Plotly/Dash：如何使行索引唯一？

Question

目标：散点图中的选定点（使用套索工具）应在数据表中突出显示。如果可能的话，使用dash JS回调，但是任何其他的解决方案都会非常感激。

问题：行索引不是唯一的，但它们在每个类别（跟踪）中重复。因此，如果突出显示散点图左上角的3个最大点。只有2行而不是3行高亮显示。这两个中只有一个是正确的。请通过将悬停在绘图点上的标签与数据表中的信息进行比较来检查这一点。

问题/解决方案：如何使数据表的行索引唯一？或者选择适当的行以另一种方式高亮显示？

要求：

• 熊猫
• 破折号
• 仪表板引导组件
• 阴谋地

代码：

import pandas as pd
import dash
from dash.dependencies import Input, Output
import dash_table
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
import plotly.express as px

df = pd.DataFrame.from_dict(
    {'term': {0: 'GOCC:0043229', 1: 'GOCC:0098588', 2: 'GOCC:0005730', 3: 'GO:0005730', 4: 'GO:0005783', 5: 'GO:0031410', 6: 'KW-0732', 7: 'KW-0156', 8: 'KW-0010'},
    'description': {0: 'Intracellular organelle', 1: 'Bounding membrane of organelle', 2: 'Nucleolus', 3: 'nucleolus', 4: 'endoplasmic reticulum', 5: 'cytoplasmic vesicle', 6: 'Signal', 7: 'Chromatin regulator', 8: 'Activator'},
     'FG_count': {0: 370, 1: 92, 2: 126, 3: 31, 4: 63, 5: 23, 6: 9, 7: 410, 8: 500},
     'logFDR': {0: 3, 1: 4, 2: 5, 3: 6, 4: 7, 5: 8, 6: 5, 7: 1, 8: 2},
     'effectSize': {0: 0.053, 1: -0.049, 2: 0.046, 3: 0.047, 4: -0.040, 5: -0.027, 6: -0.024, 7: 0.025, 8: 0.025},
     'category': {0: 'TM', 1: 'TM', 2: 'TM', 3: 'GOCC', 4: 'GOCC', 5: 'UPK', 6: 'UPK', 7: 'GOCC', 8: 'UPK'}})

app = dash.Dash(__name__, prevent_initial_callbacks=True, external_stylesheets=[dbc.themes.BOOTSTRAP])

max_marker_size = 40
sizeref = 2.0 * max(df["FG_count"]) / (max_marker_size ** 2)
app.layout = html.Div(id='general_div',
    children=[
        html.Div(id='first_row',
            children=[
                    html.Div(dcc.Graph(id='scatter_plot',
                     figure=px.scatter(data_frame=df, x="logFDR", y="effectSize", color="category", size="FG_count", hover_data={"term": True, "description": True, "FG_count": True, "logFDR": False, "effectSize": False, "category": False }, custom_data=["term", "description", "FG_count"]).update_traces(hovertemplate="<b>%{customdata[0]}</b><br>%{customdata[1]}<br>Size: %{customdata[2]}<extra></extra>", mode='markers', marker={'sizemode': 'area', 'sizeref': sizeref, 'sizemin': 3, }).update_layout(hoverlabel=dict(font_size=12, )))),
                ]
            ),

        html.Br(),

        html.Div(id="second_row",
            children=[html.Div(dash_table.DataTable(id='main_datatable', columns= [{"name": colName, "id": colName} for colName in df.columns], data=df.to_dict('records'), sort_action="native", row_selectable="multi", selected_columns=[], selected_rows=[], style_as_list_view=True,  style_cell={'minWidth': "10px", "width": "50px", "maxWidth": "80px", "fontSize": "12px", "font-family": "sans-serif", "text_align": "center", "border": "1px",}, )),
                      ]
            ),

        html.Br(),

        ]
)


def update_table_style(selectedData):
    """
    in analogy to
    https://stackoverflow.com/questions/62516573/update-dash-table-by-selecting-points-on-scatter-plot?answertab=active#tab-top
    """
    table_style_conditions = [{'if': {'row_index': 'odd'}, 'backgroundColor': "#F5F5F5", }] + [{"if": {"state": "selected"}, "backgroundColor": "inherit !important", "border": "inherit !important", "text_align": "inherit !important", }] + [{"if": {"state": "active"}, "backgroundColor": "inherit !important", "border": "inherit !important", "text_align": "inherit !important", }]

    pointIndex_list = []
    if selectedData is not None:
        for point in selectedData["points"]:
            print(point)
            pointIndex_list.append(point["pointIndex"])
        print("pointIndex_list: {}".format(pointIndex_list))
        print("point indices are not unique: ", len(pointIndex_list), "!=", len(set(pointIndex_list)))

        selected_styles = [{'if': {'row_index': point['pointIndex']},
                            'backgroundColor': 'gold'} for point in selectedData['points']]
        return (selected_styles + table_style_conditions)
    return (table_style_conditions)


@app.callback(Output('main_datatable', 'style_data_conditional'),
              [Input('scatter_plot', 'selectedData')])
def display_selected_data(selectedData):
    table_style_conditions = update_table_style(selectedData)
    return table_style_conditions

if __name__ == '__main__':
    app.run_server(debug=True, host="127.0.0.1", port=8001)

Answer 1

需要替换以下代码块。然后它就起作用了。诀窍是不使用冗余的row_索引，而是使用“term”列作为“id”。由于“术语”可通过“自定义_数据”从散点图的“点”提取，因此随后可与“过滤器_查询”一起使用，以查找数据_表中的相应行。

df["id"] = df["term"]
df = df.set_index("id", drop=False)

dash_table.DataTable( ...
    style_data={'if': {'row_index': 'odd'}, 'backgroundColor': "#F5F5F5", },
    ...
)


def update_table_style(selectedData):
    """
    in analogy to
    https://stackoverflow.com/questions/62516573/update-dash-table-by-selecting-points-on-scatter-plot?answertab=active#tab-top
    """
    table_style_conditions = [{"if": {"state": "selected"}, "backgroundColor": "inherit !important", "border": "inherit !important", "text_align": "inherit !important", }] + [{"if": {"state": "active"}, "backgroundColor": "inherit !important", "border": "inherit !important", "text_align": "inherit !important", }] # [{'if': {'row_index': 'odd'}, 'backgroundColor': "#F5F5F5", }] +

    selected_term_list = []
    if selectedData is not None:
        for point in selectedData["points"]:
            selected_term_list.append(point["customdata"][0])
        print("selected_term_list: {}".format(selected_term_list))
        selected_styles = [{'if': {'filter_query': '{id}='+"{}".format(term)},
                            'backgroundColor': 'gold'} for term in selected_term_list]
        return (selected_styles + table_style_conditions)
    return (table_style_conditions)

@app.callback(Output('main_datatable', 'style_data_conditional'),
              [Input('scatter_plot', 'selectedData')])
def display_selected_data(selectedData):
    table_style_conditions = update_table_style(selectedData)
    return table_style_conditions