通过选择散点图上的点来更新破折号表
我正在使用仪表板。这是我的代码：
# IMPORT SECTION
import dash
import dash_table
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import numpy as np
import pandas as pd
from math import ceil
from matplotlib.cm import Set3
# INPUT DATA
n = 7
d_min = 0.2
d_max = 0.8
d_step = 0.1
N_min = 2000
N_max = 8000
N_step = 1000
D = 40
h = 20
dataframe_file = 'data.xlsx'
# COLOR AND FONT DEFINITION
grey = '#e0e1f5'
black = '#212121'
scatter_colors = ['#' + ''.join(['{:02x}'.format(int(255*Set3(i)[j])) for j in range(3)]) for i in range(n)]
fontsize = 18
fontfamily = 'Arial, sans-serif'
# READ CSV DATA
df = pd.read_excel(dataframe_file)
# CREATE DATA FOR DASH DATATABLE
df_scatter_colors = ceil(len(df) / len(scatter_colors)) * scatter_colors
df_scatter_colors = df_scatter_colors[:len(df)]
df.insert(loc = 0, column = 'COLOR', value = df_scatter_colors)
headers = [{"name": i, "id": i} for i in df.columns]
table = df.to_dict('records')
table_colors = [{'if': {'row_index': i, 'column_id': 'COLOR'},
'background-color': df.iloc[i]['COLOR'],
'color': df.iloc[i]['COLOR']} for i in range(df.shape[0])]
# CREATE DATA AND LAYOUT FOR THE SCATTERPLOT
x_jitter = 0.05 * N_step * np.random.randn(len(df))
y_jitter = 0.05 * d_step * 1000 * np.random.randn(len(df))
data = [go.Scatter(x = df['NUMBER'] + x_jitter,
y = df['DIAMETER'] + y_jitter,
text = df['PRODUCT'],
mode = 'markers',
hoverinfo = 'skip',
showlegend = False,
marker_color = 'rgba(0, 0, 0, 0)',
marker = {'size': 25,
'line': {'color': df['COLOR'],
'width': 8}})]
layout = go.Layout(plot_bgcolor = black,
hovermode = 'x unified',
uirevision = 'value')
figure = go.Figure(data = data, layout = layout)
# DASHBOARD LAYOUT
app = dash.Dash(external_stylesheets = [dbc.themes.BOOTSTRAP])
app.layout = html.Div(id = 'general_div',
children = [html.Div(id = 'first_row',
children = [dcc.Graph(id = 'main_graph',
figure = figure,
style = {'height': 800,
'width': 1400})],
className = 'row'),
html.Div(id = 'second_row',
children = [dash_table.DataTable(id = 'main_table',
columns = headers,
data = table,
style_data_conditional = table_colors,
style_table = {'margin-left': '3vw',
'margin-top': '3vw'},
style_cell = {'font-family': fontfamily,
'fontSize': fontsize},
style_header = {'backgroundColor': 'rgb(230, 230, 230)',
'fontWeight': 'bold'})],
className = 'row')])
# CALLBACK DEFINITION
@app.callback(Output('main_table', 'style_data_conditional'),
[Input('main_graph', 'selectedData'),
Input('main_table', 'style_data_conditional')])
def display_selected_data(selectedData, style_data_conditional):
# what to do here and how to run this callback?
return style_data_conditional
if __name__ == "__main__":
app.run_server()
仪表板上显示一个散点图（dcc.Graph）和一个表格（dash_table.DataTable）。散点图的每个点对应于表的特定行，我从excel文件读取这些数据。
excel文件中的数据采用以下格式：
PRODUCT CODE NUMBER DIAMETER
AAAAA 1412 8000 0.049
BBBBB 1418 3900 0.08
CCCCC 1420 7600 0.06
DDDDD 1426 8500 0.049
EEEEE 1430 3900 0.08
FFFFF 1442 3900 0.08
GGGGG 1490 8500 0.049
HHHHH 1504 9000 0.18
IIIII 1514 5500 0.224
JJJJJ 1584 7600 0.06
KKKKK 1606 8500 0.049
LLLLL 1618 7600 0.06
MMMMM 1638 7600 0.06
NNNNN 1640 7600 0.06
OOOOO 1666 3900 0.08
PPPPP 1670 8000 0.049
QQQQQ 1672 8000 0.049
RRRRR 1674 7600 0.06
SSSSS 1700 7100 0.071
TTTTT 1704 8500 0.049
UUUUU 1712 7600 0.06
VVVVV 1718 7600 0.06
WWWWW 1722 8000 0.065
我想实现此功能：当用户在散点图中选择某个点时，代码将突出显示表中的相应行（例如将这些行中单元格的背景色更改为'pink'， 'COLOR'列除外，该列保持其颜色）。
检查了以下来源：
- dash-datatable-individual-highlight-using-style-data-conditionals-works-unusual
- dash-datatable-style-data-conditional-row-vice
- interactive-graphing
我试图这样绘制一个回调，但是没有成功：
@app.callback(Output('selected_data', 'children'),
[Input('main_graph', 'selectedData'),
Input('main_table', 'style_data_conditional')])
def display_selected_data(selectedData, style_data_conditional):
selected_points = []
