Print the Nth Row in a List of Data Frames

Question

I am cleaning several excel files in R. They unfortunately are of unequal dimensions, rows and columns. Currently I am storing each excel sheet as a data frame in a list. I

Answer 1

My suggestion is to write a function that does what you want on a single data frame:

myfun <- function(dat) {
  return(dat[4, , drop=FALSE])
}

If you want to return as a vector instead of data.frame, just do: return(dat[4, ]) insteaad. Then use lapply to apply that function to each element of your list:

lapply(df.list1, myfun)

With that technique, you can easily come up with ways to extend myfun to more complex functions...

Answer 2

You could also just directly lapply the extraction function @Justin suggests, e.g.:

# example data of a list containing 10 data frames:
test <- replicate(10,data.frame(a=1:10),simplify=FALSE)

# extract the fourth row of each one - setting drop=FALSE means you get a
# data frame returned even if only one vector/column needs to be returned.
lapply(test,"[",4,,drop=FALSE)

The format is:

lapply(listname,"[",rows.to.return,cols.to.return,drop=FALSE)

# the example returns the fourth row only from each data frame
#[[1]]
#  a
#4 4
# 
#[[2]]
#  a
#4 4
# etc...

To generalise this when you are completing an extraction based on a condition, you would have to change it up a little to something like the below example extracting all rows where a in each data.frame is >4. In this case, using an anonymous function is probably the clearest method, e.g.:

lapply(test, function(x) with(x,x[a>4,,drop=FALSE]) )

#[[1]]
#    a
#5   5
#6   6
#7   7
#8   8
#9   9
#10 10
# etc...

Answer 3

For example, you have a .csv file called hw1_data.csv and you want to retrieve the 47th row. Here is how to do that:

x<-read.csv("hw1_data.csv")

x[47,]

If it is a text file you can use read.table.

Answer 4

There is no need for a wrapper function, just use lapply and pass it a blank argument at the end (to represent the columns)

lapply(df.list, `[`, 4, )

This also works with any type of row argument that you would normally use in myDF[ . , ] eg: lapply(df.list,[, c(2, 4:6), )

.

---

I would suggest that if you are going to use a wrapper function, have it work more like [ does: eg

Grab(df.list, 2:3, 1:5) would select the second & third row and first through 5th column of every data.frame and Grab (df.list, 2:3) would select the second & third row of all columns

Grab <- function(ll, rows, cols) {
    if (missing(cols))
        lapply(ll, `[`, rows, )
    else 
        lapply(ll, `[`, rows, cols)
}

Grab (df.list, 2:3)