在pyplot-seaborn-pandas中用垂直线绘制条形图

Question

我在做一些我觉得直截了当的事情时遇到了麻烦。

我的数据是：

ROE_SP500_Q2_2018_quantile.to_json()

'{"index":{"0":0.0,"1":0.05,"2":0.1,"3":0.15,"4":0.2,"5":0.25,"6":0.3,"7":0.35,"8":0.4,"9":0.45,"10":0.5,"11":0.55,"12":0.6,"13":0.65,"14":0.7,"15":0.75,"16":0.8,"17":0.85,"18":0.9,"19":0.95},"ROE_Quantiles":{"0":-0.8931,"1":-0.0393,"2":0.00569,"3":0.03956,"4":0.05826,"5":0.075825,"6":0.09077,"7":0.10551,"8":0.12044,"9":0.14033,"10":0.15355,"11":0.17335,"12":0.1878,"13":0.209175,"14":0.2357,"15":0.27005,"16":0.3045,"17":0.3745,"18":0.46776,"19":0.73119}}'

我的情节代码是：

plt.close()
plt.figure(figsize=(14,8))
sns.barplot(x = 'Quantile', y = 'ROE', data = ROE_SP500_Q2_2018_quantile)
plt.vlines(x = 0.73, ymin = 0, ymax = 0.6, color = 'blue', size = 2)

plt.show()

将返回以下图像：

我想纠正以下问题：

a）刻度标签太拥挤，我无法理解

b）出现在错误位置的vline。我使用了错误的参数来设置线条的粗细，但出现错误。

您的建议将不胜感激。

Answer 1

传递给参数data DataFrame，检查seaborn.barplot：

  

数据：DataFrame，数组或数组列表，可选

     

用于绘制的数据集。如果x和y不存在，则解释为宽格式。否则，它应该是长格式。

sns.barplot(x = 'index', y = 'ROE_Quantiles', data = ROE_SP500_Q2_2018_quantile)
#TypeError: vlines() missing 2 required positional arguments: 'ymin' and 'ymax'
plt.vlines(x = 0.73, ymin = 0, ymax = 0.6, color = 'blue', linewidth=5)

---

j = '{"index":{"0":0.0,"1":0.05,"2":0.1,"3":0.15,"4":0.2,"5":0.25,"6":0.3,"7":0.35,"8":0.4,"9":0.45,"10":0.5,"11":0.55,"12":0.6,"13":0.65,"14":0.7,"15":0.75,"16":0.8,"17":0.85,"18":0.9,"19":0.95},"ROE_Quantiles":{"0":-0.8931,"1":-0.0393,"2":0.00569,"3":0.03956,"4":0.05826,"5":0.075825,"6":0.09077,"7":0.10551,"8":0.12044,"9":0.14033,"10":0.15355,"11":0.17335,"12":0.1878,"13":0.209175,"14":0.2357,"15":0.27005,"16":0.3045,"17":0.3745,"18":0.46776,"19":0.73119}}'

---

import ast

df = pd.DataFrame(ast.literal_eval(j))
print (df)
    index  ROE_Quantiles
0    0.00      -0.893100
1    0.05      -0.039300
10   0.50       0.153550
11   0.55       0.173350
12   0.60       0.187800
13   0.65       0.209175
14   0.70       0.235700
15   0.75       0.270050
16   0.80       0.304500
17   0.85       0.374500
18   0.90       0.467760
19   0.95       0.731190
2    0.10       0.005690
3    0.15       0.039560
4    0.20       0.058260
5    0.25       0.075825
6    0.30       0.090770
7    0.35       0.105510
8    0.40       0.120440
9    0.45       0.140330

plt.close()
plt.figure(figsize=(14,8))
sns.barplot(x = 'index', y = 'ROE_Quantiles', data = df)
plt.vlines(x = 0.73, ymin = 0, ymax = 0.6, color = 'blue', linewidth=5)
plt.show()