About
A Python Library for accessing harmonized spatiotemporal data and retrieving it in a Pandas DataFrame format. The main goal is to provide a tool that simplifies access to multiscale data related to health in critical regions affected by climate change. It integrates datasets such as climate reanalysis, weather forecasts, socioeconomic and demographic data, epidemiological surveillance, and drone imagery.
The client is designed to interact with the Earth Observation Data Cube tuned for Health Response Systems (EODCtHRS), which builds upon the digital infrastructure of the Brazil Data Cube (BDC) from the National Institute for Space Research (INPE), ensuring integration and interoperability between multiple data sources.
The library allows users to list available collections, retrieve metadata, and access filtered data.
Installation
See INSTALL.rst.
Using Harmonize Datasources in the Command Line
See CLI.rst.
License
Release files for harmonize-ds 0.4.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| harmonize_ds-0.4.0.tar.gz | 614.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| harmonize_ds-0.4.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 662.8 kB
Release files / harmonize_ds-0.4.0.tar.gz
| Download URL | harmonize_ds-0.4.0.tar.gz |
|---|---|
| Size | 614.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/6.2.0 CPython/3.10.12
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Release files / harmonize_ds-0.4.0-py3-none-any.whl
| Download URL | harmonize_ds-0.4.0-py3-none-any.whl |
|---|---|
| Size | 48.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.12
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