如何向seaborn条形图添加数据标签?

2024-09-28 05:23:44 发布

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我有以下代码在seaborn中生成条形图

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))
print(df):
    A   B   C   D
0   15  21  13   5
1   14  94  99  14
2   11  11  13  69
3   27  90  37   6
4   51  93  92  24
..  ..  ..  ..  ..
95  45  40  85  62
96  44  48  61  43
97  39  66  72  72
98  51  97  17  32
99  51  42  29  15


probbins = [0,10,20,30,40,50,60,70,80,90,100]
df['Groups'] = pd.cut(df['D'],bins=probbins)
plt.figure(figsize=(15,6))
chart = sns.barplot(x=df['Groups'], y=df['C'],estimator=sum,ci=None)
chart.set_title('Profit/Loss')
chart.set_xticklabels(chart.get_xticklabels(), rotation=30)
plt.show()

这给了我:

enter image description here

如何简单地将数据标签添加到此绘图?任何帮助都将不胜感激


Tags: 代码importpandasdfaschartpltseaborn
2条回答

对于那些对我如何解决它感兴趣的人:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))
print(df):
    A   B   C   D
0   31  11  65  15
1   83  21   5  87
2   16   6  81  41
3   91  78  95  70
4   26  51  26  61
..  ..  ..  ..  ..
95  31  18  91  24
96  73  97  42  45
97  76  22   2  36
98  12  43  98  27
99  33  96  67  68


probbins = [0,10,20,30,40,50,60,70,80,90,100]
df['Groups'] = pd.cut(df['D'],bins=probbins)
plt.figure(figsize=(15,6))
chart = sns.barplot(x=df['Groups'], y=df['C'],estimator=sum,ci=None)
chart.set_title('Profit/Loss')
chart.set_xticklabels(chart.get_xticklabels(), rotation=30)
# annotation here
for p in chart.patches:
             chart.annotate("%.0f" % p.get_height(), (p.get_x() + p.get_width() / 2., p.get_height()),
                 ha='center', va='center', fontsize=10, color='black', xytext=(0, 5),
                 textcoords='offset points')
plt.show()

enter image description here

从matplotlib 3.4.0开始,可以使用内置的^{}替换注释循环

在您的代码中,chart是一个Axes对象,因此您可以使用:

chart.bar_label(chart.containers[0])

profit-loss bar chart with value labels

请注意,分组条形图(带有hue)将有多个条形图containers,因此在这种情况下containers需要迭代:

for container in chart.containers:
    chart.bar_label(container)

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