`chart`

Displays data sets in a chart or a group of charts.

The chart control is based on the plotly.js graphs library.

Plotly is a graphing library that provides a vast number of visual representations of datasets with all sorts of customization capabilities. Taipy exposes the Plotly components through the chart control and heavily depends on the underlying implementation.

The core principles of creating charts in Taipy are explained in the Basic concepts section.
Advanced concepts are described in the Advanced features section.

Chart types catalog¶

Because there are so many different ways of representing data, we have sorted the chart types supported by Taipy by application category:

Basic charts

Statistical charts

Scientific charts

Financial charts

Maps

Map plots

Specialized charts

Properties¶

Name	Type	Default	Description
`data`^(★)	`any` dynamic	Required	The data object bound to this chart control. See the section on the data property below for details.
`type`	`str` indexed	scatter	Chart type. See the Plotly chart type documentation for details.
`mode`	`str` indexed	lines+markers	Chart mode. See the Plotly chart mode documentation for details.
`x`	`str` indexed		Column name for the x axis.
`y`	`str` indexed		Column name for the y axis.
`z`	`str` indexed		Column name for the z axis.
`lon`	`str` indexed		Column name for the longitude value, for 'scattergeo' charts. See Plotly Map traces.
`lat`	`str` indexed		Column name for the latitude value, for 'scattergeo' charts. See Plotly Map traces.
`r`	`str` indexed		Column name for the r value, for 'scatterpolar' charts. See Plotly Polar charts.
`theta`	`str` indexed		Column name for the theta value, for 'scatterpolar' charts. See Plotly Polar charts.
`high`	`str` indexed		Column name for the high value, for 'candlestick' charts. See Plotly Candlestick charts.
`low`	`str` indexed		Column name for the low value, for 'candlestick' charts. See Ploty Candlestick charts.
`open`	`str` indexed		Column name for the open value, for 'candlestick' charts. See Plotly Candlestick charts.
`close`	`str` indexed		Column name for the close value, for 'candlestick' charts. See Plotly Candlestick charts.
`measure`	`str` indexed		Column name for the measure value, for 'waterfall' charts. See Plotly Waterfall charts.
`locations`	`str` indexed		Column name for the locations value. See Plotly Choropleth maps.
`values`	`str` indexed		Column name for the values value. See Plotly Pie charts or Plotly Funnel Area charts.
`labels`	`str` indexed		Column name for the labels value. See Plotly Pie charts.
`parents`	`str` indexed		Column name for the parents value. See Plotly Treemap charts.
`text`	`str` indexed		Column name for the text associated to the point for the indicated trace. This is meaningful only when mode has the text option.
`base`	`str` indexed		Column name for the base value. Used in bar charts only. See the Plotly bar chart base documentation for details."
`title`	`str`		The title of this chart control.
`render`	`bool` dynamic	True	If True, this chart is visible on the page.
`on_range_change`	`Callback`		The callback function that is invoked when the visible part of the x axis changes. The function receives three parameters: state (`State`): the state instance. id (optional[str]): the identifier of the chart control. payload (dict[str, any]): the full details on this callback's invocation, as emitted by Plotly.
`columns`	`str\|list[str]\|dict[str, dict[str, str]]`	All columns	The list of column names str: ;-separated list of column names list[str]: list of names dict: {"column_name": {format: "format", index: 1}} if index is specified, it represents the display order of the columns. If not, the list order defines the index
`label`	`str` indexed		The label for the indicated trace. This is used when the mouse hovers over a trace.
`name`	`str` indexed		The name of the indicated trace.
`selected`	`dynamic(list[int]\|str` indexed		The list of the selected point indices .
`color`	`str` indexed		The color of the indicated trace (or a column name for scattered).
`selected_color`	`str` indexed		The color of the selected points for the indicated trace.
`marker`	`dict[str, any]` indexed		The type of markers used for the indicated trace. See marker for details. Color, opacity, size and symbol can be column name.
`line`	`str\|dict[str, any]` indexed		The configuration of the line used for the indicated trace. See line for details. If the value is a string, it must be a dash type or pattern (see dash style of lines for details).
`selected_marker`	`dict[str, any]` indexed		The type of markers used for selected points in the indicated trace. See selected marker for details.
`layout`	`dict[str, any]` dynamic		The plotly.js compatible layout object.
`plot_config`	`dict[str, any]`		The plotly.js compatible configuration options object.
`options`	`dict[str, any]` indexed		The plotly.js compatible data object where dynamic data will be overridden..
`orientation`	`str` indexed		The orientation of the indicated trace.
`text_anchor`	`str` indexed		Position of the text relative to the point. Valid values are: top, bottom, left, and right.
`xaxis`	`str` indexed		The x axis identifier for the indicated trace.
`yaxis`	`str` indexed		The y axis identifier for the indicated trace.
`width`	`str\|int\|float`	"100%"	The width, in CSS units, of this element.
`height`	`str\|int\|float`		The height, in CSS units, of this element.
`template`	`dict`		The Plotly layout template.
`template[dark]`	`dict`		The Plotly layout template applied over the base template when theme is dark.
`template[light]`	`dict`		The Plotly layout template applied over the base template when theme is not dark.
`decimator`	`taipy.gui.data.Decimator` indexed		A decimator instance for the indicated trace that will reduce the size of the data being sent back and forth. If defined as indexed, it will impact only the indicated trace; if not, it will apply only the the first trace.
`rebuild`	`bool` dynamic	False	Allows dynamic config refresh if set to True.
`on_change`	`Callback`		The name of a function that is triggered when the value is updated. The parameters of that function are all optional: state (`State`): the state instance. var_name (str): the variable name. value (any): the new value.
`propagate`	`bool`	App config	Allows the control's main value to be automatically propagated. The default value is defined at the application configuration level. If True, any change to the control's value is immediately reflected in the bound application variable.
`active`	`bool` dynamic	True	Indicates if this component is active. An inactive component allows no user interaction.
`id`	`str`		The identifier that will be assigned to the rendered HTML component.
`properties`	`dict[str, any]`		Bound to a dictionary that contains additional properties for this element.
`class_name`	`str` dynamic		The list of CSS class names that will be associated with the generated HTML Element. These class names will be added to the default `taipy-<element_type>`.
`hover_text`	`str` dynamic		The information that is displayed when the user hovers over this element.

