Data Wrangling Using Dplyr - r

Question

Using Dplyr, I am trying to find which country has the largest increase in wealth between 2002 and 2006 from the following data.
Country wealth_2002 wealth_2004 wealth_2006
Country_A 1000 1600 2200
Country_B 1200 1300 1800
Country_C 1400 1100 1200
Country_D 1500 1000 1100
Country_E 1100 1800 1900
To get the country's name, I have used
largest_increase <- df %>%
group_by(Country) %>%
filter(max(wealth_2006 - wealth_2002)) %>%
And this gives me
Error in filter_impl(.data, quo) :
Argument 2 filter condition does not evaluate to a logical vector
I would be really grateful if someone can help me what I am doing wrong and how I can fix this. I am very new to R so any help would be appreciated.

Answer 1

Using Base R you can use which.max to index your country column:
# This is my dummy data, you can ignore it
country <- c("Sweden", "Finland")
X1 <- c(1050, 1067)
X2 <- c(1045, 1069)
DF <- data.frame(country, X1, X2)
# Modify this to suit
DF$country[which.max(DF$X2- DF$X1)]
So for yours it would be:
df$Country[which.max(df$wealth_2006 - df$wealth_2002)]

Answer 2

Look at how filter works - you need to provide a logical "test" for each row, if it passes, it will keep the row. Also no real need to group_by country since each country is already its own row. Try something like this, where you calculate and store the wealth change for each country then keep the country/countries which have that max value:
library(dplyr)
df <- read.table(
text = "
Country wealth_2002 wealth_2004 wealth_2006
Country_A 1000 1600 2200
Country_B 1200 1300 1800
Country_C 1400 1100 1200
Country_D 1500 1000 1100
Country_E 1100 1800 1900
", header = TRUE, stringsAsFactors = FALSE
)
df %>%
mutate(wealth_change = wealth_2006 - wealth_2002) %>%
filter(wealth_change == max(wealth_change)) %>%
pull(Country) # gives us the Country column
Output:
[1] "Country_A"

Answer 3

Use dput(data) to help answers.
structure(list(Country = structure(1:5, .Label = c("Country_A",
"Country_B", "Country_C", "Country_D", "Country_E"), class = "factor"),
wealth_2002 = c(1000L, 1200L, 1400L, 1500L, 1100L), wealth_2004 = c(1600L,
1300L, 1100L, 1000L, 1800L), wealth_2006 = c(2200L, 1800L,
1200L, 1100L, 1900L)), .Names = c("Country", "wealth_2002",
"wealth_2004", "wealth_2006"), class = "data.frame", row.names = c(NA,
-5L))
library(dplyr)
data %>%
mutate(delta = wealth_2006 - wealth_2004) %>% #Create a new variable called delta with mutate
arrange(desc(delta)) %>% #sort descending by 'delta'
head(1) #return the top line.. pull out the specific value if needed
This will return the top row... of the greatest change.
Country A has a change of 600

Answer 4

You can also use top_n :
library(dplyr)
df %>% top_n(1,wealth_2006 - wealth_2002)
# Country wealth_2002 wealth_2004 wealth_2006
# 1 Country_A 1000 1600 2200