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