I have a variable term which includes loan term and has only two types: "36 months" and "60 months". I want to filter my dataset df and create two different subsets for these categories.
I have tried using the commands subset, filter,which etc but it didn't work.
codes that I have tried df1 –> df[which(df$term == "36 months"),]
, df1 –> filter(df, term == "36 months")
df1–>df[df$term %in% c("36 months"), ]
and other ways but always choices zero rows.
head(loan_data$term)
[1] " 36 months" " 60 months" " 36 months" " 36 months" " 60 months" " 36 months"
Any suggestion?
Thanks
I cannot reproduce your problem:
df <- data.frame(
id = c(1, 2, 3),
val = c("60 months", "36 months", "60 months")
)
df[df$val == "60 months", ]
# df$val == "60 months"
# 1 1 60 months
# 3 3 60 months
df[which(df$val == "60 months"),]
# df$val == "60 months"
# 1 1 60 months
# 3 3 60 months
as more robustly explained here , using...
my.data.frame %>% filter(.data[[myName]] == 1) ...
df60 <- df %>% filter(.df[[term]] == "60 months")
df30 <- df %>% filter(.df[[term]] == "30 months")
..or here
ssP <- mutate( nino, PHASE = ifelse(PHASE == "E", "N","L"))
which for your df ..
df60 <- mutate( df, term = ifelse(term == "60 months"))
df30 <- mutate( df, term = ifelse(term == "30 months"))
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