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A Python library for generating synthetic time series data

Project description

Synthetic Time Series Data Generator

A Python library for generating synthetic time series data

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Installation

Repo

After cloning this repo and creating a virtual environment, run the following command:

pip install --editable .

PyPi

Coming soon

Usage

d = DataGen()
d.start_datetime = "2019-01-01"
d.end_datetime = "2019-01-03"
d.granularity = Granularity.FIVE_MIN
d.add_dimension("product", random_choice(["A", "B", "C", "D"]))

metric1_trend = SinusoidalTrend(name="sine", amplitude=10, freq=24, phase=0, noise_level=10)

d.add_metric(name="temperature", trends=[metric1_trend])

metric2_trend = SinusoidalTrend(name="sine", amplitude=1, freq=12, phase=0, noise_level=2)
metric3_trend = LinearTrend(name="linear", limit=100, offset=10, noise_level=1)

d.add_metric(name="humidity", trends=[metric2_trend,metric3_trend])
d.generate_data()
df = d.data

# Use utility functions
processed_df = some_function(df)

Release method

  1. git tag <x.x.x>
  2. git push origin <x.x.x>

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