This question already has answers here:
Nested ifelse statement
(10 answers)
Closed 5 years ago.
Write a function called dayplan(temperature,work). The Function should at first check if it is dealing with realistic values. Thereby temperature∈[-20,40] and work∈{´Yes´, ´No´}. For realistic values the function should give out these values:
When temperature>=20 and job==´Yes´, then "Eat ice cream"
When temperature>=20 and job==´No´, then "Sea"
When temperature >20 and job ==´Yes´, then "Shopping"
When temperature<20 and job==´No´, then "Bed"
The outline of the function can look something like this:
dayplan <- function(temperature, work){
if(...){
if(...){
print("Eat ice cream.")
} else if(...) {
...
...
}
} else {
print("Inputs not feasible.")
}
}
Fill in the gaps using the conditions for each activity.
Related
Suppose we have given dataframe in R. By 0--7, it means it is taking integer values from 0-7 i.e. 0,1,2,3,4,5,6,7.
I am interested in making a function such that
If a[1,1]>alpha, it goes and checks its children i.e. 0--7 consists of a[1,2] and a[2,2].
So,
{a[2,1]>alpha
{a[4,1]>alpha
{a[5,1]>alpha
ps=list.append(0)
else ps=list.append(1)
}}}
Here, alpha is a a threshold. The ps is appended from values of 0 to 15 based on this criteria.
My code is
{for (i in 1:2)
{ if (a[j,i]>alpha)
{if (i%%2==1}
{j=j*2
if (a[j,i]>alpha
###here i want to go recursively i think and where and how should i add append values to the list
if a[j,i+1]>alpha}
if{i%%2==0}
{}
}}
I am stuck and confused at the same time. Any help or advices would be greatly appreciated.
Thanks
Just to give some background first:
I currently have 2 data frames (giraffe, leaf) and both of them share the column 'key', where the elements in the leaf data frame are a subset of giraffe. What I needed to do is compare the two data frames and when there are matching elements in both data frames in the 'key' column, the string 'leaf' will be input into another column (project) in the giraffe data frame inside the same row as the matching 'key' element. I've taken the following approach however it seems I have made a small error somewhere and after searching online, I still don't know what it is:
Truth_vector <- is.element((giraffe[,1]),(leaf[,1])) #returns a vector with 3000 elements, most are FALSE except for where the element inside 'key' is present in both data frames
i=1
for (i in 1:length(giraffe[,1])) {
if Truth_vector[i] == TRUE {
giraffe[i,5] <- 'leaf'
}
i = i+1
}
Error: unexpected '}' in "}"
Edit:
I tried implementing the solution as a function however nothing ends up happening, no error messages get returned either. What I've done is:
Project_assign <- function(prjct) {
Truth_vector <- is.element((giraffe[,1]),(prjct[,1]))
giraffe[which(Truth_vector),5] <- 'prjct'
}
Project_assign(leaf)
Edit: This was because everything was getting assigned in the function sub environment, not the global environment. Using assign('giraffe',giraffe,envir=.GlobalEnv) solves this however you should try and avoid the assign function and Instead I used a for loop going over a list of all the dataframes
You have a couple issues. First, the if criteria needs to be in parentheses, and secondly you don't need to increment i yourself. This should suffice:
for (i in 1:length(giraffe[,1])) {
if (Truth_vector[i] == TRUE) {
giraffe[i,5] <- 'leaf'
}
}
Of course, this would do it too:
giraffe[which(Truth_vector),5] <- 'leaf'
(assuming Truth_vector is not longer than the number of rows in giraffe)
I am attempting to combine a series of loops/functions into one all-encompassing function to then be able to see the result for different input values. While the steps work properly when standalone (and when given just one input), I am having trouble getting the overall function to work. The answer I am getting back is a vector of 1s, which is incorrect.
The goal is to count the number of occurrences of consecutive zeroes in the randomly generated results, and then to see how the probability of consecutive zeroes occurring changes as I change the initial percentage input provided.
Does anyone have a tip for what I'm doing wrong? I have stared at this at several separate points now but cannot figure out where I'm going wrong. Thanks for your help.
### Example
pctgs_seq=seq(0.8,1,.01)
occurs=20
iterations=10
iterate_pctgs=function(x) {
probs=rep(0,length(pctgs_seq))
for (i in 1:length(pctgs_seq)) {
all_sims=lapply(1:iterations, function (x) ifelse(runif(occurs) <= i, 1, 0))
totals=sapply(all_sims,sum)
consec_zeroes=function (x) {
g=0
for (i in 1:(length(x)-1))
{ g= g+ifelse(x[i]+x[i+1]==0,1,0) }
return (g) }
consec_zeroes_sim=sapply(all_sims,consec_zeroes)
no_consec_prob=sum(consec_zeroes_sim==0)/length(consec_zeroes_sim)
probs[i]=no_consec_prob }
return (probs)
}
answer=iterate_pctgs(pctgs_seq)
This question already has answers here:
JavaScript Date Object Comparison
(7 answers)
Closed 6 years ago.
I'm trying to figure out how best to compare dates in Angular 2 and TypeScript 1.8.7.
Given:
startDate: Date;
endDate: Date;
if(this.startDate.getUTCMilliseconds() === this.endDate.getUTCMilliseconds()){
//do stuff here
} else {
// do something else here
}
This will return an error like "startDate.getUTCMilliseconds is not a function..."
Does somebody have a best practice? Thanks,
Date object method to get milliseconds is called getTime.
You can compare Date objects directly, with operators like <, >, and ==.
this.startDate == this.endDate
I know it's irrelevant and not what you asked for, but use angular-moment / momentjs. Dates in JS are a complete mess.
We were trying to write the results from a for loop. We tried to use write.table, as.data.frame and other solutions, but with no success. We expect to have a data frame.
Currently we have only the loop, that shows year and values from a matrix which are bigger than 50. Looks like that:
for (i in 1:nrow(dobowe1)) {
if(dobowe1[i,4]>50) {
cat(dobowe1[i,"rok"],dobowe1[i,4], "\n")
}
}
Note: We don't do programming a lot, so it's hard to use other solutions from the questions that already beed asked.
Try to save each element to the vector, like here:
tabela <- numeric(nrow(dobowe1))
for (i in 1:nrow(dobowe1)) {
if(dobowe1[i,4]>50) {
tabela[i] <- paste(dobowe1[i,"rok"],dobowe1[i,4])
}
}
as.data.frame(tabela)
If you just want to visually inspect a subset of your matrix, you can just print out a filtered subset:
# create the filter:
> f <- dobowe1[,4] > 50
# use the filter to subset (index) your data.frame:
> dobowe1[f,c("rok", whatever-4th-var-is-called)]
This will automatically print it out. Or you can write it to a file with ?write.table