bankData: Direct marketing campaigns of a Portuguese banking...
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bankData R Documentation
Direct marketing campaigns of a Portuguese banking institution
Description
The marketing campaigns were based on phone calls.
Often, more than one contact to the same client was required, in order to
access if the product (bank term deposit) would be ('yes') or not ('no')
subscribed. Records are ordered by date (from May 2008 to November 2010),
similar to data analyzed in Moro et al. [2014].
Usage
bankData
Format
A data frame with 45,211 rows and 19 variables:
- age
Age of the client, numeric.
- job
Type of job, a categorical variable with the levels:
'admin.', 'blue-collar', 'entrepreneur',
'housemaid', 'management', 'retired',
'self-employed', 'services', 'student',
'technician', 'unemployed', and 'unknown'.
- marital
Marital status, a categorical variable with levels:
'divorced', 'married', 'single', and 'unknown'.
Note that 'divorced' means either divorced or widowed.
- education
A categorical variable with levels: 'basic.4y',
'basic.6y', 'basic.9y', 'high.school',
'illiterate', 'professional.course',
'university.degree', and 'unknown'.
- default
Whether credit is in default, a categorical variable with
levels: 'no', 'yes', and 'unknown'.
- balance
Account balance, numeric.
- housing
Whether the client has a housing loan, a categorical variable
with levels: 'no', 'yes', and 'unknown'.
- loan
Whether the client has personal loan, a categorical variable
with levels: 'no', 'yes', and 'unknown'.
- contact
Type of contact communication, a categorical variable
with levels: 'cellular' and 'telephone'.
- duration
Last contact duration in seconds, a numeric variable.
- campaign
Number of contacts performed during this campaign for
this client, including the last contact; a numeric variable.
- pdays
Number of days that passed by after the client was last
contacted from a previous campaign; a numeric variable, with 999
means that client was not previously contacted.
- previous
Number of contacts performed before this campaign for this
client, a numeric variable.
- poutcome
Outcome of the previous marketing campaign, a categorical
variable with levels: 'failure', 'nonexistent',
and 'success'.
- y
Whether the client has subscribed a term deposit, a categorical
variable with levels: 'yes' and 'no'.
- date
Last contact date.
Source
https://archive.ics.uci.edu/ml/datasets/Bank+Marketing
Lichman, M. (2013). UCI Machine Learning Repository
[http://archive.ics.uci.edu/ml]. Irvine, CA: University of California,
School of Information and Computer Science.
S. Moro, P. Cortez, and P. Rita. (2014) A Data-Driven Approach
to Predict the Success of Bank Telemarketing. Decision Support Systems,
Elsevier, 62:22-31, June 2014.
capitalone/otvPlots documentation built on March 15, 2024, 8:25 a.m.
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| bankData | R Documentation |
Direct marketing campaigns of a Portuguese banking institution
Description
The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to access if the product (bank term deposit) would be ('yes') or not ('no') subscribed. Records are ordered by date (from May 2008 to November 2010), similar to data analyzed in Moro et al. [2014].
Usage
bankData
Format
A data frame with 45,211 rows and 19 variables:
- age
Age of the client, numeric.
- job
Type of job, a categorical variable with the levels:
'admin.','blue-collar','entrepreneur','housemaid','management','retired','self-employed','services','student','technician','unemployed', and'unknown'.- marital
Marital status, a categorical variable with levels:
'divorced','married','single', and'unknown'. Note that'divorced'means either divorced or widowed.- education
A categorical variable with levels:
'basic.4y','basic.6y','basic.9y','high.school','illiterate','professional.course','university.degree', and'unknown'.- default
Whether credit is in default, a categorical variable with levels:
'no','yes', and'unknown'.- balance
Account balance, numeric.
- housing
Whether the client has a housing loan, a categorical variable with levels:
'no','yes', and'unknown'.- loan
Whether the client has personal loan, a categorical variable with levels:
'no','yes', and'unknown'.- contact
Type of contact communication, a categorical variable with levels:
'cellular'and'telephone'.- duration
Last contact duration in seconds, a numeric variable.
- campaign
Number of contacts performed during this campaign for this client, including the last contact; a numeric variable.
- pdays
Number of days that passed by after the client was last contacted from a previous campaign; a numeric variable, with
999means that client was not previously contacted.- previous
Number of contacts performed before this campaign for this client, a numeric variable.
- poutcome
Outcome of the previous marketing campaign, a categorical variable with levels:
'failure','nonexistent', and'success'.- y
Whether the client has subscribed a term deposit, a categorical variable with levels:
'yes'and'no'.- date
Last contact date.
Source
https://archive.ics.uci.edu/ml/datasets/Bank+Marketing
Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.
S. Moro, P. Cortez, and P. Rita. (2014) A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems, Elsevier, 62:22-31, June 2014.
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