如何使用多个自定义值标记条形图答案

【问题标题】：How to label bars with multiple custom values如何使用多个自定义值标记条形图
【发布时间】：2022-09-25 00:55:05
【问题描述】：

我有这个数据框

rules count    percentage    groups   weight

A      15      24%            1       10
B      5       2%             2       30
C      25      50%            3       50

我有以下代码：

sns.set(rc={\'figure.figsize\':(18,9.5)})
plots = sns.barplot(x=\"rules\", y=\"count\", data=df, hue=df[\'groups\'], dodge=False)
percentage = df[\'percentage\'].tolist()
weight = df[\'weight\'].tolist()
patches = plots.patches
for i in range(len(patches)):
   x = patches[i].get_x() + patches[i].get_width()/2
   y = patches[i].get_height()+.09
   plots.annotate(\'{:.1f}%\'.format(percentage[i]), (x, y), ha=\'center\',  va=\'bottom\', size=14)
   plots.annotate(\'{:.0f}\'.format(weight[i]), (x, y), ha=\'center\', va=\'top\', color=\'white\', size=15, fontweight=\"bold\")

尝试用百分比注释条形图时出现以下错误。

条形图内部是另一个数字，对应于 df 中的权重列。

IndexError                                Traceback (most recent call last)
<ipython-input-120-0ef14f891711> in <module>()
      7    x = patches[i].get_x() + patches[i].get_width()/2
      8    y = patches[i].get_height()+.09
----> 9    plots.annotate(\'{:.1f}%\'.format(percentage[i]), (x, y), ha=\'center\',  va=\'bottom\', size=14)
     10    plots.annotate(\'{:.0f}\'.format(weight[i]), (x, y), ha=\'center\', va=\'top\', color=\'white\', size=15, fontweight=\"bold\")
     11 plots.set_xticklabels(plots.get_xticklabels(), rotation=90, fontsize=15)

IndexError: list index out of range

标签： python matplotlib seaborn bar-chart plot-annotations

【解决方案1】：

从matplotlib 3.4.0 开始，最好使用matplotlib.pyplot.bar_label，如How to add value labels on a bar chart 中所述。但是，该答案并未解释如何获取这两个注释。
在python 3.10、pandas 1.4.2、matplotlib 3.5.1、seaborn 0.11.2 中测试

import pandas as pd
import seaborn as sns

# test data
data = {'rules': ['A', 'B', 'C'], 'count': [15, 5, 25],
        'percentage': ['24%', '2%', '50%'], 'groups': [1, 2, 3], 'weight': [10, 30, 50]}
df = pd.DataFrame(data)

# plot
ax = sns.barplot(x="rules", y="count", data=df, hue='groups', dodge=False)

# since you are using hue, there are multiple containers
for c in ax.containers:
    # set the bar label based on the y-axis
    ax.bar_label(c, label_type='center', padding=1)
    # add an annotations with custom labels
    ax.bar_label(c, labels=df.percentage, label_type='edge', padding=1)

# pad the spacing between the number and the edge of the figure 
ax.margins(y=0.1)

带有两个自定义标签（'weight' 和 'percentage'）的注释。

ax = sns.barplot(x="rules", y="count", data=df, hue='groups', dodge=False)

# since you are using hue, there are multiple containers
for c in ax.containers:
    # add an annotations with custom labels
    ax.bar_label(c, labels=df.weight, label_type='center')
    # add an annotations with custom labels
    ax.bar_label(c, labels=df.percentage, label_type='edge', padding=1)
    
ax.margins(y=0.1)

现有代码的问题是有9个补丁，如print(patches)或list(patches)所示，可以通过只选择高度大于0的补丁来解决。
- 出现这种情况是因为正在使用hue，但'groups' 中只有一个值对应'rules' 中的每个值。

plots = sns.barplot(x="rules", y="count", data=df, hue=df['groups'], dodge=False)
percentage = df['percentage'].tolist()
weight = df['weight'].tolist()
patches = plots.patches

# select patches with a height > 0
patches = [p for p in patches if p.get_height() > 0]

for i, p in enumerate(patches):
    
    x = p.get_x() + patches[i].get_width()/2
    y = p.get_height()+.09
    
    plots.annotate(f'{percentage[i]}', (x, y), ha='center',  va='bottom', size=14)
    plots.annotate(f'{weight[i]:.0f}', (x, y), ha='center', va='top', color='white', size=15, fontweight="bold")

【讨论】：