Validating totals

In this lesson, you'll continue to work with the accounts data frame, but this time, you have a bit more information about each account. There are three different funds that account holders can store their money in. In this exercise, you'll validate whether the total amount in each account is equal to the sum of the amount in fund_A, fund_B, and fund_C. If there are any accounts that don't match up, you can look into them further to see what went wrong in the bookkeeping that led to inconsistencies.

dplyr is loaded and accounts is available.

This exercise is part of the course

Cleaning Data in R

Exercise instructions

Create a new column called theoretical_total that contains the sum of the amounts in each fund.
Find the accounts where the total doesn't match the theoretical_total.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Find invalid totals
accounts %>%
  # theoretical_total: sum of the three funds
  ___ %>%
  # Find accounts where total doesn't match theoretical_total
  ___

Edit and Run Code

This exercise is part of the course

Cleaning Data in R

IntermediateSkill Level

4.8+

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In this chapter, you'll learn how to overcome some of the most common dirty data problems. You'll convert data types, apply range constraints to remove future data points, and remove duplicated data points to avoid double-counting.

Exercise 1: Data type constraints Exercise 2: Common data types Exercise 3: Converting data types Exercise 4: Trimming strings Exercise 5: Range constraints Exercise 6: Ride duration constraints Exercise 7: Back to the future Exercise 8: Uniqueness constraints Exercise 9: Full duplicates Exercise 10: Removing partial duplicates Exercise 11: Aggregating partial duplicates

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Exercise 1: Uniformity Exercise 2: Date uniformity Exercise 3: Currency uniformity Exercise 4: Cross field validation Exercise 5: Validating totals

Current Exercise

Exercise 6: Validating age Exercise 7: Completeness Exercise 8: Types of missingness Exercise 9: Visualizing missing data Exercise 10: Treating missing data

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Exercise 1: Comparing strings Exercise 2: Calculating distance Exercise 3: Small distance, small difference Exercise 4: Fixing typos with string distance Exercise 5: Generating and comparing pairs Exercise 6: Link or join?Exercise 7: Pair blocking Exercise 8: Comparing pairs Exercise 9: Scoring and linking Exercise 10: Score then select or select then score?Exercise 11: Putting it together Exercise 12: Congratulations!