[英]Error in get(as.character(FUN), mode = “function”, envir = envir) :
I am trying apply this function on a data frame to create a new feature but I keep getting this error:我正在尝试将此函数应用于数据框以创建新功能,但我不断收到此错误:
Error in get(as.character(FUN), mode = "function", envir = envir) : object 'INSTALLMENT' of mode 'function' was not found
get(as.character(FUN), mode = "function", envir = envir) 中的错误:找不到模式 'function' 的对象 'INSTALLMENT'
I have also tried apply(df, 2, purchase)
but then I get this error:我也试过
apply(df, 2, purchase)
但后来我得到这个错误:
Error: $ operator is invalid for atomic vectors
错误:$ 运算符对原子向量无效
The code is :代码是:
purchase = function(DataFrame){
if((DataFrame$ONEOFF_PURCHASES == 0) && (DataFrame$INSTALLMENTS_PURCHASES == 0))
return('NONE')
if((DataFrame$ONEOFF_PURCHASES > 0) && (DataFrame$INSTALLMENTS_PURCHASES > 0))
return('BOTH_ONEOFF_INSTALLMENT')
if((DataFrame$ONEOFF_PURCHASES > 0) && (DataFrame$INSTALLMENTS_PURCHASES == 0))
return('ONE_OFF')
if((DataFrame$ONEOFF_PURCHASES == 0) && (DataFrame$INSTALLMENTS_PURCHASES > 0))
return('INSTALLMENT')
}
df$PURCHASE_TYPE = apply(df, 2, purchase(df))
It looks like a ifelse()
case.它看起来像一个
ifelse()
案例。 if() ... else ...
can only treat a single boolean. if() ... else ...
只能处理单个布尔值。 To make your function work, you need to vectorize it by mapply()
or Vectorize()
.为了使您的函数工作,您需要通过
mapply()
或Vectorize()
。
Example Data示例数据
set.seed(1)
df <- data.frame(ONEOFF_PURCHASES = sample(0:1, 5, T), INSTALLMENTS_PURCHASES = sample(0:1, 5, T))
# ONEOFF_PURCHASES INSTALLMENTS_PURCHASES
# 1 0 0
# 2 1 0
# 3 0 0
# 4 0 1
# 5 1 1
Function功能
purchase <- function(x, y){
if((x == 0) && (y == 0))
return('NONE')
else if((x > 0) && (y > 0))
return('BOTH_ONEOFF_INSTALLMENT')
else if((x > 0) && (y == 0))
return('ONE_OFF')
else if((x == 0) && (y > 0))
return('INSTALLMENT')
else
return('OTHERS')
}
Vectorization矢量化
mapply(purchase, df$ONEOFF_PURCHASES, df$INSTALLMENTS_PURCHASES)
# [1] "NONE" "ONE_OFF" "NONE" "INSTALLMENT" "BOTH_ONEOFF_INSTALLMENT"
Vectorize(purchase)(df$ONEOFF_PURCHASES, df$INSTALLMENTS_PURCHASES)
# [1] "NONE" "ONE_OFF" "NONE" "INSTALLMENT" "BOTH_ONEOFF_INSTALLMENT"
Actually, we don't use the approach above in this issue.实际上,我们在这个问题中没有使用上面的方法。 We'll use
ifelse()
or dplyr::case_when()
.我们将使用
ifelse()
或dplyr::case_when()
。
library(dplyr)
df %>%
mutate(PURCHASE_TYPE = case_when(
(ONEOFF_PURCHASES == 0) & (INSTALLMENTS_PURCHASES == 0) ~ 'NONE',
(ONEOFF_PURCHASES > 0) & (INSTALLMENTS_PURCHASES > 0) ~ 'BOTH_ONEOFF_INSTALLMENT',
(ONEOFF_PURCHASES > 0) & (INSTALLMENTS_PURCHASES == 0) ~ 'ONE_OFF',
(ONEOFF_PURCHASES == 0) & (INSTALLMENTS_PURCHASES > 0) ~ 'INSTALLMENT',
TRUE ~ 'OTHERS'
))
# ONEOFF_PURCHASES INSTALLMENTS_PURCHASES PURCHASE_TYPE
# 1 0 0 NONE
# 2 1 0 ONE_OFF
# 3 0 0 NONE
# 4 0 1 INSTALLMENT
# 5 1 1 BOTH_ONEOFF_INSTALLMENT
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