https://github.com/PanosChatzi/Healthcare_and_Bioinformatics_Analyses

This repo contains the final assignments of the Data Analyst bootcamp by Workearly. Python and SQL were used to complete the assignments.
https://github.com/PanosChatzi/Healthcare_and_Bioinformatics_Analyses

data-analysis data-cleaning data-visualisation jupyter matplotlib pandas python seaborn

Last synced: 11 months ago
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This repo contains the final assignments of the Data Analyst bootcamp by Workearly. Python and SQL were used to complete the assignments.

• Host: GitHub
• URL: https://github.com/PanosChatzi/Healthcare_and_Bioinformatics_Analyses
• Owner: PanosChatzi
• Created: 2024-11-27T16:31:09.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-11-29T12:03:33.000Z (over 1 year ago)
• Last Synced: 2024-12-08T05:06:54.099Z (over 1 year ago)
• Topics: data-analysis, data-cleaning, data-visualisation, jupyter, matplotlib, pandas, python, seaborn
• Language: HTML
• Homepage:
• Size: 291 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Healthcare and Bioinformatics Data Analysis

This repo contains the final assignments of the Data Analyst bootcamp by Workearly. Here, I used Python and SQL to clean, transform, and analyze healthcare, bioinformatics and finance datasets. I also created clear figures to visualize the findings using matplotlib, seaborn, and plotly.

## Projects

  1. DrugAge: the impact of nutraceuticals on animal lifespan

  2. Cancer research analysis

  3. Longevity gene variant analysis

  4. Covid testing analysis

  5. Liquor store sales analysis

### [1. DrugAge: the impact of nutraceuticals on animal lifespan](./drugage/drugage_analysis.ipynb)

![](/drugage/overlayed_bar_and_line_plot.png)

### [2. Cancer research analysis](./cancer_research/cancer_research_analysis.ipynb)

![](/cancer_research/adjusted_rate_scatter_plot.png)

### [3. Longevity gene variant analysis](./longevity/longevity_analysis.ipynb)

![](/longevity/top_ten_populations.png)

### [4. Covid testing analysis](./covid_testing/covid_testing_analysis.ipynb)

![](/covid_testing/top_ten_countries.png)

### [5. Liquor store sales analysis](./liquor_sales/Workearly_Final_Assignment_Panagiotis_Chatzinikolaou.ipynb)

![](/liquor_sales/bottles_sold.png)

### Technologies

- Pandas for data cleaning and transformation

- Matplotlib and seaborn for data visualization

- Plotly for interactive visualizations

- Jupyter notebook for creating an interactive report

### Requirements

Install dependencies via pip:

```bash

pip install -r requirements.txt

```