I want to prepare xtabs for different stations. But it is giving me overall table across stations. I have used the following code
library(tidyverse)
df %>% group_by(Station) %>%
xtabs( ~ Observed + Forecasted, data = .)
This is giving me
#> Forecasted
#>Observed 1 3 4 5 9
#> 1 132 5 31 31 3
#> 3 16 0 6 13 7
#> 4 6 0 13 23 8
#> 5 4 0 16 33 15
#> 9 0 0 0 2 0
But I want to have the output stationwise like
Aizawl
#> Forecasted
#>Observed 1 3 4 5 9
#> 1 132 5 31 31 3
#> 3 16 0 6 13 7
#> 4 6 0 13 23 8
#> 5 4 0 16 33 15
#> 9 0 0 0 2 0
Serchhip
#> Forecasted
#>Observed 1 3 4 5 9
#> 1 132 5 31 31 3
#> 3 16 0 6 13 7
#> 4 6 0 13 23 8
#> 5 4 0 16 33 15
#> 9 0 0 0 2 0
Then I want to export the output in .csv file.
df = structure(list(Station = c("Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl",
"Aizawl", "Aizawl", "Aizawl", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip",
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip"),
Observed = c(1, 1, 1, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1,
1, 1, 1, 1, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 4, 1, 1, 4, 1, 3, 1, 1,
1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 1, 1, 1, 1, 1, 3, 5,
5, 3, 5, 3, 1, 1, 3, 1, 1, 1, 1, 1, 5, 3, 4, 1, 1, 1, 1,
1, 3, 1, 4, 1, 1, 1, 1, 1, 4, 4, 5, 1, 5, 4, 5, 5, 5, 5,
1, 5, 1, 4, 5, 4, 4, 5, 4, 5, 5, 3, 1, 5, 3, 4, 3, 4, 5,
5, 5, 5, 4, 4, 4, 5, 5, 5, 5, 5, 5, 4, 5, 3, 4, 4, 5, 3,
5, 4, 4, 5, 5, 5, 5, 4, 5, 5, 5, 5, 5, 5, 5, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 3, 5, 5, 1, 1, 3, 4, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 1,
1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5,
3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 1, 3, 4, 1, 1, 1, 1,
1, 1, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 4, 3, 9, 5, 5, 4, 1, 5, 1, 1, 1, 1, 4, 5, 5, 5,
5, 5, 5, 1, 1, 4, 1, 4, 4, 4, 5, 1, 1, 4, 3, 5, 1, 1, 4,
3, 5, 3, 4, 5, 3, 4, 4, 5, 5, 3, 4, 5, 5, 5, 5, 5, 4, 4,
4, 4, 5, 1, 9, 5, 5), Forecasted = c(1, 1, 1, 5, 5, 1, 1,
1, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5, 5, 5,
5, 9, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5, 5, 5, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 4, 1, 4, 4, 1, 1, 5, 3, 1, 1, 1, 4, 5, 5, 5, 5,
1, 1, 1, 5, 5, 1, 5, 5, 5, 9, 4, 5, 4, 4, 4, 3, 4, 4, 1,
1, 5, 5, 4, 4, 4, 1, 1, 1, 4, 4, 4, 4, 4, 4, 1, 1, 5, 4,
4, 5, 4, 4, 4, 4, 5, 4, 5, 5, 5, 5, 5, 4, 5, 5, 4, 1, 1,
4, 4, 5, 5, 5, 5, 1, 4, 5, 5, 1, 4, 4, 9, 9, 9, 9, 9, 9,
9, 9, 9, 9, 9, 9, 9, 9, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
5, 5, 5, 9, 1, 1, 1, 5, 4, 1, 1, 1, 5, 4, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 5, 5, 5, 9, 5, 5, 1, 1, 1, 1, 1,
1, 1, 1, 1, 5, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 5, 5, 4, 1, 1, 1, 1, 1, 4, 1, 1, 1,
4, 4, 4, 4, 1, 4, 1, 3, 1, 1, 1, 4, 4, 4, 4, 4, 4, 1, 1,
1, 4, 4, 3, 5, 5, 5, 4, 3, 5, 5, 5, 5, 5, 4, 5, 5, 5, 4,
5, 4, 4, 5, 5, 4, 4, 5, 4, 1, 4, 4, 5, 5, 4, 5, 4, 5, 4,
5, 5, 5, 1, 4, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
5, 5, 5, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 9)), row.names = c(NA,
364L), class = "data.frame")
If you want to operate on a xtabs(3-dimensional array) instead of list or data.frame, then put the stratified variable, i.e. Station, to the last position of the formula in xtabs().
res <- xtabs( ~ Observed + Forecasted + Station, df)
res
# , , Station = Aizawl
#
# Forecasted
# Observed 1 3 4 5 9
# 1 56 2 13 13 1
# 3 12 0 4 8 3
# 4 4 0 9 11 4
# 5 3 0 7 23 9
# 9 0 0 0 0 0
#
# , , Station = Serchhip
#
# Forecasted
# Observed 1 3 4 5 9
# 1 76 3 18 18 2
# 3 4 0 2 5 4
# 4 2 0 4 12 4
# 5 1 0 9 10 6
# 9 0 0 0 2 0
class(res)
# [1] "xtabs" "table"
To print the array to 2 individual csv files:
lapply(dimnames(res)$Station, function(x) write.csv(res[,,x], paste0("table_", x, ".csv")))
To transform the array to a data.frame format:
library(tidyr)
res %>%
as.data.frame() %>%
pivot_wider(names_from = Forecasted, values_from = Freq)
# # A tibble: 10 x 7
# Observed Station `1` `3` `4` `5` `9`
# <fct> <fct> <int> <int> <int> <int> <int>
# 1 1 Aizawl 56 2 13 13 1
# 2 3 Aizawl 12 0 4 8 3
# 3 4 Aizawl 4 0 9 11 4
# 4 5 Aizawl 3 0 7 23 9
# 5 9 Aizawl 0 0 0 0 0
# 6 1 Serchhip 76 3 18 18 2
# 7 3 Serchhip 4 0 2 5 4
# 8 4 Serchhip 2 0 4 12 4
# 9 5 Serchhip 1 0 9 10 6
# 10 9 Serchhip 0 0 0 2 0