^(★)data is the default property for this visual element.

Details¶

The chart control has a large set of properties to deal with the many types of charts it supports and the different kinds of customization that can be defined.

The data property¶

All the data sets represented in the chart control must be assigned to its data property.

The supported types for the data property are:

A list of values:
Most chart types use two axes (x/y or theta/r). When receiving a data that is just a series of values, Taipy sets the first axis values to the value index ([0, 1, ...]) and the values of the second axis to the values of the collection.
A Pandas DataFrame:
Taipy charts can be defined by setting the appropriate axis property value to the DataFrame column name.
A dictionary:
The value is converted into a Pandas DataFrame where each key/value pair is converted to a column named key and the associated value. Note that this will work only when all the values of the dictionary keys are series that have the same length.
A list of lists of values:
If all the lists have the same length, Taipy creates a Pandas DataFrame with it.
If sizes differ, then a DataFrame is created for each list, with a single column called "<index>/0" where index is the index of the current list in the data array. Then an array is built using all those DataFrames and used as described below.
A Numpy series:
Taipy internally builds a Pandas DataFrame with the provided data.
A list of Pandas DataFrames:
This can be used when your chart must represent data sets of different sizes. In this case, you must set the axis property (x, y, r, etc.) value to a string with the format: "<index>/<column>" where index is the index of the DataFrame you want to refer to (starting at index 0) and column would be the column name of the referenced DataFrame.
A list of dictionaries
The data is converted to a list of Pandas DataFrames.

