https://github.com/kevinmichaelchen/stat202

What makes some nations wealthy? - Statistics 202
https://github.com/kevinmichaelchen/stat202

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What makes some nations wealthy? - Statistics 202

• Host: GitHub
• URL: https://github.com/kevinmichaelchen/stat202
• Owner: kevinmichaelchen
• Created: 2014-04-07T17:25:01.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2014-05-24T20:45:14.000Z (over 10 years ago)
• Last Synced: 2023-03-03T03:28:17.916Z (almost 2 years ago)
• Language: R
• Homepage:
• Size: 45.1 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
STAT202

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## Downloading the data  

1. Go to the following [link](http://databank.worldbank.org/data/views/variableselection/selectvariables.aspx?source=world-development-indicators).  

2. Go to the *COUNTRY* tab and select all countries.  

3. Go to the *SERIES* tab and select all indicators.  

4. Go to the *TIME* tab and select the desired years.  

5. Press *DOWNLOAD* and go to the *CSV* tab.

7. Under *Modify Orientation*:  

  * Export range: Entire dataset

  * Data format: Table

  * Variable format: Both codes & names

  * NA preference: NA

  * Text field delimiter: none

## Overview  

This repo contains the dataset, R script, and writeups for the 202 final project. We analyze data from **The World Bank** and explore relationships between economic growth and a myriad indicators (with an emphasis on urbanization indicators).  

Running `build.R` will ask the user to choose a file of the original wide-format data (e.g., `originalData.csv`). The script will create a data frame for each year that was downloaded.  

The original data is in *wide* format:  

| Country Name | Country.Code | Indicator.Name | Indicator.Code | X1980..YR1980. | X2008..YR2008. |

| ------------ | ------------ | -------------- | -------------- | -------------- | -------------- |

| Afghanistan  | AFG          | CO2 emissions  | EN.ATM.CO2E.KT | 1.760160e+03   | 3.927357e+03   |

Note: originally the downloaded data only had 2 years: "Y1980" and "Y2008".

`YEARS <- c("Y1980", "Y2008")`.

If this changes, the `YEARS` variable at the top of `build.R` must change accordingly.  

Once `build.R` has executed, there should be CSV files for each year, in the *long* format.  

| Country Name | Country.Code | Indicator.Code | CO2 emissions |

| ------------ | ------------ | -------------- | ------------- |

| Afghanistan  | AFG          | EN.ATM.CO2E.KT | 1.760160e+03  |