Event timestamp hist#

Class#

class retentioneering.tooling.event_timestamp_hist.event_timestamp_hist.EventTimestampHist(eventstream)[source]#

Plot the distribution of events over time. Can be useful for detecting time-based anomalies, and visualising general timespan of the eventstream.

Parameters:
eventstreamEventstreamType

See also

TimedeltaHist

Plot the distribution of the time deltas between two events.

UserLifetimeHist

Plot the distribution of user lifetimes.

Eventstream.describe

Show general eventstream statistics.

Eventstream.describe_events

Show general eventstream events statistics.

Notes

See Eventstream user guide for the details.

fit(raw_events_only=False, event_list=None, lower_cutoff_quantile=None, upper_cutoff_quantile=None, bins=20)[source]#

Calculate values for the histplot.

Parameters:
raw_events_onlybool, default False

If True - statistics will only be shown for raw events. If False - statistics will be shown for all events presented in your data.

event_listlist of str, optional

Specify events to be displayed.

lower_cutoff_quantilefloat, optional

Specify time distance quantile as the lower boundary. The values below the boundary are truncated.

upper_cutoff_quantilefloat, optional

Specify time distance quantile as the upper boundary. The values above the boundary are truncated.

binsint or str, default 20

Generic bin parameter that can be the name of a reference rule or the number of bins. Passed to numpy.histogram_bin_edges.

Returns:
None
plot(width=6.0, height=4.5)[source]#

Create a sns.histplot based on the calculated values.

Parameters:
widthfloat, default 6.0

Width in inches.

heightfloat, default 4.5

Height in inches.

Returns:
matplotlib.axes.Axes

The matplotlib axes containing the plot.

property values#
Returns:
tuple(np.ndarray, np.ndarray)

  1. The first array contains the values for histogram.

  2. The first array contains the bin edges.

Eventstream#

Eventstream.event_timestamp_hist(event_list=None, raw_events_only=False, lower_cutoff_quantile=None, upper_cutoff_quantile=None, bins=20, width=6.0, height=4.5, show_plot=True)[source]#

Plot distribution of events over time. Can be useful for detecting time-based anomalies, and visualising general timespan of the eventstream.

Parameters:
show_plotbool, default True

If True, histogram is shown.

See other parameters’ description

EventTimestampHist

Returns:
EventTimestampHist

A EventTimestampHist class instance with given parameters.