CODEWITHSUNDEEP
rdataframeif-statementfilterdplyr
AlSub
AlSub

Reputation: 1155

How to properly filter a df based on a condition in R?

I am trying to sample a dataset based on date class column, quarterly for "Active" and monthly for "Inactive"

Here's my code:

library(dplyr)
library(lubridate)
  
## data ##
                 
df <- structure(list( 
             mes = c("01/01/2000", "01/02/2000", "01/03/2000", 
"01/04/2000", "01/05/2000", "01/06/2000", "01/07/2000", "01/08/2000", 
"01/09/2000", "01/10/2000", "01/11/2000", "01/12/2000"),
              status = c("Active", "Inactive",
                         "Active", "Inactive",
                         "Active", "Inactive",
                         "Active", "Active",
                         "Inactive", "Active",
                         "Inactive", "Active")),
             class = "data.frame",
             row.names = c(NA, -12L))

## setting date class for "mes" column ##

df$mes <- as.Date(df$mes,
                  format = "%d/%m/%Y")

## sampling ##

sample_df <- df %>%  
  dplyr :: filter(status %in% "Active",
                  status %in% "Inactive") %>%
            dplyr :: filter_if(status == "Active",
            month(mes) %in% c(3,6,9,12),
            month(mes) %in% c(1,2,3,4,5,6,7,8,9,10,11,12))

Console output:

Error in is_logical(.p) : objeto 'status' no encontrado

Is there any other library that I could use to accomplish this task?

Upvotes: 0

Views: 61

Answers (2)

Ronak Shah
Ronak Shah

Reputation: 388807

To filter quarterly months for "Active" status and all months for "Inactive" you could do :

library(dplyr)

df %>%
  mutate(month = lubridate::month(mes)) %>%
  filter(status == "Active" & month %in% c(3,6,9,12) | 
         status == "Inactive" & month %in% 1:12)

#         mes   status month
#1 2000-02-01 Inactive     2
#2 2000-03-01   Active     3
#3 2000-04-01 Inactive     4
#4 2000-06-01 Inactive     6
#5 2000-09-01 Inactive     9
#6 2000-11-01 Inactive    11
#7 2000-12-01   Active    12

Since you want all months for "Inactive" status you can also do :

df %>%
  mutate(month = lubridate::month(mes)) %>%
  filter(status == "Active" & month %in% c(3,6,9,12) | 
         status == "Inactive")

Upvotes: 1

akrun
akrun

Reputation: 886938

With dplyr::filter, if we use ,, then it means &, instead, we need |. Using & would result in 0 rows because 'status' can't have both 'Active' and 'Inactive' at the same location

df %>%  
  dplyr::filter(status %in% "Active"| status %in% "Inactive") %>% 
  dplyr::filter(status == 'Active', month(mes) %in% c(3, 6, 9, 12))

Also, as we are using %in%, it can take a vector of values in the rhs of the operator %in% with length >= 1

 df %>%
    dplyr::filter(status %in% c("Active", "Inactive")) %>%      
    dplyr::filter(status == 'Active', month(mes) %in% c(3, 6, 9, 12))

In the OP's filter statement

...
 month(mes) %in% c(3,6,9,12),
        month(mes) %in% c(1,2,3,4,5,6,7,8,9,10,11,12)

implies both conditions should be true, but one of them is a subset of the another condition

Upvotes: 2

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