Learn practical skills, build real-world projects, and advance your career

Anybody who is a cricket Fan should surely try to analyse this dataset as it would help you in learning with a fun factor. I have tried my best to keep this notebook as simple as possible so that even a beginner can understand it easily. At the same time I have made efforts to analyse the dataset in different aspects effectively. I will keep updating the notebook as and when I come up with new things. Hope you like it!!!

The notebook contains:

  • Basic Analysis like Teams with maximum matches, wins,etc
  • Batsman Analysis
  • Bowler Analysis
  • 200+ scores analysis

Also this is the link for my Tableau Dashboard:Indian Premier League

If you like the notebook, Please Upvote as it will keep me motivated in doing great things ahead. Thanks!!

# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load in 

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import matplotlib.pyplot as mlt
import seaborn as sns
# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory

from subprocess import check_output
print(check_output(["ls", "../input"]).decode("utf8"))

# Any results you write to the current directory are saved as output.
matches=pd.read_csv('../input/matches.csv')   
delivery=pd.read_csv('../input/deliveries.csv')
matches.head(2)
delivery.head(2)

Some Cleaning And Transformation