摺疊因素和與dplyr

鑑於突變行：摺疊因素和與dplyr

x <- data.frame(Day = c(1,2,3,4,5,6,7,8,9,10), 
       var1 = c(5,4,2,3,4,5,1,2,3,4), 
       var2 = c(3,6,2,3,4,5,7,8,1,2), 
       var3 = c(1,2,3,4,6,2,4,7,8,4), 
       var4 = c(1,3,7,5,3,7,2,3,1,2))

此刻一天變量是數字，但對應於1 =星期一，5 =星期五，6 =星期一，10 =星期五。我想所有的各天坍塌在一起，並通過日平均它們的值了：

z <- data.frame(Day = c("Monday", "Tuesday", "Wednesday", "Thursday","Friday"), 
       var1 = c(5,2.5,2,3,4), 
       var2 = c(4,6.5,5,2,3), 
       var3 = c(1.5,3,5,6,5), 
       var4 = c(4,2.5,5,3,2.5))

來源

2017-10-11 D500

使用modular%%：

days = c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday") 
x %>% group_by(Day = days[(Day - 1) %% 5 + 1]) %>% summarise_all(mean) 

# A tibble: 5 x 5 
#  Day var1 var2 var3 var4 
#  <chr> <dbl> <dbl> <dbl> <dbl> 
#1 Friday 4.0 3.0 5.0 2.5 
#2 Monday 5.0 4.0 1.5 4.0 
#3 Thursday 3.0 2.0 6.0 3.0 
#4 Tuesday 2.5 6.5 3.0 2.5 
#5 Wednesday 2.0 5.0 5.0 5.0

來源

2017-10-11 18:59:04 Psidom

如果數據是有序的，通過複製天，然後用summarise_at創建分組變量得到的mean的「 VAR」列

library(dplyr) 
v1 <- c("Monday", "Tuesday", 
      "Wednesday", "Thursday","Friday") 
x %>% 
    group_by(Day = factor(rep(v1, 2), levels = v1)) %>% 
    summarise_at(vars(matches('var')), mean) 
# A tibble: 5 x 5 
#  Day var1 var2 var3 var4 
#  <chr> <dbl> <dbl> <dbl> <dbl> 
# 1 Monday 5.0 4.0 1.5 4.0 
# 2 Tuesday 2.5 6.5 3.0 2.5 
# 3 Wednesday 2.0 5.0 5.0 5.0 
# 4 Thursday 3.0 2.0 6.0 3.0 
# 5 Friday 4.0 3.0 5.0 2.5

如果數據沒有排序，然後創建一個鍵/值數據集，與原始數據集的加入，由分組後‘天’，得到mean如上

x1 <- data.frame(Day = 1:10, DayC = c("Monday", "Tuesday", 
     "Wednesday", "Thursday","Friday"), stringsAsFactors= FALSE) 

x %>% 
    left_join(., x1) %>% 
    group_by(Day = DayC) %>% 
    summarise_at(vars(matches('var')), mean) %>% 
    arrange(factor(Day, levels = v1))

來源

2017-10-11 18:50:54 akrun

摺疊因素和與dplyr

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