我試圖在兩個月之間創建一個平均生產力的轉化函式，但我總是以某種方式把它搞砸。不確定是我的數學不好還是 dplyr 使用不當。這是腳本，包括 dput：
##################################################
# Productivity Script for Stack #
##################################################
# Loading Data:
work <- structure(list(Case_Number = 30:40, Year = c("2021", "2021",
"2021", "2021", "2021", "2021", "2021", "2021", "2021", "2021",
"2021"), Month_Number = c("9", "9", "9", "9", "10", "10", "10",
"10", "10", "10", "10"), Month_Name = c("September", "September",
"September", "September", "October", "October", "October", "October",
"October", "October", "October"), Day_Number = c(27L, 28L, 29L,
30L, 1L, 2L, 3L, 4L, 5L, 6L, 7L), Day_Name = c("Monday", "Tuesday",
"Wednesday", "Thursday", "Friday", "Saturday", "Sunday", "Monday",
"Tuesday", "Wednesday", "Thursday"), Time_Wake = c(600L, 730L,
650L, 830L, 630L, 630L, 830L, 722L, 641L, 800L, 720L), Start_Work = c(950L,
1108L, 1430L, 955L, 1313L, 1125L, 1636L, 1126L, 1027L, 1323L,
1003L), End_Work = c(1504L, 1430L, 1933L, 1335L, 1330L, 2130L,
1636L, 1600L, 1730L, 1800L, 1739L), Mins_Sleep = c(310L, 390L,
350L, 450L, 390L, 390L, 510L, 452L, 310L, 360L, 500L), Workout_Y_N = c("Y",
"N", "N", "N", "N", "Y", "Y", "Y", "N", "Y", "Y"), Workout_Before_After = c("Before",
NA, NA, NA, NA, "Before", "Before", "Before", NA, "Before", "Before"
), Time_Workout = c(730L, NA, NA, NA, NA, 915L, 1000L, 815L,
NA, 900L, 740L), Work_Environment = c("Office", "Office", "Office",
"Office", "Home", "Home", "Home", "Office", "Office", "Office",
"Office"), Coffee_Cups = c(0L, 0L, 0L, 2L, 0L, 1L, 2L, 3L, 2L,
2L, 4L), Tea_Cups = c(4L, 4L, 4L, 2L, 1L, 0L, 2L, 0L, 0L, 4L,
2L), Mins_Work = c(266L, 196L, 198L, 220L, 17L, 382L, 0L, 180L,
343L, 207L, 263L), Weather = c(NA, NA, "Sunny", "Sunny", NA,
NA, NA, NA, NA, NA, NA)), class = "data.frame", row.names = c(NA,
-11L))
# Calculate Productivity Growth:
september_work <- work %>%
filter(Month_Name=="September") %>%
summarize(September_Mins = (sum(Mins_Work))) # calcs sep work
october_work <- work %>%
filter(Month_Name == "October") %>%
summarize(October_Mins = (sum(Mins_Work, na.rm = T))) # calcs oct work
work_growth <- ((october_work - september_work) / september_work) # calc growth
work_growth # gives percentage of productivity growth
# Create average of work between October and September:
work %>%
transmute(avg_month_work = sum(september_work october_work)/2)
uj5u.com熱心網友回復：
這是一個多合一的，應該可以使用多個月/年。它提供連續月份和累計月平均值之間的滾動百分比差異
work %>%
#get sums by month
group_by(Month_Name, Month_Number, Year) %>%
summarize(monthly_mins = sum(Mins_Work)) %>%
#put in order
mutate(Month_Number = as.numeric(Month_Number),
counter = 1) %>%
arrange(Year, Month_Number) %>%
ungroup() %>%
#set up rolling pct change calc and cumulative average
transmute(
Year,
Month_Name,
pct_change = (monthly_mins / lag(monthly_mins) - 1) * 100,
avg_month_work = cumsum(monthly_mins) / cumsum(counter)
)
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