clock-plot 0.2

This package provides a simple way to visualize patterns in timeseries data mapping 24 hours onto a polar plot

clock_plot

clock_plot provides a simple way to visualize timeseries data mapping 24 hours onto the 360 degrees of a polar plot. For usage, please see the examples.ipynb Jupyter notebook

Installation

To install this package run: pip install clock_plot

Available features

Time features are automatically generated for your timeseries. These features include:

Feature	Type	Description	Example Values
year	int	Calendar year	2022
month	str	Calendar month	"January"
year_month	int	Calendar year and month in the format YYYYMM	202201
day	int	Day of calendar year	25
date	str	Expressed in the format YYYY-MM-DD	"2022-01-25"
week	int	ISO week of the calendar year	5
dayofweek	str	Short version of day of week	"Tue"
weekend	str	Either "weekday" or "weekend", where "weekend" is Saturday and Sunday	"weekend" (Sat/Sun) "weekday" (Mon-Fri)
hour	int	Hour of the day in 24 clock	14
minute	int	Minute of the hour	42
degrees	int	Angle around 24 hour clock-face measured in degrees	341
season	str	Season of the year defined based on month, with Winter being Dec-Feb	"Winter" (Dec-Feb) "Spring" (Mar-May) "Summer" (Jun-Aug) "Autumn" (Sep-Nov)

These can be used to filter your data and format your plot.

For example you could filter for a particular year, plot seasons with different colors and weekday vs weekend days with different line dashes. Examples of this are given in examples.ipynb