SQLAlchemy-Challenge

Introduction

This project is made to be able to give future references to people who plan to travel to Honolulu Hawaii or for people who want information about the weather in the place. It is composed of two parts that are:

• An analysis of the climate in the area

• A REST API from which you can make inquiries about the information
  • Here you can see the API -> Surfers Hawaii API

Note: More information about each one below

Tools

The following tools were used to do the analysis and the REST API

Analysis:

• Python (Pandas, matplotlib, sqlalchemy)
• Jupyter Notebook
• SQL

REST API:

• Python (flask, datetime, pymongo, os)
• NoSQL
• MongoDB

The platform used to mount the REST API is Heroku

Data

The information used is from the years 2016, 2017 and 2018 and is in a SQLite database and in .json format files, these can be found in the "Resources" folder, this was provided by Tecnológico de Monterrey. With this the analysis was performed as well as the REST API SQLite Database

Measurement Table

Column	Data Type
id	Integer
station	Text
date	Text
prcp	Float
tobs	Float

• id -> Registry Identification Number
• station -> Station Code
• date -> Record Date
• prcp -> Precipitation Measurement
• tobs -> Temperature Measurement

Station Table

Column	Data Type
id	Integer
station	Text
name	Text
latitude	Float
longitude	Float
elevation	Float

• id -> Station Identification Number
• station -> station code
• name -> station name
• latitude -> station latitude
• longitude -> station longitude
• elevation -> station elevation

Analysis

For this analysis, the information from the SQL database that was explained previously was used. This can be found in the file called 'climate_starter.ipynb'. The analysis was centralized in several stages:

• In this graph you can see the behavior of rainfall over time, in 2016 September was the most active month and in 2017 the most active months were February, April and October. This analysis can be made more specific to find the relationship between months and years.

• It was determined that:
  • The station "WAIHEE 837.5, HI US" has the highest number of observations
  • The lowest temperature recorded for the station "WAIHEE 837.5, HI US" is: 54.0
  • The highest temperature recorded for the station "WAIHEE 837.5, HI US" is: 85.0
  • The average temperature for the station "WAIHEE 837.5, HI US" is: 71.66

• An analysis of the WAIHEE station was made in which the temperature and frequency are related, here it can be observed that the frequency accumulates between the 75 and 80 range of the temperature

REST API

This API was created for the developers that want to get the data and give them some use. There are 4 API's deployed:

Static API's

• Precipitation (prcp)

The schema of the data is as follows:

[ 
  {
    "date": "date",
    "prcp": "float",
  }
]

• Stations

The schema of the data is as follows:

[ 
  {
    "Elevation": "float",
    "Latitude": "float",
    "Longitude": "float",
    "Name": "text",
  }
]

• Temperature Observations (tobs)

The schema of the data is as follows:

[ 
  {
    "date": "date",
    "tobs": "float",
  }
]

Dynamic API

In this REST API you have to write the range of dates from which you want to obtain the data, the information that it calculates in the desired range is the maximum and minimum temperature that there was as well as the average of this. There are an example in the Home web page that teach how to use the API.

The schema of the data is as follows:

[ 
  {
    "Avg Temperature": "float",
    "Max Temperature": "float",
    "Min Temperature": "float",
  }
]

• Surfers Hawaii API