我的数据涉及一家公司，包括总销售额以及CA，TX和WI三个县的销售额。
资料：
> dput(head(WalData))
structure(list(CA = c(11047, 9925, 11322, 12251, 16610, 14696
), TX = c(7381, 5912, 9006, 6226, 9440, 9376), WI = c(6984, 3309,
8883, 9533, 11882, 8664), Total = c(25412, 19146, 29211, 28010,
37932, 32736), date = structure(c(1296518400, 1296604800, 1296691200,
1296777600, 1296864000, 1296950400), tzone = "UTC", class = c("POSIXct",
"POSIXt")), event_type = c("NA", "NA", "NA", "NA", "NA", "Sporting"
), snap_CA = c(1, 1, 1, 1, 1, 1), snap_TX = c(1, 0, 1, 0, 1,
1), snap_WI = c(0, 1, 1, 0, 1, 1)), row.names = c(NA, -6L), class = c("tbl_df",
"tbl", "data.frame"))
我尝试使用以下代码来计算三个州在公司总销售额中的平均销售份额。
另外，我需要每年，每年的月份和一周中的同一天的平均百分比。
install.packages("dplyr")
install.packages("lubridate")
library(dplyr)
library(lubridate)
df1 <- df %>%
dplyr::mutate(YEAR = lubridate::year(date),
MONTH = lubridate::month(date),
WEEKDAY = lubridate::wday(date),
P_CA = CA / Total,
P_TX = TX / Total,
P_WI = WI / Total)
# Average per Year
df1 %>%
dplyr::group_by(YEAR) %>%
dplyr::summarise(AV_CA = mean(P_CA, na.rm = TRUE),
AV_TX = mean(P_TX, na.rm = TRUE),
AV_WI = mean(P_WI, na.rm = TRUE))
# Average per Month
df1 %>%
dplyr::group_by(MONTH) %>%
dplyr::summarise(AV_CA = mean(P_CA, na.rm = TRUE),
AV_TX = mean(P_TX, na.rm = TRUE),
AV_WI = mean(P_WI, na.rm = TRUE))
# Average per Weekday
df1 %>%
dplyr::group_by(WEEKDAY) %>%
dplyr::summarise(AV_CA = mean(P_CA, na.rm = TRUE),
AV_TX = mean(P_TX, na.rm = TRUE),
AV_WI = mean(P_WI, na.rm = TRUE))
输出：
> df1 <- df %>%
+ dplyr::mutate(YEAR = lubridate::year(date),
+ MONTH = lubridate::month(date),
+ WEEKDAY = lubridate::wday(date),
+ P_CA = CA / Total,
+ P_TX = TX / Total,
+ P_WI = WI / Total)
Error in UseMethod("mutate_") :
no applicable method for 'mutate_' applied to an object of class "function"
> # Average per Year
> df1 %>%
+ dplyr::group_by(YEAR) %>%
+ dplyr::summarise(AV_CA = mean(P_CA, na.rm = TRUE),
+ AV_TX = mean(P_TX, na.rm = TRUE),
+ AV_WI = mean(P_WI, na.rm = TRUE))
Error in eval(lhs, parent, parent) : object 'df1' not found
它带有错误：UseMethod（“ mutate_”）中的错误：'mutate_'的适用方法不适用于类“ function”的对象
我不知道出什么问题了，我仔细检查了代码和数据的正确性。请给出一个解决方案。
问题是，df不会在全局环境中将其创建为对象，并且df如果我们这样做，则会有一个带有名称的函数?df
df（x，df1，df2，ncp，log = FALSE）
基本上，错误是基于应用mutate函数df而不是对象
检查R没有创建对象的新会话
df %>%
dplyr::mutate(YEAR = lubridate::year(date),
MONTH = lubridate::month(date),
WEEKDAY = lubridate::wday(date),
P_CA = CA / Total,
P_TX = TX / Total,
P_WI = WI / Total)
UseMethod（“ mutate_”）中的错误：没有适用于“ mutate_”的适用方法应用于“功能”类的对象
现在，我们将“ df”定义为
df <- WalData
df %>%
dplyr::mutate(YEAR = lubridate::year(date),
MONTH = lubridate::month(date),
WEEKDAY = lubridate::wday(date),
P_CA = CA / Total,
P_TX = TX / Total,
P_WI = WI / Total)
# A tibble: 6 x 15
# CA TX WI Total date event_type snap_CA snap_TX snap_WI YEAR MONTH WEEKDAY P_CA P_TX P_WI
# <dbl> <dbl> <dbl> <dbl> <dttm> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#1 11047 7381 6984 25412 2011-02-01 00:00:00 NA 1 1 0 2011 2 3 0.435 0.290 0.275
#2 9925 5912 3309 19146 2011-02-02 00:00:00 NA 1 0 1 2011 2 4 0.518 0.309 0.173
#3 11322 9006 8883 29211 2011-02-03 00:00:00 NA 1 1 1 2011 2 5 0.388 0.308 0.304
#4 12251 6226 9533 28010 2011-02-04 00:00:00 NA 1 0 0 2011 2 6 0.437 0.222 0.340
#5 16610 9440 11882 37932 2011-02-05 00:00:00 NA 1 1 1 2011 2 7 0.438 0.249 0.313
#6 14696 9376 8664 32736 2011-02-06 00:00:00 Sporting 1 1 1 2011 2 1 0.449 0.286 0.265
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