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Delving deeper into data

1. Delving deeper into data

After our deep dive into data exploration and aggregate analysis, we will now examine user fitness behavior fluctuations throughout the week. Let's explore!

2. Data dive recap

Before we do that, let's revisit what we have already done. We transformed date-related fields from strings to dates, merged datasets, computed BMI, categorized lifestyle indexes, and set sitting thresholds. That's quite an accomplishment!

3. Data dive reflections

In the previous chapter, our goal was to determine where the users stand in relation to these norms. We analyzed users' activity levels, health risks, and BMI to determine their position in relation to established norms. The slide summarizes all the findings.

4. WHO guidelines: weekly physical activity

The World Health Organization (WHO) recommends at least 150 to 300 minutes of Moderate to Vigorous Physical Activity (MVPA) per week for all adults, including people living with chronic conditions or disability. Physical activity is vital for maintaining overall health, enhancing mood, and reducing the risk of chronic diseases.

5. Weekday behavior pattern

Analyzing weekly behavior patterns provides valuable insights for targeted interventions and lifestyle improvements. In this chapter, we will focus on finding: Sleep patterns by weekday, weekday step count analysis, and weekly active minutes summary.

6. Revisiting business questions

To attract more customers, we need to enhance our products and marketing strategy. Key sub-questions to consider include: - What is the predominant lifestyle based on the lifestyle index? - How do users' physical activity levels compare to recommended norms? - What are users' activity/exercise schedules? - What are the most tracked activities?

7. Let's practice!

While keeping all the business-related questions in mind, let's endeavor to complete the last chapter to find all the answers!

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