Python project: Medicine Scenario

Note: This project was completed as an individual assignment at Brainster Data Science Academy.

Project Description:

Analyzing the diabetes dataset to derive meaningful insights about disease management and outcomes.

Dataset info:

Dr. Zeus has collected data from 1000 diabetic patients over a year, focusing on how they manage their condition.

The dataset includes:

Duration of diabetes ('Kolku dolgo e dijabeticar')
Quarterly hemoglobin A1C levels ('Kolku mu e tromesechen (hemoglobin A1C) she4er')
Medication type (insulin or tablets) ('Dali e na insulin ili na tabli?')
Current blood glucose level ('Glukoza (momentalna) vo krv')
Presence of diabetic retinopathy ('Dali ima dijabetesna retinopatija?')

Tasks:

Data Cleaning:

Rename columns. Handle missing values appropriately.

Highest Glucose Level Analysis:

Identify the patient with the highest current glucose level. Plot all patients' glucose levels and analyze the distribution.

Hemoglobin A1C Analysis:

Calculate average hemoglobin A1C levels per disease duration. Identify the duration with the highest average glucose levels. Plot and describe the data.

Medication Comparison Analysis:

Compare the average duration of diabetes for patients on insulin vs. tablets. Determine which treatment method shows better results.

A1C Level Grouping Analysis:

Group patients by normal (below 5.7) and elevated A1C levels. Plot data based on the length of disease for both groups.

Diabetic Retinopathy Analysis:

Analyze the correlation between diabetic retinopathy and other factors. Separate patients into groups based on the presence of retinopathy and examine characteristics. Use plots to support analysis.