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World Co2 Emissions Exploratory Data Analysis , Visualization & Story Telling Using Python

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World CO2 Emissions Exploratory Data Analysis | Visualization & Story Telling.

Introduction

World Co2 Emissions Exploratory Data Analysis , Visualization & Story Telling Using Python ( Based On 2016 )

Objectives

  • Analyse The Data And Build Useful Insights & Visualization

  • Identify The Releationship Between Each Features.

  • Find Reasons For The Each Realtionships.

Summary About Dataset

Features

  • Country: Unique Identifier.

  • Code: Country Code.

  • CO2Emissions: CO2 Emission by country (tons, 2016).

  • YearlyChange: Yearly CO2 Emission Change in Percentage.

  • Percapita: CO2 Emission Per Capita.

  • Population: Population of the Country (2016).

  • LifeExpectancy: Life Expectancy of the Country (2016).

Technology

Pandas, Numpy, Matplotlib, seaborn

Resources

https://www.worldometers.info/ | Already Submitted To This Repository ( Package.rar )

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World Co2 Emissions Exploratory Data Analysis , Visualization & Story Telling Using Python

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