如何根据 R 中的分组依据将单独的列值添加到另一列？
How to add seperate column values to another column based on group by in R?
我有一个名为“DF1”的数据table（结构如下）：
# A tibble: 10 x 4
# Groups: Month [1]
Response.Status UNSUBSCRIBE Month Year
<fct> <fct> <fct> <chr>
1 SURVEY_OPENED NA Nov 2020
2 NOT_RESPONDED TRUE Nov 2020
3 EMAIL_OPENED NA Nov 2020
4 NOT_RESPONDED NA Nov 2020
5 NOT_RESPONDED TRUE Nov 2020
6 EMAIL_OPENED NA Nov 2020
7 NOT_RESPONDED TRUE Nov 2020
8 EMAIL_OPENED NA Nov 2020
9 SURVEY_OPENED TRUE Nov 2020
10 EMAIL_OPENED NA Nov 2020
structure(list(Response.Status = structure(c(5L, 2L, 1L, 2L,
2L, 1L), .Label = c("EMAIL_OPENED", "NOT_RESPONDED", "PARTIALLY_SAVED",
"SUBMITTED", "SURVEY_OPENED", "UNDELIVERED_OR_BOUNCED"), class = "factor"),
UNSUBSCRIBE = structure(c(NA_integer_, TRUE, NA_integer_,
TRUE, NA_integer_, TRUE), .Label = "TRUE", class = "factor"),
Month = c("Nov", "Nov", "Nov", "Nov", "Nov", "Nov"), Year = c("2020",
"2020", "2020", "2020", "2020", "2020")), row.names = c(NA,
-6L), groups = structure(list(Month = "Nov", .rows = structure(list(
1:6), ptype = integer(0), class = c("vctrs_list_of", "vctrs_vctr",
"list"))), row.names = 1L, class = c("tbl_df", "tbl", "data.frame"
), .drop = TRUE), class = c("grouped_df", "tbl_df", "tbl", "data.frame"
))
我转换这个 table 是为了计算每月总金额“Response.Status”，下面的 table 称为“Updated_DF”：
Updated_DF <- DF1 %>%
mutate(Month = format(as.Date(date, format = "%Y/%m/%d"), "%m/%Y")) %>%
group_by(Month, Response.Status) %>%
summarise(sum = n()) %>%
pivot_wider(names_from = Month, values_from = sum)
# A tibble: 6 x 16
Response.Status `01/2020` `02/2020` `03/2020` `04/2020` `05/2020` `06/2020` `07/2020` `08/2020` `09/2019` `09/2020` `10/2019` `10/2020` `11/2019` `11/2020` `12/2019`
<fct> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
1 EMAIL_OPENED 1090 3123 4087 5005 2098 1876 4278 3665 901 4162 883 2597 1187 690 883
2 NOT_RESPONDED 3205 9733 13177 15255 5470 4788 12708 10731 2835 15088 2846 8094 3665 1938 2667
3 PARTIALLY_SAVED 5 34 56 8 28 22 73 86 11 14 7 23 8 8 2
4 SUBMITTED 216 557 838 828 357 310 654 621 214 1001 233 497 264 122 194
5 SURVEY_OPENED 164 395 597 1016 245 212 513 625 110 588 123 349 202 94 120
6 UNDELIVERED_OR_BOUNCED 92 280 318 260 109 127 319 321 63 445 69 192 93 39 74
“Updated_DF”的数据结构：
structure(list(Response.Status = structure(1:6, .Label = c("EMAIL_OPENED",
"NOT_RESPONDED", "PARTIALLY_SAVED", "SUBMITTED", "SURVEY_OPENED",
"UNDELIVERED_OR_BOUNCED"), class = "factor"), `01/2020` = c(1090L,
3205L, 5L, 216L, 164L, 92L), `02/2020` = c(3123L, 9733L, 34L,
557L, 395L, 280L), `03/2020` = c(4087L, 13177L, 56L, 838L, 597L,
318L), `04/2020` = c(5005L, 15255L, 8L, 828L, 1016L, 260L), `05/2020` = c(2098L,
5470L, 28L, 357L, 245L, 109L), `06/2020` = c(1876L, 4788L, 22L,
310L, 212L, 127L), `07/2020` = c(4278L, 12708L, 73L, 654L, 513L,
319L), `08/2020` = c(3665L, 10731L, 86L, 621L, 625L, 321L), `09/2019` = c(901L,
2835L, 11L, 214L, 110L, 63L), `09/2020` = c(4162L, 15088L, 14L,
1001L, 588L, 445L), `10/2019` = c(883L, 2846L, 7L, 233L, 123L,
69L), `10/2020` = c(2597L, 8094L, 23L, 497L, 349L, 192L), `11/2019` = c(1187L,
