CODEWITHSUNDEEP
rrcpp
Michal Majka
Michal Majka

Reputation: 5471

Rcpp subsetting rows of DataFrame

I wished to create a following subset of the iris dataset using the Rcpp package:

head(subset(iris, Species == "versicolor"))

  Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
51          7.0         3.2          4.7         1.4 versicolor
52          6.4         3.2          4.5         1.5 versicolor
53          6.9         3.1          4.9         1.5 versicolor
54          5.5         2.3          4.0         1.3 versicolor
55          6.5         2.8          4.6         1.5 versicolor
56          5.7         2.8          4.5         1.3 versicolor

I know how to subset columns of Rcpp::DataFrame - there is an overloaded operator [ which works as in R: x["var"]. However, I cannot find any way that would allow me to subset rows of a DataFrame with a not fixed number of columns.

I would like to write a function subset_rows_rcpp_iris which takes Rcpp::DataFrame (which will always be iris) and a CharacterVector level_of_species as inputs. It will return DataFrame object.

DataFrame subset_rows_rcpp_iris(DataFrame x, CharacterVector level_of_species) {
    ...
}

First, I want to find indices of rows that satisfy logical query. My problem is that if I access the Species vector in test function, save it as a CharacterVector and then compare it with level_of_species I get always only one TRUE value in case of setosa and FALSE values in other cases.

cppFunction('
    LogicalVector test(DataFrame x, CharacterVector level_of_species) {
            CharacterVector sub = x["Species"];
            LogicalVector ind = sub == level_of_species;
            return(ind);
            }
')
head(test(iris, "setosa"))

[1]  TRUE FALSE FALSE FALSE FALSE FALSE

If this worked, I could rewrite test function and use the vector with TRUE/FALSE values to subset each of the column of the data frame separately and then combine them again with Rcpp::DataFrame::create.

Upvotes: 4

Views: 2369

Answers (1)

joel.wilson
joel.wilson

Reputation: 8413

cppFunction('LogicalVector test(DataFrame x, StringVector level_of_species) {
  using namespace std;  
  StringVector sub = x["Species"];
  std::string level = Rcpp::as<std::string>(level_of_species[0]);
  Rcpp::LogicalVector ind(sub.size());
  for (int i = 0; i < sub.size(); i++){
      ind[i] = (sub[i] == level);
  }

  return(ind);
}')

xx=test(iris, "setosa")
> table(xx)
 xx
 FALSE  TRUE 
   100    50

Subsetting done!!! (i myself learnt a lot from this question..thanks!)

cppFunction('Rcpp::DataFrame test(DataFrame x, StringVector level_of_species) {
  using namespace std;  
  StringVector sub = x["Species"];
  std::string level = Rcpp::as<std::string>(level_of_species[0]);
  Rcpp::LogicalVector ind(sub.size());
  for (int i = 0; i < sub.size(); i++){
    ind[i] = (sub[i] == level);
  }

 // extracting each column into a vector
 Rcpp::NumericVector   SepalLength = x["Sepal.Length"];
 Rcpp::NumericVector   SepalWidth = x["Sepal.Width"];
 Rcpp::NumericVector PetalLength = x["Petal.Length"];
 Rcpp::NumericVector   PetalWidth = x["Petal.Width"];


 return Rcpp::DataFrame::create(Rcpp::Named("Sepal.Length")  = SepalLength[ind],
                                Rcpp::Named("Sepal.Width")  = SepalWidth[ind],
                                Rcpp::Named("Petal.Length")  = PetalLength[ind],
                                Rcpp::Named("Petal.Width")  = PetalWidth[ind]
);}')

yy=test(iris, "setosa")
> str(yy)
 'data.frame':  50 obs. of  4 variables:
 $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
 $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
 $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
 $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...

Upvotes: 4

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