pandas 标签居中的堆叠条形图

sr4lhrrt  于 2023-05-12  发布在  其他
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我正试图“稳健地”将数据标签集中在堆叠条形图中。下面给出了一个简单的代码示例和结果。正如您所看到的,数据标签并没有真正在所有矩形中居中。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()

oogrdqng

oogrdqng1#

导入测试DataFrame

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

matplotlib v3.4.2更新

  • 使用matplotlib.pyplot.bar_label,它会自动将值居中。
  • 有关.bar_label的其他详细信息和示例,请参见How to add value labels on a bar chart
  • 使用pandas v1.2.4进行测试,它使用matplotlib作为绘图引擎。
  • 如果条形图的某些部分将为零,请参阅我的answer,它展示了如何为.bar_label()定制labels
  • 如果需要,ax.bar_label(c, fmt='%0.0f', label_type='center')将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')

其他小段标签移除选项可以使用fmt

  • 在matplotlib 3.7更新中,bar_labelfmt参数现在接受{}样式的格式字符串。
  • fmt=lambda x: f'{x:.0f}' if x > 0 else ''
  • fmt=lambda x: np.where(x > 0, f'{x:.0f}', '')np.where
ax = df.plot(kind='bar', stacked=True, figsize=(8, 6), rot=0, xlabel='Class', ylabel='Count')
for c in ax.containers:
    ax.bar_label(c, fmt=lambda x: f'{x:.0f}' if x > 0 else '', label_type='center')

海运选项

Seaborn DataFrame格式

# 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

轴级图

# 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')

图级图

# 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')

原始应答

  • 使用.patches方法解包matplotlib.patches.Rectangle对象的列表,堆叠条形图的每个部分对应一个对象。
  • 每个.Rectangle都有用于提取定义矩形的各种值的方法。
  • 每个.Rectangle都是从左到右,从下到上的顺序,因此当迭代.patches时,每个级别的所有.Rectangle对象都按顺序出现。
  • 标签是使用f-stringlabel_text = f'{height}'制作的,因此可以根据需要添加任何其他文本,例如label_text = f'{height}%'
  • label_text = f'{height:0.0f}'将显示无小数位的数字。

Plot

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()

  • 要打印水平条,请执行以下操作:
  • kind='barh'
  • label_text = f'{width}'
  • if width > 0:
  • 署名:jsoma/chart.py
k3fezbri

k3fezbri2#

为什么要写va="bottom"?必须使用va="center"

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