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Exploratory Data Analysis of IPL Matches-Part I | by Bipin P ...

Exploratory Data Analysis of IPL Matches-Part I Objectives:. To find the team that won the most number of matches in a season. To find the team that lost the most... Data Preparation and Cleaning. Let’s star t by reading the csv file to Pandas DataFrame. So there are 756 rows and 18... Exploratory ...

IPL Data Analysis | Data Science | Python | AI | TechTrunk ...

IPL Data Analysis. In this article analysis of summary of IPL matches from 2008 to 2017 is done using Data Science and python packages like pandas, matplotlib and seaborn. The Dataset can be downloaded from here. data collected includes some properties like-Season; City in which match held; Team1; Team2; Winner; Toss decision; Win by runs; Win by wickets

IPL Data Analysis and Visualization Project using Python ...

Introduction. Data science is the study of data to extract knowledge and insights from the ...

Analysing IPL Data to begin Data Analytics with Python | by ...

Since usually such tutorials are based on in-bui l t datasets like iris, It becomes harder for the learner to connect with the analysis and hence learning becomes difficult. To overcome this, The dataset that we use in this notebook is IPL (Indian Premier League) Dataset posted on Kaggle Datasets sourced from cricsheet. IPL is one of the most popular cricket tournaments in the world, thus the problems we try to solve and the questions that we try to answer should be familiar to anyone who ...

Data Analysis on IPL Data. Being a cricket lover, I was ...

Being a cricket lover, I was waiting for the start of IPL,2020, as we all know this is the best tournament of the world. So, I thought to introduce myself performing IPL Data analysis with some ...

GitHub - srinathkr07/IPL-Data-Analysis: Data Analytics with ...

Data Analysis with IPL match-by-match dataset from the seasons 2008 to 2019. Dataset has been downloaded from Kaggle and it can be found here: https://www.kaggle.com/nowke9/ipldata. The dataset contains two files: deliveries.csv and matches.csv . The file used for this analysis is matches.csv. Things analysed: i) Match won by the maximum margin of runs.

Analyzing IPL Match Results Using Data Mining Algorithms

is analyzed by applying the data mining algorithms to the IPL dataset (2008-2015). Some of the popular variables considered in cricket literature home-field advantage, are coin-toss result, bat-first or second. Thus we measure the outcome of an Indian Premier League (IPL) matches using the data miningalgorithms. In this work Classification and

Indian Premier League (Cricket) | Kaggle

The dataset contains 2 files: deliveries.csv and matches.csv. matches.csv contains details related to the match such as location, contesting teams, umpires, results, etc. deliveries.csv is the ball-by-ball data of all the IPL matches including data of the batting team, batsman, bowler, non-striker, runs scored, etc.