TIL

R
Author

Kevin

Published

2021-12-19

I wrote some functions and scripts had to complete troubleshooting to make them work

I am not sure why I could not recall how to filter multiple values under on variable but here we are! The slice function is also becoming one of my favorite tools.

pre_numeric <- pre_summary %>%
  dplyr::filter(skim_type == "numeric") %>%
  dplyr::slice_tail(n = 6) %>%
  dplyr::filter(skim_variable == "var2_avg" |
                  skim_variable == "var1_avg" |
                  skim_variable == "var3_avg") 
                  

In this function, I have to make sure that NA values are converted to zero before I can determine success or failure. The df has to be called first and then start the new dplyr statement.

get_var_score <- function(df){
  
    df <- dplyr::mutate(df, var_adjusted = 4 - sc1) 
    df <- dplyr::mutate(df, var_avg = sc0 / var_adjusted) 
    df$var_avg <- tidyr::replace_na(df$var_avg, 0)
    df 
    dplyr::mutate(df, var_success = if_else(var_avg >= 4.45, TRUE, FALSE))
    
    
}

Here I needed to actually filter navalues in this column to see troubled records.

issue_13 <- survey %>%
  dplyr::filter(is.na(initials_1)) 
  

About

Kevin is a nonprofit data professional operating out of Lakeland, Florida.
My expertise is helping nonprofits collect, manage and analyze their program data.