我在L5num中列出了10种产品，并且我有PANID。我正在尝试为多项逻辑模型创建一个选择模型，但我首先尝试进行一些数据准备。
数据如下：
PANID WEEK L5num
1669 3174607 2008-09-08 9
21356 3362137 2011-08-01 7
15540 3174607 2010-10-04 9
5869 3150938 2009-07-13 3
18401 3174607 2011-02-28 9
10616 3174607 2010-03-22 8
我正在尝试构建数据，以使ID 3174607选择产品9等。我正在尝试以类似于以下格式的格式放置数据：
PANID Product
3174607 0
3174607 0
3174607 0
3174607 0
3174607 0
3174607 0
3174607 0
3174607 0
3174607 0
3174607 1
3174607 0
…
Next PANID
因此该人从10种产品中选择了9种。
希望这是有道理的，任何帮助将不胜感激
编辑：
非常感谢您的答复。我已经使用了您所有的答案，并且都可以使用。我的原始帖子确实有一点“添加”。我也希望reshape我的数据。我的数据有x个变量，我在原始帖子中没有讨论。
数据看起来像
PANID WEEK L5num X1 X2 X3 X4...
是否可以应用您建议的方法同时包含x变量？因此输出将与当前建议的相同，但RHS上带有x变量 编辑2：
我用“ x”变量添加相同的数据
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5089L, 13868L, 6397L), class = "data.frame")
答案 0 :(得分：2)
这里是使用tabulate和data.table的选项
library(data.table)
setDT(dat)
n <- dat[, uniqueN(L5num)] # 10
out <- dat[, .(Product = tabulate(L5num, n)), by = PANID]
out # ^ total number of products
为说明起见，我使用一个小例子。
输入：
(dt <- as.data.table(head(unique(dat[, c("PANID", "L5num")]), 2)))
# PANID L5num
#1: 3801365 4
#2: 3174607 9
输出：
out <- dt[, .(Product = tabulate(L5num, 10)), by = PANID]
out
# PANID Product
# 1: 3801365 0
# 2: 3801365 0
# 3: 3801365 0
# 4: 3801365 1
# 5: 3801365 0
# 6: 3801365 0
# 7: 3801365 0
# 8: 3801365 0
# 9: 3801365 0
#10: 3801365 0
#11: 3174607 0
#12: 3174607 0
#13: 3174607 0
#14: 3174607 0
#15: 3174607 0
#16: 3174607 0
#17: 3174607 0
#18: 3174607 0
#19: 3174607 1
#20: 3174607 0
编辑
如果需要将此操作应用于多个列，则需要做
n <- dat[, uniqueN(L5num)] # 10
cols <- setdiff(names(dat), c("PANID", "WEEK")) # don't apply function to "WEEK" column
out <- dat[, lapply(.SD, tabulate, nbins = n), by = PANID, .SDcols = cols]
编辑2
我不确定预期的输出是什么，但是如果要扩展所有“ x”列，则可以使用联接。
输入：
(dt <- as.data.table(head(unique(dat), 2)))
# PANID WEEK L5num Family.Size
#1: 3362137 2010-06-28 7 2
#2: 3109124 2010-06-21 3 3
现在计算并与“ PANID”上的dt合并
out <- dt[dt[, .(Product = tabulate(L5num, n)), by = PANID], on = "PANID"
][, L5num := NULL] # removes column L5num
out
# PANID WEEK Family.Size Product
# 1: 3362137 2010-06-28 2 0
# 2: 3362137 2010-06-28 2 0
# 3: 3362137 2010-06-28 2 0
# 4: 3362137 2010-06-28 2 0
# 5: 3362137 2010-06-28 2 0
# 6: 3362137 2010-06-28 2 0
# 7: 3362137 2010-06-28 2 1
# 8: 3362137 2010-06-28 2 0
# 9: 3362137 2010-06-28 2 0
#10: 3362137 2010-06-28 2 0
#11: 3109124 2010-06-21 3 0
#12: 3109124 2010-06-21 3 0
#13: 3109124 2010-06-21 3 1
#14: 3109124 2010-06-21 3 0
#15: 3109124 2010-06-21 3 0
#16: 3109124 2010-06-21 3 0
#17: 3109124 2010-06-21 3 0
#18: 3109124 2010-06-21 3 0
#19: 3109124 2010-06-21 3 0
#20: 3109124 2010-06-21 3 0
答案 1 :(得分：1)
如果Data是输入data.frame，则：
library(mlogit)
mlogit.data(Data, choice = "L5num", shape = "wide")
答案 2 :(得分：0)
我们还可以使用以下基本R方法：
n <- 10 # Number of products
data.frame(PANID = rep(df$PANID, each = n),
Product = replace(numeric(n * nrow(df)), 0:(nrow(df) - 1) * n + df$L5num, 1))
# PANID Product
# 1 3801365 0
# 2 3801365 0
# 3 3801365 0
# 4 3801365 1
# 5 3801365 0
...
我们从Product列开始，以numeric(n * nrow(df))给出的零向量开始，然后在0:(nrow(df) - 1) * n + df$L5num的所需位置（replace）处添加一个。
如果还有更多变量，我们可以做
data.frame(PANID = rep(df$PANID, each = n),
Product = replace(numeric(n * nrow(df)), 0:(nrow(df) - 1) * n + df$L5num, 1),
df[rep(1:nrow(df), each = n), -1:-3, drop = FALSE])
# PANID Product Family.Size
# 13036 3362137 0 2
# 13036.1 3362137 0 2
# 13036.2 3362137 0 2
其中，每个n的多余变量将重复PANID次。如果变量多于一个，则不需要drop = FALSE。
答案 3 :(得分：0)
使用dummyVars软件包-
get_queryset答案 4 :(得分：0)
使用tidyverse，您可以执行以下操作：
df %>%
do(data.frame(PANID = rep(.$PANID, each = 10), #Replicating "PANID" and "L5num" 10x
L5num = rep(.$L5num, each = 10))) %>%
mutate(temp = gl(length(PANID)/10, 10)) %>% #For all "PANID" values generating an ID
group_by(temp) %>% #Grouping by ID
mutate(rowid = seq_along(temp)) %>% #Sequencing around ID to create a row ID
mutate(Product = ifelse(rowid == L5num, 1, 0)) %>% #Checking whether the row ID is equal to "L5num"
ungroup() %>%
select(-rowid,-L5num,-temp) #Removing the redundant variables
PANID Product
<int> <dbl>
1 3174607 0.
2 3174607 0.
3 3174607 0.
4 3174607 0.
5 3174607 0.
6 3174607 0.
7 3174607 0.
8 3174607 0.
9 3174607 1.
10 3174607 0.
11 3362137 0.
12 3362137 0.
13 3362137 0.
14 3362137 0.
15 3362137 0.
16 3362137 0.
17 3362137 1.
18 3362137 0.
19 3362137 0.
20 3362137 0.