51 ratings
2,103 already enrolled
Learn the steps needed to be taken in order to prepare you dataset for data exploration
Learn to use data exploration and visualization to uncover initial pattern in your data
Learn to use plotly module
By the end of this project, you will learn to use data Exploration techniques in order to uncover some initial patterns, insights and interesting points in your dataset. We are going to use a dataset consisting 5 CSV files, consisting of the data related to players in FIFA video game. We will clean and prepare it by dropping useless columns, calculating new features for our dataset and filling up the null values properly. and then we will start our exploration and we'll do some visualizations. Note: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Data Pre-Processing
Plotly
Pandas
Data Visualization (DataViz)
Exploratory Data Analysis
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
importing FIFA20 players dataset and take a look at the columns
prepare our dataset for Data exploration by dropping useless columns and calculating new features
Plotting a scatter plot to see the relationship between the Overall ratings and age of the players and their price
Plotting a pie chart to see the proportion of right-foot players and left-foot players
Creating a method to plot a Scatterpolar for comparing a Players growth over Time
Creating a method to pick top 5 player based on a the player position and the player value in euro
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
by MK
Sep 23, 2020Not bad at all. Fun and great way to get into using pandas. The second to last task was too rushed and a bit of a stretch though. Slow down at that point I suggest.
by BY
Sep 23, 2020The project was very instructive! Thanks a lot! :)
by MM
Sep 16, 2020Great idea, but there is room for improvement in the implementation.
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