我在为数据帧编写函数时遇到了两个问题。我经常得到一个带有 2 个变量的数据框,我想将它们重新编码为一个变量。
If V1>0 and V2 <0 then new_variable = "V1>0, V2<0.
在所有数据框中,我有 V1 和 V2 有不同的名称。
问题1。不知道为什么test_df$newVar,这个函数后得到的只有“C>0,I>0”
#Using test FUN on example data frame
test_df.afterFUN <- test_fun(test_df, var1 = "V1", var2 = "V2", newVar = "category")
问题2。为什么这个函数“newVar”的最后一个参数没有将名称更改为“类别”?如果我运行适合单个数据框的此函数的代码(重命名变量等),它将起作用并给我想要的东西(看看 test_df2)
rm(list = ls())
library("dplyr") # for filter
# Preparing example data frame
rama <- rbind(c(-5:20, -20:5), c(-20:5, -5:20))
rama <- t(rama)
colnames(rama) <- c("V1", "V2")
test_df <- as.data.frame(rama)
#Test FUN
test_fun <- function(df, var1, var2, newVar) {
df1 <- filter(df, var1 == 0, var2 == 0)
df1 <- mutate(df1, newVar = "C=0, I=0")
df2 <- filter(df, var1 == 0, var2 > 0)
df2 <- mutate(df2, newVar = "C=0, I>0")
df3 <- filter(df, var1 == 0, var2 < 0)
df3 <- mutate(df3, newVar = "C=0, I<0")
df4 <- filter(df, var1 > 0, var2 == 0)
df4 <- mutate(df4, newVar = "C>0, I=0")
df5 <- filter(df, var1 > 0, var2 > 0)
df5 <- mutate(df5, newVar = "C>0, I>0")
df6 <- filter(df, var1 > 0, var2 < 0)
df6 <- mutate(df6, newVar = "C>0, I<0")
df7 <- filter(df, var1 < 0, var2 == 0)
df7 <- mutate(df7, newVar = "C<0, I=0")
df8 <- filter(df, var1 < 0, var2 > 0)
df8 <- mutate(df8, newVar = "C<0, I>0")
df9 <- filter(df, var1 < 0, var2 < 0)
df9 <- mutate(df9, newVar = "C<0, I<0")
df <- rbind(df1, df2, df3, df4, df5, df6, df7, df8, df9)
return(df)
}
#Using test FUN on example data frame
test_df.afterFUN <- test_fun(test_df, var1 = "V1", var2 = "V2", newVar = "category")
# Procedure outside of funcion fitted to test_df
df1 <- filter(test_df, V1 == 0, V2 == 0)
df1 <- mutate(df1, newVar = "C=0, I=0")
df2 <- filter(test_df, V1 == 0, V2 > 0)
df2 <- mutate(df2, newVar = "C=0, I>0")
df3 <- filter(test_df, V1 == 0, V2 < 0)
df3 <- mutate(df3, newVar = "C=0, I<0")
df4 <- filter(test_df, V1 > 0, V2 == 0)
df4 <- mutate(df4, newVar = "C>0, I=0")
df5 <- filter(test_df, V1 > 0, V2 > 0)
df5 <- mutate(df5, newVar = "C>0, I>0")
df6 <- filter(test_df, V1 > 0, V2 < 0)
df6 <- mutate(df6, newVar = "C>0, I<0")
df7 <- filter(test_df, V1 < 0, V2 == 0)
df7 <- mutate(df7, newVar = "C<0, I=0")
df8 <- filter(test_df, V1 < 0, V2 > 0)
df8 <- mutate(df8, newVar = "C<0, I>0")
df9 <- filter(test_df, V1 < 0, V2 < 0)
df9 <- mutate(df9, newVar = "C<0, I<0")
test_df2 <- rbind(df1, df2, df3, df4, df5, df6, df7, df8, df9)