Connecting Backend Paging with a Graph

[BalaNagendraReddy]

Question

Hey team,

I have a question regarding the use of Connecting Backend Paging with a Graph.

Based on the filtering of the table graph needs to be change, How we can achieve the same by using vizro.

Thank you so much for the amazing work on this tool, and for the help in advance!

from dash import Dash, dash_table, dcc, html, Input, Output, callback
import pandas as pd

app = Dash(__name__)

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminder2007.csv')

PAGE_SIZE = 5

app.layout = html.Div(
    className="row",
    children=[
        html.Div(
            dash_table.DataTable(
                id='table-paging-with-graph',
                columns=[
                    {"name": i, "id": i} for i in sorted(df.columns)
                ],
                page_current=0,
                page_size=20,
                page_action='custom',

                filter_action='custom',
                filter_query='',

                sort_action='custom',
                sort_mode='multi',
                sort_by=[]
            ),
            style={'height': 750, 'overflowY': 'scroll'},
            className='six columns'
        ),
        html.Div(
            id='table-paging-with-graph-container',
            className="five columns"
        )
    ]
)

operators = [['ge ', '>='],
             ['le ', '<='],
             ['lt ', '<'],
             ['gt ', '>'],
             ['ne ', '!='],
             ['eq ', '='],
             ['contains '],
             ['datestartswith ']]


def split_filter_part(filter_part):
    for operator_type in operators:
        for operator in operator_type:
            if operator in filter_part:
                name_part, value_part = filter_part.split(operator, 1)
                name = name_part[name_part.find('{') + 1: name_part.rfind('}')]

                value_part = value_part.strip()
                v0 = value_part[0]
                if (v0 == value_part[-1] and v0 in ("'", '"', '`')):
                    value = value_part[1: -1].replace('\\' + v0, v0)
                else:
                    try:
                        value = float(value_part)
                    except ValueError:
                        value = value_part

                # word operators need spaces after them in the filter string,
                # but we don't want these later
                return name, operator_type[0].strip(), value

    return [None] * 3


@callback(
    Output('table-paging-with-graph', "data"),
    Input('table-paging-with-graph', "page_current"),
    Input('table-paging-with-graph', "page_size"),
    Input('table-paging-with-graph', "sort_by"),
    Input('table-paging-with-graph', "filter_query"))
def update_table(page_current, page_size, sort_by, filter):
    filtering_expressions = filter.split(' && ')
    dff = df
    for filter_part in filtering_expressions:
        col_name, operator, filter_value = split_filter_part(filter_part)

        if operator in ('eq', 'ne', 'lt', 'le', 'gt', 'ge'):
            # these operators match pandas series operator method names
            dff = dff.loc[getattr(dff[col_name], operator)(filter_value)]
        elif operator == 'contains':
            dff = dff.loc[dff[col_name].str.contains(filter_value)]
        elif operator == 'datestartswith':
            # this is a simplification of the front-end filtering logic,
            # only works with complete fields in standard format
            dff = dff.loc[dff[col_name].str.startswith(filter_value)]

    if len(sort_by):
        dff = dff.sort_values(
            [col['column_id'] for col in sort_by],
            ascending=[
                col['direction'] == 'asc'
                for col in sort_by
            ],
            inplace=False
        )

    return dff.iloc[
        page_current*page_size: (page_current + 1)*page_size
    ].to_dict('records')


@callback(
    Output('table-paging-with-graph-container', "children"),
    Input('table-paging-with-graph', "data"))
def update_graph(rows):
    dff = pd.DataFrame(rows)
    return html.Div(
        [
            dcc.Graph(
                id=column,
                figure={
                    "data": [
                        {
                            "x": dff["country"],
                            "y": dff[column] if column in dff else [],
                            "type": "bar",
                            "marker": {"color": "#0074D9"},
                        }
                    ],
                    "layout": {
                        "xaxis": {"automargin": True},
                        "yaxis": {"automargin": True},
                        "height": 250,
                        "margin": {"t": 10, "l": 10, "r": 10},
                    },
                },
            )
            for column in ["pop", "lifeExp", "gdpPercap"]
        ]
    )


if __name__ == '__main__':
    app.run(debug=True)

https://dash.plotly.com/datatable/callbacks

Code/Examples

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Other information

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Which package?

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• [X] I agree to follow the Code of Conduct.

[Joseph-Perkins]

hi @BalaNagendraReddy 👋 thanks for the question! we will double check and reply with guidance on how this might be achieved in Vizro 👍

in the meantime we wanted to check whether you're also aiming to retain the ability to sort and filter the data in the table, using the inbuilt controls at the top of the table?

[BalaNagendraReddy]

Hi @Joseph-Perkins ,

Thanks for your reply.

Mainly, focusing on filter rather than sorting, based on the filter, graph needs to be change. That is my expectation.