FIFA20 Data Exploration using Python

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在此指导项目中,您将:

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初级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

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.

您要培养的技能

Data Pre-ProcessingPlotlyPandasData Visualization (DataViz)Exploratory Data Analysis

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  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

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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