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# 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 |
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extract_key_from_url("https://docs.google.com/spreadsheets/d/1IbDM8z5XicMIXgr93FPwjgwoTTKMuyLfzU6cQrGZzH8/pub?gid=0") | |
## [1] "1IbDM8z5XicMIXgr93FPwjgwoTTKMuyLfzU6cQrGZzH8" |
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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 | |
## |
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gdp_per_capita <- gs_key("phAwcNAVuyj1jiMAkmq1iMg",lookup = FALSE, verbose=FALSE) %>% gs_read(ws = "Data", check.names=FALSE) | |
## Accessing worksheet titled "Data" |
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df2 <- gs_key("phAwcNAVuyj1jiMAkmq1iMg",lookup = FALSE, verbose=FALSE) %>% gs_read(ws = "Data", range = "A1:D8") | |
## Accessing worksheet titled "Data" |
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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 |
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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 |
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colnames(gdp_per_capita)[1] | |
## [1] "GDP per capita" | |
colnames(gdp_per_capita)[1] <- c("Country") |
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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) |
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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] |
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