Treating missing data
In this exercise, you're working with another version of the accounts data that contains missing values for both the cust_id and acct_amount columns.
You want to figure out how many unique customers the bank has, as well as the average amount held by customers. You know that rows with missing cust_id don't really help you, and that on average, the acct_amount is usually 5 times the amount of inv_amount.
In this exercise, you will drop rows of accounts with missing cust_ids, and impute missing values of inv_amount with some domain knowledge. dplyr and assertive are loaded and accounts is available.
Deze oefening maakt deel uit van de cursus
Cleaning Data in R
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Create accounts_clean
accounts_clean <- accounts %>%
# Filter to remove rows with missing cust_id
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accounts_clean