churn: Churn data set

In liver: Foundations Toolkit and Datasets for Data Science

Churn data set

Description

This dataset comes from IBM Sample Data Sets. Customer churn occurs when customers stop doing business with a company, also known as customer attrition. the data set contains 5000 rows (customers) and 20 columns (features). the "Churn" column is our target which indicate whether customer churned (left the company) or not.

Usage

data(churn)

Format

A data frame with 5000 rows (customers) and 20 columns (variables/features). the 20 variables are:

• state: Categorical, for the 51 states and the District of Columbia.

• area.code: Categorical.

• account.length: count, how long account has been active.

• voice.plan: Categorical, yes or no, voice mail plan.

• voice.messages: Count, number of voice mail messages.

• intl.plan: Categorical, yes or no, international plan.

• intl.mins: Continuous, minutes customer used service to make international calls.

• intl.calls: Count, total number of international calls.

• intl.charge: Continuous, total international charge.

• day.mins: Continuous, minutes customer used service during the day.

• day.calls: Count, total number of calls during the day.

• day.charge: Continuous, total charge during the day.

• eve.mins: Continuous, minutes customer used service during the evening.

• eve.calls: Count, total number of calls during the evening.

• eve.charge: Continuous, total charge during the evening.

• night.mins: Continuous, minutes customer used service during the night.

• night.calls: Count, total number of calls during the night.

• night.charge: Continuous, total charge during the night.

• customer.calls: Count, number of calls to customer service.

• churn: Categorical, yes or no. Indicator of whether the customer has left the company (yes or no).

Details

For more information related to the dataset see:

OpenML: ⁠https://www.openml.org/search?type=data&sort=runs&id=40701&status=active⁠

data.world: ⁠https://data.world/earino/churn⁠

References

Umayaparvathi, V., and Iyakutti, K. (2016). A survey on customer churn prediction in telecom industry: Datasets, methods and metrics. International Research Journal of Engineering and Technology (IRJET), 3(04), 1065-1070

Saha, S., Saha, C., Haque, M. M., Alam, M. G. R., and Talukder, A. (2024). ChurnNet: Deep learning enhanced customer churn prediction in telecommunication industry. IEEE access, 12, 4471-4484.

See Also

adult, risk, churnTel, bank, advertising, marketing, insurance, cereal, housePrice, house

Examples

data(churn)

str(churn)

liver documentation built on Sept. 9, 2025, 5:49 p.m.