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      1. 将线段添加到绘图图的简洁方法(使用 python/jupyter 笔记本)?

        Succint way to add line segments to plotly graph (with python/jupyter notebook)?(将线段添加到绘图图的简洁方法(使用 python/jupyter 笔记本)?)

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                • 本文介绍了将线段添加到绘图图的简洁方法(使用 python/jupyter 笔记本)?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着跟版网的小编来一起学习吧!

                  问题描述

                  我想用这样的几个水平线段创建一个棒棒糖图 -

                  I want to create a lollipop plot with several horizontal line segments like this - https://python-graph-gallery.com/184-lollipop-plot-with-2-group. I'd like to use plotly since I prefer the graphics (and easy interactivity) but can't find a succint way.

                  There's both line graphs (https://plot.ly/python/line-charts/) and you can add lines in the layout (https://plot.ly/python/shapes/#vertical-and-horizontal-lines-positioned-relative-to-the-axes), but both of these solutions require each line segment to be added separately, with about 4-8 lines of code each. While I could just for-loop this, would appreciate if anyone can point me to anything with inbuilt vectorization, like the matplotlib solution (first link)!

                  Edit: Also tried the following code, to first make the plot ala matplotlib, then convert to plotly. The line segments disappear in the process. Starting to think it's just impossible.

                  mpl_fig = plt.figure()
                  
                  # make matplotlib plot - WITH HLINES
                  plt.rcParams['figure.figsize'] = [5,5]
                  ax = mpl_fig.add_subplot(111)
                  ax.hlines(y=my_range, xmin=ordered_df['value1'], xmax=ordered_df['value2'], 
                  color='grey', alpha=0.4)
                  ax.scatter(ordered_df['value1'], my_range, color='skyblue', alpha=1, 
                  label='value1')
                  ax.scatter(ordered_df['value2'], my_range, color='green', alpha=0.4 , 
                  label='value2')
                  ax.legend()
                  
                  # convert to plotly
                  plotly_fig = tls.mpl_to_plotly(mpl_fig)
                  plotly_fig['layout']['xaxis1']['showgrid'] = True
                  plotly_fig['layout']['xaxis1']['autorange'] = True
                  plotly_fig['layout']['yaxis1']['showgrid'] = True
                  plotly_fig['layout']['yaxis1']['autorange'] = True
                  
                  # plot: hlines disappear :/
                  iplot(plotly_fig)
                  

                  解决方案

                  Plotly doesn't provide a built in vectorization for such chart, because it can be done easily by yourself, see my example based on your provided links:

                  import pandas as pd
                  import numpy as np
                  import plotly.offline as pyo
                  import plotly.graph_objs as go
                  
                  # Create a dataframe
                  value1 = np.random.uniform(size = 20)
                  value2 = value1 + np.random.uniform(size = 20) / 4
                  df = pd.DataFrame({'group':list(map(chr, range(65, 85))), 'value1':value1 , 'value2':value2 })
                  
                  my_range=range(1,len(df.index)+1)
                  
                  # Add title and axis names
                  data1 = go.Scatter(
                          x=df['value1'],
                          y=np.array(my_range),
                          mode='markers',
                          marker=dict(color='blue')
                      )
                  
                  
                  data2 = go.Scatter(
                          x=df['value2'],
                          y=np.array(my_range),
                          mode='markers',
                          marker=dict(color='green')
                      )
                  
                  # Horizontal line shape
                  shapes=[dict(
                          type='line',
                          x0 = df['value1'].loc[i],
                          y0 = i + 1,
                          x1 = df['value2'].loc[i],
                          y1 = i + 1,
                          line = dict(
                              color = 'grey',
                              width = 2
                          )
                      ) for i in range(len(df['value1']))]
                  
                  
                  layout = go.Layout(
                      shapes = shapes,
                      title='Lollipop Chart'
                  )
                  
                  # Plot the chart
                  fig = go.Figure([data1, data2], layout)
                  
                  pyo.plot(fig)
                  

                  With the result I got:

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