I'm an absolute R beginner here working on a Master's project.
I have a data.frame that contains information on trotting horses (their wins, earnings, time records and such). The data is organised in a way that every row contains information for a specific year the horse competed and including a first row for each horse of "Total", so there's a summary for every variable for it's total competing life. It looks like this:
I created a new variable with their age using the age_calc function in the eeptools package:
travdata$Age<-age_calc(as.Date(travdata$Birth.date), enddate=as.Date("2016-12-31"),
units="years")
With no problems. What I'm trying to figure out is if there is any way I can calculate the age of the horses for each specific year I have info on them-that is, the "Total" row would have their age up until 2016-12-31, for the year 2015 it would have their age at that time and so on. I've been trying to include if statements in age_calc but it won't work and I'm really at a loss on how best to do this.
Any literature or help you could point me to would be much, much appreciated.
MWE
travdata <- data.frame(
"Id.Number"=c(rep("1938-98",3),rep("1803-97",7),rep("1221-03",4)),
"Name"=c(rep("Muuttuva",3),rep("Pelson Poika",7),rep("Muusan Muisto",4)),
"Sex"=c(rep("Mare",3),rep("Gelding",7),rep("Gelding",4)),
"Birth.year"=c(rep(1998,3),rep(1997,7),rep(2003,4)),
"Birth.date"=c(rep("1998-07-01",3),rep("1997-07-14",7),rep("2003-05-07",4)),
"Competition.year" = c("Total",2005,2004,"Total",2003,2004,2006,2005,2002,2001,2008,2010,"Total",2009),
"starts"=c(20,11,9,44,21,6,7,5,3,2,1,1,4,2),
"X1st.placements"=c(0,0,0,3,3,0,0,0,0,0,0,0,0,0),
"X2nd.placements"=c(2,2,0,1,0,1,0,0,0,0,0,0,0,0),
"X3rd.placements"=c(2,2,0,1,1,0,0,0,0,0,0,0,0,0),
"Earnings.euro"=c(1525,1425,100,2078,1498,580,0,0,0,0,0,0,10,10)
)
The trick is to filter out the "Total" rows and specify a format for the as.Date() function
library(eeptools)
travdata <- data.frame(
"Id.Number"=c(rep("1938-98",3),rep("1803-97",7),rep("1221-03",4)),
"Name"=c(rep("Muuttuva",3),rep("Pelson Poika",7),rep("Muusan Muisto",4)),
"Sex"=c(rep("Mare",3),rep("Gelding",7),rep("Gelding",4)),
"Birth.year"=c(rep(1998,3),rep(1997,7),rep(2003,4)),
"Birth.date"=c(rep("1998-07-01",3),rep("1997-07-14",7),rep("2003-05-07",4)),
"Competition.year" = c("Total",2005,2004,"Total",2003,2004,2006,2005,2002,2001,2008,2010,"Total",2009),
"starts"=c(20,11,9,44,21,6,7,5,3,2,1,1,4,2),
"X1st.placements"=c(0,0,0,3,3,0,0,0,0,0,0,0,0,0),
"X2nd.placements"=c(2,2,0,1,0,1,0,0,0,0,0,0,0,0),
"X3rd.placements"=c(2,2,0,1,1,0,0,0,0,0,0,0,0,0),
"Earnings.euro"=c(1525,1425,100,2078,1498,580,0,0,0,0,0,0,10,10)
)
travdata$Age<-age_calc(as.Date(travdata$Birth.date),
enddate=as.Date("2016-12-31"), units="years")
competitions <- travdata[travdata$Competition.year!="Total",]
competitions$Competition.age<-age_calc(
as.Date(competitions$Birth.date),
enddate=as.Date(competitions$Competition.year, format="%Y"),
units="years",F)
I have two data frames: rainfall data collected daily and nitrate concentrations of water samples collected irregularly, approximately once a month. I would like to create a vector of values for each nitrate concentration that is the sum of the previous 5 days' rainfall. Basically, I need to match the nitrate date with the rain date, sum the previous 5 days' rainfall, then print the sum with the nitrate data.
I think I need to either make a function, a for loop, or use tapply to do this, but I don't know how. I'm not an expert at any of those, though I've used them in simple cases. I've searched for similar posts, but none get at this exactly. This one deals with summing by factor groups. This one deals with summing each possible pair of rows. This one deals with summing by aggregate.
Here are 2 example data frames:
# rainfall df
mm<- c(0,0,0,0,5, 0,0,2,0,0, 10,0,0,0,0)
date<- c(1:15)
rain <- data.frame(cbind(mm, date))
# b/c sums of rainfall depend on correct chronological order, make sure the data are in order by date.
rain[ do.call(order, list(rain$date)),]
# nitrate df
nconc <- c(15, 12, 14, 20, 8.5) # nitrate concentration
ndate<- c(6,8,11,13,14)
nitrate <- data.frame(cbind(nconc, ndate))
I would like to have a way of finding the matching rainfall date for each nitrate measurement, such as:
match(nitrate$date[i] %in% rain$date)
(Note: Will match work with as.Date dates?) And then sum the preceding 5 days' rainfall (not including the measurement date), such as:
sum(rain$mm[j-6:j-1]
And prints the sum in a new column in nitrate
print(nitrate$mm_sum[i])
To make sure it's clear what result I'm looking for, here's how to do the calculation 'by hand'. The first nitrate concentration was collected on day 6, so the sum of rainfall on days 1-5 is 5mm.
Many thanks in advance.
You were more or less there!
nitrate$prev_five_rainfall = NA
for (i in 1:length(nitrate$ndate)) {
day = nitrate$ndate[i]
nitrate$prev_five_rainfall[i] = sum(rain$mm[(day-6):(day-1)])
}
Step by step explanation:
Initialize empty result column:
nitrate$prev_five_rainfall = NA
For each line in the nitrate df: (i = 1,2,3,4,5)
for (i in 1:length(nitrate$ndate)) {
Grab the day we want final result for:
day = nitrate$ndate[i]
Take the rainfull sum and it put in in the results column
nitrate$prev_five_rainfall[i] = sum(rain$mm[(day-6):(day-1)])
Close the for loop :)
}
Disclaimer: This answer is basic in that:
It will break if nitrate's ndate < 6
It will be incorrect if some dates are missing in the rain dataframe
It will be slow on larger data
As you get more experience with R, you might use data manipulation packages like dplyr or data.table for these types of manipulations.
#nelsonauner's answer does all the heavy lifting. But one thing to note, in my actual data my dates are not numerical like they are in the example above, they are dates listed as MM/DD/YYYY with the appropriate as.Date(nitrate$date, "%m/%d/%Y").
I found that the for loop above gave me all zeros for nitrate$prev_five_rainfall and I suspected it was a problem with the dates.
So I changed my dates in both data sets to numerical using the difference in number of days between a common start date and the recorded date, so that the for loop would look for a matching number of days in each data frame rather than a date. First, make a column of the start date using rep_len() and format it:
nitrate$startdate <- rep_len("01/01/1980", nrow(nitrate))
nitrate$startdate <- as.Date(all$startdate, "%m/%d/%Y")
Then, calculate the difference using difftime():
nitrate$diffdays <- as.numeric(difftime(nitrate$date, nitrate$startdate, units="days"))
Do the same for the rain data frame. Finally, the for loop looks like this:
nitrate$prev_five_rainfall = NA
for (i in 1:length(nitrate$diffdays)) {
day = nitrate$diffdays[i]
nitrate$prev_five_rainfall[i] = sum(rain$mm[(day-5):(day-1)]) # 5 days
}