Tips and tricks for Working with Demographic Data [CARTOframes & Python]
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The document outlines tips and tricks for working with demographic data using the Carto platform, emphasizing the ease of accessing this data through the Data Observatory. It introduces tools such as CartoFrames and highlights the integration of demographic information into Python workflows to enhance data analysis. Additionally, it provides links to useful documentation and contact information for assistance.
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Tips and tricks for Working with Demographic Data [CARTOframes & Python]
- 1. Tips and Tricks for working with Demographic Data FOLLOW @CARTO ON TWITTER
- 2. 2018CARTO — Turn Location Data into Business Outcomes Today’s speakers Holly Orr Customer Success Manager Alex Roth Solutions Engineer
- 3. How the Data Observatory makes demographic data access easy. How to use CARTOframes to get demographic data from the DO. How to use the CARTO platform to work with demographic data insights. What you’ll learn today...
- 4. Census Data Python CARTO What we assume you’re familiar with...
- 5. Demographics is defined as statistical data about the characteristics of a population, such as the age, gender and income of the people within the population. When the census assembles data about people's ages and genders, this is an example of assembling information about demographics.
- 10. What we realized is that we need an easier way to incorporate demographic data in the CARTO platform.
- 12. ● Created out of an internal need on our data science team ● Saves time: integrates CARTO maps, data, analysis into Python workflows ● Plays nicely with Python data science ecosystem: pandas, matplotlib, geopandas, Jupyter ● Supports iterative and reproducible workflows What is CARTOframes and why should I care?
- 13. SUGAR In computer science, syntactic sugar is syntax within a programming language that is designed to make things easier to read or to express. It makes the language "sweeter" for human use: things can be expressed more clearly, more concisely, or in an alternative style that some may prefer.
- 14. IDE: Interactive Computational Environment Project Jupyter's operating philosophy is to support interactive data science and scientific computing across all programming languages via the development of open-source software.
- 15. Presentation
- 16. Enrichment Augment any data with demographic data from around the globe with ease Data Observatory Data Services API Routing & Traffic Geocoding Create locations from addresses and understand travel time all from within CARTO ETL Develop robust ETL processes and update mechanisms so your data is always enriched Premium data to understand and analyze deeper trends and behavior Mastercard Human Mobility POI
- 17. Integration Using CARTO’s APIs and SDKs, connect your analysis into the places that matter most for you and your team
- 19. Useful Documentation Links: Data Observatory https://carto.com/developers/data-observatory/ Developers Center: CARTO Data Observatory https://carto.com/developers/data-observatory/ Developers Center: DO + CARTOframes https://carto.com/developers/cartoframes/guides/Data-Observatory/ CARTOframes Latest Documents:
- 20. Developers Center: CARTO Data Observatory https://carto.com/developers/data-observatory/ Developers Center: DO + CARTOframes https://carto.com/developers/cartoframes/guides/Data-Observatory/ How can I change sync table data with SQL?: https://carto.com/help/working-with-data/sync-sql/ How to insert geometries to a CARTO dataset https://carto.com/help/working-with-data/add-geometries/Developer
- 21. Thanks for listening! Any questions? Request a demo at CARTO.COM Holly Orr Customer Success Manager // holly@carto.com Alex Roth Solutions Engineer // alex@carto.com