Loop within Loop in R-CodePudding

I am trying to figure out how to run two different loops on the same code. I am trying to create a matrix where I am filling a column with the mean of a variable for each year.

Here's the code I am using to do it right now:

matplot2 = as.data.frame(matrix(NA, nrow=16, ncol=4))

matplot2[1,1] = mean(matplot[matplot$Year==2003, 'TotalTime'])
matplot2[2,1] = mean(matplot[matplot$Year==2004, 'TotalTime'])
matplot2[3,1] = mean(matplot[matplot$Year==2005, 'TotalTime'])
matplot2[4,1] = mean(matplot[matplot$Year==2006, 'TotalTime'])
matplot2[5,1] = mean(matplot[matplot$Year==2007, 'TotalTime'])
matplot2[6,1] = mean(matplot[matplot$Year==2008, 'TotalTime'])
matplot2[7,1] = mean(matplot[matplot$Year==2009, 'TotalTime'])
matplot2[8,1] = mean(matplot[matplot$Year==2010, 'TotalTime'])
matplot2[9,1] = mean(matplot[matplot$Year==2011, 'TotalTime'])
matplot2[10,1] = mean(matplot[matplot$Year==2012, 'TotalTime'])
matplot2[11,1] = mean(matplot[matplot$Year==2013, 'TotalTime'])
matplot2[12,1] = mean(matplot[matplot$Year==2014, 'TotalTime'])
matplot2[13,1] = mean(matplot[matplot$Year==2015, 'TotalTime'])
matplot2[14,1] = mean(matplot[matplot$Year==2016, 'TotalTime'])
matplot2[15,1] = mean(matplot[matplot$Year==2017, 'TotalTime'])
matplot2[16,1] = mean(matplot[matplot$Year==2018, 'TotalTime'])

If it were just the year changing, I would write the loop like this:

for(i in 2003:2018) {
     matplot2[1,1] = mean(matplot[matplot$Year==i, 'TotalTime'])
}

But, I need the row number in the matrix I'm printing the results into to change as well. How can I write a loop where I am printing the results of all these means into one column of a matrix?

In other words, I need to be able to have it loop matplot2[j,1] in addition to the matplot$Year==i.

Any suggestions would be greatly appreciated!

CodePudding user response：

Your literal calculations of the mean(TotalTime) can all be reduced to a single command (with no for loop required):

matplot2 <- aggregate(TotalTime ~ Year, data = matplot, FUN = mean)

That should return a two-column frame with the unique values of Year in the first column, and the respective means in the second column.

Demonstrated with data I have:

head(mtcars)
#                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
# Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
# Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
# Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
# Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
# Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
# Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1
res <- aggregate(disp ~ cyl, data = mtcars, FUN = mean)
res
#   cyl     disp
# 1   4 105.1364
# 2   6 183.3143
# 3   8 353.1000

This and more can be seen in summarize by group (of which this question is essentially a dupe, even if you didn't know to ask it that way).

CodePudding user response：

R is a vectorized language so passing a vector of values for the index and year should work.

i<-1:16
matplot2[i,1] = mean(matplot[matplot$Year==(2002   i), 'TotalTime'])