The dataset consist of data about IPL matches played from the year 2008 to 2019. IPL is a professional Twenty20 cricket league founded by the Board of Control for Cricket in India (BCCI) in 2008. The league has 8 teams representing 8 different Indian cities or states. It enjoys tremendous popularity and the brand value of the IPL in 2019 was estimated to be ₹475 billion (US$6.7 billion). So let’s analyze IPL through stats.

Objectives:

• To find the team that won the most number of matches in a season.To find the team that lost the most number of matches in a season.Does winning toss increases the chances of victory.To find the player with the most player of the match awards.To find the city that hosted the maximum number of IPL matches.To find the most winning team for each season.To find the on-field umpire with the maximum number of IPL matches.To find the biggest victories in IPL while defending a total and while chasing a total.

Data Preparation and Cleaning

Let’s start by reading the csv file to Pandas DataFrame.

import pandas as pd
ipl_matches_df = pd.read_csv('matches.csv')
```<iframe class="ql-video" frameborder="0" allowfullscreen="true" src="https://cdn.embedly.com/widgets/media.html?src=https%3A%2F%2Fjovian.ml%2Fembed%3Furl%3Dhttps%3A%2F%2Fjovian.ml%2Fbipinp2013%2Fipl-analysis%2Fv%2F47%26cellId%3D16&amp;dntp=1&amp;display_name=Jovian&amp;url=https%3A%2F%2Fjovian.ml%2Fbipinp2013%2Fipl-analysis%2Fv%2F47%26cellId%3D16&amp;image=https%3A%2F%2Fjovian.ml%2Fapi%2Fgist%2Fb666a87e630444ec8ba8cd07b2036301%2Fpreview%2F6c3cac496d90416ca563a7b0ac77e2f3&amp;key=a19fcc184b9711e1b4764040d3dc5c07&amp;type=text%2Fhtml&amp;scroll=auto&amp;schema=jovian" height="793" width="680"></iframe>

So there are 756 rows and 18 columns. 756 rows imply that there were 756 IPL matches held between 2008 and 2019.

#data-science #exploratory-data-analysis #indian-premier-league #ipl