pm4py.vis.view_dotted_chart(log: Union[EventLog, DataFrame], format: str = 'png', attributes=None, bgcolor: str = 'white')[source]#

Displays the dotted chart

The dotted chart is a classic visualization of the events inside an event log across different dimensions. Each event of the event log is corresponding to a point. The dimensions are projected on a graph having: - X axis: the values of the first dimension are represented there. - Y-axis: the values of the second dimension are represented there. - Color: the values of the third dimension are represented as different colors for the points of the dotted chart.

The values can be either string, numeric or date values, and are managed accordingly by the dotted chart. The dotted chart can be built on different attributes. A convenient choice for the dotted chart is to visualize the distribution of cases and events over the time, with the following choices: - X-axis: the timestamp of the event. - Y-axis: the index of the case inside the event log. - Color: the activity of the event.

The aforementioned choice permits to identify visually patterns such as: - Batches. - Variations in the case arrival rate. - Variations in the case finishing rate.

  • log – Event log

  • format (str) – Image format

  • attributes – Attributes that should be used to construct the dotted chart. If None, the default dotted chart will be shown: x-axis: time y-axis: cases (in order of occurrence in the event log) color: activity. For custom attributes, use a list of attributes of the form [x-axis attribute, y-axis attribute, color attribute], e.g., [“concept:name”, “org:resource”, “concept:name”])

import pm4py

pm4py.view_dotted_chart(dataframe, format='svg')
pm4py.view_dotted_chart(dataframe, attributes=['time:timestamp', 'concept:name', 'org:resource'])

Deprecated since version 2.3.0: This will be removed in 3.0.0. the dotted chart visualization will be removed in a future release.