draggable-line-chart 1.0.0

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

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-line-chart

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. It can include the following keys:

  • 'title': The title of the chart.
  • '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.
  • '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.
  • '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.

• 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.

Raises

• ValueError: If the data is not a pandas Series or DataFrame or if the DataFrame does not have only numeric columns.

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): Same options as line chart

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): Same options as line chart except tension.

Example

import numpy as np
import pandas as pd
import streamlit as st

from draggable_charts import line_chart, scatter_chart, bezier_chart

st.header("Line charts")
st.subheader("Custom")
st.write("Drag the points vertically")
initial_data = pd.DataFrame({
    "Col1": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
    "Col2": [1, 4, 9, 16, np.nan, 36, 49, 64, 81, 200],
    "Col3": [-1, -2, -3, -4, -5, -6, -7, -8, -50, -100]
})

plot_options = {
    "title": "My Plot",
    "colors": ['#1f77b4', '#ff7f0e', '#2ca02c'],
    "x_label": "X Axis",  # Default: No text
    "y_label": "Y Axis",  # Default: No text
    "x_grid": True,  # default: True
    "y_grid": True,  # default: True
    'legend_position': 'right',  # default: 'top'
    'legend_align': 'start',  # default: 'center'
    'tension': 0,  # default: 0.3
    'fill_gaps': True,  # default: False
    'fixed_lines': ["Col3"],  # default: []
}
new_data = line_chart(data=initial_data, options=plot_options, key="my_chart")
# new_data

st.subheader("Default")
series_data = pd.Series([1, 2, 3, 4, 5, np.nan, 7, 8, 9, 10])
new_series_data = line_chart(data=series_data)
# new_series_data

st.header("Scatter chart")
st.subheader("Numerical")
st.write("Drag the dots to anywhere")
x_num = [1, 2, 3, 4, 5]
y = ["R", "G", "H"]
scatter_data = {
    "trace 1": {"x": x_num, "y": [1, 4, 9, 16, 25]},
    "trace 2": {"x": x_num, "y": [1, 8, 27, 64, 125]},
    "trace 3": {"x": x_num, "y": [1, 16, 81, 256, 625]},
}
new_scatter_data = scatter_chart(data=scatter_data)
# new_scatter_data

st.subheader("Categorical")
st.write("Drag from one category to another")
x_cat = ["A", "B", "C", "D", "E"]
y_cat = ["R", "G", "H", "I", "J"]
scatter_data = {
    "trace 1": {"x": x_cat, "y": ["R", "R", "H", "H", "J"]},
    "trace 2": {"x": x_cat, "y": ["R", "G", "H", "I", "J"]},
    "trace 3": {"x": x_cat, "y": ["G", "G", "G", "G", "G"]},
}
new_scatter_data = scatter_chart(
    data=scatter_data,
    options={"x_labels": x_cat, "y_labels": y_cat, "show_line": True}
)
# new_scatter_data

st.subheader("Num + Cat")
st.write("Drag continuous in Y and discrete in X")
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}
)
# new_scatter_data

st.subheader("Bezier charts")
st.write("Drag the blue points")
data = {
    "trace 1": {"x": [1, 2, 3, 4, 5], "y": [1, -8, 10, 16, -25]},
}
new_data = bezier_chart(data)
#new_data