R：如何绘制 rpivotTable 或 dcast table，其中汇总列与 excel 相同，用于报告连续数据
R: How to plot rpivotTable or dcast table with summarised column in between same as excel for reporting of continues data
R：如何绘制 rpivotTable 或 dcast table，其中汇总列与 excel 相同，用于报告连续数据。
检查附加的屏幕截图和数据集，尝试了不同的方式在 dcast 和 rpivot 中添加汇总列table但没有得到。
示例数据集如下。
Buyer year_month Late_Days
A 2018-01 0 or Early
B 2018-01 >=5
C 2018-02 >=10
A 2018-04 0 or Early
A 2018-03 >=5
B 2018-03 >=10
C 2018-05 0 or Early
A 2018-06 >=5
B 2018-07 >=10
A 2018-11 0 or Early
B 2018-11 >=5
A 2019-01 >=10
B 2019-01 0 or Early
A 2019-01 >=5
A 2019-02 >=10
dput(DF) 的结果
year_month("12-2019", "01-2020", "01-2020", "06-2018", "08-2018", "09-2018", "12-2018", "03-2019",
"11-2016", "11-2016", "04-2019", "07-2017", "08-2017", "09-2017", "10-2017", "11-2017", "12-2017",
"01-2018", "02-2018","03-2018", "04-2018", "05-2018", "06-2018", "07-2018", "08-2018", "09-2018",
"07-2017", "08-2017", "09-2017", "10-2017", "11-2017", "12-2017", "01-2018", "02-2018","03-2018",
"04-2018", "05-2018", "06-2018", "07-2018", "08-2018", "09-2018","08-2017", "09-2017", "03-2018",
"04-2019") Late_Days = c("<=20", "<=10", "<=5", "<=20", "0 or early", "0 or early", "0 or early",
"0 or early", "0 or early", "<=30", "0 or early", "<=10", "<=5",
"0 or early", "0 or early", "0 or early", ">30", "<=20", "<=20",
"<=20", "<=20", ">30", "<=20", "<=5", "<=5", "<=5", "<=5", "<=10",
"<=10", ">30", "<=5", "0 or early", "<=5", "0 or early", "0 or early",
"0 or early", "<=10", "<=5", "0 or early", "0 or early", "0 or early"
"<=20", "<=5", "<=5", "<=5")Buyer = c(
"C", "D", "D", "D", "D", "A", "D", "A", "A", "C", "A", "A", "A", "A", "A",
"A", "A", "A", "A", "A", "A", "A", "A", "C", "C", "A", "C", "A", "A", "A",
"A", "B", "B", "A", "A", "B", "B", "B", "A", "A", "C", "C", "A", "A", "A",
)row.names = c(1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L,
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 20L, 31L,
32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L)
我试过的代码
datatable(dcast(inventory, Buyer ~ year_month), filter = 'top')
查看excel报告的截图。是否可以在 R 中生成。
我不知道用你的 Late_Days 列中的字符串求和。所以我用一些随机数字替换了字符串（见下面的代码）
** 提供的示例数据 **
df <- data.frame(year_month = c("12-2019", "01-2020", "01-2020", "06-2018", "08-2018", "09-2018", "12-2018", "03-2019",
"11-2016", "11-2016", "04-2019", "07-2017", "08-2017", "09-2017", "10-2017", "11-2017", "12-2017",
"01-2018", "02-2018","03-2018", "04-2018", "05-2018", "06-2018", "07-2018", "08-2018", "09-2018",
"07-2017", "08-2017", "09-2017", "10-2017", "11-2017", "12-2017", "01-2018", "02-2018","03-2018",
"04-2018", "05-2018", "06-2018", "07-2018", "08-2018", "09-2018","08-2017", "09-2017", "03-2018",
"04-2019"),
Late_Days = c("<=20", "<=10", "<=5", "<=20", "0 or early", "0 or early", "0 or early",
"0 or early", "0 or early", "<=30", "0 or early", "<=10", "<=5",
"0 or early", "0 or early", "0 or early", ">30", "<=20", "<=20",
"<=20", "<=20", ">30", "<=20", "<=5", "<=5", "<=5", "<=5", "<=10",
"<=10", ">30", "<=5", "0 or early", "<=5", "0 or early", "0 or early",
"0 or early", "<=10", "<=5", "0 or early", "0 or early", "0 or early",
"<=20", "<=5", "<=5", "<=5"),
Buyer = c( "C", "D", "D", "D", "D", "A", "D", "A", "A", "C", "A", "A", "A", "A", "A",
"A", "A", "A", "A", "A", "A", "A", "A", "C", "C", "A", "C", "A", "A", "A",
"A", "B", "B", "A", "A", "B", "B", "B", "A", "A", "C", "C", "A", "A", "A" ),
stringsAsFactors = FALSE
)
代码
library( data.table )
library( janitor )
#set data to data.table format
data.table::setDT(df)
#replace Late_Days with numeric, or elese we've got nothing to sum...
