Python Dash 如何显示数据表中的所有行？

Question

I have made an interactive table using dash and plotly in python, currently the table only gives the first few rows, is there a way to make the table have pages or be scrollable so all rows are interactively viewable?

Here is the code I'm using:

data = X_interactive

app = JupyterDash(__name__)

app.layout = html.Div([
    dash_table.DataTable(
        id='datatable-interactivity',
        columns=[
            {"name": i, "id": i, "deletable": True, "selectable": True} for i in X_interactive.columns
        ],
        data=X_interactive.to_dict('records'),
        editable=True,
        filter_action="native",
        sort_action="native",
        sort_mode="multi",
        column_selectable="single",
        row_selectable="multi",
        row_deletable=True,
        selected_columns=[],
        selected_rows=[],
        page_action="native",
        page_current= 0,
        page_size= 10,
    ),
    html.Div(id='datatable-interactivity-container')
])

@app.callback(
    Output('datatable-interactivity', 'style_data_conditional'),
    Input('datatable-interactivity', 'selected_columns')
)
def update_styles(selected_columns):
    return [{
        'if': { 'column_id': i },
        'background_color': '#D2F3FF'
    } for i in selected_columns]

@app.callback(
    Output('datatable-interactivity-container', "children"),
    Input('datatable-interactivity', "derived_virtual_data"),
    Input('datatable-interactivity', "derived_virtual_selected_rows"))
def update_graphs(rows, derived_virtual_selected_rows):

    if derived_virtual_selected_rows is None:
        derived_virtual_selected_rows = []

    dff = X_interactive if rows is None else pd.DataFrame(rows)

    colors = ['#7FDBFF' if i in derived_virtual_selected_rows else '#0074D9'
              for i in range(len(dff))]

    return [
        dcc.Graph(
            id=column,
            figure={
                "data": [
                    {
                        "x": dff["Gene"],
                        "y": dff[column],
                        "type": "bar",
                        "marker": {"color": colors},
                    }
                ],
                "layout": {
                    "xaxis": {"automargin": True},
                    "yaxis": {
                        "automargin": True,
                        "title": {"text": column}
                    },
                    "height": 250,
                    "margin": {"t": 10, "l": 10, "r": 10},
                },
            },
        )
        # check if column exists - user may have deleted it
        # If `column.deletable=False`, then you don't
        # need to do this check.
        for column in ["col1", "col2", "col3"] if column in dff
    ]

    
app.run_server(mode='inline',port=8056)

From trying to find similar questions I've been trying to get pages with pagination_settings but I'm new to python and not sure how to properly get it into my current code without losing how the table currently is (interactive with being able to filter columns).

Just trying to add pagination_settings within html.Div() gives me an error:

TypeError: The `dash_table.DataTable` component (version 4.11.2) with the ID "datatable-interactivity" received an unexpected keyword argument: `pagination_settings

Answer 1

pagination-settings isn't a valid arguement as seen by the error below:

TypeError: The `dash_table.DataTable` component (version 4.10.1) with the ID 

"table" received an unexpected keyword argument: `pagination_settings`
Allowed arguments: active_cell, cell_selectable, column_selectable, columns, css, data, data_previous, data_timestamp, derived_filter_query_structure, derived_viewport_data, derived_viewport_indices, derived_viewport_row_ids, derived_viewport_selected_columns, derived_viewport_selected_row_ids, derived_viewport_selected_rows, derived_virtual_data, derived_virtual_indices, derived_virtual_row_ids, derived_virtual_selected_row_ids, derived_virtual_selected_rows, dropdown, dropdown_conditional, dropdown_data, editable, end_cell, export_columns, export_format, export_headers, fill_width, filter_action, filter_query, fixed_columns, fixed_rows, hidden_columns, id, include_headers_on_copy_paste, is_focused, loading_state, locale_format, markdown_options, merge_duplicate_headers, page_action, page_count, page_current, page_size, persisted_props, persistence, persistence_type, row_deletable, row_selectable, selected_cells, selected_columns, selected_row_ids, selected_rows, sort_action, sort_as_null, sort_by, sort_mode, start_cell, style_as_list_view, style_cell, style_cell_conditional, style_data, style_data_conditional, style_filter, style_filter_conditional, style_header, style_header_conditional, style_table, tooltip, tooltip_conditional, tooltip_data, tooltip_delay, tooltip_duration, virtualization

And by looking at the official documentation to get pagination in a datatable

Code from the documentation:

import dash
from dash.dependencies import Input, Output
import dash_table
import pandas as pd


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

df[' index'] = range(1, len(df) + 1)

app = dash.Dash(__name__)

PAGE_SIZE = 5

app.layout = dash_table.DataTable(
    id='datatable-paging',
    columns=[
        {"name": i, "id": i} for i in sorted(df.columns)
    ],
    page_current=0,
    page_size=PAGE_SIZE,
    page_action='custom'
)
if __name__ == '__main__':
    app.run_server(debug=True)

You can see that the required and accepted arguments are page_current , page_size , page_action , page_count (from the error).

In your code, I think adding the page_count argument should end up being the fix.

Answer 2

If you want to display all dataframe rows in your datatable set this option:

pd.set_option('display.max_rows',None)