SQLAlchemy - Surfs Up!

Step 1 - Climate Analysis and Exploration

I used Python and SQLAlchemy to do basic climate analysis and data exploration of your climate database. All of the analysis was completed using SQLAlchemy ORM queries, Pandas, and Matplotlib.

Precipitation Analysis

• I designed a query to retrieve the last 12 months of precipitation data, selecting only the date and prcp values.

• The query results were loaded into a Pandas DataFrame and the index was set to the date column.

• The DataFrame values were sorted by date.

• The results were plotted using the DataFrame plot method.

  

Station Analysis

• I designed queries calculating the total number of stations, the most active stations(most observations), and retrieving the last 12 months of temperature observation data.

• The results were plotted as a histogram.

  

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Step 2 - Climate App

I designed a Flask API based on the queries I developed in the earlier steps, using Flask to create my routes and 'jsonify' to to convert my API data into a valid JSON response object.

Routes

• /

  • Home page.

• /api/v1.0/precipitation

• /api/v1.0/stations

• /api/v1.0/tobs

• /api/v1.0/<start> and /api/v1.0/<start>/<end>

  • A JSON list of the minimum temperature, the average temperature, and the max temperature for a given start or start-end range.

  • When given the start only, calculate TMIN, TAVG, and TMAX for all dates greater than and equal to the start date.

  • When given the start and the end date, calculate the TMIN, TAVG, and TMAX for dates between the start and end date inclusive.

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Optional: Other Recommended Analyses

Temperature Analysis I

• Identify the average temperature in June at all stations across all available years in the dataset. Do the same for December temperature.

• Use the t-test to determine whether the difference in the means, if any, is statistically significant. Will you use a paired t-test, or an unpaired t-test? Why?

Temperature Analysis II

• Use the calc_temps function to calculate the min, avg, and max temperatures for your trip using the matching dates from the previous year (i.e., use "2017-01-01" if your trip start date was "2018-01-01").

  

Daily Rainfall Average

• Calculate the rainfall per weather station using the previous year's matching dates.

• Calculate the daily normals. Normals are the averages for the min, avg, and max temperatures.