在条形图上显示值

Question

我发现了一些与此主题类似的帖子。但它们对我没有帮助。

我对 Python 和 Seaborn 比较陌生。

这是我的代码：

import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline

x_axis = ["A", "B","C","D","E","F"]
y_axis = [78.5, 79.6, 81.6, 75.4, 78.3, 79.6]

plt.ylabel('Accuracy')
plt.title('Accuracy of Classifier')

g=sns.barplot(x_axis, y_axis, color="red")

我只是想在每个条形图的顶部显示 y_axis 的值。

Answer 1

遍历补丁并注释条。

import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline

x_axis = ["A", "B","C","D","E","F"]
y_axis = [78.5, 79.6, 81.6, 75.4, 78.3, 79.6]

plt.ylabel('Accuracy')
plt.title('Accuracy of Classifier')

g=sns.barplot(x_axis, y_axis, color="red")
ax=g
#annotate axis = seaborn axis
for p in ax.patches:
    ax.annotate("%.2f" % p.get_height(), (p.get_x() + p.get_width() / 2., p.get_height()),
                ha='center', va='center', fontsize=11, color='gray', xytext=(0, 20),
                textcoords='offset points')
_ = g.set_ylim(0,120) #To make space for the annotations

输出：

---

使用matplotlib v3.4.2条形图：

import matplotlib.pyplot as plt
%matplotlib inline

x_axis = ["A", "B","C","D","E","F"]
y_axis = [78.5, 79.6, 81.6, 75.4, 78.3, 79.6]

fig,ax = plt.subplots()

plt.ylabel('Accuracy')
plt.title('Accuracy of Classifier')

g=ax.bar(x_axis, y_axis, color="red")
ax.bar_label(g, padding=10)

_ = ax.set_ylim(0,120) #To make space for the annotations

输出：