I need to do a term paper with R (never did it before) and I have the following problem that I cannot solve.
I have a dataset with all countries of all years since 1950 (so one row (observation) is one country in one year, the next row is the same country one year later and so on). Now I need to construct a new variable, which is filled with the average value of the previous three years of a given variable.
Specifically it is about the democracy level of a country. So I have the variable of the democracy level of a country for a year T, and I need a new variable, which indicates the "democracy growth" of the previous three years T(-3,0).
How can I construct this new variable?
As I said I never used R before, but I need to use mutate() and then I need to address year-3, year-2, year-1 and divide it by 3. But how to I address the previous three years? Case_when or something?
I'm trying to replace the missing values in R with the value that follows, I have annual data for income by country, and for the missing income value for 2001 for country A I want it to pull the next value (this is for time series analysis with multiple different countries and different columns for different variables - income is just one of them)
I wrote this code for replacing the missing values with the mean, but statistically I think it makes more sense to replace the missing values with the value right below it (that comes next, the next year) since the numbers will be very different depending on the country so if I take an average it'll be of all years for all countries).
Social_data_R<-within(Social_data_R,incomeNAavg[is.na(income)]<-mean(income,na.rm=TRUE))
I tried replacing the mean part of the code above with income[i+1] but it didn't recognize 'i' (I uploaded the data from excel, so didn't create the dataframe manually)
I'm trying to add a new column to my data table that contains the average of some of the following rows. How many rows to be selected for the average however depends on the time stamp of the rows.
Here is some test data:
DT<-data.table(Weekstart=c(1,2,2,3,3,4,5,5,6,6,7,7,8,8,9,9),Art=c("a","b","a","b","a","a","a","b","b","a","b","a","b","a","b","a"),Demand=c(1:16))
I want to add a column with the mean of all demands, which occured in the weeks ("Weekstart") up to three weeks before the respective week (grouped by Art, excluding the actual week).
With rollapply from zoo-library, it works like this:
setorder(DT,-Weekstart)
DT[,RollMean:=rollapply(Demand,width=list(1:3),partial=TRUE,FUN=mean,align="left",fill=NA),.(Art)]
The problem however is, some data is missing. In the example, the data for the Art b lack the week no 4, there is no Demand in week 4. As I want the average of the three prior weeks, not the three prior rows, the average is wrong. Instead, the result for Art b for week 6 should look like this:
DT[Art=="b"&Weekstart==6,RollMean:=6]
(6 instead of 14/3, because only Week 5 and Week 3 count: (8+4)/2)
Here is what I tired so far:
It would be possible to loop through the minima of the week of the following rows in order to create a vector that defines for each row, how wide the 'width' should be (the new column 'rollwidth'):
i<-3
DT[,rollwidth:=Weekstart-rollapply(Weekstart,width=list(1:3),partial=TRUE,FUN=min,align="left",fill=1),.(Art)]
while (max(DT[,Weekstart-rollapply(Weekstart,width=list(1:i),partial=TRUE,FUN=min,align="left",fill=NA),.(Art)][,V1],na.rm=TRUE)>3) {
i<-i-1
DT[rollwidth>3,rollwidth:=i]
}
But that seems very unprofessional (excuse my poor skills). And, unfortunately, the rollapply with width and rollwidth doesnt work as intended (produces warnings as 'rollwidth' is considered as all the rollwidths in the table):
DT[,RollMean2:=rollapply(Demand,width=list(1:rollwidth),partial=TRUE,FUN=mean,align="left",fill=NA),.(Art)]
What does work is
DT[,RollMean3:=rollapply(Demand,width=rollwidth,partial=TRUE,FUN=mean,align="left",fill=NA),.(Art)]
but then again, the average includes the actual week (not what I want).
Does anybody know how to apply a criterion (i.e. the difference in the weeks shall be <= 3) instead of a number of rows to the argument width?
Any suggestions are appreciated!
I have a column with a few dozen grades that have been assigned values Good, Average or Poor. I have a different column with employment rates. I want the maximum employment rate associated with Good, Average and Poor. I can get it to pull the value for each one in three different commands using the code below, but I need it written as a single command similar to this:
max(unHomework$Employment.Rate[unHomework$Job.Satisfaction.Category == 'Poor'])
We can use data.table
library(data.table)
setDT(unHomework)[, .(MaxER =max(Employment.Rate)), by = Job.Satisfaction.Category]
I'll describe my data:
First column are corine_values, going from 1 to 50.
Second column are bird_names, there are 70 different bird_names, each corine_value has several bird_names.
Third column contains the sex of the bird_name.
Fourth column contains a V1-value (measurement) that belongs to the category described by the first three columns.
I want to create a table where the the row names are the bird_names. First all the females in alphabetical order, followed by the males in alphabetical order. The column names should be the corine_values, from small to big. The data in the table should be the corresponding V1-values.
I've been trying some things, but to be honest I'm just starting with R and I don't really have a clue how to do it. I can sort the data, but not on multiple levels (like alphabetical and sex combined). I'm exporting everything to Excel now and doing it manually, which is very time-consuming.