Project_3
Project_3:
I participated in a Competition on DataCamp:
Data Analysis with Python Pandas, and Numpy libraries.
SQL query to analyze some insight from 3 different tables.
I created a report that answers the following questions for 2 different challenges:
Challenge I: Help your colleague gain insights on the type of vehicles that have lower CO2 emissions. Include:
What is the median engine size in liters?
What is the average fuel consumption for regular gasoline (Fuel Type = X), premium gasoline (Z), ethanol (E), and diesel (D)?
What is the correlation between fuel consumption and CO2 emissions?
Which vehicle class has lower average CO2 emissions, 'SUV - SMALL' or 'MID-SIZE'?
What are the average CO2 emissions for all vehicles? For vehicles with an engine size of 2.0 liters or smaller?
Any other insights you found during your analysis?
Challenge II: Help your team leader understand your company's products. Include:
What is the most expensive item your company sells? The least expensive?
How many different products of each category does your company sell?
What are the top three brands with the highest average list price? The top three categories?
Any other insights you found during your analysis?
Click on the bottom below to access the challange on DataCamp.