Plotly Figure Widget 幫助我創(chuàng)建一個(gè)交互式散點(diǎn)圖，即，我可以在散點(diǎn)圖上選擇數(shù)據(jù)點(diǎn)，并根據(jù)選擇我的表小部件顯示記錄。我需要幫助將此表轉(zhuǎn)換為熊貓數(shù)據(jù)框。import plotly.graph_objs as goimport plotly.offline as pyimport pandas as pdimport numpy as npfrom ipywidgets import interactive, HBox, VBoxpy.init_notebook_mode()df = pd.read_csv('https://raw.githubusercontent.com/jonmmease/plotly_ipywidget_notebooks/master/notebooks/data/cars/cars.csv')f = go.FigureWidget([go.Scatter(y = df['City mpg'], x = df['City mpg'], mode = 'markers')])scatter = f.data[0]N = len(df)scatter.x = scatter.x + np.random.rand(N)/10 *(df['City mpg'].max() - df['City mpg'].min())scatter.y = scatter.y + np.random.rand(N)/10 *(df['City mpg'].max() - df['City mpg'].min())scatter.marker.opacity = 0.5def update_axes(xaxis, yaxis):    scatter = f.data[0]    scatter.x = df[xaxis]    scatter.y = df[yaxis]    with f.batch_update():        f.layout.xaxis.title = xaxis        f.layout.yaxis.title = yaxis        scatter.x = scatter.x + np.random.rand(N)/10 *(df[xaxis].max() - df[xaxis].min())        scatter.y = scatter.y + np.random.rand(N)/10 *(df[yaxis].max() - df[yaxis].min())axis_dropdowns = interactive(update_axes, yaxis = df.select_dtypes('int64').columns, xaxis = df.select_dtypes('int64').columns)# Create a table FigureWidget that updates on selection from points in the scatter plot of ft = go.FigureWidget([go.Table(    header=dict(values=['ID','Classification','Driveline','Hybrid'],                fill = dict(color='#C2D4FF'),                align = ['left'] * 5),    cells=dict(values=[df[col] for col in ['ID','Classification','Driveline','Hybrid']],               fill = dict(color='#F5F8FF'),               align = ['left'] * 5))])def selection_fn(trace,points,selector):    t.data[0].cells.values = [df.loc[points.point_inds][col] for col in ['ID','Classification','Driveline','Hybrid']]scatter.on_selection(selection_fn)# Put everything togetherVBox((HBox(axis_dropdowns.children),f,t))只是期望在將散點(diǎn)圖上的點(diǎn)選擇到熊貓數(shù)據(jù)框后創(chuàng)建的表。