英文:
Replace value on specific column if condition is met
问题
我有一个名为wide df的数据框，其中columns代表了许多给定years中每个month的颜色变化：
df <- data.frame(id = as.integer(c(123,124,125,126)),
change = as.integer(c(0,1,0,1)),
change_date = as.character(c(NA, "May.2010", NA, "Sep.2010")),
`Jan.2010` = as.character(c("green", "black", "pink", "grey")),
`Feb.2010` = as.character(c("green", "black", "pink", "grey")),
`Mar.2010` = as.character(c("green", "red", "pink", "grey")),
`Apr.2010` = as.character(c("green", "red", "pink", "grey")),
`May.2010` = as.character(c("green", "red", "pink", "grey")),
`Jun.2010` = as.character(c("green", NA, "pink", "grey")),
`Jul.2010` = as.character(c("green", NA, "pink", "grey")),
`Ago.2010` = as.character(c("red", NA, "pink", "grey")),
`Sep.2010` = as.character(c("red", NA, "pink", "grey")),
`Oct.2010` = as.character(c("red", NA, "pink", NA)),
`Nov.2010` = as.character(c("red", NA, "pink", NA)),
`Dez.2010` = as.character(c("red", NA, "grey", NA))
)
df
如果发生变化（change == 1），我希望发生变化的相应列month.year接收值"CHANGE"：
id change change_date Jan.2010 Feb.2010 Mar.2010 Apr.2010 May.2010 Jun.2010 Jul.2010 Ago.2010 Sep.2010 Oct.2010 Nov.2010 Dez.2010
1 123 0 <NA> green green green green green green green red red red red red
2 124 1 May.2010 black black red red CHANGE <NA> <NA> <NA> <NA> <NA> <NA> <NA>
3 125 0 <NA> pink pink pink pink pink pink pink pink pink pink pink grey
4 126 1 Sep.2010 grey grey grey grey grey grey grey grey CHANGE <NA> <NA> <NA>
我尝试过的解决方案都以不同的方式失败了。感谢您的帮助。
英文:
I have a wide df with columns representing the months of many given years and the changes of colour in each month:
df <- data.frame(id = as.integer(c(123,124,125,126)),
change = as.integer(c(0,1,0,1)),
change_date = as.character(c(NA, "May.2010", NA, "Sep.2010")),
`Jan.2010` = as.character(c("green", "black", "pink", "grey")),
`Feb.2010` = as.character(c("green", "black", "pink", "grey")),
`Mar.2010` = as.character(c("green", "red", "pink", "grey")),
`Apr.2010` = as.character(c("green", "red", "pink", "grey")),
`May.2010` = as.character(c("green", "red", "pink", "grey")),
`Jun.2010` = as.character(c("green", NA, "pink", "grey")),
`Jul.2010` = as.character(c("green", NA, "pink", "grey")),
`Ago.2010` = as.character(c("red", NA, "pink", "grey")),
`Sep.2010` = as.character(c("red", NA, "pink", "grey")),
`Oct.2010` = as.character(c("red", NA, "pink", NA)),
`Nov.2010` = as.character(c("red", NA, "pink", NA)),
`Dez.2010` = as.character(c("red", NA, "grey", NA))
)
df
id change change_date Jan.2010 Feb.2010 Mar.2010 Apr.2010 May.2010 Jun.2010 Jul.2010 Ago.2010 Sep.2010 Oct.2010 Nov.2010 Dez.2010
1 123 0 <NA> green green green green green green green red red red red red
2 124 1 May.2010 black black red red red <NA> <NA> <NA> <NA> <NA> <NA> <NA>
3 125 0 <NA> pink pink pink pink pink pink pink pink pink pink pink grey
4 126 1 Sep.2010 grey grey grey grey grey grey grey grey grey <NA> <NA> <NA>
If a change occurs (change == 1), I want the correspondent column month.year in which the change occurs to receive the value "CHANGE":
id change change_date Jan.2010 Feb.2010 Mar.2010 Apr.2010 May.2010 Jun.2010 Jul.2010 Ago.2010 Sep.2010 Oct.2010 Nov.2010 Dez.2010
1 123 0 <NA> green green green green green green green red red red red red
2 124 1 May.2010 black black red red CHANGE <NA> <NA> <NA> <NA> <NA> <NA> <NA>
3 125 0 <NA> pink pink pink pink pink pink pink pink pink pink pink grey
4 126 1 Sep.2010 grey grey grey grey grey grey grey grey CHANGE <NA> <NA> <NA>
The solutions I've tried failed in different ways. I appreciate your help on this.
答案1
得分: 3
在基本的R语言中，您可以这样做：
# 找出需要更改的行和对应的列
with(df,
data.frame(
index = which(change == 1),
column = change_date[change == 1]
)
) -> to_change
# 使用该对象在循环中进行所有更改
for(i in seq_along(to_change$index)){
df[to_change$index[i], to_change$column[i]] = "CHANGE"
}
请注意，这是代码示例，不是完整的句子或段落。
英文:
In base R, you can do it like this:
# Work out which rows need changed, and which corresponding column
with(df,
data.frame(
index = which(change == 1),
column = change_date[change == 1]
)
) -> to_change
# Use that object to make all the changes in a loop
for(i in seq_along(to_change$index)){
df[to_change$index[i], to_change$column[i]] = "CHANGE"
}
答案2
得分: 3
这是基于R语言的向量化方法 -
# 行号
row <- which(df$change == 1)
# 列号
col <- match(df$change_date[row], names(df))
# 创建一个包含行/列索引以更改值的矩阵
df[cbind(row, col)] <- "CHANGE"
df
# id change change_date Jan.2010 Feb.2010 Mar.2010 Apr.2010 May.2010
#1 123 0 <NA> green green green green green
#2 124 1 May.2010 black black red red CHANGE
#3 125 0 <NA> pink pink pink pink pink
#4 126 1 Sep.2010 grey grey grey grey grey
# Jun.2010 Jul.2010 Ago.2010 Sep.2010 Oct.2010 Nov.2010 Dez.2010
#1 green green red red red red red
#2 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#3 pink pink pink pink pink pink grey
#4 grey grey grey CHANGE <NA> <NA> <NA>
英文:
Here is vectorised base R way -
# Row numbers
row <- which(df$change == 1)
# Column numbers
col <- match(df$change_date[row], names(df))
# Create a matrix of row/column index to change the values
df[cbind(row, col)] <- "CHANGE"
df
# id change change_date Jan.2010 Feb.2010 Mar.2010 Apr.2010 May.2010
#1 123 0 <NA> green green green green green
#2 124 1 May.2010 black black red red CHANGE
#3 125 0 <NA> pink pink pink pink pink
#4 126 1 Sep.2010 grey grey grey grey grey
# Jun.2010 Jul.2010 Ago.2010 Sep.2010 Oct.2010 Nov.2010 Dez.2010
#1 green green red red red red red
#2 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#3 pink pink pink pink pink pink grey
#4 grey grey grey CHANGE <NA> <NA> <NA>
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