R: Adding columns from one data frame to another, non-matching number of rows - rscript

Question

I have a .txt file with millions of rows of data - DateTime (1-min intervals) and Precipitation.
I have a .csv file with thousands of rows of data - DateTime (daily intevals), MaxTemp, MinTemp, WindSpd, WindDir.
I import the .txt file as a data frame and do a few transformations. I then move this into a new data frame.
I import the .csv file as a data frame do a few transformations. I then want to add the columns from this data frame into the new data frame (total of 7 columns). However, R throws an error: "Error in data.frame(..., check.names = FALSE) : arguments imply differing number of rows: 10382384, 32868, 1"
I know the number of rows is different, however, this is the format I need for the next step in processing. This could be easily done in Excel were it not for the crazy amount of rows.
Simulated code is below, which produces the same error:
a <- as.character(c(1,2,3,4,5,6,7,8,9,10))
b <- c(paste("Date", a))
c <- c(rnorm(10, mean = 5, sd = 2.1))
Frame1 <- data.frame(b,c)
d <- as.character(c(1,2,3))
e <- c(paste("Date", d))
f <- c(rnorm(3, mean = 1, sd = 0.7))
g <- c(rnorm(3, mean = 3, sd = 2))
h <- c(rnorm(3, mean = 8, sd = 1))
Frame2 <- data.frame(e,f,g,h)
NewFrame <- cbind(Frame1)
NewFrame <- cbind(NewFrame, Frame2)
I have tried a *_join but it throws error: "Error: by must be supplied when x and y have no common variables.
i use by = character()` to perform a cross-join." which to me reads like it wants to match things up, which I don't need. I really just need to plop these two datasets side-by-side for the next processing step. Help?

Answer 1

The data frames MUST have an equal number of rows. To compensate then, I just added a bunch of rows to the smaller dataset so that it contains the same amount of rows as the larger dataset (in my case, it will always be the .csv file) and filled it with "NA" values. The following application I use for downstream processing knows how to handle the "NA" values so this works well for me.
I've run the solution with a representative dataset and I am able to cbind the two data frames together.
Sample code with the simulated dataset:
#create data frame 1
a <- as.character(c(1:10))
b <- c(paste("Date", a))
c <- c(rnorm(10, mean = 5, sd = 2.1))
Frame1 <- data.frame(b,c)
#create date frame 2
d <- as.character(c(1,2,3))
e <- c(paste("Date", d))
f <- c(rnorm(3, mean = 1, sd = 0.7))
g <- c(rnorm(3, mean = 3, sd = 2))
h <- c(rnorm(3, mean = 8, sd = 1))
Frame2 <- data.frame(e,f,g,h)
#find the maximum number of rows
maxlen <- max(nrow(Frame1), nrow(Frame2))
#finds the minimum number of rows
rowrow <- min(nrow(Frame1), nrow(Frame2))
#adds enough rows to the smaller dataset to equal the number of rows
#in the larger dataset. Populates the rows with "NA" values
Frame2[rowrow+(maxlen-rowrow),] <- NA
#creates the new data frame from the two frames
NewFrame <- cbind(NewFrame, Frame2)