for point in selectedData['points']:
selected_points.append(point['marker.line.color'])
selected = [{'if': {'filter': '{COLOR} eq ' + f'"{color}"',
'column_id': 'PRODUCT'},
'backgroundColor': 'pink'} for color in selected_points]
style_data_conditional.extend(selected)
return style_data_conditional
谢谢。
版本信息
Python 3.7.0
dash 1.12.0
dash-bootstrap-components 0.10.1
dash-core-components 1.10.0
dash-html-components 1.0.3
matplotlib 3.0.2
numpy 1.15.4
plotly 4.7.0
1 个答案:
答案 0 :(得分：2)
我设法通过将selectedData作为来自main_graph的输入并通过功能main_table处理style_data_conditional的{{1}}作为输出来解决了这个问题。 br />
在这里，我用深灰色为奇数行着色，以提高表的可见性，然后通过有条件的样式设置所选行的背景色。最后，我根据每行的颜色（每行的第一列上报告的颜色）更改第一列的背景。
代码：
update_table_style着色部分是这样的：
# IMPORT SECTION
import dash
import dash_table
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import numpy as np
import pandas as pd
from math import ceil
from matplotlib.cm import Set3
# INPUT DATA
n = 7
d_min = 0.2
d_max = 0.8
d_step = 0.1
N_min = 2000
N_max = 8000
N_step = 1000
D = 40
h = 20
dataframe_file = 'data.xlsx'
# COLOR AND FONT DEFINITION
grey = '#e0e1f5'
black = '#212121'
scatter_colors = ['#' + ''.join(['{:02x}'.format(int(255*Set3(i)[j])) for j in range(3)]) for i in range(n)]
fontsize = 18
fontfamily = 'Arial, sans-serif'
# READ CSV DATA
df = pd.read_excel(dataframe_file)
# CREATE DATA FOR DASH DATATABLE
df_scatter_colors = ceil(len(df) / len(scatter_colors)) * scatter_colors
df_scatter_colors = df_scatter_colors[:len(df)]
df.insert(loc = 0, column = 'COLOR', value = df_scatter_colors)
headers = [{"name": i, "id": i} for i in df.columns]
table = df.to_dict('records')
# CREATE DATA AND LAYOUT FOR THE SCATTERPLOT
x_jitter = 0.05 * N_step * np.random.randn(len(df))
y_jitter = 0.05 * d_step * 1000 * np.random.randn(len(df))
data = [go.Scatter(x = df['NUMBER'] + x_jitter,
y = df['DIAMETER'] + y_jitter,
text = df['PRODUCT'],
mode = 'markers',
hoverinfo = 'skip',
showlegend = False,
marker_color = 'rgba(0, 0, 0, 0)',
marker = {'size': 25,
'line': {'color': df['COLOR'],
'width': 8}})]
layout = go.Layout(plot_bgcolor = black,
hovermode = 'x unified',
uirevision = 'value')
figure = go.Figure(data = data, layout = layout)
def update_table_style(selectedData):
table_style_conditions = [{'if': {'row_index': 'odd'},
'backgroundColor': 'rgb(240, 240, 240)'}]
if selectedData != None:
points_selected = []
for point in selectedData['points']:
points_selected.append(point['pointIndex'])
selected_styles = [{'if': {'row_index': i},
'backgroundColor': 'pink'} for i in points_selected]
table_style_conditions.extend(selected_styles)
table_style_conditions.extend([{'if': {'row_index': i, 'column_id': 'COLOR'},
'background-color': df.iloc[i]['COLOR'],
'color': df.iloc[i]['COLOR']} for i in range(df.shape[0])])
return table_style_conditions
# DASHBOARD LAYOUT
app = dash.Dash(external_stylesheets = [dbc.themes.BOOTSTRAP])
app.layout = html.Div(id = 'general_div',
children = [html.Div(id = 'first_row',
children = [dcc.Graph(id = 'main_graph',
figure = figure,
style = {'height': 800,
'width': 1400})],
className = 'row'),
html.Div(id = 'second_row',
children = [dash_table.DataTable(id = 'main_table',
columns = headers,
data = table,
# style_data_conditional = table_colors,
style_table = {'margin-left': '3vw',
'margin-top': '3vw'},
style_cell = {'font-family': fontfamily,
'fontSize': fontsize},
style_header = {'backgroundColor': 'rgb(230, 230, 230)',
'fontWeight': 'bold'})],
className = 'row')])
# CALLBACK DEFINITION
@app.callback(Output('main_table', 'style_data_conditional'),
[Input('main_graph', 'selectedData')])
def display_selected_data(selectedData):
table_style_conditions = update_table_style(selectedData)
return table_style_conditions
if __name__ == "__main__":
app.run_server()
这是我得到的结果：
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