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ProjectPlan_Improved.md

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Data Description The source file contains rows of BMI-related information, which is tab-delimited. Each row includes:

  • A person’s unique identifier (person_id)
  • An encounter identifier (encounter_id)
  • A numerical BMI value (bmi)
  • The person’s height in centimeters (height_cm)
  • The person’s weight in kilograms (weight_kg)
  • The date of measurement (measurement_date)

This raw data from an EHR system was not collected for research purposes. There are multiple rows per person.

Task to Be Accomplished

  1. Read the Data

    • Import the file using a chosen delimiter (e.g., comma or tab).
    • Convert columns to appropriate types (particularly for dates).

  2. Clean and Filter

    • Flag rows with missing or unreasonable heights/weights.
    • Check for and flag large discrepancies between reported BMI and the BMI computed from height and weight.
    • Write the flagged entries in a separate file and continue only with the rows that pass these checks.

  3. Representative Record Selection

    • For each person, flag extreme outlier measurements (use the standard IQR approach), output them in a separate file, and continue with the remaining records.
    • For each person, select one “typical” row based on the median BMI among the remaining records.
    • If there are no valid measurements left for a person, flag them and output them in a separate file.
    • If there are multiple valid measurements, select the one closest to the median BMI.

  4. Categorize BMI, Height, and Weight

    • Assign people to categories (e.g., Underweight, Normal, Overweight, etc.) based on BMI, defined as:
      • Underweight: BMI < 18.5 kg/m²
      • Normal: 18.5 ≤ BMI < 25 kg/m²
      • Overweight: 25 ≤ BMI < 30 kg/m²
      • Obesity I: 30 ≤ BMI < 35 kg/m²
      • Obesity II: 35 ≤ BMI < 40 kg/m²
      • Obesity III: BMI ≥ 40 kg/m²
    • Create categories for height (Short, Average, Tall), defined as:
      • Short: height < 150 cm
      • Average: 150 cm ≤ height < 180 cm
      • Tall: height ≥ 180 cm
    • Create categories for weight (Light, Medium, Heavy, etc.), defined as:
      • Light: weight < 50 kg
      • Medium: 50 kg ≤ weight < 80 kg
      • Heavy: 80 kg ≤ weight < 100 kg
      • Very Heavy: weight ≥ 100 kg

Expected Output

  1. Cleaned Dataset

    • One TSV file with one row per person:
      • The "typical" BMI, plus the height, weight, and date of that measurement.
      • Categorical variables for BMI, height, and weight.

  2. Summary Table

    • A summary about the flagged entries, including:
      • The number of rows removed due to missing or implausible values.
      • The number of rows removed due to large discrepancies between reported and calculated BMI.
      • The number of extreme outlier measurements removed.
      • The number of individuals with only invalid measurements.
      • The number of individuals with valid measurements.
      • The distribution of the number of BMI measurements (e.g., mean, median, standard deviation) per person.
    • A short overview of how many individuals fall into each BMI category (plus height/weight categories).
    • May be saved as a text or Markdown file.

  3. Data Dictionary

    • A separate text listing each column and a brief explanation (e.g., person_id: a unique identifier for the person).