How dakar2024/datacollection works
This is a Streamlit dashboard for scraping and exploring animal listings from CoinAfrique. The main workflow is user-triggered scraping, saving category CSVs, then selecting cleaned data for visualization or download; users can also browse uncleaned CSVs and open an evaluation form. The excerpts show the scraping, UI, and visualization behavior, but omit the exact CSV save destination and some page details, so those connections are not inferred.
Main entry points: tech.py Streamlit dashboard · data_clean Cleaned CSVs · data_unclean Uncleaned CSVs
Components 8
Dashboard
- Streamlit dashboard
tech.py
CSV datasets
- Cleaned CSVs
data_clean - Uncleaned CSVs
data_unclean
Data acquisition
- Listing scraper
tech.py
Exploration
- Chart generation
tech.py
Other components
- Dashboard user
- CoinAfrique
- KoboToolbox form
Connections 7
- Dashboard user → Streamlit dashboard: uses
- Streamlit dashboard → Listing scraper: invokes scraping
- Listing scraper → CoinAfrique: requests listings
- Streamlit dashboard → Cleaned CSVs: reads and downloads
- Streamlit dashboard → Uncleaned CSVs: reads and downloads
- Streamlit dashboard → Chart generation: requests charts
- Streamlit dashboard → KoboToolbox form: embeds form