set.seed(123)
df[, Late_Days := sample(0:20, nrow(df), replace = TRUE) ]
#get year and month to separate columns
df[, c("month", "year") := data.table::tstrsplit( year_month, "-" ) ][]
#get yearly summarise, with totals
l <- lapply( unique(df$year), function(x) {
temp <- df[ year == x, ]
ans <- data.table::dcast( temp[, .(sum(Late_Days)), by = .(Buyer, year, month) ], Buyer ~ year + month, value.var = "V1", fill = 0 )
ans <- janitor::adorn_totals(ans, where = c("col"), name = paste0( x, "_Total"))
} )
#bind together
ans <- data.table::rbindlist( l, use.names = TRUE, fill = TRUE )
#melt to ling
ans <- data.table::melt( ans, id.vars = "Buyer" )
#get summary per buyer, per period
ans <- ans[, sum(value, na.rm = TRUE), by = .(Buyer, variable)]
#cast to wide again
final <- data.table::dcast( ans, Buyer ~ variable, value.var = "V1" )
#get the order right
colorder = c("Buyer", sort( names(final)[!names(final) == "Buyer"] ) )
#reorder, and get totals by column
janitor::adorn_totals( final[, ..colorder ], where = "row" )
输出
# Buyer 2016_11 2016_Total 2017_07 2017_08 2017_09 2017_10 2017_11 2017_12 2017_Total 2018_01 2018_02 2018_03 2018_04 2018_05 2018_06
# A 19 19 18 17 31 13 14 9 102 8 38 9 13 16 10
# B 0 0 0 0 0 0 0 8 8 9 0 0 20 5 1
# C 13 13 14 12 0 0 0 0 26 0 0 0 0 0 0
# D 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2
# Total 32 32 32 29 31 13 14 17 136 17 38 9 33 21 13
# 2018_07 2018_08 2018_09 2018_12 2018_Total 2019_03 2019_04 2019_12 2019_Total 2020_01 2020_Total
# 4 7 28 0 133 4 9 0 13 0 0
# 0 0 0 0 35 0 0 0 0 0 0
# 6 20 11 0 37 0 0 14 14 0 0
# 0 9 0 10 21 0 0 0 0 31 31
# 10 36 39 10 226 4 9 14 27 31 31
R：如何绘制 rpivotTable 或 dcast table，其中汇总列与 excel 相同，用于报告连续数据。
检查附加的屏幕截图和数据集，尝试了不同的方式在 dcast 和 rpivot 中添加汇总列table但没有得到。
示例数据集如下。
Buyer year_month Late_Days
A 2018-01 0 or Early
B 2018-01 >=5
C 2018-02 >=10
A 2018-04 0 or Early
A 2018-03 >=5
B 2018-03 >=10
C 2018-05 0 or Early
A 2018-06 >=5
B 2018-07 >=10
A 2018-11 0 or Early
B 2018-11 >=5
A 2019-01 >=10
B 2019-01 0 or Early
A 2019-01 >=5
A 2019-02 >=10
dput(DF) 的结果
year_month("12-2019", "01-2020", "01-2020", "06-2018", "08-2018", "09-2018", "12-2018", "03-2019",
"11-2016", "11-2016", "04-2019", "07-2017", "08-2017", "09-2017", "10-2017", "11-2017", "12-2017",
"01-2018", "02-2018","03-2018", "04-2018", "05-2018", "06-2018", "07-2018", "08-2018", "09-2018",
"07-2017", "08-2017", "09-2017", "10-2017", "11-2017", "12-2017", "01-2018", "02-2018","03-2018",
"04-2018", "05-2018", "06-2018", "07-2018", "08-2018", "09-2018","08-2017", "09-2017", "03-2018",
"04-2019") Late_Days = c("<=20", "<=10", "<=5", "<=20", "0 or early", "0 or early", "0 or early",
"0 or early", "0 or early", "<=30", "0 or early", "<=10", "<=5",
"0 or early", "0 or early", "0 or early", ">30", "<=20", "<=20",
"<=20", "<=20", ">30", "<=20", "<=5", "<=5", "<=5", "<=5", "<=10",
"<=10", ">30", "<=5", "0 or early", "<=5", "0 or early", "0 or early",
"0 or early", "<=10", "<=5", "0 or early", "0 or early", "0 or early"
"<=20", "<=5", "<=5", "<=5")Buyer = c(
"C", "D", "D", "D", "D", "A", "D", "A", "A", "C", "A", "A", "A", "A", "A",
"A", "A", "A", "A", "A", "A", "A", "A", "C", "C", "A", "C", "A", "A", "A",
"A", "B", "B", "A", "A", "B", "B", "B", "A", "A", "C", "C", "A", "A", "A",
)row.names = c(1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L,
