Skip to main content

Timeseries Analysis

Project description

timeseries

A Python library for the interpretation and treatment of time-series data.

pip install va-timeseries

What is it?

A set of methods to process timeseries data.

Main Features

Seasonal Decomposition -> trend -> detrend -> seasonal -> residual -> plot()

Seasonal Adjustment

timeseries.seasonal_pattern (series, period)
timeseries.series_frequencies (series)
timeseries.cycle_periods (series) <- estimate

Trending

timeseries.linear_regression (x, y)
timeseries.henderson (series, window)
timeseries.rolling_average (series, window)

Methods for identifying and describing trends in data.

Control Charts

cc = timeseries.control_chart(series, samples=8)

Predict

// predict (cycles)

Helper Methods

timeseries.fillna (series, filler=0)
timeseries.mean (series)
timeseries.standard_deviation (series)
timeseries.variance (series)
timeseries.matches (series, rule)
timeseries.f_x (series, function)

Dependencies

License

Apache-2.0

Credits

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

va-timeseries-1.0.5.tar.gz (223.5 kB view hashes)

Uploaded Source

Built Distribution

va_timeseries-1.0.5-py3-none-any.whl (16.1 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page