I have a shared folder in google drive. I'll use this link as an example:
https://drive.google.com/drive/u/1/folders/1on07liV24xKCVpcWkOJEu6Ci8Lmcl9hi
I have a script in r like below:
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
##Work Directory?
write_csv(mtcars, 'mtcars_dataset.csv')
How do I set my work directory to be this shared folder?
I attempted to use the googledrive package but I could only find a way to access files rather than folders.
You can set your working directory manually by
setwd("C:/Users/*user name*/Google Drive/*shared folder*")
If you are using googledrive package, there is the function drive_upload. You can take a look on the documentation.
Basically you need to specify your file, the path to upload and a name for the file.
I hope it's clear!
Related
When I run colnames(), it never shows the name of this first column.
For example, after wasting a lot of time researching online, I discovered the name of the first column in mtcars is das_Auto.
Why doesn't this name show when I run this code?
[colnames(mtcars)][1]
What's the easiest way to determine the name of the first column in a data set?
This is because the first 'column' of mtcars is not actually a column but an index. If you want to convert it to a column you can run the below:
df <- cbind(das_Auto = rownames(mtcars), mtcars)
rownames(df) <- 1:nrow(mtcars)
head(df)
das_Auto mpg cyl disp hp drat wt qsec vs am gear carb
1 Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
2 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
3 Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
4 Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
5 Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
6 Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
I want to deal with NA values in my data but do not want to scale and center it so I simply do this:
preProcess(data, method = "knnImpute", k=10)
or this:
preProcess(data, method = "bagImpute")
However it automatically scales and centers data which seems intentional (states that in documentation). How do I avoid that and simply do imputation?
You can't avoid scaling and centering your data when using method = "knnImpute", presumably because it does not usually make sense to use knn without doing so.
However, method = "bagImpute" or method = "medianImpute" will not scale and center the data unless you ask it to. For example:
mtcars[1, 1] <- NA
pc <- preProcess(data, method = "bagImpute")
head(predict(pc, 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
My question is how to use "apply" function to do what "for loop" does in this example:
mtcars
for (i in colnames(mtcars)){
print(head(mtcars[i]))
}
What I need is to get R to read one column after the other, ideally by index (ie mtcars[1], then mtcars[2], then mtcars[3]...) rather than colnames.
Your help is highly appreciated.
Thanks
Use the apply function
apply(mtcars, 2 ,head)
this is the result
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
Explanation
2 in the parameter of apply function means you're going to pass each column to your defined function , if you pass 1 instead of 2 this means that you're going to send each row instead of column
I would like to define a string
string<- "modelName"
That could be used to name an object later. Something like
paste0(string) <- mtcars
cat(string) <- mtcars
print(string) <- mtcars
get(string) <- mtcars
The needed result is the dataset called "modelName". None of the examples above work, obviously.
Question:
How can create one create an object which name is defined by the sourced string?
As #Spacedman notes this is not generally the way things are done but you can use assign
string<- "modelName"
assign(string, mtcars)
> head(modelName)
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
In general it may be perferable to use sometthing like a list:
x <- list()
x[[string]] <- mtcars
> head(x$modelName)
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
I pass data frame name as string into a function. How do I get content of referenced data frame from the string? Suppose I have string 'mtcars' and I want to print data frame mtcars:
printdf <- function(dataframe) {
print(dataframe)
}
printdf('mtcars');
I think you'll need a get in there if the input is a string. Also, depending on your usage of the function, the explicit print might not be necessary:
printdf <- function(dataframe) {
get(dataframe)
# print(get(dataframe))
}
head(printdf("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