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Introduction to Python for Data Analysis

bookCostly Customers

Sometimes we don't receive as much as we spend. The same with some customers in our DataFrame. We do spend more money to 'buy' this customer, but we don't receive the the same amount of money.

Let's find the percentage of these customers!

We want to find costly customers, not payments. To do that, we need to add additional customer_id.nunique() that will find only unique customers with their costly (or not) payments.

To find the percentage, use the next formula:

Task

Swipe to start coding

  1. Count the number of the costly customers:
  • Set the condition if the value in the 'cost' column is greater than the value in the 'money_spent' column
  • Use unique customers to find the metric
  1. Print the number of the costly customers.
  2. Find the percentage of costly customers using the formula.
  3. Print the result of countings in the 0.00 format.

Solution

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SectionΒ 4. ChapterΒ 6
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bookCostly Customers

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Sometimes we don't receive as much as we spend. The same with some customers in our DataFrame. We do spend more money to 'buy' this customer, but we don't receive the the same amount of money.

Let's find the percentage of these customers!

We want to find costly customers, not payments. To do that, we need to add additional customer_id.nunique() that will find only unique customers with their costly (or not) payments.

To find the percentage, use the next formula:

Task

Swipe to start coding

  1. Count the number of the costly customers:
  • Set the condition if the value in the 'cost' column is greater than the value in the 'money_spent' column
  • Use unique customers to find the metric
  1. Print the number of the costly customers.
  2. Find the percentage of costly customers using the formula.
  3. Print the result of countings in the 0.00 format.

Solution

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Everything was clear?

How can we improve it?

Thanks for your feedback!

close

Awesome!

Completion rate improved to 2.08
SectionΒ 4. ChapterΒ 6
single

single

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