Python

FIFA 21 Players Dataset Data Cleaning & Transformation

⚽FIFA21 Data Cleaning & Transformation

FIFA21 is a popular video game that simulates soccer matches. Often, data collected from this game might be messy, containing missing values and various formating issues. As an enthusiastic soccer fan, I put together this project to practice data cleaning and data exploring for analysis using Python and Pandas.

🛠️Tools

• Python

📊The FIFA21 Dataset

I found the FIFA21 Dataset on Kaggle. The dataset contains 17,000+ players featuring in FIFA21, each with more than 70 attributes.

💡Highlights

• England had the highest amount of players, making up 8.98% of all players.
• Spain had the most players in the Top 100.
• Identified highly valuable, underpaid players by comparing player overall performance and wages.

✏️Data Wrangling

• Removed rows with missing values
• Converted height and weight columns to appropriate data types
• Cleaned and transformed the value, wage, and release clause columns into columns of integeters
• Removed the unnecessary newlien characters
• Separated the Team and Contract columns
• Converted ‘star’ characters to numeric data
• Converted attribute stats to an average of the sum