Optimisation in Data Science Assignment

An Optimisation Project in Python. Understanding trends in Football Transfers and building a regression model to predict the market value of players.

Part I

Goal: To understand the trend of how much clubs have been paying over the market value for players over the past 14 seasons.

Files for PART I:

• Transfers.csv - The CSV file that contains the full Kaggle dataset.
• Calculating_Difference.py - The python file that calculates the Difference metric and the Average Difference.
  • Mean_Table.csv is created.
  • Line_Graph.png - Image of the line graph
• Plot_Difference.py - Python file where the line graph for Average Difference is plotted.

Packages used in PART I:

• import pandas as pd
• import numpy as np
• import matplotlib.pyplot as plt

Part II

Goal: To create a Linear Regression model that can accurately predict the Market Value of players in the coming seasons.

Files for PART II:

• Transfers.csv - The CSV file that contains the full Kaggle dataset.
• Plot_Regression.py - Python file for creating the full Linear Regression model.
  • Actual_Predicted.csv is created.
  • Linear_Regression.png - Image of the linear regression model and scatter plot

Packages used in PART II:

• import numpy as np
• import pandas as pd
• import matplotlib.pyplot as plt
• from sklearn.model_selection import train_test_split
• from sklearn.linear_model import LinearRegression
• from sklearn import metrics