R中的分组xtabs
Group wise xtabs in R
我想为不同的站准备xtabs。但它给了我整体 table 跨站。我使用了以下代码
library(tidyverse)
df %>% group_by(Station) %>%
xtabs( ~ Observed + Forecasted, data = .)
这是给了我
#> 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
但我希望像
这样的站位输出
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
然后我想将输出导出到 .csv 文件中。
数据
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")
如果您想将其写入 CSV，最好将数据保存为 CSV 友好格式。这个输出
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
可能会导致问题，使用 dplyr 和 tidyr 可以轻松准备 CSV 格式友好的输出。
library(dplyr)
library(tidyr)
df %>%
group_by(Station, Observed, Forecasted) %>%
tally() %>%
pivot_wider(names_from = Forecasted, values_from = n) %>%
replace(is.na(.), 0)
# A tibble: 9 x 7
# Groups: Station, Observed [9]
Station Observed `1` `3` `4` `5` `9`
<chr> <dbl> <int> <int> <int> <int> <int>
1 Aizawl 1 56 2 13 13 1
2 Aizawl 3 12 0 4 8 3
3 Aizawl 4 4 0 9 11 4
4 Aizawl 5 3 0 7 23 9
5 Serchhip 1 76 3 18 18 2
6 Serchhip 3 4 0 2 5 4
7 Serchhip 4 2 0 4 12 4
8 Serchhip 5 1 0 9 10 6
9 Serchhip 9 0 0 0 2 0
此时您可以轻松导出到 CSV，或者直接通过链接管道导出。
df %>%
group_by(Station, Observed, Forecasted) %>%
tally() %>%
pivot_wider(names_from = Forecasted, values_from = n) %>%
replace(is.na(.), 0) %>%
readr::write_csv("my_output.csv")
使用 by.
res <- by(df, df$Station, xtabs, f=~Observed + Forecasted)
res
# df$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
# ---------------------------------------------------------
# df$Station: Serchhip
# Forecasted
# Observed 1 3 4 5 9
# 1 76 3 18 18 2
# 3 4 0 2 5 4
# 4 2 0 4 12 4
# 5 1 0 9 10 6
# 9 0 0 0 2 0
## Output .csv
lapply(names(res), function(x) write.csv(res[[x]], paste0("myfile_", x,".csv")))
如果你想对xtabs（3维数组）进行操作而不是list或data.frame，那么把分层变量，即Station，到 xtabs().
中公式的最后位置
res <- xtabs( ~ Observed + Forecasted + Station, df)
res
# , , Station = Aizawl
#
# Forecasted
# Observed 1 3 4 5 9
# 1 56 2 13 13 1
# 3 12 0 4 8 3
# 4 4 0 9 11 4
# 5 3 0 7 23 9
# 9 0 0 0 0 0
#
# , , Station = Serchhip
#
# Forecasted
# Observed 1 3 4 5 9
# 1 76 3 18 18 2
# 3 4 0 2 5 4
# 4 2 0 4 12 4
# 5 1 0 9 10 6
# 9 0 0 0 2 0
class(res)
# [1] "xtabs" "table"
要将数组打印到 2 个单独的 csv 文件：
lapply(dimnames(res)$Station, function(x) write.csv(res[,,x], paste0("table_", x, ".csv")))
要将数组转换为 data.frame 格式：
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
我想为不同的站准备xtabs。但它给了我整体 table 跨站。我使用了以下代码
library(tidyverse)
df %>% group_by(Station) %>%
xtabs( ~ Observed + Forecasted, data = .)
这是给了我
#> 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
但我希望像
这样的站位输出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
然后我想将输出导出到 .csv 文件中。
数据
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")
如果您想将其写入 CSV，最好将数据保存为 CSV 友好格式。这个输出
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
可能会导致问题，使用 dplyr 和 tidyr 可以轻松准备 CSV 格式友好的输出。
library(dplyr)
library(tidyr)
df %>%
group_by(Station, Observed, Forecasted) %>%
tally() %>%
pivot_wider(names_from = Forecasted, values_from = n) %>%
replace(is.na(.), 0)
# A tibble: 9 x 7
# Groups: Station, Observed [9]
Station Observed `1` `3` `4` `5` `9`
<chr> <dbl> <int> <int> <int> <int> <int>
1 Aizawl 1 56 2 13 13 1
2 Aizawl 3 12 0 4 8 3
3 Aizawl 4 4 0 9 11 4
4 Aizawl 5 3 0 7 23 9
5 Serchhip 1 76 3 18 18 2
6 Serchhip 3 4 0 2 5 4
7 Serchhip 4 2 0 4 12 4
8 Serchhip 5 1 0 9 10 6
9 Serchhip 9 0 0 0 2 0
此时您可以轻松导出到 CSV，或者直接通过链接管道导出。
df %>%
group_by(Station, Observed, Forecasted) %>%
tally() %>%
pivot_wider(names_from = Forecasted, values_from = n) %>%
replace(is.na(.), 0) %>%
readr::write_csv("my_output.csv")
使用 by.
res <- by(df, df$Station, xtabs, f=~Observed + Forecasted)
res
# df$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
# ---------------------------------------------------------
# df$Station: Serchhip
# Forecasted
# Observed 1 3 4 5 9
# 1 76 3 18 18 2
# 3 4 0 2 5 4
# 4 2 0 4 12 4
# 5 1 0 9 10 6
# 9 0 0 0 2 0
## Output .csv
lapply(names(res), function(x) write.csv(res[[x]], paste0("myfile_", x,".csv")))
如果你想对xtabs（3维数组）进行操作而不是list或data.frame，那么把分层变量，即Station，到 xtabs().
res <- xtabs( ~ Observed + Forecasted + Station, df)
res
# , , Station = Aizawl
#
# Forecasted
# Observed 1 3 4 5 9
# 1 56 2 13 13 1
# 3 12 0 4 8 3
# 4 4 0 9 11 4
# 5 3 0 7 23 9
# 9 0 0 0 0 0
#
# , , Station = Serchhip
#
# Forecasted
# Observed 1 3 4 5 9
# 1 76 3 18 18 2
# 3 4 0 2 5 4
# 4 2 0 4 12 4
# 5 1 0 9 10 6
# 9 0 0 0 2 0
class(res)
# [1] "xtabs" "table"
要将数组打印到 2 个单独的 csv 文件：
lapply(dimnames(res)$Station, function(x) write.csv(res[,,x], paste0("table_", x, ".csv")))
要将数组转换为 data.frame 格式：
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