Project-1

Project Title:

Is GDP affected by Rainfall & Temperature Changes (over the period from 2005 - 2015)?

Contributors:

Emeka Obianyor Kiran Mundae Charles Robinson Nick Orewiler Sadie Barnett-Boudreau

Project Description/Outline:

We will be using weather (temperature and precipitation) data and available GDP data to establish any correlations between GDP, precipitation and temperature if they exsist. We will further break our data further into groups (based on GDP classifications) and analyze to establish any correlations when looking at these subsets. We set out a few questions to answer to help guide our analysis.

Research Questions to Answer:

1. Are there any discernable correlation between Temperature changes and GDP for the chosen countries? • Look for discernable trends in GDP with respect to temperature fluctuations over a 10-year period.
2. Are there any discernable correlation between precipitation and GDP for the chosen countries? • Look for discernable trends in GDP with respect to precipitation fluctuations over a 10-year period.
3. Does weather (temperature and precipitation) changes correlate with GDP in Agriculture based economies? • Analyze temperature changes and/or precipitation for countries whose GDP is predominantly agricultural based, e.g., Suriname: 0.53%, Greenland: 0.57%, Singapore: 0.95%, and the Bahamas: 1.40%.
4. How does weather (temperature and precipitation) changes correlate with GDP in Industrial based economies? • Analyze temperature changes and/or precipitation for countries whose GDP is predominantly industry based, e.g., Saudi Arabia: 44.2%, United Arab Emirates: 49.8%, Iraq: 51%, Qatar: 50.3%, Kuwait: 58.7%, Angola: 61.4%, Azerbaijan: 53.5%, Puerto Rico: 50.1%, Libya: 52.3%.
5. How does weather (temperature and precipitation) changes correlate with GDP in Service based economies? • Analyze temperature changes and/or precipitation for countries whose GDP is predominantly service based, e.g., European Union: 70.9%, United States: 80%, United Kingdom: 79.2%, Hong Kong: 92.3%, Panama: 82%, Lebanon: 83%, Macau: 93.7%, Bermuda: 93.8%.

Data Sets to be Used:

RESTful API: http://restcountries.eu/ Countries by GDP Sector Composition: https://en.m.wikipedia.org/wiki/List_of_countries_by_GDP_sector_composition Weather Data: https://climateknowledgeportal.worldbank.org/download-datahttps://www.imf.org/external/datamapper/NGDP_RPCH@WEO/OEMDC/ADVEC/WEOWORLD?year=2020 GDP Data: https://data.worldbank.org/indicator/NY.GDP.MKTP.CD

Rough Breakdown of Tasks:

Each contributor would tackle one of the five questions posed above. Additionally, all contributors will work together on: merging/building the data sets in Jupyter Notebook, setting up functional API’s, Buiding a powerpoint presentation and final report to describe our findings.

GitHub Repository:

https://github.com/SBBoudreau/Project-1 Clone to SSH: git@github.com:SBBoudreau/Project-1.git