I've decided to treat myself to a long holiday vacation in Honolulu, Hawaii! For the trip planning, I need to do some climate analysis on the area.
- SQLAlchemy
- Matplotlib
- Pandas
- Numpy and Scipy
-
Choose a start date and end date for your trip: '08/01 - 08/07'
-
Using SQLAlchemy:
- Use
create_engine
to connect to your sqlite database. - Use
automap_base()
to reflect your tables into classes and save a reference to those classes calledStation
andMeasurement
.
- Use
- Plot the precipitation the last 12 months (8/23/2016 to 8/23/2017)
- Print the summary statistics for the precipitation data.
-
Find the most active stations: 'USC00519281'
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Retrieve the last 12 months of temperature observation data (TOBS).
- Flask to create routes.
-
/
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Home page.
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List all routes that are available.
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-
/api/v1.0/precipitation
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Convert the query results to a dictionary using
date
as the key andprcp
as the value. -
Return the JSON representation of your dictionary.
-
-
/api/v1.0/stations
- Return a JSON list of stations from the dataset.
-
/api/v1.0/tobs
-
Query the dates and temperature observations of the most active station for the last year of data.
-
Return a JSON list of temperature observations (TOBS) for the previous year.
-
-
/api/v1.0/<start>
and/api/v1.0/<start>/<end>
- Return a JSON list of the minimum temperature, the average temperature, and the max temperature for a given start or start-end range.
- Test if June and December temperature observations were significantly different using a t-test.
Calculate and plot the min, avg, and max temperature for my chosen trip date (08/01/2017 - 08/07/2017) as a bar chart.