Costly 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:
Swipe to start coding
- 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
- Print the number of the costly customers.
- Find the percentage of costly customers using the formula.
- Print the result of countings in the
0.00format.
Lösung
Danke für Ihr Feedback!
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Completion rate improved to 2.08Costly 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:
Swipe to start coding
- 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
- Print the number of the costly customers.
- Find the percentage of costly customers using the formula.
- Print the result of countings in the
0.00format.
Lösung
Wechseln Sie zum Desktop, um in der realen Welt zu übenFahren Sie dort fort, wo Sie sind, indem Sie eine der folgenden Optionen verwendenDanke für Ihr Feedback!
Awesome!
Completion rate improved to 2.08single
