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Exam AWS Certified Machine Learning - Specialty topic 1 question 306 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 306
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A data scientist is building a forecasting model for a retail company by using the most recent 5 years of sales records that are stored in a data warehouse. The dataset contains sales records for each of the company’s stores across five commercial regions. The data scientist creates a working dataset with StoreID. Region. Date, and Sales Amount as columns. The data scientist wants to analyze yearly average sales for each region. The scientist also wants to compare how each region performed compared to average sales across all commercial regions.

Which visualization will help the data scientist better understand the data trend?

  • A. Create an aggregated dataset by using the Pandas GroupBy function to get average sales for each year for each store. Create a bar plot, faceted by year, of average sales for each store. Add an extra bar in each facet to represent average sales.
  • B. Create an aggregated dataset by using the Pandas GroupBy function to get average sales for each year for each store. Create a bar plot, colored by region and faceted by year, of average sales for each store. Add a horizontal line in each facet to represent average sales.
  • C. Create an aggregated dataset by using the Pandas GroupBy function to get average sales for each year for each region. Create a bar plot of average sales for each region. Add an extra bar in each facet to represent average sales.
  • D. Create an aggregated dataset by using the Pandas GroupBy function to get average sales for each year for each region. Create a bar plot, faceted by year, of average sales for each region. Add a horizontal line in each facet to represent average sales.
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Suggested Answer: D 🗳️
by kyuhuck at Feb. 7, 2024, 11:35 a.m.
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pandkast
10 months, 1 week ago
Selected Answer: D
It is the best way
upvoted 1 times
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AIWave
1 year, 1 month ago
Selected Answer: D
D: visualization provides insights into regional sales trends over time and allows for comparisons between regions and the overall average.
upvoted 2 times
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Alice1234
1 year, 2 months ago
D. Create an aggregated dataset by using the Pandas GroupBy function to get average sales for each year for each region. Create a bar plot, faceted by year, of average sales for each region. Add a horizontal line in each facet to represent average sales. This visualization allows the data scientist to compare yearly average sales across regions and see how each region's performance relates to the overall average, providing clear insights into trends and deviations.
upvoted 3 times
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kyuhuck
1 year, 2 months ago
Selected Answer: D
Explanation: The best visualization for this task is to create a bar plot, faceted by year, of average sales for each region and add a horizontal line in each facet to represent average sales. This way, the data scientist can easily compare the yearly average sales for each region with the overall average sales and see the IT Certification Guaranteed, The Easy Way! 170 trends over time. The bar plot also allows the data scientist to see the relative performance of each region within each year and across years. The other options are less effective because they either do not show the yearly trends, do not show the overall average sales, or do not group the data by region. References: pandas.DataFrame.groupby - pandas 2.1.4 documentation pandas.DataFrame.plot.bar - pandas 2.1.4 documentation Matplotlib - Bar Plot - Online Tutorials Library
upvoted 2 times
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