3665L, 8L, 264L, 202L, 93L), `11/2020` = c(690L, 1938L, 8L, 122L,
94L, 39L), `12/2019` = c(883L, 2667L, 2L, 194L, 120L, 74L)), row.names = c(NA,
-6L), class = c("tbl_df", "tbl", "data.frame"))
我想做的是将 DF1 中的“UNSUBSCRIBE”字段添加到我的转置过程中，以便 Response.Status 包含每个月“UNSUBSCRIBE”的总和 TRUE 值——即使它是一个单独的列。
我完全不知道如何做到这一点 - 我最终计划使用格式table并为此添加颜色主题。
预期输出：
Response.Status `01/2020` `02/2020` `03/2020` `04/2020` `05/2020` `06/2020` `07/2020` `08/2020` `09/2019` `09/2020` `10/2019` `10/2020` `11/2019` `11/2020` `12/2019`
<fct> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
1 EMAIL_OPENED 1090 3123 4087 5005 2098 1876 4278 3665 901 4162 883 2597 1187 690 883
2 NOT_RESPONDED 3205 9733 13177 15255 5470 4788 12708 10731 2835 15088 2846 8094 3665 1938 2667
3 PARTIALLY_SAVED 5 34 56 8 28 22 73 86 11 14 7 23 8 8 2
4 SUBMITTED 216 557 838 828 357 310 654 621 214 1001 233 497 264 122 194
5 SURVEY_OPENED 164 395 597 1016 245 212 513 625 110 588 123 349 202 94 120
6 UNDELIVERED_OR_BOUNCED 92 280 318 260 109 127 319 321 63 445 69 192 93 39 74
7 UNSUBSCRIBE 92 280 318 260 109 127 319 321 63 445 69 192 93 39 74
这是您要找的吗？
library(dplyr)
library(tidyr)
DF1 %>%
mutate(UNSUBSCRIBE = if_else(UNSUBSCRIBE == "TRUE", "UNSUBSCRIBE", NA_character_)) %>%
pivot_longer(c(Response.Status, UNSUBSCRIBE), values_to = "Response.Status") %>%
drop_na() %>%
count(Month, Year, Response.Status) %>%
pivot_wider(names_from = c("Month", "Year"), names_sep = "/", values_from = n)
输出
# A tibble: 4 x 2
Response.Status `Nov/2020`
<chr> <int>
1 EMAIL_OPENED 2
2 NOT_RESPONDED 3
3 SURVEY_OPENED 1
4 UNSUBSCRIBE 3
我有一个名为“DF1”的数据table（结构如下）：
# A tibble: 10 x 4
# Groups: Month [1]
Response.Status UNSUBSCRIBE Month Year
<fct> <fct> <fct> <chr>
1 SURVEY_OPENED NA Nov 2020
2 NOT_RESPONDED TRUE Nov 2020
3 EMAIL_OPENED NA Nov 2020
4 NOT_RESPONDED NA Nov 2020
5 NOT_RESPONDED TRUE Nov 2020
6 EMAIL_OPENED NA Nov 2020
7 NOT_RESPONDED TRUE Nov 2020
8 EMAIL_OPENED NA Nov 2020
9 SURVEY_OPENED TRUE Nov 2020
10 EMAIL_OPENED NA Nov 2020
structure(list(Response.Status = structure(c(5L, 2L, 1L, 2L,
2L, 1L), .Label = c("EMAIL_OPENED", "NOT_RESPONDED", "PARTIALLY_SAVED",
"SUBMITTED", "SURVEY_OPENED", "UNDELIVERED_OR_BOUNCED"), class = "factor"),
UNSUBSCRIBE = structure(c(NA_integer_, TRUE, NA_integer_,
TRUE, NA_integer_, TRUE), .Label = "TRUE", class = "factor"),
Month = c("Nov", "Nov", "Nov", "Nov", "Nov", "Nov"), Year = c("2020",
"2020", "2020", "2020", "2020", "2020")), row.names = c(NA,
-6L), groups = structure(list(Month = "Nov", .rows = structure(list(
1:6), ptype = integer(0), class = c("vctrs_list_of", "vctrs_vctr",
"list"))), row.names = 1L, class = c("tbl_df", "tbl", "data.frame"
), .drop = TRUE), class = c("grouped_df", "tbl_df", "tbl", "data.frame"
))
我转换这个 table 是为了计算每月总金额“Response.Status”，下面的 table 称为“Updated_DF”：
Updated_DF <- DF1 %>%
mutate(Month = format(as.Date(date, format = "%Y/%m/%d"), "%m/%Y")) %>%
group_by(Month, Response.Status) %>%
summarise(sum = n()) %>%
pivot_wider(names_from = Month, values_from = sum)
