Transposing data frames

问题:

Happy Weekends.

I've been trying to replicate the results from this blog post in R. I am looking for a method of transposing the data without using t, preferably using tidyr or reshape. In example below, metadata is obtained by transposing data.

metadata <- data.frame(colnames(data), t(data[1:4, ]) )
colnames(metadata) <- t(metadata[1,])
metadata <- metadata[-1,]
metadata$Multiplier <- as.numeric(metadata$Multiplier)

Though it achieves what I want, I find it little unskillful. Is there any efficient workflow to transpose the data frame?

dput of data

data <- structure(list(Series.Description = c("Unit:", "Multiplier:", 
"Currency:", "Unique Identifier: "), Nominal.Broad.Dollar.Index. = c("Index:_1997_Jan_100", 
"1", NA, "H10/H10/JRXWTFB_N.M"), Nominal.Major.Currencies.Dollar.Index. = c("Index:_1973_Mar_100", 
"1", NA, "H10/H10/JRXWTFN_N.M"), Nominal.Other.Important.Trading.Partners.Dollar.Index. = c("Index:_1997_Jan_100", 
"1", NA, "H10/H10/JRXWTFO_N.M"), AUSTRALIA....SPOT.EXCHANGE.RATE..US..AUSTRALIAN...RECIPROCAL.OF.RXI_N.M.AL. = c("Currency:_Per_AUD", 
"1", "USD", "H10/H10/RXI$US_N.M.AL"), SPOT.EXCHANGE.RATE...EURO.AREA. = c("Currency:_Per_EUR", 
"1", "USD", "H10/H10/RXI$US_N.M.EU"), NEW.ZEALAND....SPOT.EXCHANGE.RATE..US..NZ...RECIPROCAL.OF.RXI_N.M.NZ.. = c("Currency:_Per_NZD", 
"1", "USD", "H10/H10/RXI$US_N.M.NZ"), United.Kingdom....Spot.Exchange.Rate..US..Pound.Sterling.Reciprocal.of.rxi_n.m.uk = c("Currency:_Per_GBP", 
"0.01", "USD", "H10/H10/RXI$US_N.M.UK"), BRAZIL....SPOT.EXCHANGE.RATE..REAIS.US.. = c("Currency:_Per_USD", 
"1", "BRL", "H10/H10/RXI_N.M.BZ"), CANADA....SPOT.EXCHANGE.RATE..CANADIAN...US.. = c("Currency:_Per_USD", 
"1", "CAD", "H10/H10/RXI_N.M.CA"), CHINA....SPOT.EXCHANGE.RATE..YUAN.US.. = c("Currency:_Per_USD", 
"1", "CNY", "H10/H10/RXI_N.M.CH"), DENMARK....SPOT.EXCHANGE.RATE..KRONER.US.. = c("Currency:_Per_USD", 
"1", "DKK", "H10/H10/RXI_N.M.DN"), HONG.KONG....SPOT.EXCHANGE.RATE..HK..US.. = c("Currency:_Per_USD", 
"1", "HKD", "H10/H10/RXI_N.M.HK"), INDIA....SPOT.EXCHANGE.RATE..RUPEES.US. = c("Currency:_Per_USD", 
"1", "INR", "H10/H10/RXI_N.M.IN"), JAPAN....SPOT.EXCHANGE.RATE..YEA.US.. = c("Currency:_Per_USD", 
"1", "JPY", "H10/H10/RXI_N.M.JA"), KOREA....SPOT.EXCHANGE.RATE..WON.US.. = c("Currency:_Per_USD", 
"1", "KRW", "H10/H10/RXI_N.M.KO"), Malaysia...Spot.Exchange.Rate..Ringgit.US.. = c("Currency:_Per_USD", 
"1", "MYR", "H10/H10/RXI_N.M.MA"), MEXICO....SPOT.EXCHANGE.RATE..PESOS.US.. = c("Currency:_Per_USD", 
