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Surf's Up! Querying a SQL database, hosting that data in a JSON app, and then visualizing that data.

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Surf's Up!

Aloha! (Description):

  • The following is an analysis of weather at one of my favorites states to live in, Hawaii. The goal to visualize precipitation, temperature frequency, and average temperature.

How'd I do it?:

  • I used numerous Python analysis libraries to conduct this project. I used SQL Alchemy to query the hawaii.sqlite database. I used pandas to turn these queries into dataframes and then into csv's. Then I used pandas again to clean the data and then numpy and matplotlib to visualize the data. Finally, I created app.py using the Flask library to host the data in JSON format.

Where to find what:

  • You can find the data clean up process under Notebook/data_engineering.ipynb.

  • You can find the database engineering process under Notebook/database_engineering.ipynb.

  • You can find the analysis and visualizations under Notebook/climate_analysis.ipynb.

  • You can find my climate API under climate_app.py. Run from the command line or terminal to make calls that returns data in JSON format.

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Surf's Up! Querying a SQL database, hosting that data in a JSON app, and then visualizing that data.

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