如何迭代散点图的列表列表并创建独特元素的图例 [英] How to iterate a list of list for a scatter plot and create a legend of unique elements

问题描述

背景:

我有一个 list_of_x_and_y_list 包含 x 和 y 值，它看起来像:

[[[(44800, 14888), (132000, 12500), (40554, 12900)], [(None, 193788), (101653, 78880), (3866, 1600)]]]

我有另一个 data_name_list ["data_a","data_b"] 所以

• "data_a" = [(44800，14888)，(132000，12500)，(40554，12900)]

• "data_b" = [(None, 193788), (101653, 78880), (3866, 160000)]

list_of_x_and_y_list 的 len /或 data_name_list 的 len 为>20.

问题:

如何为 data_name_list 中的每个项目(颜色相同)创建散点图?

我尝试过的:

  fig = plt.figure()ax = fig.add_subplot(1, 1, 1)斧= plt.axes(facecolor ='#FFFFFF')prop_cycle = plt.rcParams['axes.prop_cycle']颜色= prop_cycle.by_key()['颜色']打印(list_of_x_and_y_list)对于x_and_y_list，data_name，zip中的颜色(list_of_x_and_y_list，data_name_list，颜色):对于 x_and_y_list 中的 x_and_y，:打印(x_and_y)x，y = x_and_yax.scatter(x，y，label = data_name，color = color)#"label = data_name"创建#庞大的传说清单！# :(plt.title('Matplot散点图')plt.legend(loc = 2)file_name = "3kstc.png"fig.savefig(file_name，dpi = fig.dpi)print("Generated:{}".format(file_name))

问题:

这个图例好像很长，不知道怎么改:

相关研究:

• Background:

  I have a list_of_x_and_y_list that contains x and y values which looks like:

  [[(44800, 14888), (132000, 12500), (40554, 12900)], [(None, 193788), (101653, 78880), (3866, 160000)]]
  

  I have another data_name_list ["data_a","data_b"] so that

  • "data_a" = [(44800, 14888), (132000, 12500), (40554, 12900)]

  • "data_b" = [(None, 193788), (101653, 78880), (3866, 160000)]

  The len of list_of_x_and_y_list / or len of data_name_list is > 20.

  Question:

  How can I create a scatter plot for each item (being the same colour) in the data_name_list?

  What I have tried:

     fig = plt.figure()
     ax = fig.add_subplot(1, 1, 1)
     ax = plt.axes(facecolor='#FFFFFF')
     prop_cycle = plt.rcParams['axes.prop_cycle']
     colors = prop_cycle.by_key()['color']
  
     print(list_of_x_and_y_list)
     for x_and_y_list, data_name, color in zip(list_of_x_and_y_list, data_name_list, colors):
         for x_and_y in x_and_y_list,:
            print(x_and_y)
            x, y = x_and_y
            ax.scatter(x, y, label=data_name, color=color) # "label=data_name" creates 
                                                           # a huge list as a legend! 
                                                           # :(
  
  
         plt.title('Matplot scatter plot')
         plt.legend(loc=2)
         file_name = "3kstc.png"
         fig.savefig(file_name, dpi=fig.dpi)
         print("Generated: {}".format(file_name))
  

  The Problem:

  The legend appears to be a very long list, which I don't know how to rectify:

  Relevant Research:

  • Matplotlib scatterplot
  • Scatter Plot
  • Scatter plot in Python using matplotlib

  解决方案

  The reason you get a long repeated list as a legend is because you are providing each point as a separate series, as matplotlib does not automatically group your data based on the labels.

  A quick fix is to iterate over the list and zip together the x-values and the y-values of each series as two tuples, so that the x tuple contains all the x-values and the y tuple the y-values.

  Then you can feed these tuples to the plt.plot method together with the labels.

  I felt that the names list_of_x_and_y_list were uneccessary long and complicated, so in my code I've used shorter names.

  import matplotlib.pyplot as plt
  
  data_series = [[(44800, 14888), (132000, 12500), (40554, 12900)],
                 [(None, 193788), (101653, 78880), (3866, 160000)]]
  data_names = ["data_a","data_b"]
  
  fig = plt.figure()
  ax = fig.add_subplot(1, 1, 1)
  ax = plt.axes(facecolor='#FFFFFF')
  prop_cycle = plt.rcParams['axes.prop_cycle']
  colors = prop_cycle.by_key()['color']
  
  for data, data_name, color in zip(data_series, data_names, colors):
      x,y = zip(*data)
      ax.scatter(x, y, label=data_name, color=color)
      plt.title('Matplot scatter plot')
      plt.legend(loc=1)
  

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