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Visualizing event sequences

When studying sequences of events (e.g care trajectories, drug sequences, ...), it might be useful to visualize individual sequences. To that end, we provide the plot_event_sequences function to plot individual sequences given an events dataframe.

Load a synthetic dataset

An events dataset has been created to illustrate the visualization function. It can be load as follows :

from eds_scikit.datasets.synthetic.event_sequences import load_event_sequences

df_events = load_event_sequences()

The df_events dataset contains occurrences of 12 events, derived from 7 events' families ("A", "B", "C", "D", "E", "F", "G).

Events can be both one-time and continuous.

An index_date is also provided and refers to the inclusion date of each patient in the cohort.

The first raws of the dataframe are as follows :

df_events.head()
| | person_id | event_family | event | event_start_datetime | event_end_datetime | index_date | |---|-----------|--------------|-------|----------------------|--------------------|------------| | 0 | 1 | A | a1 | 2020-01-01 | 2020-01-02 | 2020-01-01 | | 1 | 1 | A | a2 | 2020-01-03 | 2020-01-04 | 2020-01-01 | | 2 | 1 | B | b1 | 2020-01-03 | 2020-01-06 | 2020-01-01 | | 3 | 1 | C | c1 | 2020-01-05 | NaT | 2020-01-01 | | 4 | 1 | C | c2 | 2020-01-06 | 2020-01-08 | 2020-01-01 |

Visualize individual sequences

Basic usage

Individual sequences of events can be plotted using the plot_event_sequences function :

from eds_scikit.plot.event_sequences import plot_event_sequences

chart = plot_event_sequences(df_events)
chart

Image title

Advanced parameters

Further configuration can be provided, including : - dim_mapping : dictionary to set colors and labels for each event type. - family_col: column name of events' families. - list_person_ids: List of specific person_id - same_x_axis_scale: boolean to set all individual charts to the same scale

Here we provide an exemple of dim_mapping, and we plot sequences aggregated following the event_family classification.

dim_mapping = {
    "a1": {"color": (255, 200, 150), "label": "eventA1"},
    "a2": {"color": (255, 150, 150), "label": "eventA2"},
    "a3": {"color": (255, 100, 150), "label": "eventA3"},
    "b1": {"color": (100, 200, 150), "label": "eventB1"},
    "c1": {"color": (50, 255, 255), "label": "eventC1"},
    "c2": {"color": (50, 200, 255), "label": "eventC2"},
    "c3": {"color": (50, 100, 255), "label": "eventC3"},
    "d1": {"color": (180, 200, 100), "label": "eventD1"},
    "d2": {"color": (180, 150, 100), "label": "eventD2"},
    "e1": {"color": (130, 60, 10), "label": "eventE1"},
    "f1": {"color": (255, 0, 0), "label": "eventF1"},
    "g1": {"color": (100, 0, 200), "label": "eventG1"},
}

plot_event_sequences(
    df_events,
    family_col="event_family",
    dim_mapping=dim_mapping,
    same_x_axis_scale=True,
    title="Event sequences",
)

Image title

Please check the documentation for further details on the function's parameters.

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