FIFA20 Data Exploration using Python

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在此指導項目中,您將:

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
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

  • Data Pre-Processing
  • Plotly
  • Pandas
  • Data Visualization (DataViz)
  • Exploratory Data Analysis

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  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

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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