Exploratory Data Analysis on English Premier Data (2020/2021)

the_analystee
2 min readMar 13, 2022

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The aim of this study is to carry out a descriptive statistical analysis and visualisation of the 2020/2021 EPL season The following are the objectives:

A. Data Wrangling

1. Import the necessary Python libraries
2. Observe the dataset for inconsistencies and carryout data imputation where necessary

B. Exploratory Data Analysis (EDA)

1. Analyse statistical data of the respective clubs
2. Analyze the statistical data of the players

Importing the libraries and dataset

The libraries needed for this analysis are:

1. Pandas: For importing the dataset and to work on the DataFrame
2. NumPy: To carryout respective mathematical operations on the dataset
3. Matplotlib: For data visualisation

Exploratory Data Analysis (EDA)

Player Statistics

Objectives:

1. Who are the leagues most lethal scorers?
2. Who are the leagues top assist makers
3. Who are the best passers
4. Who are the dirtiest and most disciplined players?

Despite finishing the season at 7th position, Tottenham Hotspur has 2 players in among the league’s Top 5 goalscorers with Golden Boot Award winner, Harry Kane (23) leading the poll and his strike partner Son Heung-Min (17) placing 5th overall. Mo Salah (22), Bruno Fernandes (18) and Patrick Bamford (17) who play for Liverpool, Manchester United and Leeds United respectively complete the Top 5.

Harry Kane did not only outscore every other player in the league, but he was also the most generous in laying assists for his teammates with a whooping 14 assists despite playing as the top striker. Interestingly, his strike partner Son Heung-Min also recorded 10 assists which shows how much both players enjoy playing together. Another player with great attacking output is Bruno Fernandes who recorded 12 assists alongside the 18 goals he scored. Kevin De Bruyne (12) and Jack Grealish (12) complete the poll.

DATA VISUALISATION

The following visuals were developed using Power BI Desktop

Club Analysis
Player Analysis

Thank you for reading.

The complete analysis and other files such as dataset, images and Power BI files can be gotten from my GitHub repository. Follow this link to interact with the dashboard on Power BI.

Kindly upvote and give your feedback as it will help me improve both in analytics and report writing as I continue to work on my skills.

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the_analystee

Data Analyst — MS Excel, SQL, Python, Power BI and Researcher | Networker | SDG 4 Advocate |