Hi, this repo contains a couple of examples to use the BreezoMeter API to get data for Air Quality at a specific city or location around the world and save that data into datasets with CSV format.
The main idea is to get historical records, save it into CSV files and post tweets with Air Quality conditions every day in the morning, afternoon, and evening.
There's a story behind every dataset and here's your opportunity to share yours.
Work in progress ...
What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.
Work in progress ...
We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.
Work in progress ...
Your data will be in front of the world's largest data science community. What questions do you want to see answered?
Work in progress ...
- Python 3:
- See requirements.txt file.
See ./src directory.
See ./output directory.
| Directory | Readme |
|---|---|
| ./doc | README.md |
| ./input | README.md |
| ./output | README.md |
| ./src | README.md |
Please read and execute each step below:
Create and use Python virtual environment:
$promt> python3 -m venv .venv
$promt> source .venv/bin/activateInstall all Python requirements:
$promt> pip3 install -r requirements.txtRun Python Script:
$promt> ./run.shThe BreezoMeter output is generated within ./output directory.
Work in progress ...
That's all for now ...
Getting in touch with @sebaxtianbach
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
