<jupyter_start><jupyter_text>Example: CanvasXpress dashboard Chart No. 1This example page demonstrates how to, using the Python package, create a chart that matches the CanvasXpress online example located at:https://www.canvasxpress.org/examples/dashboard-1.htmlThis example is generated using the reproducible JSON obtained from the above page and the `canvasxpress.util.generator.generate_canvasxpress_code_from_json_file()` function.Everything required for the chart to render is included in the code below.  Simply run the code block.<jupyter_code>from canvasxpress.canvas import CanvasXpress 
from canvasxpress.js.collection import CXEvents 
from canvasxpress.render.jupyter import CXNoteBook 

cx = CanvasXpress(
    render_to="dashboard1",
    data={
        "y": {
            "vars": [
                "Age"
            ],
            "smps": [
                "1",
                "2",
                "3",
                "4",
                "5",
                "6",
                "7",
                "8",
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        }
    },
    config={
        "graphOrientation": "vertical",
        "graphType": "Bar",
        "groupingFactors": [
            "Pclass"
        ],
        "stackBy": "Survived",
        "summaryType": "count",
        "theme": "lastAirBenderFire"
    },
    width=613,
    height=613,
    events=CXEvents(),
    after_render=[
        [
            "createHistogram",
            [
                "Survived",
                None,
                None
            ]
        ],
        [
            "createDOE",
            [
                None,
                None,
                None
            ]
        ]
    ],
    other_init_params={
        "version": 35,
        "events": False,
        "info": False,
        "afterRenderInit": False,
        "noValidate": True
    }
)

display = CXNoteBook(cx) 
display.render(output_file="dashboard_1.html")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08719838578594849, 'fraction_numerical': 0.07619407934684116, 'mean_word_length': 0.241643082490489, 'pattern_counts': {'":': 25, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 1, 'lorem ipsum': 0, 'www.': 1, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '369839', 'license': 'MIT', 'n_tokens_mistral': 58934, 'n_tokens_neox': 46988, 'n_words': 9513, 'path': 'tutorials/notebook/cx_site_chart_examples/dashboard_1.ipynb', 'repo_name': 'docinfosci/canvasxpress-python', 'size': '214098'}