# A tibble: 6 x 16
Response.Status `01/2020` `02/2020` `03/2020` `04/2020` `05/2020` `06/2020` `07/2020` `08/2020` `09/2019` `09/2020` `10/2019` `10/2020` `11/2019` `11/2020` `12/2019`
<fct> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
1 EMAIL_OPENED 1090 3123 4087 5005 2098 1876 4278 3665 901 4162 883 2597 1187 690 883
2 NOT_RESPONDED 3205 9733 13177 15255 5470 4788 12708 10731 2835 15088 2846 8094 3665 1938 2667
3 PARTIALLY_SAVED 5 34 56 8 28 22 73 86 11 14 7 23 8 8 2
4 SUBMITTED 216 557 838 828 357 310 654 621 214 1001 233 497 264 122 194
5 SURVEY_OPENED 164 395 597 1016 245 212 513 625 110 588 123 349 202 94 120
6 UNDELIVERED_OR_BOUNCED 92 280 318 260 109 127 319 321 63 445 69 192 93 39 74
“Updated_DF”的数据结构：
structure(list(Response.Status = structure(1:6, .Label = c("EMAIL_OPENED",
"NOT_RESPONDED", "PARTIALLY_SAVED", "SUBMITTED", "SURVEY_OPENED",
"UNDELIVERED_OR_BOUNCED"), class = "factor"), `01/2020` = c(1090L,
3205L, 5L, 216L, 164L, 92L), `02/2020` = c(3123L, 9733L, 34L,
557L, 395L, 280L), `03/2020` = c(4087L, 13177L, 56L, 838L, 597L,
318L), `04/2020` = c(5005L, 15255L, 8L, 828L, 1016L, 260L), `05/2020` = c(2098L,
5470L, 28L, 357L, 245L, 109L), `06/2020` = c(1876L, 4788L, 22L,
310L, 212L, 127L), `07/2020` = c(4278L, 12708L, 73L, 654L, 513L,
319L), `08/2020` = c(3665L, 10731L, 86L, 621L, 625L, 321L), `09/2019` = c(901L,
2835L, 11L, 214L, 110L, 63L), `09/2020` = c(4162L, 15088L, 14L,
1001L, 588L, 445L), `10/2019` = c(883L, 2846L, 7L, 233L, 123L,
69L), `10/2020` = c(2597L, 8094L, 23L, 497L, 349L, 192L), `11/2019` = c(1187L,
3665L, 8L, 264L, 202L, 93L), `11/2020` = c(690L, 1938L, 8L, 122L,
94L, 39L), `12/2019` = c(883L, 2667L, 2L, 194L, 120L, 74L)), row.names = c(NA,
-6L), class = c("tbl_df", "tbl", "data.frame"))
我想做的是将 DF1 中的“UNSUBSCRIBE”字段添加到我的转置过程中，以便 Response.Status 包含每个月“UNSUBSCRIBE”的总和 TRUE 值——即使它是一个单独的列。
我完全不知道如何做到这一点 - 我最终计划使用格式table并为此添加颜色主题。
预期输出：
Response.Status `01/2020` `02/2020` `03/2020` `04/2020` `05/2020` `06/2020` `07/2020` `08/2020` `09/2019` `09/2020` `10/2019` `10/2020` `11/2019` `11/2020` `12/2019`
<fct> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
1 EMAIL_OPENED 1090 3123 4087 5005 2098 1876 4278 3665 901 4162 883 2597 1187 690 883
2 NOT_RESPONDED 3205 9733 13177 15255 5470 4788 12708 10731 2835 15088 2846 8094 3665 1938 2667
3 PARTIALLY_SAVED 5 34 56 8 28 22 73 86 11 14 7 23 8 8 2
4 SUBMITTED 216 557 838 828 357 310 654 621 214 1001 233 497 264 122 194
5 SURVEY_OPENED 164 395 597 1016 245 212 513 625 110 588 123 349 202 94 120
6 UNDELIVERED_OR_BOUNCED 92 280 318 260 109 127 319 321 63 445 69 192 93 39 74
7 UNSUBSCRIBE 92 280 318 260 109 127 319 321 63 445 69 192 93 39 74
这是您要找的吗？
library(dplyr)
library(tidyr)
DF1 %>%
mutate(UNSUBSCRIBE = if_else(UNSUBSCRIBE == "TRUE", "UNSUBSCRIBE", NA_character_)) %>%
pivot_longer(c(Response.Status, UNSUBSCRIBE), values_to = "Response.Status") %>%
drop_na() %>%
count(Month, Year, Response.Status) %>%
pivot_wider(names_from = c("Month", "Year"), names_sep = "/", values_from = n)
输出
# A tibble: 4 x 2
Response.Status `Nov/2020`
<chr> <int>
1 EMAIL_OPENED 2
2 NOT_RESPONDED 3
3 SURVEY_OPENED 1
4 UNSUBSCRIBE 3