如何解决使用收集时尝试维护索引
我正在尝试将我的数据从宽转换为长，但是由于某种原因，ID列没有 转换后显示。这是我的数据：
> head(dca)
# A tibble: 6 x 11
ResponseId Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 "Response … "Regardi… "Regardi… "Regardi… "Regardi… "Regardi… "Regardi… "Regard… "Regard… "Regard… "Regard…
2 "{\"Import… "{\"Impo… "{\"Impo… "{\"Impo… "{\"Impo… "{\"Impo… "{\"Impo… "{\"Imp… "{\"Imp… "{\"Imp… "{\"Imp…
3 "R_2V7lrA7… "Using F… "Using T… "Using Y… "Using T… "Using T… "Using I… "Using … "Using … "Using … "Using …
4 "R_3nozPOT… "Using F… "Using T… "Using T… "Using T… "Using T… "Using I… "Using … "Using … "Using … "Using …
5 "R_2TB0Wwy… "Using Y… "Using T… "Using T… "Using T… "Using T… "Using F… "Using … "Using … "Using … "Using …
6 "R_2woFtS9… "Using Y… "Using T… "Using Y… "Using T… "Using I… "Using I… "Using … "Using … "Using … "Using …
应用以下转换后：
library(tidyr)
keycol <- "ResponseId"
valuecol <- "Response"
gathercols <- c("Q9","Q10","Q11","Q12","Q13","Q14","Q15","Q16","Q17","Q18" )
dca_long<- gather_(dca,dca$ResponseId,keycol,valuecol,gathercols)
这就是我得到的：
> head(dca_long)
# A tibble: 6 x 2
ResponseId 'Response`
<chr> <chr>
1 Q9 "Regarding the use of social media,which of the following options would you prefer?"
2 Q9 "{\"ImportId\":\"QID12\"}"
3 Q9 "Using Facebook on PC for utility"
4 Q9 "Using Facebook on PC for utility"
5 Q9 "Using Youtube on mobile for entertainment"
6 Q9 "Using Youtube on mobile for entertainment"
基本上，我希望dca_long中有一列具有与dca中ResponseId的值匹配的列。我这样做是为了使dca进一步适合mlogit()。
评论中有人要求输出以更好地理解代码：
> dput(head(dca))
structure(list(ResponseId = c("Response ID","{\"ImportId\":\"_recordId\"}","R_2V7lrA7n29xU0i6","R_3nozPOTbJBE1OBa","R_2TB0WwyWCugTyEg","R_2woFtS93jHyiv8F"),Q9 = c("Regarding the use of social media,which of the following options would you prefer?","{\"ImportId\":\"QID12\"}","Using Facebook on PC for utility","Using Youtube on mobile for entertainment","Using Youtube on mobile for entertainment"),Q10 = c("Regarding the use of social media,"{\"ImportId\":\"QID13\"}","Using TikTok on PC for utility","Using Twitter on mobile for entertainment","Using Twitter on mobile for entertainment"),Q11 = c("Regarding the use of social media,"{\"ImportId\":\"QID14\"}","Using Youtube on PC for utility","Using Youtube on PC for utility"),Q12 = c("Regarding the use of social media,"{\"ImportId\":\"QID15\"}","Using Twitter on mobile for utility","Using Twitter on mobile for utility"),Q13 = c("Regarding the use of social media,"{\"ImportId\":\"QID16\"}","Using TikTok on Mobile for utility","Using Instagram on PC for entertainment"),Q14 = c("Regarding the use of social media,"{\"ImportId\":\"QID17\"}","Using Instagram on PC for utility","Using Facebook on Mobile for entertainment","Using Instagram on PC for utility"),Q15 = c("Regarding the use of social media,"{\"ImportId\":\"QID18\"}","Using Facebook on mobile for utility"),Q16 = c("Regarding the use of social media,"{\"ImportId\":\"QID19\"}","Using Facebook on PC for entertainment","Using Tiktok on mobile for utility","Using Facebook on PC for entertainment"),Q17 = c("Regarding the use of social media,"{\"ImportId\":\"QID20\"}","Using Youtube on PC for entertainment","Using Instagram on mobile for utility","Using Instagram on mobile for utility"),Q18 = c("Regarding the use of social media,"{\"ImportId\":\"QID21\"}","Using Instagram on mobile for entertainment","Using Instagram on mobile for entertainment")),row.names = c(NA,-6L),class = c("tbl_df","tbl","data.frame"))
解决方法
此示例可以帮助您解决问题。
#simulated wide data for reproducibility
wide_data <- read.table(header=TRUE,text='
subject sex time_1 time_2 time_3
1 M 15 16 23
2 F 25 20 48
3 F 30 25 55
4 M 35 32 60
')
使用gather，您应该得到类似以下的内容。
gather(data = olddata_wide,key = alternative,value = time,c(time_1,time_2,time_3),factor_key=TRUE)
subject sex alternative time
1 1 M time_1 15
2 2 F time_1 25
3 3 F time_1 30
