带居中标签的堆叠条形图

Question

我试图在堆叠条形图中“稳健地”居中数据标签。下面给出了一个简单的代码示例和结果。如您所见，数据标签并不是在所有矩形中都居中。我错过了什么？

import numpy as np
import matplotlib.pyplot as plt

A = [45, 17, 47]
B = [91, 70, 72]

fig = plt.figure(facecolor="white")

ax = fig.add_subplot(1, 1, 1)
bar_width = 0.5
bar_l = np.arange(1, 4)
tick_pos = [i + (bar_width / 2) for i in bar_l]

ax1 = ax.bar(bar_l, A, width=bar_width, label="A", color="green")
ax2 = ax.bar(bar_l, B, bottom=A, width=bar_width, label="B", color="blue")
ax.set_ylabel("Count", fontsize=18)
ax.set_xlabel("Class", fontsize=18)
ax.legend(loc="best")
plt.xticks(tick_pos, ["C1", "C2", "C3"], fontsize=16)
plt.yticks(fontsize=16)

for r1, r2 in zip(ax1, ax2):
    h1 = r1.get_height()
    h2 = r2.get_height()
    plt.text(r1.get_x() + r1.get_width() / 2., h1 / 2., "%d" % h1, ha="center", va="bottom", color="white", fontsize=16, fontweight="bold")
    plt.text(r2.get_x() + r2.get_width() / 2., h1 + h2 / 2., "%d" % h2, ha="center", va="bottom", color="white", fontsize=16, fontweight="bold")

plt.show()

Answer 1

• 以下方法更简洁，易于缩放。
• 将数据放入熊猫中。数据帧是绘制堆叠条形图的最简单方法。
• 使用 pandas.DataFrame.plot.bar（堆叠=真）或熊猫。数据帧（种类='条形'，堆叠=真）是绘制堆叠条形图的最简单方法。
  • 此方法返回一个 matplotlib.axes.Axes 或它们的一个 numpy.ndarray。

  import pandas as pd
  import matplotlib.pyplot as plt
  
  A = [45, 17, 47]
  B = [91, 70, 72]
  C = [68, 43, 13]
  
  # pandas dataframe
  df = pd.DataFrame(data={'A': A, 'B': B, 'C': C})
  df.index = ['C1', 'C2', 'C3']
  
       A   B   C
  C1  45  91  68
  C2  17  70  43
  C3  47  72  13
  

  < li >使用< code > matplotlib . py plot . bar _ label ，它会自动将值放在条形的中央。 < li >有关< code >的更多详细信息和示例，请参阅如何在条形图上添加数值标签。条形标签。 < li >使用< code>pandas v1.2.4进行测试，该版本使用< code>matplotlib作为绘图引擎。 < li >如果条形图的某些部分为零，请参见我的回答，其中显示了如何为< code >自定义< code >标签。bar_label()。 < li> ax.bar_label(c，fmt='%0.0f '，label_type='center')会根据需要更改数字格式以不显示小数位。

  ax = df.plot(kind='bar', stacked=True, figsize=(8, 6), rot=0, xlabel='Class', ylabel='Count')
  for c in ax.containers:
  
      # Optional: if the segment is small or 0, customize the labels
      labels = [v.get_height() if v.get_height() > 0 else '' for v in c]
      
      # remove the labels parameter if it's not needed for customized labels
      ax.bar_label(c, labels=labels, label_type='center')
  

  

  • seborn是matplotlib
  的高级api
  • seaborn.barplotapi没有堆叠选项，但它可以用sns.histplot或sns.displot实现。

  # create the data frame
  df = pd.DataFrame(data={'A': A, 'B': B, 'C': C, 'cat': ['C1', 'C2', 'C3']})
  
      A   B   C cat
  0  45  91  68  C1
  1  17  70  43  C2
  2  47  72  13  C3
  
  # convert the dataframe to a long form
  df = df.melt(id_vars='cat')
  
    cat variable  value
  0  C1        A     45
  1  C2        A     17
  2  C3        A     47
  3  C1        B     91
  4  C2        B     70
  5  C3        B     72
  6  C1        C     68
  7  C2        C     43
  8  C3        C     13
  

  # plot
  ax = sns.histplot(data=df, x='cat', hue='variable', weights='value', discrete=True, multiple='stack')
  
  # iterate through each container
  for c in ax.containers:
  
      # Optional: if the segment is small or 0, customize the labels
      labels = [v.get_height() if v.get_height() > 0 else '' for v in c]
      
      # remove the labels parameter if it's not needed for customized labels
      ax.bar_label(c, labels=labels, label_type='center')
  

  

  # plot
  g = sns.displot(data=df, x='cat', hue='variable', weights='value', discrete=True, multiple='stack')
  
  # iterate through each axes
  for ax in g.axes.flat:
  
      # iterate through each container
      for c in ax.containers:
  
          # Optional: if the segment is small or 0, customize the labels
          labels = [v.get_height() if v.get_height() > 0 else '' for v in c]
  
          # remove the labels parameter if it's not needed for customized labels
          ax.bar_label(c, labels=labels, label_type='center')
  

  

  • 使用. patches方法解压matplotlib.patches.Rectangle对象的列表，堆叠条的每个部分一个。
    • 每个。矩形有提取定义矩形的各种值的方法。
    • 每个。矩形是从左到右，从下到上的顺序，所以所有的。矩形对象，对于每个级别，在遍历时按顺序显示。补丁。
    • label_text=f“｛高度：0.0f｝”将显示不带小数位数的数字

    plt.style.use('ggplot')
    
    ax = df.plot(stacked=True, kind='bar', figsize=(12, 8), rot='horizontal')
    
    # .patches is everything inside of the chart
    for rect in ax.patches:
        # Find where everything is located
        height = rect.get_height()
        width = rect.get_width()
        x = rect.get_x()
        y = rect.get_y()
        
        # The height of the bar is the data value and can be used as the label
        label_text = f'{height}'  # f'{height:.2f}' to format decimal values
        
        # ax.text(x, y, text)
        label_x = x + width / 2
        label_y = y + height / 2
    
        # plot only when height is greater than specified value
        if height > 0:
            ax.text(label_x, label_y, label_text, ha='center', va='center', fontsize=8)
        
    ax.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.)    
    ax.set_ylabel("Count", fontsize=18)
    ax.set_xlabel("Class", fontsize=18)
    plt.show()
    

    

    < li >要绘制水平条: < ul > < Li > < code > kind = ' barh ' < Li > < code > label _ text = f“{ width }” < li> 如果宽度