This repository contains jupyter-notebook with detailed data analysis on various datasets.
The Indian Premier League (IPL) is a professional Twenty20 cricket league in India contested during March or April and May of every year by eight teams representing eight different cities in India. I have made an effort to analyze the IPL data for all seasons from 2008 to 2016. Also, Providing some interesting charts and statistics of players and IPL teams.
Links View Notebook Dataset [Kaggle]
Coronavirus is a family of viruses that are named after their spiky crown. The novel coronavirus, also known as SARS-CoV-2, is a contagious respiratory virus that first reported in Wuhan, China. Here, I am exploring COVID-19 through data analysis and projections.
Links View Notebook Dataset [Kaggle]
Exploring the ITC Limited stocks of NIFTY-50 data and along with the sectoral indices and visualising them to obtain important information. Time Series is a class of data science problems where the primary values of interest are a series of data points measured over a period of time. Here, I’ve done the analysis of stocks.
Links View Notebook Dataset [Kaggle]
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Numpy : Numpy is Numerical Python library for doing high level math computations involving complex data structures like matrices
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Pandas : Pandas is a great library for Data Science. It provides high level abstraction implementation for analysing the data. Click this link for its documentation.
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Seaborn and Matplotlib : Seaborn is another important package for visualizing the data, it provides one line python functions to plot the data similiar to MatPlotLib in MATLab except Matplotlib is not useful in some cases for visualizing where seaborn compensates this lack. Seaborn has great visualising tools like Violinplots for making better inference from the data.
Feel free to submit issues and enhancement requests.
This project is licensed under the terms of the GLP-3.0 license
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