CARTO Python package for data scientists
A Python package for integrating CARTO maps, analysis, and data services into data science workflows.
Python data analysis workflows often rely on the de facto standards pandas and Jupyter notebooks. Integrating CARTO into this workflow saves data scientists time and energy by not having to export datasets as files or retain multiple copies of the data. Instead, CARTOframes give the ability to communicate reproducible analysis while providing the ability to gain from CARTO’s services like hosted, dynamic or static maps and Data Observatory augmentation.
Try it Out
If you do not have an API key, you can still use cartoframes for creating maps locally.
Create interactive maps from pandas DataFrames (CARTO account not required)
Publish interactive maps to CARTO’s platform
Write and read pandas DataFrames to/from CARTO tables and queries
Create customizable, interactive CARTO maps in a Jupyter notebook using DataFrames or hosted data
Augment your data with CARTO’s Data Observatory
Use CARTO for cloud-based analysis
Visualize spatial data programmatically as matplotlib images, as notebook-embedded interactive maps, or published map visualizations
Perform cloud-based spatial data processing using CARTO’s analysis tools
Extract, transform, and Load (ETL) data using the Python ecosystem for getting data into and out of CARTO
Data Services integrations using CARTO’s Location Data Streams
Complete documentation: https://carto.com/developers/cartoframes/
Source code: https://github.com/CartoDB/cartoframes
Bug tracker / feature requests: https://github.com/CartoDB/cartoframes/issues
cartoframes users must have a CARTO API key for most cartoframes functionality. For example, writing DataFrames to an account, reading from private tables, and visualizing data on maps all require an API key. CARTO provides API keys for education and nonprofit uses, among others. Request access at firstname.lastname@example.org. API key access is also given through GitHub’s Student Developer Pack.
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