circlepacking

D3Blocks.circlepacking(df, size: str = 'sum', zoom: str = 'click', speed: int = 750, border={'color': '#FFFFFF', 'fill': '#FFFFFF', 'padding': 5, 'width': 1.5}, font: dict = {'color': '#000000', 'outlinecolor': '#FFFFFF', 'size': 20, 'type': 'Source Serif Pro'}, title: str = 'Circlepacking - D3blocks', filepath: str = 'Circlepacking.html', figsize=[900, 1920], showfig: bool = True, overwrite: bool = True, notebook: bool = False, save_button: bool = True, return_html: bool = False, reset_properties: bool = True)

Circlepacking block.

The Circlepacking chart is a visualization to hierarchically show the data as a set of nested circles. For demonstration purposes, the “energy” and “stormofswords” dataset can be used. The javascript code is forked from Mike Bostock and then Pythonized.

Parameters:

  • df (pd.DataFrame()) –

    Input data containing the following columns:

    • ’source’, ‘target’, ‘weight’

    • ’level0’, ‘level1’, ‘level2’, ‘weight’

  • size (str (default: "sum")) –

    Size of the nodes can automatically be set in with:

    • ’sum’ : This is the sum of the weights for the edges

    • ’constant’ : All nodes are set to 1

  • speed (int (default: 750)) – Speed in ms to zoom in/out

  • zoom (str (default: "click")) –

    Zooming method.

    • ’click’

    • ’mouseover’

  • border (dict.) –

    border properties.

    • {‘color’: ‘#FFFFFF’, ‘width’: 1.5, ‘fill’: ‘#FFFFFF’, “padding”: 2}

    • border color: color for the circles

    • width: width for the circles

    • fill: fill color for the circles

    • padding: size of the circles

  • font (dict.) –

    font properties.

    • {‘size’: 20, ‘type’:’sans-serif’}

  • title (String, (default: None)) –

    Title of the figure.

    • ’Circlepacking’

  • filepath (String, (Default: user temp directory)) –

    • File path to save the output.

    • Temporarily path: ‘d3blocks.html’

    • Relative path: ‘./d3blocks.html’

    • Absolute path: ‘c://temp//d3blocks.html’

    • None: Return HTML

  • figsize (tuple) –

    Size of the figure in the browser, [width, height].

    • [1000, 1200]

    • [None, None]: Use the screen resolution.

  • showfig (bool, (default: True)) –

    • True: Open browser-window.

    • False: Do not open browser-window.

  • overwrite (bool, (default: True)) –

    • True: Overwrite the html in the destination directory.

    • False: Do not overwrite destination file but show warning instead.

  • notebook (bool) –

    • True: Use IPython to show chart in notebook.

    • False: Do not use IPython.

  • save_button (bool, (default: True)) –

    • True: Save button is shown in the HTML to save the image in svg.

    • False: No save button is shown in the HTML.

  • return_html (bool, (default: False)) –

    • True: Return html

    • False: Nothing is returned

  • reset_properties (bool, (default: True)) –

    • True: Reset the node_properties at each run.

    • False: Use the d3.node_properties()

Returns:

  • d3.node_properties (DataFrame of dictionary) – Contains properties of the unique input label/nodes/samples.

  • d3.edge_properties (DataFrame of dictionary) – Contains properties of the unique input edges/links.

  • d3.config (dictionary) – Contains configuration properties.

Examples

>>> # Load d3blocks
>>> from d3blocks import D3Blocks
>>> #
>>> # Initialize
>>> d3 = D3Blocks()
>>> #
>>> # Load example data
>>> df = d3.import_example('animals')
>>> df = d3.import_example('energy')
>>> #
>>> # Plot
>>> d3.circlepacking(df)
>>> #

Examples

>>> # Load d3blocks
>>> from d3blocks import D3Blocks
>>> #
>>> # Initialize
>>> d3 = D3Blocks(chart='Circlepacking', frame=True)
>>> #
>>> # Import example
>>> df = d3.import_example('energy')
>>> #
>>> # Node properties
>>> d3.set_node_properties(df)
>>> print(d3.node_properties)
>>> #
>>> d3.set_edge_properties(df)
>>> print(d3.edge_properties)
>>> #
>>> # Show the chart
>>> d3.show()

Examples

>>> # Load d3blocks
>>> from d3blocks import D3Blocks
>>> #
>>> # Initialize
>>> d3 = D3Blocks()
>>> #
>>> # Import example
>>> df = d3.import_example('energy')
>>> #
>>> html = d3.circlepacking(df,
>>>                         speed=1500,
>>>                         zoom='mouseover',
>>>                         filepath='c://temp//circlepacking.html',
>>>                         border={'color': '#FFFFFF', 'width': 1.5, 'fill': '#FFFFFF', "padding": 2},
>>>                         overwrite=True,
>>>                         )
>>> #
>>> # Show the chart
>>> d3.show()

Input Data

The input dataset is a DataFrame that is hierarchically ordered from left to right. The number can be 3 levels and the column weight is obligatory.

#                      source            target   weight
# 0      Agricultural 'waste'    Bio-conversion  124.729
# 1            Bio-conversion            Liquid    0.597
# 2            Bio-conversion            Losses   26.862
# 3            Bio-conversion             Solid  280.322
# 4            Bio-conversion               Gas   81.144
# ..                      ...               ...      ...
# 63       Thermal generation  District heating   79.329
# 64                    Tidal  Electricity grid    9.452
# 65  UK land based bioenergy    Bio-conversion  182.010
# 66                     Wave  Electricity grid   19.013
# 67                     Wind  Electricity grid  289.366

# [68 rows x 3 columns]

Charts