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 20L, 31L,
32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L)
我试过的代码
datatable(dcast(inventory, Buyer ~ year_month), filter = 'top')
查看excel报告的截图。是否可以在 R 中生成。
我不知道用你的 Late_Days 列中的字符串求和。所以我用一些随机数字替换了字符串（见下面的代码）
** 提供的示例数据 **
df <- data.frame(year_month = c("12-2019", "01-2020", "01-2020", "06-2018", "08-2018", "09-2018", "12-2018", "03-2019",
"11-2016", "11-2016", "04-2019", "07-2017", "08-2017", "09-2017", "10-2017", "11-2017", "12-2017",
"01-2018", "02-2018","03-2018", "04-2018", "05-2018", "06-2018", "07-2018", "08-2018", "09-2018",
"07-2017", "08-2017", "09-2017", "10-2017", "11-2017", "12-2017", "01-2018", "02-2018","03-2018",
"04-2018", "05-2018", "06-2018", "07-2018", "08-2018", "09-2018","08-2017", "09-2017", "03-2018",
"04-2019"),
Late_Days = c("<=20", "<=10", "<=5", "<=20", "0 or early", "0 or early", "0 or early",
"0 or early", "0 or early", "<=30", "0 or early", "<=10", "<=5",
"0 or early", "0 or early", "0 or early", ">30", "<=20", "<=20",
"<=20", "<=20", ">30", "<=20", "<=5", "<=5", "<=5", "<=5", "<=10",
"<=10", ">30", "<=5", "0 or early", "<=5", "0 or early", "0 or early",
"0 or early", "<=10", "<=5", "0 or early", "0 or early", "0 or early",
"<=20", "<=5", "<=5", "<=5"),
Buyer = c( "C", "D", "D", "D", "D", "A", "D", "A", "A", "C", "A", "A", "A", "A", "A",
"A", "A", "A", "A", "A", "A", "A", "A", "C", "C", "A", "C", "A", "A", "A",
"A", "B", "B", "A", "A", "B", "B", "B", "A", "A", "C", "C", "A", "A", "A" ),
stringsAsFactors = FALSE
)
代码
library( data.table )
library( janitor )
#set data to data.table format
data.table::setDT(df)
#replace Late_Days with numeric, or elese we've got nothing to sum...
set.seed(123)
df[, Late_Days := sample(0:20, nrow(df), replace = TRUE) ]
#get year and month to separate columns
df[, c("month", "year") := data.table::tstrsplit( year_month, "-" ) ][]
#get yearly summarise, with totals
l <- lapply( unique(df$year), function(x) {
temp <- df[ year == x, ]
ans <- data.table::dcast( temp[, .(sum(Late_Days)), by = .(Buyer, year, month) ], Buyer ~ year + month, value.var = "V1", fill = 0 )
ans <- janitor::adorn_totals(ans, where = c("col"), name = paste0( x, "_Total"))
} )
#bind together
ans <- data.table::rbindlist( l, use.names = TRUE, fill = TRUE )
#melt to ling
ans <- data.table::melt( ans, id.vars = "Buyer" )
#get summary per buyer, per period
ans <- ans[, sum(value, na.rm = TRUE), by = .(Buyer, variable)]
#cast to wide again
final <- data.table::dcast( ans, Buyer ~ variable, value.var = "V1" )
#get the order right
colorder = c("Buyer", sort( names(final)[!names(final) == "Buyer"] ) )
#reorder, and get totals by column
janitor::adorn_totals( final[, ..colorder ], where = "row" )
输出
# Buyer 2016_11 2016_Total 2017_07 2017_08 2017_09 2017_10 2017_11 2017_12 2017_Total 2018_01 2018_02 2018_03 2018_04 2018_05 2018_06
# A 19 19 18 17 31 13 14 9 102 8 38 9 13 16 10
# B 0 0 0 0 0 0 0 8 8 9 0 0 20 5 1
# C 13 13 14 12 0 0 0 0 26 0 0 0 0 0 0
# D 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2
# Total 32 32 32 29 31 13 14 17 136 17 38 9 33 21 13
# 2018_07 2018_08 2018_09 2018_12 2018_Total 2019_03 2019_04 2019_12 2019_Total 2020_01 2020_Total
# 4 7 28 0 133 4 9 0 13 0 0
# 0 0 0 0 35 0 0 0 0 0 0
# 6 20 11 0 37 0 0 14 14 0 0
# 0 9 0 10 21 0 0 0 0 31 31
# 10 36 39 10 226 4 9 14 27 31 31