Create a dashboard with four graphic representations

Reference no: EM132392692

Assignment

You have been hired as a data analyst and one of your first tasks includes selecting a car, primarily for your use, that will become part of the company fleet.

Your manager has already narrowed down the choices to four vehicles: a 2019 Ford Escape, 2019 Honda CRV, 2019 Hyundai Santa Fe, or 2019 Toyota Rav 4. Because you will purchase the car with company funds, your manager has asked you to select a vehicle based on the company's criteria; however, your own criteria for choosing a car are different.

You must use data visualization best practices to create a dashboard, using data you will scrape, and tell a story for your manager to support your car selection.

Criteria 1 (Company Criteria):

Safety features - weighted at 10

Maintenance cost - weighted at 5

Price point - weighted at 7

Criteria 2 (Your Criteria):

Insurance

Fuel Economy

Resale Value

Data Scrapping need to be done through Python and visualization need to be done through Tableau.

Either used Edmunds or JD power site to scrape the data.

Data Scrape

A. Scrape and submit the data for criteria 1 in the scenario.

B. Scrape and submit the data for criteria 2 in the scenario.

Data Configuration

C. Clean the data for criteria 1 and submit with labeled ranges and weights.

D. Clean the data for criteria 2 and submit with labeled ranges and weights. Include the weights you have selected for all three aspects of criteria 2.

E. Combine all the data and submit with labeled ranges and weightings for all six aspects of the criteria sets.

Data Presentation

F. Present your data visually based on criteria 1 in three data visualization or comparative graphic formats.

G. Present your data visually based on criteria 2 in three data visualization or comparative graphic formats.

H. Create a dashboard with four graphic representations, using accurate patterns and proportions, of all of your data for all six aspects of the criteria in the scenario.

Refer to the attachment for the cleaned and uncleaned data.

You can use the Edmund site to obtain the same data for the 2019 model using python.

Attachment:- Data Folder.rar

Reference no: EM132392692

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