FIFA20 Data Exploration using Python

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In this Guided Project, you will:

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

Clock100 Minutes
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

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.

Skills you will develop

Data Pre-ProcessingPlotlyPandasData Visualization (DataViz)Exploratory Data Analysis

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. importing FIFA20 players dataset and take a look at the columns

  2. prepare our dataset for Data exploration by dropping useless columns and calculating new features

  3. Plotting a scatter plot to see the relationship between the Overall ratings and age of the players and their price

  4. Plotting a pie chart to see the proportion of right-foot players and left-foot players

  5. Creating a method to plot a Scatterpolar for comparing a Players growth over Time

  6. Creating a method to pick top 5 player based on a the player position and the player value in euro

How Guided Projects work

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



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