"1", "MXN", "H10/H10/RXI_N.M.MX"), NORWAY....SPOT.EXCHANGE.RATE..KRONER.US.. = c("Currency:_Per_USD", 
"1", "NOK", "H10/H10/RXI_N.M.NO"), SWEDEN....SPOT.EXCHANGE.RATE..KRONOR.US.. = c("Currency:_Per_USD", 
"1", "SEK", "H10/H10/RXI_N.M.SD"), SOUTH.AFRICA....SPOT.EXCHANGE.RATE..RAND.US.. = c("Currency:_Per_USD", 
"1", "ZAR", "H10/H10/RXI_N.M.SF"), Singapore...SPOT.EXCHANGE.RATE..SINGAPORE...US.. = c("Currency:_Per_USD", 
"1", "SGD", "H10/H10/RXI_N.M.SI"), SRI.LANKA....SPOT.EXCHANGE.RATE..RUPEES.US.. = c("Currency:_Per_USD", 
"1", "LKR", "H10/H10/RXI_N.M.SL"), SWITZERLAND....SPOT.EXCHANGE.RATE..FRANCS.US.. = c("Currency:_Per_USD", 
"1", "CHF", "H10/H10/RXI_N.M.SZ"), TAIWAN....SPOT.EXCHANGE.RATE..NT..US.. = c("Currency:_Per_USD", 
"1", "TWD", "H10/H10/RXI_N.M.TA"), THAILAND....SPOT.EXCHANGE.RATE....THAILAND. = c("Currency:_Per_USD", 
"1", "THB", "H10/H10/RXI_N.M.TH"), VENEZUELA....SPOT.EXCHANGE.RATE..BOLIVARES.US.. = c("Currency:_Per_USD", 
"1", "VEB", "H10/H10/RXI_N.M.VE")), .Names = c("Series.Description", 
"Nominal.Broad.Dollar.Index.", "Nominal.Major.Currencies.Dollar.Index.", 
"Nominal.Other.Important.Trading.Partners.Dollar.Index.", "AUSTRALIA....SPOT.EXCHANGE.RATE..US..AUSTRALIAN...RECIPROCAL.OF.RXI_N.M.AL.", 
"SPOT.EXCHANGE.RATE...EURO.AREA.", "NEW.ZEALAND....SPOT.EXCHANGE.RATE..US..NZ...RECIPROCAL.OF.RXI_N.M.NZ..", 
"United.Kingdom....Spot.Exchange.Rate..US..Pound.Sterling.Reciprocal.of.rxi_n.m.uk", 
"BRAZIL....SPOT.EXCHANGE.RATE..REAIS.US..", "CANADA....SPOT.EXCHANGE.RATE..CANADIAN...US..", 
"CHINA....SPOT.EXCHANGE.RATE..YUAN.US..", "DENMARK....SPOT.EXCHANGE.RATE..KRONER.US..", 
"HONG.KONG....SPOT.EXCHANGE.RATE..HK..US..", "INDIA....SPOT.EXCHANGE.RATE..RUPEES.US.", 
"JAPAN....SPOT.EXCHANGE.RATE..YEA.US..", "KOREA....SPOT.EXCHANGE.RATE..WON.US..", 
"Malaysia...Spot.Exchange.Rate..Ringgit.US..", "MEXICO....SPOT.EXCHANGE.RATE..PESOS.US..", 
"NORWAY....SPOT.EXCHANGE.RATE..KRONER.US..", "SWEDEN....SPOT.EXCHANGE.RATE..KRONOR.US..", 
"SOUTH.AFRICA....SPOT.EXCHANGE.RATE..RAND.US..", "Singapore...SPOT.EXCHANGE.RATE..SINGAPORE...US..", 
"SRI.LANKA....SPOT.EXCHANGE.RATE..RUPEES.US..", "SWITZERLAND....SPOT.EXCHANGE.RATE..FRANCS.US..", 
"TAIWAN....SPOT.EXCHANGE.RATE..NT..US..", "THAILAND....SPOT.EXCHANGE.RATE....THAILAND.", 
"VENEZUELA....SPOT.EXCHANGE.RATE..BOLIVARES.US.."), row.names = c(NA, 
4L), class = "data.frame")

回答1:

Using tidyr, you gather all the columns except the first, and then you spread the gathered columns.

Try:

library(dplyr)
library(tidyr)
data %>%
  gather(var, val, 2:ncol(data)) %>%
  spread(Series.Description, val)