我正在尝试计算每人独特水果的平均数量(我通常的实践数据)。这对这两行代码都非常有效:
with(df, tapply(fruit, names, FUN = function(x) length(unique(x))))->uniques
sum(uniques)/length(unique(df$names))
aggregate(df[,"fruit"], by=list(id=names), FUN = function(x) length(unique(x)))->d1
sum(d1$x)/length(unique(df$names))
我的问题是,当我在真实数据上使用代码时,它不起作用。我的真实数据是处方数据,我想要平均每人独特药物的数量。使用 tapply 代码,它似乎创建了原始 df 中不存在的全新患者 ID。它还返回了 1000 个 NA 值。我的 id 列中没有缺失值,drug_code 列中也没有缺失值
with(dt3, tapply(drug_code, id, FUN = function(x) length(unique(x))))->uniques
head(uniques)
uniques
Patient HAI0000001 NA
Patient HAI0000003 NA
Patient HAI0000008 NA
Patient HAI0000010 NA
Patient HAI0000014 NA
Patient HAI0000020 NA
table(dt3$id=="Patient HAI0000001") ##checking to see if HA10000001 occurs in original df. the dim of df are 228954 rows and 5 cols
FALSE
228954
对于聚合代码,我收到一个错误:
aggregate(dt3[,"drug_code"], by=list(id=id), FUN = function(x) length(unique(x)))->d1
Error in aggregate.data.frame(as.data.frame(x), ...) :
arguments must have same length
我不明白发生了什么。我的真实数据与我的实践数据相似,因为它有一个 id col 并有一个 drug/fruit 列。两个df中都没有丢失数据。我知道 lapply 更适合数据帧,但我不一定需要 df 返回。在任何情况下,tapply 代码都适用于 df 的练习数据。有谁知道这里发生了什么?
练习 DF:
names<-as.character(c("john", "john", "john", "john", "john", "mary", "mary","mary","mary","mary", "jim", "sylvia","ted","ted","mary", "sylvia", "jim", "ted", "john", "ted"))
dates<-as.Date(c("2010-07-01", "2010-09-01", "2010-11-01", "2010-12-01", "2011-01-01", "2010-08-12", "2010-11-11", "2010-05-12", "2010-12-03", "2010-07-12", "2010-12-21", "2010-02-18", "2010-10-29", "2010-08-13", "2010-11-11", "2010-05-12", "2010-04-01", "2010-05-06", "2010-09-28", "2010-11-28" ))
fruit<-as.character(c("kiwi","apple","banana","orange","apple","orange","apple","orange", "apple", "apple", "pineapple", "peach", "nectarine", "grape", "melon", "apricot", "plum", "lychee", "watermelon", "apple" ))
df<-data.frame(names,dates,fruit)
真实数据示例:
head(dt3)
id quantity date_of_claim drug_code index
1 Patient HAI0000560 1 2009-10-15 R03AC02 2010-04-06
2 Patient HAI0000560 1 2009-10-15 R03AK06 2010-04-06
3 Patient HAI0000560 30 2009-10-15 R03BB04 2010-04-06
4 Patient HAI0000560 30 2009-10-15 A02BC01 2010-04-06
5 Patient HAI0000560 50 2009-10-15 M02AA15 2010-04-06
6 Patient HAI0000560 30 2009-10-15 N02BE51 2010-04-06