Generate crosstabulations from dataframe of categorical variables in survey

Tag: r,data.frame,crosstab

I've got some survey results and am trying to do some basic cross tabulations. Each column is a type of chemical, and the number 0:5 are how useful they were.

I'm trying to figure out a nice table that presents the freq, and percent. Using table, or xtabs, I'm able to get individual results for each column, but I'd like to figure out a way to create a nice table that I'll be able to output into Latex that includes all the chemicals on one table.

Thanks for any help you can provide.

Data Frame :

df <- read.table(text = "   
V1 V2 V3 V4 V5 V6 V7
1  NA NA NA NA NA NA NA
2   0  0  0  0  0  0  0
3   0  0  0  0  0  0 NA
4  NA NA NA NA NA NA  5
5   0  0  0  0  0  2  0
6  NA  4 NA NA NA NA NA
7   0  0  0  0  0  0  0
8  NA NA NA NA NA  3 NA
9  NA  2 NA NA NA  3 NA
10 NA  4 NA NA NA NA NA
11  0  0  0  0  0  0  0
12  0  0  0  0  0  0  0
13  0  0  0  0  0  0  0
14 NA NA NA NA NA  2  3
15 NA  3 NA  3 NA NA NA
16 NA  4 NA NA NA NA NA
17  0  0  0  0  0  0  0
18 NA  5 NA  5 NA NA NA
19  0  0  0  0  0  0  0
20 NA  1 NA NA NA NA NA", header = T)

Desired Output (Accurate numbers for V1 and V2) :

                     V1            V2           etc....
                  Freq Percent   Freq Percent
No                 9     100       9    56.2
Poor               0      0        1    6.2 
Somewhat effective 0      0        1    6.2
Good               0      0        1    6.2
Very Good          0      0        3    18.75
NA                 0      0        1    6.2

Best How To :

Here, we are getting the frequency for each column by using lapply and table. lapply gets the data.frame in a list environment and then use table after converting the column to factor with levels specified as 0:5. Use, prop.table to get the proportion, cbind the Freq and Percent, convert the list to data.frame by do.call(cbind, and finally rename the row.names and colnames

  res <-  do.call(cbind,lapply(df, function(x) {
            x1 <- table(factor(x, levels=0:5,
               labels=c('No', 'Poor', 'Somewhat Effective', 
                               'Good', 'Very Good', 'NA') ))
             cbind(Freq=x1, Percent=round(100*prop.table(x1),2))}))
 colnames(res) <- paste(rep(paste0('V',1:7),each=2),
                                     colnames(res),sep=".")

  head(res,2)
  #     V1.Freq V1.Percent V2.Freq V2.Percent V3.Freq V3.Percent V4.Freq
  #No         9        100       9      56.25       9        100       9
  #Poor       0          0       1       6.25       0          0       0
  #     V4.Percent V5.Freq V5.Percent V6.Freq V6.Percent V7.Freq V7.Percent
  #No        81.82       9        100       8      66.67       8         80
  #Poor       0.00       0          0       0       0.00       0          0

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