问题描述
我有 300 万行的 df。我想按 member_casual 分组，将日期转换为星期几，并获得按成员分组的一周中每一天的观察计数（频率）。
member_casual date
member 11/12/2021
member 11/13/2021
casual 10/15/2021
member 9/3/2021
casual 6/23/2021
... ...
member Sunday 114999
Monday 145987
Tuesday 89433
...
casual Sunday 18448
Monday 111748
...
我可以在一个 df/table 中获取个人、成员或临时用户，但不能包含一个组。
df_daym <- filter( df,member_casual == "member" )
df_daym <- count( weekdays((as.Date(df_daym$started_at))))
df_daym
只为会员制作这个
x. freq
Friday 307671
Monday 268096
Saturday 324283
Sunday 266256
Thursday 301321
Tuesday 285632
Wednesday 306113
解决方法
您可以使用 lubridate 中的 wday 获取工作日，然后使用 dplyr 中的 group by 和 summarise 获取其余部分。
library(dplyr)
library(lubridate)
df %>%
mutate(weekday = wday(date,label = TRUE,abbr = FALSE) %>%
group_by(weekday,member_casual) %>%
summarise(n = n())
强烈建议在这种情况下使用 janitor::tabyl()。试试这个
df %>% mutate(weekday = weekdays(date)) %>% tabyl(weekday,member_casual)
检查虚拟数据
set.seed(123)
df <- data.frame(member_casual = sample(c('member','casual'),1000,T),date = as.Date('2010-01-01') + sample(1:10000,1000))
library(janitor)
df %>% mutate(weekday = weekdays(date)) %>% tabyl(weekday,member_casual)
weekday casual member
Friday 64 66
Monday 76 81
Saturday 82 79
Sunday 61 69
Thursday 77 57
Tuesday 59 71
Wednesday 75 83
将日期更改为“Date”类，使用 cake_id flour_g butter_g sugar_g salt_g eggs_count bakingpowder_g milk_ml water_ml vanillaextract_ml lemonzest_g mixingtime_min bakingtime_min preheattime_min coolingtime_min bakingtemp_c preheattemp_c color_red color_green color_blue traysize_small traysize_medium traysize_large milktype_lowfat milktype_skim milktype_whole trayshape caketaste
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198 170 80 500 6 3 2 25 50 1 1 5 60 20 15 175 150 1 0 0 1 0 0 0 1 0 square 2
199 180 50 600 4 4 4 15 80 1 1 5 50 20 15 170 170 1 0 0 1 0 0 0 1 0 rectangle 2
获取星期几并使用 weekdays 获取计数。
table