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

• Analyse The Data And Build Useful Insights & Visualization

• Identify The Releationship Between Each Features.

• Find Reasons For The Each Realtionships.

• 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).

Pandas, Numpy, Matplotlib, seaborn

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