在 pyplot-seaborn-pandas 中绘制带有垂直线的条形图

Question

我在做一些我认为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()

返回以下图像：

我想更正以下问题：

a) 以我不理解的奇怪方式过度拥挤的刻度标签

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，我得到了一个错误。

Answer 1

传递给参数dataDataFrame，检查seaborn.barplot：

data：DataFrame、数组或数组列表，可选

用于绘图的数据集。如果 x 和 y 不存在，则将其解释为宽格式。否则它应该是长格式的。

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()