Explored team and player performance in the World Cup 2023 dataset through thorough EDA, uncovering insights on batting, bowling, opposition, ground dynamics, and temporal trends.
--> Python is a high-level, general-purpose, and very popular programming language.
--> Python programming language (latest Python 3) is being used in web development, Machine Learning applications, along with all cutting-edge technology in Software Industry.
--> Python is available across widely used platforms like Windows, Linux, and macOS.
--> The biggest strength of Python is huge collection of standard library.
--> Colaboratory, or “Colab” for short, is a product from Google Research which allows anybody to write and execute python code in Jupyter notebook through the browser.
--> Visit colab at:
--> Create account using google account.
--> Once account creation is done, we can directly start coding in colab.
--> It supports Python and R.
--> Files are directly saved in Google Drive.
--> To install python library this command is used-
pip install library_name
--> Data Visualization is the presentation of data in pictorial format.
--> Target was to see the performance analysis and variations using data visualization.
--> In this project visualization of CSV file containing data of players is done in python.
--> Data visualization is done to analyze performance of team and players.
--> Patterns found in the analysis are listed.
--> This contains data about various players and respective data in Comma Separated Value (CSV) format.
--> CSV file contains the details of automobile-mileage,length,body-style among other attributes.
--> It contains the following dimensions-[1408 rows X 20 columns].
Short Description about all libraries used in Project.
- Pandas (Panel Data/ Python Data Analysis) - This library is mostly used for analyzing, cleaning, exploring, and manipulating data.
- Matplotlib - It is a data visualization and graphical plotting library.
- Seaborn - It is an extension of Matplotlib library used to create more attractive and informative statistical graphics.
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