CODEWITHSUNDEEP
rif-statementdplyrmultiple-conditions
Jay
Jay

Reputation: 57

if else statement based on multiple conditions

I have the following table which represents a child, his siblings and the case they are assigned under. The resource ids represent the house where they were placed together.

child_id|sibling_id|case_id|resource_id
    1       8         123      12856
    1       9         123      12856
    3      11         321      12555
    4      12         323      10987
    4      13         323      10956
    6      14         156      10554
    6      15         156      10554
   10      16         156      10553
   10      17         145      18986
   10      18         145      18986

I want to create a new column placed_together which shows a yes or a no for those children that were placed together based on their case_ids. So my result should look like this

child_id|sibling_id|case_id|resource_id|placed_together
        1       8         123      12856  Yes
        1       9         123      12856  Yes
        3      11         321      12555  No
        4      12         323      10987  No
        4      13         323      10956  No 
        6      14         156      10554  No
        6      15         156      10554  No 
       10      16         156      10553  No
       10      17         145      18986  Yes
       10      18         145      18986  Yes

Any help would be appreciated. I dont know how to create an if statement based on these conditions since a case_id can be the same for a group but their resource id can be different for one of the child.

Upvotes: 2

Views: 125

Answers (2)

rodolfoksveiga
rodolfoksveiga

Reputation: 1261

Assuming that your dataframe was named df, you can do something like this:

# create a function that defines if a child is placed together
IsPlacedTogether = function(x, y) ifelse(sum(x == y) > 1, 'Yes', 'No')
# apply this function to every child in your data
df$placed_together = sapply(df$case_id, IsPlacedTogether, df$case_id)

Upvotes: 0

Onyambu
Onyambu

Reputation: 79338

Probably using tidyverse:

library(tidyverse)
df %>%
   group_by(case_id) %>%
   mutate(placedTogether = if_else(n()>1 &length(unique(child_id))==1 & 
                             length(unique(resource_id))==1, "Yes", "No"))
# A tibble: 10 x 5
# Groups:   case_id [5]
   child_id sibling_id case_id resource_id placedTogether
      <int>      <int>   <int>       <int> <chr>         
 1        1          8     123       12856 Yes           
 2        1          9     123       12856 Yes           
 3        3         11     321       12555 No            
 4        4         12     323       10987 No            
 5        4         13     323       10956 No            
 6        6         14     156       10554 No            
 7        6         15     156       10554 No            
 8       10         16     156       10553 No            
 9       10         17     145       18986 Yes           
10       10         18     145       18986 Yes

Upvotes: 1

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