R dplyr：在列中查找特定值，然后用该值替换右侧后续列中的相邻单元格

我正在尝试创建一个地点和事件时间的矩阵。就我而言，一旦事件发生（“1”），它就是永久性的并且不能返回到“0”。一旦列中的单元格为“1”，我将尝试用“1”填充右侧后续列中的相邻单元格（请参见下面的示例）。

site <- c('A','B','C','D','E','F','G') #site
time <- c(0,1,4,0,3,2,0) # time in which even occured
event <- c(0,1,1,0,1,1,0) # did a event occur
data <- data.frame(site, time, event)

site.time.matrix <- cast(data, site~time)

# This is the output      # This is the desired output
#site   0  1  2  3  4     #site   0  1  2  3  4
#    A  0 NA NA NA NA     #    A  0  0  0  0  0
#    B NA  1 NA NA NA     #    B  0  1  1  1  1
#    C NA NA NA NA  1     #    C  0  0  0  0  1
#    D  0 NA NA NA NA     #    D  0  0  0  0  0
#    E NA NA NA  1 NA     #    E  0  0  0  1  1
#    F NA NA  1 NA NA     #    F  0  0  1  1  1
#    G  0 NA NA NA NA     #    G  0  0  0  0  0

我发现了一些使用 dplyr 的有前途的代码，例如（使用replace函数替换多个元素 https://stackoverflow.com/questions/28250018/replacing-more-than-one-elements-with-replace-function or 将函数应用于数据框中的每一列，观察每列现有的数据类型 https://stackoverflow.com/questions/7303322/apply-function-to-each-column-in-a-data-frame-observing-each-columns-existing-da）它替换值，尽管我不确定如何在后续列参数中指定相邻单元格。

如果这个问题不清楚，我很抱歉，这是我在 StackOverflow 上的第一篇文章。

谢谢。

第一篇用户帖子详细、可重复且有趣，这是令人欣喜的惊喜，+1！

With na.locf from zoo你可以做的包：

library(reshape) # for cast function
library(zoo)    #for na.locf function short for if NA, last observation carrried forward, ?na.locf

site <- c('A','B','C','D','E','F','G') #site
time <- c(0,1,4,0,3,2,0) # time in which even occured
event <- c(0,1,1,0,1,1,0) # did a event occur
data <- data.frame(site, time, event)

site.time.matrix <- reshape::cast(data, site~time)

site.time.matrix.fill <- site.time.matrix


# Transpose the matrix excluding first column, carry forward last observation and 
# transpose again to return to original matrix structure

site.time.matrix.fill[,-1] <- t(na.locf(t(site.time.matrix.fill[,-1])))

site.time.matrix.fill[is.na( site.time.matrix.fill)] <- 0

site.time.matrix.fill

#  site 0 1 2 3 4
#1    A 0 0 0 0 0
#2    B 0 1 1 1 1
#3    C 0 0 0 0 1
#4    D 0 0 0 0 0
#5    E 0 0 0 1 1
#6    F 0 0 1 1 1
#7    G 0 0 0 0 0