pyzdc 0.6.0

PyZDC is a Python package designed to facilitate the extraction, transformation, and analysis of epidemiological data related to Dengue, Zika, and Chikungunya.

PyZDC

PyZDC is a Python tool designed to simplify the analysis of epidemiological data related to the Aedes aegypti, focusing on diseases such as Dengue, Zika, and Chikungunya. It is fast, extensible, and easy to use.

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Features

• Automated extraction of epidemiological data.
• Data transformation and validation using DuckDB and Pandera.
• Specific functions to access processed tables, including notifications, personal data, clinical signs, and more.
• Fully compatible with Python 3.12+.

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Installation

Install the package via pip:

pip install pyzdc

Install the package using uv or poetry:

# uv
uv add pyzdc

# poetry
poetry add pyzdc

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Quick Example

Here’s a quick example to get you started:

import pandas as pd
import pyzdc as zdc

# Fetch notification data for Chikungunya cases in 2022 and 2023
df = zdc.get_notifications(years=[2022, 2023], disease="CHIK")

# Display the first few rows
print(df.head())

# Save the DataFrame to a CSV file
df.to_csv("notifications.csv", index=False)

This will output something like:

       notification_id    notification_type  disease_condition_id      notification_date    notification_week    notification_year    notification_state_id    notification_city_id    notification_region_id    notification_health_unit_id 
  0                  1                    2  A92.0                              20220108               202201                 2022                       12                  120033                  1941                            9542566 
  1                  2                    2  A92.0                              20220216               202207                 2022                       12                  120033                  1941                            9542566 
  2                  3                    2  A92.0                              20220126               202204                 2022                       12                  120033                  1941                            9542566 
  3                  4                    2  A92.0                              20220108               202201                 2022                       12                  120033                  1941                            9542566 
  4                  5                    2  A92.0                              20220126               202204                 2022                       12                  120033                  1941                            2000083 

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Help

For more information, see the documentation.

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Contributing

Contributions are welcome! Follow these steps to contribute:

1. Fork the Repository

Create a fork of the repository in your GitHub account.

2. Clone the Repository

Clone your fork locally:

git clone https://github.com/your-username/dq-sus.git
cd dq-sus

3. Create a Branch

Create a branch for your changes:

git checkout -b feature-name

4. Install Dependencies

Install the required dependencies using pip or uv:

pip install -r requirements.txt

5. Make Changes and Test

Implement your changes and ensure all tests pass:

pytest

6. Commit and Push

Commit your changes and push to your fork:

git add .
git commit -m "Add feature description"
git push origin feature-name

7. Open a Pull Request

Submit a pull request to the dev branch of the original repository.

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Security

To report security vulnerabilities, please review our security policy.

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License

This project is licensed under the MIT License.