transform data frame to numeric matrix

Question

I have this dataframe:

df <- data.frame(
    column_names = c("x1", "x1", "x2", "x2")
    ,row_names = c("y1", "y2", "y1", "y2")
    ,n = c(1,2,3,4)
)

and would like to transform it into a matrix like this:

 x1 x2
y2 2 4
y1 1 3

How can I achieve this please?

Answer 1

You can use data.table::dcast to reshape the data, then remove the row_names column, set the rownames, and order the rows by rownames descending.

out <- data.table::dcast(df, row_names ~ column_names, value.var = 'n')
out_mat <- as.matrix(out[, -1])
rownames(out_mat) <- out$row_names
out_mat <- out_mat[order(rownames(out_mat), decreasing = T),]

out_mat
#    x1 x2
# y2  2  4
# y1  1  3

Or with tidyverse

library(tidyverse)

df %>% 
  spread(column_names, n) %>% 
  arrange(desc(row_names)) %>% 
  column_to_rownames('row_names') %>% 
  as.matrix

#    x1 x2
# y2  2  4
# y1  1  3

Answer 2

You can do this with tidyr :

library(tidyr)
df <- spread(df, column_names, n)
df <- df[order(df$row_names, decreasing = TRUE),]

Edited for decreasing y values.

Answer 3

This will give you the exact output you asked for (a matrix with row and column names, arranged by descending y ):

library(dplyr)

mtx <- df %>% 
  group_by(row_names) %>%
  arrange(column_names) %>% 
  summarise(out=list(n)) %>% 
  arrange(desc(row_names)) %>% 
  pull(out) %>% 
  do.call('rbind', .)

rownames(mtx) <- df %>% 
  distinct(row_names) %>% 
  arrange(desc(row_names)) %>% 
  pull(row_names)

colnames(mtx) <- df %>% 
  distinct(column_names) %>% 
  arrange(column_names) %>% 
  pull(column_names)