如何填充数据直到最后一个非缺失值? [英] How do I fill data until last non-missing value?

问题描述

我有一些数据按let分组:

I have some data grouped by let like so:

events <- structure(list(let = c("A", "A", "A", "B", "B", "B"), age = c(0L, 
4L, 16L, 0L, 8L, 7L), value = c(61L, 60L, 13L, 29L, 56L, 99L)),
class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6"))

  let age value
1   A   0    61
2   A   4    60
3   A  16    13
4   B   0    29
5   B   8    56
6   B   7    99

我该如何投射数据框，以便:

How can I cast the data frame so that:

1. 年龄是分为几周的多列.因此，对于每一列，取小于或等于0、7、14等天的最大年龄的值
2. 直到let填满最后一个非缺失值.

1. Age is multiple columns grouped into weeks. So for each column, take the value of the largest age that is less than or equal to 0, 7, 14, etc. days
2. Fill in age UNTIL the last non-missing value by let.

最终结果如下:

    events.cast <- data.frame(
 let = LETTERS[1:2],
  T0_value = c(61,29),
  T1_value = c(60,99),
  T2_value = c(60,56),
  T3_value = c(13,56))

 let T0_value T1_value T2_value T3_value
1   A       61       60       60       13
2   B       29       99       56       NA

请注意，这来自上一个问题我问.

推荐答案

我们可以在complete之前创建一个'actuals'列，并根据发生的情况使用它在'value'列中创建NA NA在事实"中

We could create a column of 'actuals' before the complete and use that to create the NA in 'value' column based on the occurrence of NA in 'actuals'

library(dplyr)
library(tidyr)
library(stringr)
events %>% 
    group_by(grp = cut(age, breaks = c(-Inf,0, 7, 14, 21),
        labels = str_c("T", 0:3, "_value")), let) %>% 
    slice(which.max(value)) %>%
    ungroup %>%
    select(-age) %>% 
    mutate(actuals = TRUE) %>%  
    group_by(let) %>% 
    complete(grp = unique(.$grp)) %>% 
    fill(value) %>%
    ungroup %>%
    mutate(i1 = cumsum(is.na(actuals)), 
           value = replace(value, i1 == max(i1), NA)) %>%
    select(-i1, -actuals) %>%
    pivot_wider(names_from = grp, values_from = value)
# A tibble: 2 x 5
#  let   T0_value T1_value T2_value T3_value
#  <chr>    <int>    <int>    <int>    <int>
#1 A           61       60       60       13
#2 B           29       99       56       NA

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