Demonstrate data handling skills and summarize data with clarity.
Certainly! Let's take a hypothetical dataset and work through it systematically to demonstrate data handling skills. Here's an example scenario:
Dataset (Monthly Sales in Units by Product)
| Month | Product A | Product B | Product C |
|---|---|---|---|
| January | 120 | 80 | 90 |
| February | 150 | 60 | 95 |
| March | 170 | 75 | 100 |
Steps to Summarize
Identify Trends: Analyze changes in sales over the months for each product.
Calculate Key Metrics:
1) Total Sales per Product: Sum up monthly sales.
2) Average Monthly Sales per Product: Calculate mean sales over the three months.
3) Best and Worst Performers: Highlight peak performance and areas needing improvement.
Summary of Analysis
Total Sales:
Product A: 440 units
Product B: 215 units
Product C: 285 units
Average Monthly Sales:
Product A: 146.67 units
Product B: 71.67 units
Product C: 95 units
Observation:
Product A consistently had the highest sales, with growth each month.
Product B showed fluctuating sales, with a sharp dip in February.
Product C had steady improvement, indicating growing demand.
This approach demonstrates handling raw data, identifying patterns, performing simple calculations, and summarizing findings clearly.
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