# Step Count Dashboard: Unveiling Patterns and Predictions

Data Collection and Analysis Methods

The dataset records my daily step counts along with date and month details. The analysis employs R and various packages such as flexdashboard, ggplot2, plotly, and shiny. The primary goals are to uncover insights into step count trends, identify outliers, explore relationships with external factors, and predict future step counts.

Data Exploration Questions

  1. Monthly and Yearly Trends How does step count vary across different months and years?
  2. Outlier Detection Can we identify outliers or unusual patterns in daily step counts?
  3. Weekday Variation How does step count vary across different weekdays?
  4. Weekday vs. Weekend Trends What are the distribution patterns of step counts on weekdays compared to weekends?
  5. Predictive Analysis Can we predict future step counts based on historical data?

# Question 1

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# Question 2

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Outlier Detection

# Question 3

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Weekday Variation

# Question 4

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# Question 5

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Predictive Analysis

# Summary