Skip to main content

A small example package

Project description

BMI calculation

The following are the objective,

  1. Calculate the BMI (Body Mass Index) using Formula 1, BMI Category and Health risk from Input data (person_detail.json) of the person and add them as 3 new columns.

         Formula 1 - BMI
         BMI(kg/m2) = mass(kg) / height(m)2
    
  2. Count the total number of overweight people using ranges in the column BMI Category.

     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
    

There are few major functions used in the whole program,

  1. 'fitness_calc.py' (in 'src' directory) has the functions to calculate BMI, Categorization and the count of Overweight persons.
  2. 'utility.py' is created to make functions generic. It has the file handling functions.
  3. 'test.py' has the function to unit test the code.
  4. 'main.py' is used to get the desired output from the input data.
  5. 'person_detail.json' has the input data containing persons' Gender, Height and Weight.
  6. 'Final_BMI_Results.csv' will give the desired out in .csv format.
  7. 'setup.py' has the required package details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

code-20220213-pinakpani-pinak47-0.0.1.tar.gz (2.9 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file code-20220213-pinakpani-pinak47-0.0.1.tar.gz.

File metadata

  • Download URL: code-20220213-pinakpani-pinak47-0.0.1.tar.gz
  • Upload date:
  • Size: 2.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.0 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10

File hashes

Hashes for code-20220213-pinakpani-pinak47-0.0.1.tar.gz
Algorithm Hash digest
SHA256 96c725b982badc4870e3ecc45cb08e1dfa743dbedd075c850e78283feedd0ef0
MD5 13803f3a3fcffc2695c6cd40660c6478
BLAKE2b-256 7511d9bd1c3f6b21fd6789208f719b048c0d870506cfb4e772e55cf62f594295

See more details on using hashes here.

File details

Details for the file code_20220213_pinakpani_pinak47-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: code_20220213_pinakpani_pinak47-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 3.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.0 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10

File hashes

Hashes for code_20220213_pinakpani_pinak47-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 90d4d93c6cb00dec9b6fe2962a0886838a7472d6969848a28b71579552487ece
MD5 b70c13066f0cd7e41cc929211c3ce1d4
BLAKE2b-256 234a8f6f7b216d0fbb91ea0ac612e0bb2f475c3a45ce5ab7bc9f4faaf5f2f867

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page