davidcomfort

# install.packages("googlesheets")
suppressMessages(library(dplyr))
library(googlesheets)
library(dplyr)

gs_url("https://docs.google.com/spreadsheets/d/1IbDM8z5XicMIXgr93FPwjgwoTTKMuyLfzU6cQrGZzH8/pub?gid=0",lookup = FALSE)

## Sheet-identifying info appears to be a browser URL.
## googlesheets will attempt to extract sheet key from the URL.
## Putative key: 1IbDM8z5XicMIXgr93FPwjgwoTTKMuyLfzU6cQrGZzH8

davidcomfort

extract_key_from_url("https://docs.google.com/spreadsheets/d/1IbDM8z5XicMIXgr93FPwjgwoTTKMuyLfzU6cQrGZzH8/pub?gid=0")

## [1] "1IbDM8z5XicMIXgr93FPwjgwoTTKMuyLfzU6cQrGZzH8"

davidcomfort

gs_key("1IbDM8z5XicMIXgr93FPwjgwoTTKMuyLfzU6cQrGZzH8", verbose=FALSE, lookup = FALSE)

##                   Spreadsheet title: indicator gapminder population
##                  Spreadsheet author: gapdata
##   Date of googlesheets registration: 2015-10-05 16:54:10 GMT
##     Date of last spreadsheet update: 2012-09-07 13:50:39 GMT
##                          visibility: public
##                         permissions: rw
##                             version: new
## 

davidcomfort

gdp_per_capita <- gs_key("phAwcNAVuyj1jiMAkmq1iMg",lookup = FALSE,  verbose=FALSE) %>% gs_read(ws = "Data", check.names=FALSE)
## Accessing worksheet titled "Data"

davidcomfort

df2 <- gs_key("phAwcNAVuyj1jiMAkmq1iMg",lookup = FALSE, verbose=FALSE) %>% gs_read(ws = "Data", range = "A1:D8")
## Accessing worksheet titled "Data"

davidcomfort

df2 %>% rename_(.dots=setNames(names(.), (gsub("X", "", names(.)))))

## Source: local data frame [7 x 4]
## 
##          GDP.per.capita        1800        1801        1802
##                   (chr)       (chr)       (chr)       (chr)
## 1              Abkhazia          NA          NA          NA
## 2           Afghanistan 634.4000136 634.4000136 634.4000136
## 3 Akrotiri and Dhekelia          NA          NA          NA
## 4               Albania 860.5879664 861.4817538 862.3764694

davidcomfort

head(gdp_per_capita)[1:5]

## Source: local data frame [6 x 5]
## 
##          GDP per capita     1800      1801      1802      1803
##                   (chr)    (dbl)     (dbl)     (dbl)     (dbl)
## 1              Abkhazia       NA        NA        NA        NA
## 2           Afghanistan  634.400  634.4000  634.4000  634.4000
## 3 Akrotiri and Dhekelia       NA        NA        NA        NA
## 4               Albania  860.588  861.4818  862.3765  863.2721

davidcomfort

colnames(gdp_per_capita)[1]

## [1] "GDP per capita"

colnames(gdp_per_capita)[1] <- c("Country")

davidcomfort

child_mortality <- gs_key("0ArfEDsV3bBwCcGhBd2NOQVZ1eWowNVpSNjl1c3lRSWc",lookup = FALSE,  verbose=FALSE) %>% gs_read(ws = "Data", check.names=FALSE)
## Accessing worksheet titled "Data"

democracy_score <- gs_key("0ArfEDsV3bBwCdGQ2YlhDSWVIdXdpMmhLY2ZZRHdNNnc",lookup = FALSE,  verbose=FALSE) %>% gs_read(ws = "Data", check.names=FALSE)
## Accessing worksheet titled "Data"

life_expectancy  <- gs_key("tiAiXcrneZrUnnJ9dBU-PAw",lookup = FALSE,  verbose=FALSE) %>% gs_read(ws = "Data", check.names=FALSE)
## Accessing worksheet titled "Data"

population <- gs_key("phAwcNAVuyj0XOoBL_n5tAQ",lookup = FALSE,  verbose=FALSE) %>% gs_read(ws = "Data", check.names=FALSE)

davidcomfort

library(RCurl)
## Loading required package: bitops

countries <- getURL("https://raw.githubusercontent.com/lukes/ISO-3166-Countries-with-Regional-Codes/master/all/all.csv")
countries <- read.csv(text=countries, header = TRUE, stringsAsFactors=FALSE)
countries <- read.csv("data/countries.csv",  
                      header = TRUE, 
                      stringsAsFactors= FALSE, check.names=FALSE)
countries <- tbl_df(countries)
str(countries)[1:5]