4 4 M time_1 35
5 1 M time_2 16
6 2 F time_2 20
7 3 F time_2 25
8 4 M time_2 32
9 1 M time_3 23
10 2 F time_3 48
11 3 F time_3 55
12 4 M time_3 60
如果这没有帮助。请复制一小段数据（dca）来处理其中的数据。最好！
[已编辑]
使用您发布的数据：
df<- structure(list(ResponseId = c("Response ID","{\"ImportId\":\"_recordId\"}","R_2V7lrA7n29xU0i6","R_3nozPOTbJBE1OBa","R_2TB0WwyWCugTyEg","R_2woFtS93jHyiv8F"),Q9 = c("Regarding the use of social media,which of the following options would you prefer?","{\"ImportId\":\"QID12\"}","Using Facebook on PC for utility","Using Youtube on mobile for entertainment","Using Youtube on mobile for entertainment"),Q10 = c("Regarding the use of social media,"{\"ImportId\":\"QID13\"}","Using TikTok on PC for utility","Using Twitter on mobile for entertainment","Using Twitter on mobile for entertainment"),Q11 = c("Regarding the use of social media,"{\"ImportId\":\"QID14\"}","Using Youtube on PC for utility","Using Youtube on PC for utility"),Q12 = c("Regarding the use of social media,"{\"ImportId\":\"QID15\"}","Using Twitter on mobile for utility","Using Twitter on mobile for utility"),Q13 = c("Regarding the use of social media,"{\"ImportId\":\"QID16\"}","Using TikTok on Mobile for utility","Using Instagram on PC for entertainment"),Q14 = c("Regarding the use of social media,"{\"ImportId\":\"QID17\"}","Using Instagram on PC for utility","Using Facebook on Mobile for entertainment","Using Instagram on PC for utility"),Q15 = c("Regarding the use of social media,"{\"ImportId\":\"QID18\"}","Using Facebook on mobile for utility"),Q16 = c("Regarding the use of social media,"{\"ImportId\":\"QID19\"}","Using Facebook on PC for entertainment","Using Tiktok on mobile for utility","Using Facebook on PC for entertainment"),Q17 = c("Regarding the use of social media,"{\"ImportId\":\"QID20\"}","Using Youtube on PC for entertainment","Using Instagram on mobile for utility","Using Instagram on mobile for utility"),Q18 = c("Regarding the use of social media,"{\"ImportId\":\"QID21\"}","Using Instagram on mobile for entertainment","Using Instagram on mobile for entertainment")),row.names = c(NA,-6L),class = c("tbl_df","tbl","data.frame"))
并使用我先前发布的摘录部分：
df_long<- gather(data = df,value = value_answer,Q9:Q18,factor_key=TRUE)
您应该能够获得如下内容，其中保留了Response ID变量：
ResponseId alternative value_answer
<chr> <fct> <chr>
1 "Response ID" Q9 "Regarding the use of social media,which of the foll~
2 "{\"ImportId\":\"_rec~ Q9 "{\"ImportId\":\"QID12\"}"
3 "R_2V7lrA7n29xU0i6" Q9 "Using Facebook on PC for utility"
4 "R_3nozPOTbJBE1OBa" Q9 "Using Facebook on PC for utility"
5 "R_2TB0WwyWCugTyEg" Q9 "Using Youtube on mobile for entertainment"
6 "R_2woFtS93jHyiv8F" Q9 "Using Youtube on mobile for entertainment"
我希望这会对您有所帮助。最好！
,这接近您要完成的工作吗？
library(tidyr)
library(dplyr)
dca_long <- dca %>%
gather(key = "question",value = "response",2:ncol(.))
# # A tibble: 60 x 3
# ResponseId question response
# <chr> <chr> <chr>
# 1 "Response ID" Q9 "Regarding the use of social media,which of the following options would you prefer?"
# 2 "{\"ImportId\":\"_recordId\"}" Q9 "{\"ImportId\":\"QID12\"}"
# 3 "R_2V7lrA7n29xU0i6" Q9 "Using Facebook on PC for utility"
# 4 "R_3nozPOTbJBE1OBa" Q9 "Using Facebook on PC for utility"
# 5 "R_2TB0WwyWCugTyEg" Q9 "Using Youtube on mobile for entertainment"
# 6 "R_2woFtS93jHyiv8F" Q9 "Using Youtube on mobile for entertainment"
# 7 "Response ID" Q10 "Regarding the use of social media,which of the following options would you prefer?"
# 8 "{\"ImportId\":\"_recordId\"}" Q10 "{\"ImportId\":\"QID13\"}"
# 9 "R_2V7lrA7n29xU0i6" Q10 "Using TikTok on PC for utility"
# 10 "R_3nozPOTbJBE1OBa" Q10 "Using Twitter on mobile for entertainment"
# # … with 50 more rows
看起来您的数据仍然需要清理。
本质上，我希望dca_long中有一列，以使dca中的ResponseId的值匹配。
all(unique(dca$ResponseId) == unique(dca_long$ResponseId))
# [1] TRUE
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