library(tidyverse)

ss06hidData <- read_csv("./data/ss06hid.csv")
sso6hidData_part <- ss06hidData[, c("ACR", "AGS")]
sso6hidData_part <- sso6hidData_part %>% 
    mutate(agricultureLogical = ifelse(ACR == 3 & AGS == 6, TRUE, FALSE))
head(which(sso6hidData_part$agricultureLogical), 3)

## [1] 125 238 262

library(jpeg)
img <- readJPEG("./img/jeff.jpg", native = TRUE)
quantile(img, probs = c(0.3, 0.8))

##       30%       80% 
## -15259150 -10575416

GDPdata <- read_csv("./data/GDP.csv", skip = 4)
GDPdata <- na.omit(GDPdata[, 1:2])
names(GDPdata) <- c("CountryCode","GDPrank")

EDSTATS_Country_data <- read_csv("./data/EDSTATS_Country.csv")
innerJoinData <- inner_join(EDSTATS_Country_data, GDPdata, by ="CountryCode")
innerJoinData %>% 
    arrange(desc(GDPrank)) %>% 
    summarise(matches = n(), 
              the_13rd_country = .$`Long Name`[which(GDPrank == 13)]
    )

## # A tibble: 1 x 2
##   matches the_13rd_country
##     <int> <chr>           
## 1     189 Kingdom of Spain

Data <- innerJoinData %>% 
    group_by(`Income Group`) %>% 
    mutate(GDPrank = as.numeric(GDPrank)) %>% 
    summarise(meanValue = mean(GDPrank)) 
Data[which(Data$`Income Group` %in% c( "High income: OECD", "High income: nonOECD")), "meanValue"]

## # A tibble: 2 x 1
##   meanValue
##       <dbl>
## 1      91.9
## 2      33.0

library(Hmisc)
innerJoinData <- transform(innerJoinData, GDPrank = as.numeric(GDPrank))
innerJoinData <- innerJoinData %>%
    mutate(five_cut_groups = cut2(GDPrank,  g = 5))

with(innerJoinData, {table(Income.Group, five_cut_groups)})

##                       five_cut_groups
## Income.Group           [  1, 39) [ 39, 77) [ 77,115) [115,154) [154,190]
##   High income: nonOECD         4         5         8         5         1
##   High income: OECD           18        10         1         1         0
##   Low income                   0         1         9        16        11
##   Lower middle income          5        13        12         8        16
##   Upper middle income         11         9         8         8         9