将 NSE enquo 与 dply 和 tidyr 一起使用（complete(nesting(...), ... 的问题）
Using NSE enquo with dply and tidyr (issue with complete(nesting(...), ...)
我正在尝试将 NSE 与 dplyr 和 tidyr 一起使用。
我有一份产品清单，每个地区每个月的销量。产品和区域具有层次结构（ProductLevel1 比 ProductLevel2 更粗糙，比 Product Level3 更粗糙 ...）。在制作图表之前，我想使用 tidyr::nesting 和 tidyr::complete.
添加没有交易量的月份
这是在 tidyr::nesting 级别，功能似乎失败了。
f_test <- function(IS1, finerProductLevel, finerRegionLevel) {
qfinerProductLevel <- enquo(finerProductLevel)
qfinerRegionLevel <- enquo(finerRegionLevel)
IS2 <- IS1 %>%
group_by(calDate, !! qfinerRegionLevel, !! qfinerProductLevel) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup()
IS3 <- IS2 %>%
complete(nesting(!! qfinerProductLevel, !! qfinerRegionLevel),
calDate, fill = list(Vol=0))
}
f_test(IS1, ProductLevel4, RegionLevel4_18)
我收到的错误是：
Error in eval_tidy(xs[[i]], unique_output) : object 'ProductLevel4' not found
如果我把嵌套函数中的!!去掉，那么错误就是
Error: Columns `qfinerProductLevel`, `qfinerRegionLevel` must be 1d atomic vectors or lists
之前有一个类似的问题没有答案：dplyr programming: unquote-splicing causes overscope error with complete() and nesting()
数据集样本：
IS1 <- structure(list(COPASalesOffice = c("DACH", "DACH", "EMO", "EMO",
"France", "French Africa", "Israel", "Italy", "Middle East",
"Nordic", "South Hub", "South Hub", "Spain Portugal", "Spain Portugal",
"Turkey", "Turkey", "Turkey", "UK Ireland", "UK Ireland"), calDate = structure(c(16861,
17440, 16983, 17410, 16436, 16709, 16161, 16222, 17136, 16526,
16861, 16922, 16587, 17136, 16495, 16283, 16983, 16222, 16740
), class = "Date"), Vol = c(75.17, 121.731, 0, 23, 0, 15, 30,
173.36, 0, 9.217, -1, 0, 0.849, 12.154, 0, 0, 25, 1, 20.313),
RegionLevel0 = c("EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR",
"EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR",
"EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR"
), RegionLevel1 = c("Europe", "Europe", "MEAR", "MEAR", "Europe",
"MEAR", "MEAR", "Europe", "MEAR", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe"), RegionLevel2 = c("EU5-NB", "EU5-NB", "CIS", "CIS",
"EU5-NB", "MEA", "MEA", "EU5-NB", "MEA", "EU5-NB", "CEE",
"CEE", "EU5-NB", "EU5-NB", "CEE", "CEE", "CEE", "EU5-NB",
"EU5-NB"), RegionLevel4_18 = c("R01", "R01", "R20", "R20",
"R03", "R14", "R17", "R04", "R12", "R06", "R08", "R08", "R05",
"R05", "R09", "R09", "R09", "R02", "R02"), ProductLevel1 = c("aqueous",
"aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous",
"aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous",
"aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous"
), ProductLevel2 = c("aq8", "aq8", "aq8", "aq8", "aq8", "aq4",
"aq4", "aq4", "aq8", "aq8", "aq8", "aq8", "aq8", "aq8", "aq8",
"aq8", "aq4", "aq8", "aq8"), ProductLevel3 = c("8.24-44",
"8.24-44", "8.24-44", "8.24-44", "8.24-44", "4.24-44", "4.24-44",
"4.24-44", "8.A2", "8.24-44", "64in", "8.A2", "8.24-44",
"64in", "8.24-44", "8.24-44", "4.24-44", "8.24-44", "8.24-44"
), ProductLevel4 = c("T636-596-642, H&H", "T804, SC-P6/7/8/9000",
"T636-596-642, H&H", "T636-596-642, H&H", "T40X, 9000", "T692-693-694-698 Opr",
"T611-612, 74x0-94x0", "T611-612, 74x0-94x0", "T850, SCP800",
"T543-544, 40-76-9600", "T591, 11880", "T605-606, 48x0",
"T543-544, 40-76-9600", "T591, 11880", "T46X, 7000", "T602-603, 78x0-98x0",
"T692-693-694-698 Opr", "T47X, 9500", "T543-544, 40-76-9600"
)), row.names = c(NA, -19L), class = c("tbl_df", "tbl", "data.frame"
), .Names = c("COPASalesOffice", "calDate", "Vol", "RegionLevel0",
