https://github.com/serhatderya/medical_examination_research
This repository contains a research about medical examinations (such as body measurements, results from various blood tests, and lifestyle choices).
https://github.com/serhatderya/medical_examination_research
catplot data-analysis data-analytics data-cleaning data-preparation data-preprocessing data-science data-visualization eda exploratory-data-analysis exploratory-data-visualizations heatmap jupyter-notebook medical preprocessing python research seaborn
Last synced: about 2 months ago
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This repository contains a research about medical examinations (such as body measurements, results from various blood tests, and lifestyle choices).
- Host: GitHub
- URL: https://github.com/serhatderya/medical_examination_research
- Owner: SerhatDerya
- Created: 2022-03-20T13:17:57.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-03-20T13:53:20.000Z (about 4 years ago)
- Last Synced: 2025-06-07T00:05:13.945Z (about 1 year ago)
- Topics: catplot, data-analysis, data-analytics, data-cleaning, data-preparation, data-preprocessing, data-science, data-visualization, eda, exploratory-data-analysis, exploratory-data-visualizations, heatmap, jupyter-notebook, medical, preprocessing, python, research, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 1.08 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ~~ Medical Examination Research ~~
## Description
The rows in the dataset represent patients and the columns represent information like body measurements, results from various blood tests, and lifestyle choices.
| Feature | Variable Type | Variable | Value Type |
|:-------:|:------------:|:-------------:|:----------:|
| Age | Objective Feature | age | int (days) |
| Height | Objective Feature | height | int (cm) |
| Weight | Objective Feature | weight | float (kg) |
| Gender | Objective Feature | gender | categorical code |
| Systolic blood pressure | Examination Feature | ap_hi | int |
| Diastolic blood pressure | Examination Feature | ap_lo | int |
| Cholesterol | Examination Feature | cholesterol | 1: normal, 2: above normal, 3: well above normal |
| Glucose | Examination Feature | gluc | 1: normal, 2: above normal, 3: well above normal |
| Smoking | Subjective Feature | smoke | binary |
| Alcohol intake | Subjective Feature | alco | binary |
| Physical activity | Subjective Feature | active | binary |
| Presence or absence of cardiovascular disease | Target Variable | cardio | binary |
## Tasks
#### 1) Preprocess
* "cholesterol" and "gluc" variables' values turned into appropriate values.
* "overweight" variable was added.
* Incorrect and outlier data was eliminated.
#### 2) EDA & Visualization
* Data was converted to long format and a chart was created that shows the value counts of the categorical features. Chart was splitted by "cardio" variable.
* A correlation matrix of the dataset was created and was used for creating a heatmap.