[英]How to reshape a dataframe into percentage of categorical data
我有一個包含縱向信息(長格式)的數據框。
mydata<-structure(list(record_id = c("a", "a", "a", "b", "b", "b", "c", "c","c"),event = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), .Label =c("e2", "e3", "e4"), class = "factor"), var1 = structure(c(2L, 1L, 1L, 1L,1L, 1L, 1L, 1L, 1L), .Label = c("no", "yes"), class = "factor"),var2 =structure(c(1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L), .Label = c("no", "yes"), class = "factor"), var3 = structure(c(2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L),.Label = c("no", "yes"), class = "factor")), row.names = c(NA, -9L), class= c("tbl_df", "tbl", "data.frame"))
而且我需要將這些數據轉換成一個數據框,以根據事件(e2,e3,e4)總結每個變量(var1,var2,var3)的“是”計數的百分比,以具有如下所示的內容:
mydata_result<-structure(list(Event = structure(c(1L, 1L, 1L, 2L, 2L, 2L,3L, 3L, 3L), .Label = c("e2", "e3", "e4"), class = "factor"), Variable =structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), .Label = c("var1", "var2", "var3"), class = "factor"), percentage_of_yes = c(0.33, 0.33, 0.66, 0, 0.33, 0.66, 0, 0, 0)), row.names = c(NA, -9L), class = c("tbl_df", "tbl","data.frame"))
謝謝!
使用tidyverse
,我們可以轉換為長格式,按變量和事件分組,然后進行百分比計數,即
library(tidyverse)
mydata %>%
gather(var, val, -c(1:2)) %>%
group_by(event, var) %>%
summarise(new = sum(val == 'yes')/n())
這使,
# A tibble: 9 x 3 # Groups: event [?] event var new <fct> <chr> <dbl> 1 e2 var1 0.333 2 e2 var2 0.333 3 e2 var3 0.667 4 e3 var1 0 5 e3 var2 0.333 6 e3 var3 0.667 7 e4 var1 0 8 e4 var2 0 9 e4 var3 0
這是data.table
的替代data.table
library(data.table)
melt(setDT(mydata), id.vars = c("record_id", "event"))[,
.(percentage_of_yes = round(mean(value == "yes"), 3)),
.(event, Variable = variable)]
# event Variable percentage_of_yes
#1: e2 var1 0.333
#2: e3 var1 0.000
#3: e4 var1 0.000
#4: e2 var2 0.333
#5: e3 var2 0.333
#6: e4 var2 0.000
#7: e2 var3 0.667
#8: e3 var3 0.667
#9: e4 var3 0.000
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