Analysis Process
5
Why is EDA Important
6
Types of EDA
7
Examples of EDA
8
Outliers
9
Advantages
10
Data Set
11
Demo
12
Importing Libraries
13
Data Analysis
14
Statistics
15
Questions
16
Maximum wickets
17
Plotting beautiful looking things
18
Highest Wins
19
Toss Decision
Description:
Explore the world of data analysis through a practical case study on Indian Premier League (IPL) data using Exploratory Data Analysis (EDA). Learn the importance of data analysis, its process, types of EDA, and how to handle outliers. Dive into a hands-on demonstration using Python to import libraries, analyze IPL statistics, and create visually appealing plots. Discover insights on maximum wickets, highest wins, and toss decisions. Gain valuable skills in data-driven decision-making applicable across various sectors and functions, setting the foundation for a career in data science, big data analytics, and machine learning.

IPL Data Analysis Using EDA - EDA Case Study - What Is EDA? - Great Learning

Great Learning
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