Partners
CDC Wonder API Data
PROJECT OVERVIEW AND AIM:
This project will utilize the CDC WONDER online public health database to access key national datasets for analysis and visualization. The project involves developing a Python Selenium script to automate the data download process from the CDC Wonder website. Requesters provide specific links to download data, and the script takes these links as input. It then automatically downloads the requested data from the provided links. Once the data is downloaded, the script will further process and format it into the required format. The final step is to present the downloaded and formatted data to the requester, ensuring that it meets their specific formatting needs. This project streamlines the data retrieval and formatting process, making it more efficient and user-friendly for requesters.
Key Findings:
1. Successfully implemented Python Selenium script for automated data downloads.
2. Challenges encountered during text-to-CSV conversion due to inconsistent formatting.
3. Ongoing efforts to find effective solutions and maintain project objectives.
4. Incorporation of data year in all downloaded files as a new requisite.
5. No new requirements identified for the CDC Wonder API.
6. Files and script shared with Jay for further work, indicating progress towards completion.
Workflow:
1. Initial data exploration and understanding of CDC website data and APIs.
2. Development of Python Selenium script for automated data downloads.
3. Successful retrieval of data from 51 specified links.
4. Challenges faced during conversion of text files to CSV format.
5. Ongoing communication with stakeholders, including Jay, to address formatting issues and optimize the process.
6. Addition of data year in all downloaded files as a new requisite.
7. Sharing files and script with Jay for further work.
8. Workflow involved initial exploration, script development, data downloading, formatting challenges, ongoing optimization, and sharing with stakeholders.
