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

European Soccer Data Analysis

The dataset I am going to use is from European Soccer Database (https://www.kaggle.com/hugomathien/soccer) has more than 25,000 matches and more than 10,000 players for European professional soccer seasons from 2008 to 2016.

The dataset also has a set of about 35 statistics for each player, derived from EA Sports' FIFA video games. It is not just the stats that come with a new version of the game but also the weekly updates. So for instance if a player has performed poorly over a period of time and his stats get impacted in FIFA, you would normally see the same in the dataset.

During this course, I have learnt the basics of python programming, uses of numpy library, data analysis using pandas and visually present the data using several visualization libraries.

project_name = "zerotopandas-course-project-akg"
from google.colab import drive
drive.mount('/content/drive')
Mounted at /content/drive

Importing Modules

import jovian
import sqlite3
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as  sns