draggable-charts

draggable-charts

Streamlit component that displays a interactive charts with draggable points. Users can click and drag points on the chart to adjust their values. The updated data of the chart is returned.

Installation instructions

pip install draggable-charts

Usage

Line Chart:

• data (pd.Series, pd.DataFrame): The data to display in the chart. Index is always X values and columns are Y values. Columns should have only numeric values. Series.name is the trace name. If a DataFrame is provided, the column names are the trace names.

• options (dict[str: any], optional): A dictionary of options for the chart.

• on_change (Callable, optional): A callback function that is called with the new data of the chart after user interaction.

• args (tuple, optional): The arguments to pass to the callback function.

• kwargs (dict, optional): The keyword arguments to pass to the callback function.

• key (str, optional): An optional string to use as the unique key for the widget. If this is None, and the component's arguments are changed, the component will be re-mounted in the Streamlit frontend and lose its current state.

Returns

• new_data (pd.Series, pd.DataFrame): The data of the chart after user interaction. The format is the same as the input format.

Scatter Chart:

• data (dict): The data to display in the chart. Control points will be added in between. It has the form {"trace 1": {"x": [1,2,3], "y": [1, 4, 9]}, "trace 2": ... }

• options (dict): A dictionary of options for the chart.

• on_change (Callable, optional): A callback function that is called with the new data of the chart after user interaction.

• args (tuple, optional): The arguments to pass to the callback function.

• kwargs (dict, optional): The keyword arguments to pass to the callback function.

• key (str, optional): An optional string to use as the unique key for the widget. If this is None, and the component's arguments are changed, the component will be re-mounted in the Streamlit frontend and lose its current state.

Returns

• new_data (dict[str, dict]): The data of the chart after user interaction. The format is the same as the input format.

Bezier Chart:

• data (dict): The data to display in the chart. It has the form {"trace 1": {"x": [1,2,3], "y": [1, 4, 9]}, "trace 2": ... }

• options (dict): A dictionary of options for the chart.

• on_change (Callable, optional): A callback function that is called with the new data of the chart after user interaction.

• args (tuple, optional): The arguments to pass to the callback function.

• kwargs (dict, optional): The keyword arguments to pass to the callback function.

• key (str, optional): An optional string to use as the unique key for the widget. If this is None, and the component's arguments are changed, the component will be re-mounted in the Streamlit frontend and lose its current state.

Returns

• new_data (dict[str, dict]): The data of the chart after user interaction. The format is the same as the input format.

Cuadratic Bezier Chart:

• data (dict): The data to display in the chart. It has the form {"trace 1": {"x": [1,2,3], "y": [1, 4, 9]}, "trace 2": ... }

• options (dict): A dictionary of options for the chart.

• on_change (Callable, optional): A callback function that is called with the new data of the chart after user interaction.

• args (tuple, optional): The arguments to pass to the callback function.

• kwargs (dict, optional): The keyword arguments to pass to the callback function.

• key (str, optional): An optional string to use as the unique key for the widget. If this is None, and the component's arguments are changed, the component will be re-mounted in the Streamlit frontend and lose its current state.

Returns

• new_data (dict[str, dict]): The data of the chart after user interaction. The format is the same as the input format.

options:

All options are sent in the same dictionary options. There are common options that applies to the canvas, and specific options applied to traces. Canvas options are:

Canvas options:

• 'title': The title of the chart.
• 'x_label': Text in x-axis.
• 'y_label': Text in y-axis.
• 'x_grid': A boolean indicating whether to display the grid for the x-axis.
• 'y_grid': A boolean indicating whether to display the grid for the y-axis.
• 'legend': A boolean indicating whether to display the legend. If not provided, the legend will be displayed by default.
• 'legend_position': The position of the legend. It can be 'top', 'left', 'bottom', or 'right'.
• 'legend_align': The alignment of the legend. It can be 'start', 'center', or 'end'. If not provided, default options will be used.
• 'labels': Default {}. Dictionary with a map from original labels to custom labels.
• 'x_format': Default None. A printf-style format string controlling how the canvas should display X numeric ticks. Check: https://d3js.org/d3-format#locale_format
• 'y_format': Default ".2~s". A printf-style format string controlling how the canvas should display Y numeric ticks.

Chart options:

• 'show_line: Boolean that indicates whether to display the line connecting the points on the graph.
• 'colors': A list of colors for the chart traces. Each color must be a hexadecimal color code. The order of the colors corresponds to the order of the columns.
• 'tension': The tension of the lines. 0 gives straight lines, 0.5 gives smooth lines. Default is 0.3.
• 'fill_gaps': A Boolean that indicates whether NaN values are filled in the lines. If False, lines will be broken at NaN values. Default is False.
• 'fixed_lines': List of column names that cannot be dragged. Default is an empty list.
• 'border_dash': Default [(0,0)]. A list of tuples with length and spacing of dashes per every trace. It will repeat if more traces than tuples are provided.
• 'point_radius': Default [3]. The radius of the point shape per trace. If set to 0, the point is not rendered.

Example

import streamlit as st

from draggable_charts import scatter_chart

st.subheader("Scatter")
x_cat = ["A", "B", "C", "D", "E"]
scatter_data = {
    "trace 1": {"x": x_cat, "y": [1, 4, 9, 16, 25]},
    "trace 2": {"x": x_cat, "y": [1, 8, 27, 64, 125]},
    "trace 3": {"x": x_cat, "y": [1, 16, 81, 256, 625]},
}
new_scatter_data = scatter_chart(
    data=scatter_data,
    options={"x_labels": x_cat, "show_line": True,
             "tension": 0, "fixed_lines": ["trace 1"]}
)
new_scatter_data