Pandas is one of the most important software library used for data manipulation, wrangling, visualization and so on. This course introduces Data Analysis from scratch up to an intermediate level by covering the basics of Python, Numpy, Pandas, Data Visualization, and Exploratory Data Analysis. More about this course can be found using this link Data Analysis with Python: Zero to Pandas
This repository contains multiple CSV files and four Jupyter notebooks: three assignments and one project notebook.
This assignment features introduction to fundamental concepts in Python such as variables, loops, lists, dictionary, arithmetic operations and so on.
Introduction to Numpy. In this assignment, I demonstrated basic understanding of Numpy by performing some operations on Polynomials.
Pandas. The objective of this assignment is to gain some hands-on experience with the Pandas library for analyzing tabular data. In this assignment I created data frames from CSV files, queried and index operations on data frames, grouped, merged and aggregated data frames, fixed missing and invalid values in data and so on.
Using the concepts I learned from the previous lessons, I performed an analysis of player stats in the 2018/2019 English Premier League session. Information about the datasets, visualization and insights can be found in the project notebook