Indexed properties¶

Chart controls can hold several traces that may display different data sets.
To indicate properties for a given trace, you will use the indexed properties (the ones whose type is indexed(type)). When setting the value of an indexed property, you can specify which trace this property should apply to: you will use the property_name[index] syntax, where the indices start at index 1, to specify which trace is targeted for this property.

Indexed properties can have a default value (using the property_name syntax with no index) which is overridden by any specified indexed property:
Here is an example where i_property is an indexed property:

# This value applies to all the traces of the chart control
general_value = <some_value>
# This value applies to only the second trace of the chart control
specific_value = <some_other_value>

page = "<|...|chart|...|i_property={general_value}|i_property[2]={specific_value}|...|>"

In the definition for page, you can see that the value general_value is set to the property without the index operator ([]) syntax. That means it applies to all the traces of the chart control.
specific_value, on the other hand, applies only to the second trace.

An indexed property can also be assigned an array, without the index operator syntax. Then each value of the array is set to the property at the appropriate index, in sequence:

values = [
    value1,
    value2,
    value3
]

page = "<|...|chart|...|i_property={values}|...|>"

is equivalent to

page = "<|...|chart|...|i_property[1]={value1}|i_property[2]={value2}|i_property[3]={value3}|...|>"

or slightly shorter (and if there are no more than three traces):

page = "<|...|chart|...|i_property={value1}|i_property[2]={value2}|i_property[3]={value3}|...|>"

The rebuild property¶

You can download the entire source code used in this section from the GitHub repository.

Some of the chart control's properties may result in Taipy GUI having to entirely reconstruct the graphical component running on the front-end (the user's browser). The chart control provides some properties that are dynamic and allow for an instant page update. Changing the values of the other properties is not immediately reflected on the page.
Setting the value of the rebuild property to True, however, will ensure that the control is entirely rebuilt on the front-end and refreshed on the page. Using this property will have an impact on the user experience since it involves a potentially extensive code generation. Make sure, when you use the rebuild property, that the deployment environment can support the performance hit gracefully for the end users.

Here is an example of how this property can be used.
Consider the code below:

chart.py

from taipy.gui import Gui
import math

# x values: [-10..10]
x_range = range(-10, 11)
data = {
    "X": x_range,
    "Y": [x*x for x in x_range],
    "Y2": [math.cos(2 * math.pi * x / 10) / 360 for x in x_range]
}

types = [("bar", "Bar"), ("line", "Line")]
selected_type = types[0]

page = """
<|{data}|chart|type={selected_type[0]}|x=X|y=Y|>

<|{selected_type}|toggle|lov={types}|>
"""

Gui(page=page).run()

This application displays a chart representing two functions of the values stored in the array x_range: the squared value and a cosine function.
A toggle control is added to the page to let the user choose the chart type dynamically: a line chart or a bar chart.

Here is what this application looks like when you run it:

If the user switches the type in the toggle button, this would be the resulting page:

You can see that although the toggle value was changed, the chart was not impacted by the new setting. That is because the type property is not dynamic.
To display the chart with the new type setting, one would have to refresh the browser page.

However, Taipy GUI can rebuild and refresh the chart automatically if you set it's rebuild property to True. The Markdown chart definition can be changed to:

<|{data}|chart|type={selected_type[0]}|x=X|y=Y|rebuild|>

If you run the application again, as soon as the user selects the new chart type using the toggle button, the page will reflect the change without explicit refresh:

After the type was switched, with *rebuild* set to True

Styling¶

All the chart controls are generated with the "taipy-chart" CSS class. You can use this class name to select the charts on your page and apply style.

The Stylekit provides a specific class that you can use to style charts:

has-background
When the chart control uses the has-background class, the rendering of the chart background is left to the charting library.
The default behavior is to render the chart transparently.

Usage¶

Here is a list of several sub-sections that you can check to get more details on a specific domain covered by the chart control: