DataBuilder
Have you ever needed some dummy data to demonstrate some basic data analysis / machine learning topics?
DataBuilder can save you time by creating customized dummy data sets within minutes.
Installation
pip install databuilder
Quick Example
import databuilder as db
# make a dummy dataset about "our employees"
config = {
'fields': {
'empID': db.ID(),
'first_name': db.Name(first_only=True),
'last_name': db.Name(last_only=True),
'department': db.Group(["Sales", "Acct", "Mktg", "IT"]),
'salary': db.NormalDist(50000, 10000),
'hire_date': db.Date("1990-01-01", "2020-12-31")
}
}
# create a Pandas DataFrame with
# the fields defined in `config`
df = db.create_df(config, n=200)
print(df.head(2))
#
# Example output:
# empID first_name last_name department salary hire_date
# 0 1 Frank Ward IT 69210 2004-05-05
# 1 2 Barbara George Mktg 46744 2019-05-20
Complete Usage Guide
Detailed docs on how to use DataBuilder can be found in the docs/ folder of this repo (or click here)
Metadata
Release files for databuilder 0.0.2
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| File | Size | Uploaded | Provenance | Actions |
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| databuilder-0.0.2-py3-none-any.whl | Python 3 | none | any | Details for databuilder-0.0.2-py3-none-any.whl |
Total release size: 16.7 kB
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Release files / databuilder-0.0.2-py3-none-any.whl
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