"RegionLevel1", "RegionLevel2", "RegionLevel4_18", "ProductLevel1",
"ProductLevel2", "ProductLevel3", "ProductLevel4"))
和会话信息：
Rstudio 1.1.442
R version 3.4.4 (2018-03-15)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
Matrix products: default
locale:
[1] LC_COLLATE=French_France.1252 LC_CTYPE=French_France.1252 LC_MONETARY=French_France.1252 LC_NUMERIC=C LC_TIME=French_France.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] forcats_0.3.0 stringr_1.3.0 dplyr_0.7.4 purrr_0.2.4 readr_1.1.1 tidyr_0.8.0 tibble_1.4.2 ggplot2_2.2.1 tidyverse_1.2.1
在对 f_test() 函数的调用中，您传递的第二个和第三个参数是不存在的对象的名称。您可能想引用它们，以便将它们作为字符串传递。此外，您可能希望您的 f_test() 函数成为 return 某物...我怀疑 return(IS3) 是您期望的结果。
IS1 <- structure(list(COPASalesOffice = c("DACH", "DACH", "EMO", "EMO", "France", "French Africa", "Israel", "Italy", "Middle East", "Nordic", "South Hub", "South Hub", "Spain Portugal", "Spain Portugal", "Turkey", "Turkey", "Turkey", "UK Ireland", "UK Ireland"), calDate = structure(c(16861, 17440, 16983, 17410, 16436, 16709, 16161, 16222, 17136, 16526, 16861, 16922, 16587, 17136, 16495, 16283, 16983, 16222, 16740 ), class = "Date"), Vol = c(75.17, 121.731, 0, 23, 0, 15, 30, 173.36, 0, 9.217, -1, 0, 0.849, 12.154, 0, 0, 25, 1, 20.313), RegionLevel0 = c("EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR" ), RegionLevel1 = c("Europe", "Europe", "MEAR", "MEAR", "Europe", "MEAR", "MEAR", "Europe", "MEAR", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe"), RegionLevel2 = c("EU5-NB", "EU5-NB", "CIS", "CIS", "EU5-NB", "MEA", "MEA", "EU5-NB", "MEA", "EU5-NB", "CEE", "CEE", "EU5-NB", "EU5-NB", "CEE", "CEE", "CEE", "EU5-NB", "EU5-NB"), RegionLevel4_18 = c("R01", "R01", "R20", "R20", "R03", "R14", "R17", "R04", "R12", "R06", "R08", "R08", "R05", "R05", "R09", "R09", "R09", "R02", "R02"), ProductLevel1 = c("aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous" ), ProductLevel2 = c("aq8", "aq8", "aq8", "aq8", "aq8", "aq4", "aq4", "aq4", "aq8", "aq8", "aq8", "aq8", "aq8", "aq8", "aq8", "aq8", "aq4", "aq8", "aq8"), ProductLevel3 = c("8.24-44", "8.24-44", "8.24-44", "8.24-44", "8.24-44", "4.24-44", "4.24-44", "4.24-44", "8.A2", "8.24-44", "64in", "8.A2", "8.24-44", "64in", "8.24-44", "8.24-44", "4.24-44", "8.24-44", "8.24-44" ), ProductLevel4 = c("T636-596-642, H&H", "T804, SC-P6/7/8/9000", "T636-596-642, H&H", "T636-596-642, H&H", "T40X, 9000", "T692-693-694-698 Opr", "T611-612, 74x0-94x0", "T611-612, 74x0-94x0", "T850, SCP800", "T543-544, 40-76-9600", "T591, 11880", "T605-606, 48x0", "T543-544, 40-76-9600", "T591, 11880", "T46X, 7000", "T602-603, 78x0-98x0", "T692-693-694-698 Opr", "T47X, 9500", "T543-544, 40-76-9600" )), row.names = c(NA, -19L), class = c("tbl_df", "tbl", "data.frame" ), .Names = c("COPASalesOffice", "calDate", "Vol", "RegionLevel0", "RegionLevel1", "RegionLevel2", "RegionLevel4_18", "ProductLevel1", "ProductLevel2", "ProductLevel3", "ProductLevel4"))
library(dplyr)
library(tidyr)
f_test <- function(IS1, finerProductLevel, finerRegionLevel) {
qfinerProductLevel <- enquo(finerProductLevel)
qfinerRegionLevel <- enquo(finerRegionLevel)
IS2 <- IS1 %>%
group_by(calDate, !! qfinerRegionLevel, !! qfinerProductLevel) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup()
IS3 <- IS2 %>%
complete(nesting(!! qfinerProductLevel, !! qfinerRegionLevel),
calDate, fill = list(Vol=0))
return(IS3)
}
f_test(IS1, "ProductLevel4", "RegionLevel4_18")
根据评论更新
如果您要复制类似这样的结果...
