for loop: not equally-sized data frames in R - r

Question

I'm working on a data frame which looks like this
Here's how it looks like:
shape id day hour week id footfall category area name
22496 22/3/14 3 12 634 Work cluster CBD area 1
22670 22/3/14 3 12 220 Shopping cluster Orchard Road 1
23287 22/3/14 3 12 723 Airport Changi Airport 2
16430 22/3/14 4 12 947 Work cluster CBD area 2
4697 22/3/14 3 12 220 Residential area Ang Mo Kio 2
4911 22/3/14 3 12 1001 Shopping cluster Orchard Rd 3
11126 22/3/14 3 12 220 Residential area Ang Mo Kio 2
and so on... until 635 rows return.
with the other dataset that I want to compare with can be found here
Here's how it looks like:
category Foreigners Locals
Work cluster 1600000 3623900
Shopping cluster 1800000 3646666.667
Airport 15095152 8902705
Residential area 527700 280000
and also this last dataset that i want to compare with their previousHour
The first and second share the same attribute, i.e. category & first and third dataset share the same attribute hour.
As for previousHour based on category. Eg, for workcluster here
The previousHour should look like this:
hour
0
3
4
4
4
5
until 144 rows return... for each category.
Click here for shopping category
previousHour eg. for shopping should look like this:
hour
0
3
3
4
4
5
until 144 rows return...
Click here for airport category
Click here for residential category
all 144 rows return...
SumHour dataset:
category sumHour
1 Airport 2208
2 Residential area 1656
3 Shopping cluster 1656
4 Work cluster 1656
Here's, what I ideally want to find in R:
#for n in 1: number of rows{
# calculate sumHours(in SumHours dataset) - previousHour = newHourSum and store it as newHourSum
# calculate hour/(newHourSum-previousHour) * Foreigners and store it as footfallHour
# add to the empty dataframe }
I'm not sure how to do that and here's what i tried:
mergetbl <- function(tbl1, tbl2)
{
newtbl = data.frame(hour=numeric(),forgHour=numeric())
ntbl1rows<-nrow(tbl1) # get the number of rows
for(n in 1:ntbl1rows)
{
#for n in 1: number of rows{
# check the previous hour from IDA dataset !!!!
# calculate sumDate - previousHour = newHourSum and store it as newHourSum
# calculate hour/(newHourSum-previousHour) * Foreigners and store it as footfallHour
# add to the empty dataframe }
newHourSum <- 3588 - tbl1
footfallHour <- (tbl1$hour/(newHourSum-previousHour)) * tbl2$Foreigners
newtbl <- rbind(newtbl, footfallHour)
}
}
But nothing happened to newtbl...
Here's what ideally looks like for newtbl:
hour forgHour
0 1337.79 (the function should calculate this)
3 ...
3 ...
3 ...
4 ...
3 ...
and so on...

Answer 1

Thinking in terms of vectors gives this :
Try this:
### this is to get your Foreigners/Locals to be at the same size as tbl1
Foreigners=ifelse(tbl1$category=="Work cluster",tbl2$Foreigners[1], ifelse (tbl1$category=="Shopping cluster", tbl2$Foreigners[2], ifelse(tbl1$category=="Airport", tbl2$Foreigners[3], tbl2$Foreigners[4])))
Locals=ifelse(tbl1$category=="Work cluster",tbl2$Locals[1], ifelse (tbl1$category=="Shopping cluster", tbl2$Locals[2], ifelse(tbl1$category=="Airport", tbl2$Locals[3], tbl2$Locals[4])))
And now, the function
resultHour = function(tbl1, tbl2, ForeOrLoca)
{
previousHour = rep (0, nrow(tbl1))
for (i in 2:nrow(tbl1))
{
previousHour[i] = tbl1$hour[i-1]
}
### The conditional sum matching the category from tbl1
NewHourSum = ifelse(tbl1$category=="Work cluster",sum(with(tbl1, hour*I(category == "Work cluster"))), ifelse (tbl1$category=="Shopping cluster", sum(with(tbl1, hour*I(category == "Shopping cluster"))), ifelse(tbl1$category=="Airport", sum(with(tbl1, hour*I(category == "Airport"))), sum(with(tbl1, hour*I(category == "Residential area"))))))
##and finally, this
hour = as.vector(tbl1$hour)
footfallHour <- (hour/(newHourSum - previousHour)) * ForeOrLoca
newtbl <- cbind(hour, footfallHour)
return (newtbl)
}
this is the output I get :
> head(newtbl)
hour footfallHour
[1,] 3 1337.7926
[2,] 3 1506.2762
[3,] 3 12631.9264
[4,] 4 1785.2162
[5,] 3 441.7132
[6,] 3 1506.2762
Using the function:
TheResultIWant = resultHour (tbl1,tbl2)

Answer 2

For your new question.
Provided you cut your data frame into several containing only one category, you can use this function:
new_function_hour_result = function (tbl1_categ, vec_categ, prevHour_Categ, sumHour_Categ)
hour = as.vector(tbl1_categ$hour)
footfallHour <- (hour/(sumHour_Categ- previousHour)) * vec_categ
newtbl <- cbind(hour, footfallHour)
return (newtbl)
}
With tbl1_categ your data frame for a given category, vec_categ your foreigner or local data for a given category, prevHour_Categ the previousHour for a given category, and finally sumHour_Categ the sumHour for a given category.
To get your vectors to be the same size as the df they will be compared to :
for instance, for the vec_categ in the case locals/airport category:
locals_airport = rep(category[3,3], nrow = nrow(tbl1_airport))
for foreigners and airport category: foreig_airport = rep(category[3,2], nrow = nrow(tbl1_airport))
this will repeat the value contained in category[3,2], nrow(tbl1_airport) times.
for locals and workcluster: locals_workcluster = rep(category[1,3], nrow = nrow(tbl1_workcluster))
and so on for each vector (ie prevHour_Categ, sumHour_Categ, vec_categ) for each category!!