Surf’s Up

I did a climate analysis before going on a trip to Honolulu,Hawaii.

Part 1: Analyze and Explore the Climate Data

1. First, I created a SQLAlchemy engine to connect to my SQLite database(hawaii.sqlite).

2. I connected to the database and saved references to the station and measurements tables.

3. I found the most recent date in the dataset (it was 2017-08-23) and obtained the precipitation data for the last 12 months of data.

4. I loaded the results onto a dataframe and created a plot to display those results:

5. I displayed the summary statistics for the precipitation data. The summary showed:

   • The count of datapoints was: 2015.00
   • The mean inches of precipitation were: 0.18
   • The standard deviation was: 0.46
   • The minimum inches of precipitation were: 0.00
   • The 25% inches of precipitation were: 0.00
   • The 50% inches of precipitation were: 0.02
   • The 75% inches of precipitation were: 0.13
   • The maximum inches of precipitation were: 6.70

6. Then, I obtained the total number of stations in the dataset (they were 9) and listed the stations and the number of entries from each station in the dataset in descending order:

   • USC00519281: 2772 entries
   • USC00519397: 2724 entries
   • USC00513117: 2709 entries
   • USC00519523: 2669 entries
   • USC00516128: 2612 entries
   • USC00514830: 2202 entries
   • USC00511918: 1979 entries
   • USC00517948: 1372 entries
   • USC00518838: 511 entries

7. I obtained the lowest, highest and average temperatures for the most active station:

   • Most active station: USC00519281
   • Minimum temperature: 54.0
   • Maximum temperature: 85.0
   • Average temperature: 71.66

   

Part 2: Design Your Climate App

1. I created a Flask API. In the homepage I displayed all the available routes:

   • /api/v1.0/precipitation
   • /api/v1.0/stations
   • /api/v1.0/tobs
   • /api/v1.0/start
   • /api/v1.0/start/end
     • Where the 'start' and 'end' date should be in the YYYY-MM-DD format.

2. In /api/v1.0/precipitation, I displayed the last 12 months of precipitation data.

3. In /api/v1.0/stations I displayed a list of the 9 stations in the dataset.

4. In /api/v1.0/tobs I displayed the temperature observations for the most active station 'USC00519281' during the last 12 months of data.

5. In /api/v1.0/start & /api/v1.0/start/end, I displayed a list that calculated the minimumm temperature, the average temperature and the maximum temperature for the 'start' and 'end' dates entered in the url by the user.