EXECUTIVE SUMMARY

This project provides analysis of Hawaii weather and makes available queries via API.

REPOSITORY NAVIGATION

• Climate Analysis is a Jypyter Notebook that calculates and visualizes average rainfall in a bar chart and average temperature in a histogram.
• The Climate App is a Flask API application that provides climate data for 5 database queries. More detail for using the API is below.
• Additional Temperature Analysis 1 runs a t-test to compare June and December average temperatures.
• Additional Temperature Analysis 2 calculates and visualizes the minmum, average and maximum temperatures during a specified vacation date range with a bar chart and an area chart.

OBJECTIVE

Analyze compensation data for over 300,000 employees:

• Create code to set up a database using Postgre SQL, import data from csv files, and run queries
• Import data into a Jupyter Notebook
• Create code to analyze and plot compensation data
• Provide recommendations to the corporate compensation committee

API DOCUMENTATION

• Dowload the Climate App API starter code and the Hawaii weather sqlite database into the same folder on your drive.
• Run the python app on your computer.
• In your navigator enter this address: http://127.0.0.1:5000/
• You will have a menu of five API route options:
  • /api/v1.0/precipitation provides average daily rainfall for the past year.
  • /api/v1.0/stations provides a list of the stations with their coordinates, elevation and measurement activity levels.
  • /api/v1.0/tobs provides average daily temperatures for the past year.
  • /api/v1.0/ provides the minimum, average, and maximum temperature from a start date to present. Start dates should be in the following format: yyyy-mm-dd. Example: '/api/v1.0/2014-01-01'
  • /api/v1.0// provides the minimum, average, and maximum temperature from a start date to and end date. Start and end dates should be in the following format: yyyy-mm-dd. Example: '/api/v1.0/2014-01-01/2016-12-31'

DATA

Sqlite database with data from 9 weather stations on the islands of Hawaii. The original sources is Menne, M.J., I. Durre, R.S. Vose, B.E. Gleason, and T.G. Houston, 2012: An overview of the Global Historical Climatology Network-Daily Database. Journal of Atmospheric and Oceanic Technology, 29, 897-910, https://doi.org/10.1175/JTECH-D-11-00103.1.

DEPENDENCIES

• from sqlalchemy import create_engine
• from sqlalchemy.dialects import postgresql
• from config import pgadmin_pw
• import pandas as pd
• import matplotlib.pyplot as plt
• from matplotlib import style
• style.use('fivethirtyeight')
• import math
• import numpy as np
• import pandas as pd
• import datetime as dt
• from scipy import stats
• from datetime import datetime as dt
• from datetime import timedelta

PANDAS ANALYSIS

CONCLUSIONS

Hawaii has amazing weather.

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