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import numpy as np
import pandas as pd
import panel as pn


The Vizzu pane renders Vizzu charts inside Panel. Note that to use the Vizzu pane in the notebook, the Panel extension has to be loaded with ‘vizzu’ as an argument to ensure that vizzu.js is initialized.


For details on other options for customizing the component see the layout and styling how-to guides.

  • object (dict | pd.DataFrame): The data expressed as a Python dictionary of arrays or DataFrame.

  • animation (dict): Animation settings (see vizzu.Anim).

  • config (dict): The config contains all of the parameters needed to render a particular static chart or a state of an animated chart (see vizzu.Config.Chart).

  • columns (list): Optional column definitions. If not defined will be inferred from the data.

  • tooltips (boolean): Whether to enable tooltips on the chart.


  • animate: Accepts a dictionary of new ‘data’, ‘config’ and ‘style’ values which is used to update the chart.

  • stream: Streams new data to the plot.

  • patch: Patches one or more rows in the data.

The Vizzu renders a dataset (defined either as a dictionary of columns or a DataFrame) given a config defining how to plot the data:

data = {
    'Name': ['Alice', 'Bob', 'Ted', 'Patrick', 'Jason', 'Teresa', 'John'],
    'Weight': 50+np.random.randint(0, 10, 7)*10

vizzu = pn.pane.Vizzu(
    data, config={'geometry': 'rectangle', 'x': 'Name', 'y': 'Weight', 'title': 'Weight by person'},
    duration=400, height=400, sizing_mode='stretch_width', tooltip=True


One of the major selling points behind Vizzu is the dynamic animations when either the data or the config is updated, e.g. if we change the ‘geometry’ we can see the animation smoothly transition between the two states.

vizzu.animate({'geometry': 'circle'})
vizzu.animate({'geometry': 'area'})

Note that the Vizzu pane will keep track of any changes you make as part of the .animate() call ensuring that the plot can be re-created easily:


{'geometry': 'area', 'x': 'Name', 'y': 'Weight', 'title': 'Weight by person'}

Column Types#

Vizzu supports two column types:

  • 'dimension': Usually used for non-numeric data and/or the independent dimension of a chart (e.g. the x-axis)

  • 'measure': Numeric values usually used for dependent variables of a chart (e.g. the y-axis values)

The Vizzu pane automatically infers the types based on the dtypes of the data but in certain cases it may be necessary to explicitly override the type of a column using column_types parameter. One common example is when plotting integers on the x-axis, which would ordinarily be treated as a ‘measure’ but should be treated as the independent dimension in the case of a line or bar chart.

The example below demonstrates this case, here we want to treat the ‘index’ as an independent variable and override the default inferred type with column_types={'index': 'dimension'}:

df = pd.DataFrame(np.random.randn(50), columns=list('Y')).cumsum()

    df, column_types={'index': 'dimension'}, config={'x': 'index', 'y': 'Y', 'geometry': 'line'},
    height=300, sizing_mode='stretch_width'


Vizzu provides a variety of preset chart types. In ipyvizzu these are expressed by calling helper methods on the Config object. The Vizzu pane instead allows you to provide 'preset' as a key of the config. In the example below we dynamically create a config that switches the preset based on a RadioButtonGroup:

windturbines = pd.read_csv('')

agg = windturbines.groupby(['p_year', 't_manu'])[['p_cap']].sum().sort_index(level=0).reset_index()

chart_type = pn.widgets.RadioButtonGroup(options={'Stream': 'stream', 'Bar': 'stackedColumn'}, align='center')

preset_chart = pn.pane.Vizzu(
    config=pn.bind(lambda preset: {'preset': preset, 'x': 'p_year', 'y': 'p_cap', 'stackedBy': 't_manu'}, chart_type),
    column_types={'p_year': 'dimension'},
        'plot': {
            "xAxis": {
                "label": {
                    "angle": "-45deg"

pn.Column(chart_type, preset_chart).embed()


The Vizzu pane exposes a number of options which can be changed from both Python and Javascript. Try out the effect of these parameters interactively:

pn.Row(vizzu.controls(jslink=True), vizzu)

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