IS1 %>%
group_by(calDate, ProductLevel4, RegionLevel4_18) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup() %>%
complete(nesting(ProductLevel4, RegionLevel4_18),
calDate, fill = list(Vol=0))
使用除 "bare variable names"（不是字符串）以外的函数，像这样...
f_test(IS1, ProductLevel4, RegionLevel4_18)
那你可以这样写...
f_test <-
function(df, grp1, grp2) {
sym_grp1 <- rlang::ensym(grp1)
sym_grp2 <- rlang::ensym(grp2)
df %>%
group_by(calDate, !!sym_grp1, !!sym_grp2) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup() %>%
complete(nesting(!!sym_grp1, !!sym_grp2),
calDate, fill = list(Vol=0))
}
f_test(IS1, ProductLevel4, RegionLevel4_18)
进一步更新
您也可以使用 rlang::ensyms() 一次做 both/all 变量，然后 !!! 取消引用并拼接它们...
test <- function(data, var1, var2) {
vars <- rlang::ensyms(var1, var2)
data %>%
group_by(calDate, !!!vars) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup() %>%
complete(nesting(!!!vars), calDate, fill = list(Vol=0))
}
test(IS1, ProductLevel4, RegionLevel4_18)
这将允许您使用 ... 接受任意数量的参数...
test <- function(data, ...) {
vars <- rlang::ensyms(...)
data %>%
group_by(calDate, !!!vars) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup() %>%
complete(nesting(!!!vars), calDate, fill = list(Vol=0))
}
test(IS1, ProductLevel4, RegionLevel4_18)
test(IS1, ProductLevel4)
test(IS1, ProductLevel4, RegionLevel4_18, ProductLevel2)
我正在尝试将 NSE 与 dplyr 和 tidyr 一起使用。
我有一份产品清单，每个地区每个月的销量。产品和区域具有层次结构（ProductLevel1 比 ProductLevel2 更粗糙，比 Product Level3 更粗糙 ...）。在制作图表之前，我想使用 tidyr::nesting 和 tidyr::complete.
这是在 tidyr::nesting 级别，功能似乎失败了。
f_test <- function(IS1, finerProductLevel, finerRegionLevel) {
qfinerProductLevel <- enquo(finerProductLevel)
qfinerRegionLevel <- enquo(finerRegionLevel)
IS2 <- IS1 %>%
group_by(calDate, !! qfinerRegionLevel, !! qfinerProductLevel) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup()
IS3 <- IS2 %>%
complete(nesting(!! qfinerProductLevel, !! qfinerRegionLevel),
calDate, fill = list(Vol=0))
}
f_test(IS1, ProductLevel4, RegionLevel4_18)
我收到的错误是：
Error in eval_tidy(xs[[i]], unique_output) : object 'ProductLevel4' not found
如果我把嵌套函数中的!!去掉，那么错误就是
Error: Columns `qfinerProductLevel`, `qfinerRegionLevel` must be 1d atomic vectors or lists
之前有一个类似的问题没有答案：dplyr programming: unquote-splicing causes overscope error with complete() and nesting()
数据集样本：
IS1 <- structure(list(COPASalesOffice = c("DACH", "DACH", "EMO", "EMO",
"France", "French Africa", "Israel", "Italy", "Middle East",
"Nordic", "South Hub", "South Hub", "Spain Portugal", "Spain Portugal",
"Turkey", "Turkey", "Turkey", "UK Ireland", "UK Ireland"), calDate = structure(c(16861,
17440, 16983, 17410, 16436, 16709, 16161, 16222, 17136, 16526,
16861, 16922, 16587, 17136, 16495, 16283, 16983, 16222, 16740
), class = "Date"), Vol = c(75.17, 121.731, 0, 23, 0, 15, 30,
173.36, 0, 9.217, -1, 0, 0.849, 12.154, 0, 0, 25, 1, 20.313),
RegionLevel0 = c("EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR",
"EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR",
"EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR"
), RegionLevel1 = c("Europe", "Europe", "MEAR", "MEAR", "Europe",
