BMI Calculator using python Problem Statement Given the following JSON data
[{"Gender": "Male", "HeightCm": 171, "WeightKg": 96 }, { "Gender": "Male", "HeightCm": 161, "WeightKg": 85 }, { "Gender": "Male", "HeightCm": 180, "WeightKg": 77 }, { "Gender": "Female", "HeightCm": 166, "WeightKg": 62}, {"Gender": "Female", "HeightCm": 150, "WeightKg": 70}, {"Gender": "Female", "HeightCm": 167, "WeightKg": 82}] as the input with weight and height parameters of a person, we have to perform the following:
- BMI (Body Mass Index) using Formula 1, BMI Category and Health risk from Table 1 of the person and add them as 3 new columns
- Count the total number of overweight people using ranges in the column BMI Category of Table 1, check this is consistent programmatically and add any other observations in the documentation
Formula 1 - BMI
BMI(kg/m2) = mass(kg) / height(m)2 The BMI (Body Mass Index) in (kg/m2) is equal to the weight in kilograms (kg) divided by your height in meters squared (m)2. For example, if you are 175cm (1.75m) in height and 75kg in weight, you can calculate your BMI as follows: 75kg / (1.75m²) = 24.49kg/m²
Table 1 - BMI Category and the Health Risk
BMI Category BMI Range (kg/m2) Health risk
- Underweight 18.4 and below Malnutrition risk
- Normal weight 18.5 - 24.9 Low risk
- Overweight 25 - 29.9 Enhanced risk
- Moderately obese 30 - 34.9 Medium risk
- Severely obese 35 - 39.9 High risk
- Very severely obese 40 and above Very high risk