The data contains marketing information collected by direct phone calls to evaluate whether clients subscribe to a bank term deposit for a Portuguese banking institution.

File information

1. bank-additional-full.csv with all examples, ordered by date (from May 2008 to November 2010).
2. bank-additional.csv with 10% of the examples, randomly selected from bank-additional-full.csv.
3. bank-additional-balanced.csv with 10% of the examples selected with 50% of successful responses.
4. bank-additional-names.txt with detailed information on attributes, source of the dataset, and citation.

Column descriptors

Demographics:

• age: Customer's age (numeric)
• job: Type of job (categorical: 'admin.', 'services', ...)
• marital: Marital status (categorical: 'married', 'single', ...)
• education: Level of education (categorical: 'basic.4y', 'high.school', ...)

Past customer events:

• default: Has credit in default? (categorical: 'no', 'unknown', ...)
• housing: Has housing loan? (categorical: 'no', 'yes', ...)
• loan: Has personal loan? (categorical: 'no', 'yes', ...)

Past direct marketing contacts:

• contact: Contact communication type (categorical: 'cellular', 'telephone', ...)
• month: Last contact month of year (categorical: 'may', 'nov', ...)
• day_of_week: Last contact day of the week (categorical: 'mon', 'fri', ...)
• duration: Last contact duration, in seconds (numeric). Important note: If duration = 0 then y = 'no'.

Campaign information:

• campaign: Number of contacts performed during this campaign and for this client (numeric, includes the last contact)
• pdays: Number of days that passed by after the client was last contacted from a previous campaign (numeric)
• previous: Number of contacts performed before this campaign and for this client (numeric)
• poutcome: Outcome of the previous marketing campaign (categorical: nonexistent, success, ...)

Socioeconomic factors:

• emp.var.rate: Employment variation rate - quarterly indicator (numeric)
• cons.price.idx: Consumer price index - monthly indicator (numeric)
• cons.conf.idx: Consumer confidence index - monthly indicator (numeric)
• euribor3m: Euribor 3 month rate - daily indicator (numeric)
• nr.employed: Number of employees - quarterly indicator (numeric)

Target variable:

The dataset can be used to train a classifier to predict if a client will subscribe (yes/no) to a bank term deposit. Thus, y is whether the client subscribed to a term deposit (binary: 'yes', 'no')

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