"MEAR", "MEAR", "Europe", "MEAR", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe"), RegionLevel2 = c("EU5-NB", "EU5-NB", "CIS", "CIS",
"EU5-NB", "MEA", "MEA", "EU5-NB", "MEA", "EU5-NB", "CEE",
"CEE", "EU5-NB", "EU5-NB", "CEE", "CEE", "CEE", "EU5-NB",
"EU5-NB"), RegionLevel4_18 = c("R01", "R01", "R20", "R20",
"R03", "R14", "R17", "R04", "R12", "R06", "R08", "R08", "R05",
"R05", "R09", "R09", "R09", "R02", "R02"), ProductLevel1 = c("aqueous",
"aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous",
"aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous",
"aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous"
), ProductLevel2 = c("aq8", "aq8", "aq8", "aq8", "aq8", "aq4",
"aq4", "aq4", "aq8", "aq8", "aq8", "aq8", "aq8", "aq8", "aq8",
"aq8", "aq4", "aq8", "aq8"), ProductLevel3 = c("8.24-44",
"8.24-44", "8.24-44", "8.24-44", "8.24-44", "4.24-44", "4.24-44",
"4.24-44", "8.A2", "8.24-44", "64in", "8.A2", "8.24-44",
"64in", "8.24-44", "8.24-44", "4.24-44", "8.24-44", "8.24-44"
), ProductLevel4 = c("T636-596-642, H&H", "T804, SC-P6/7/8/9000",
"T636-596-642, H&H", "T636-596-642, H&H", "T40X, 9000", "T692-693-694-698 Opr",
"T611-612, 74x0-94x0", "T611-612, 74x0-94x0", "T850, SCP800",
"T543-544, 40-76-9600", "T591, 11880", "T605-606, 48x0",
"T543-544, 40-76-9600", "T591, 11880", "T46X, 7000", "T602-603, 78x0-98x0",
"T692-693-694-698 Opr", "T47X, 9500", "T543-544, 40-76-9600"
)), row.names = c(NA, -19L), class = c("tbl_df", "tbl", "data.frame"
), .Names = c("COPASalesOffice", "calDate", "Vol", "RegionLevel0",
"RegionLevel1", "RegionLevel2", "RegionLevel4_18", "ProductLevel1",
"ProductLevel2", "ProductLevel3", "ProductLevel4"))
和会话信息：
Rstudio 1.1.442
R version 3.4.4 (2018-03-15)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
Matrix products: default
locale:
[1] LC_COLLATE=French_France.1252 LC_CTYPE=French_France.1252 LC_MONETARY=French_France.1252 LC_NUMERIC=C LC_TIME=French_France.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] forcats_0.3.0 stringr_1.3.0 dplyr_0.7.4 purrr_0.2.4 readr_1.1.1 tidyr_0.8.0 tibble_1.4.2 ggplot2_2.2.1 tidyverse_1.2.1
在对 f_test() 函数的调用中，您传递的第二个和第三个参数是不存在的对象的名称。您可能想引用它们，以便将它们作为字符串传递。此外，您可能希望您的 f_test() 函数成为 return 某物...我怀疑 return(IS3) 是您期望的结果。
IS1 <- structure(list(COPASalesOffice = c("DACH", "DACH", "EMO", "EMO", "France", "French Africa", "Israel", "Italy", "Middle East", "Nordic", "South Hub", "South Hub", "Spain Portugal", "Spain Portugal", "Turkey", "Turkey", "Turkey", "UK Ireland", "UK Ireland"), calDate = structure(c(16861, 17440, 16983, 17410, 16436, 16709, 16161, 16222, 17136, 16526, 16861, 16922, 16587, 17136, 16495, 16283, 16983, 16222, 16740 ), class = "Date"), Vol = c(75.17, 121.731, 0, 23, 0, 15, 30, 173.36, 0, 9.217, -1, 0, 0.849, 12.154, 0, 0, 25, 1, 20.313), RegionLevel0 = c("EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR", "EMEAR" ), RegionLevel1 = c("Europe", "Europe", "MEAR", "MEAR", "Europe", "MEAR", "MEAR", "Europe", "MEAR", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe"), RegionLevel2 = c("EU5-NB", "EU5-NB", "CIS", "CIS", "EU5-NB", "MEA", "MEA", "EU5-NB", "MEA", "EU5-NB", "CEE", "CEE", "EU5-NB", "EU5-NB", "CEE", "CEE", "CEE", "EU5-NB", "EU5-NB"), RegionLevel4_18 = c("R01", "R01", "R20", "R20", "R03", "R14", "R17", "R04", "R12", "R06", "R08", "R08", "R05", "R05", "R09", "R09", "R09", "R02", "R02"), ProductLevel1 = c("aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous", "aqueous" ), ProductLevel2 = c("aq8", "aq8", "aq8", "aq8", "aq8", "aq4", "aq4", "aq4", "aq8", "aq8", "aq8", "aq8", "aq8", "aq8", "aq8", "aq8", "aq4", "aq8", "aq8"), ProductLevel3 = c("8.24-44", "8.24-44", "8.24-44", "8.24-44", "8.24-44", "4.24-44", "4.24-44", "4.24-44", "8.A2", "8.24-44", "64in", "8.A2", "8.24-44", "64in", "8.24-44", "8.24-44", "4.24-44", "8.24-44", "8.24-44" ), ProductLevel4 = c("T636-596-642, H&H", "T804, SC-P6/7/8/9000", "T636-596-642, H&H", "T636-596-642, H&H", "T40X, 9000", "T692-693-694-698 Opr", "T611-612, 74x0-94x0", "T611-612, 74x0-94x0", "T850, SCP800", "T543-544, 40-76-9600", "T591, 11880", "T605-606, 48x0", "T543-544, 40-76-9600", "T591, 11880", "T46X, 7000", "T602-603, 78x0-98x0", "T692-693-694-698 Opr", "T47X, 9500", "T543-544, 40-76-9600" )), row.names = c(NA, -19L), class = c("tbl_df", "tbl", "data.frame" ), .Names = c("COPASalesOffice", "calDate", "Vol", "RegionLevel0", "RegionLevel1", "RegionLevel2", "RegionLevel4_18", "ProductLevel1", "ProductLevel2", "ProductLevel3", "ProductLevel4"))
library(dplyr)
library(tidyr)
f_test <- function(IS1, finerProductLevel, finerRegionLevel) {
qfinerProductLevel <- enquo(finerProductLevel)
qfinerRegionLevel <- enquo(finerRegionLevel)
IS2 <- IS1 %>%
group_by(calDate, !! qfinerRegionLevel, !! qfinerProductLevel) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup()
IS3 <- IS2 %>%
complete(nesting(!! qfinerProductLevel, !! qfinerRegionLevel),
calDate, fill = list(Vol=0))
return(IS3)
}
f_test(IS1, "ProductLevel4", "RegionLevel4_18")
根据评论更新
如果您要复制类似这样的结果...
IS1 %>%
group_by(calDate, ProductLevel4, RegionLevel4_18) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup() %>%
complete(nesting(ProductLevel4, RegionLevel4_18),
calDate, fill = list(Vol=0))
使用除 "bare variable names"（不是字符串）以外的函数，像这样...
f_test(IS1, ProductLevel4, RegionLevel4_18)
那你可以这样写...
f_test <-
function(df, grp1, grp2) {
sym_grp1 <- rlang::ensym(grp1)
sym_grp2 <- rlang::ensym(grp2)
df %>%
group_by(calDate, !!sym_grp1, !!sym_grp2) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup() %>%
complete(nesting(!!sym_grp1, !!sym_grp2),
calDate, fill = list(Vol=0))
}
f_test(IS1, ProductLevel4, RegionLevel4_18)
进一步更新
您也可以使用 rlang::ensyms() 一次做 both/all 变量，然后 !!! 取消引用并拼接它们...
test <- function(data, var1, var2) {
vars <- rlang::ensyms(var1, var2)
data %>%
group_by(calDate, !!!vars) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup() %>%
complete(nesting(!!!vars), calDate, fill = list(Vol=0))
}
test(IS1, ProductLevel4, RegionLevel4_18)
这将允许您使用 ... 接受任意数量的参数...
test <- function(data, ...) {
vars <- rlang::ensyms(...)
data %>%
group_by(calDate, !!!vars) %>%
summarize(Vol = sum(Vol, na.rm = TRUE)) %>%
ungroup() %>%
complete(nesting(!!!vars), calDate, fill = list(Vol=0))
}
test(IS1, ProductLevel4, RegionLevel4_18)
test(IS1, ProductLevel4)
test(IS1, ProductLevel4, RegionLevel4_18, ProductLevel2)