如何正确调整 matplotlib 中的误差线？

Question

我需要修复如图所示的错误栏，但我不知道如何使用它。我收到错误，但它不起作用。请问你能帮我吗？

#! /usr/bin/python3
# -*- coding: utf-8 -*-

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

x = np.arange(9)
country = [
    "Finland",
    "Denmark",
    "Switzerland",
    "Iceland",
    "Netherland",
    "Norway",
    "Sweden",
    "Luxembourg"
]
data = {
    "Explained by : Log GDP per Capita": [1.446, 1.502, 1.566, 1.482, 1.501, 1.543, 1.478, 1.751],
    "Explained by : Social Support": [1.106, 1.108, 1.079, 1.172, 1.079, 1.108, 1.062, 1.003],
    "Explained by : Healthy life expectancy": [0.741, 0.763, 0.816, 0.772, 0.753, 0.782, 0.763, 0.760],
    "Explained by : Freedom to make life choices": [0.691, 0.686, 0.653, 0.698, 0.647, 0.703, 0.685, 0.639],
    "Explained by : Generosity": [0.124, 0.208, 0.204, 0.293, 0.302, 0.249, 0.244, 0.166],
    "Explained by : Perceptions of corruption": [0.481, 0.485, 0.413, 0.170, 0.384, 0.427, 0.448, 0.353],
    "Dystopia + residual": [3.253, 2.868, 2.839, 2.967, 2.798, 2.580, 2.683, 2.653]
}
error_value = [[7.904, 7.780], [7.687, 7.552], [7.643, 7.500], [7.670, 7.438], [7.518, 7.410], [7.462, 7.323], [7.433, 7.293], [7.396, 7.252]]

df = pd.DataFrame(data, index=country)

df.plot(width=0.1, kind='barh', stacked=True, figsize=(11, 8))
plt.subplots_adjust(bottom=0.2)
# plt.errorbar(country, error_value, yerr=error_value)
plt.axvline(x=2.43, label="Dystopia (hapiness=2.43)")

plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.05),
           fancybox=True, shadow=True, ncol=3)
plt.xticks(x)
plt.show()

Answer 1

误差线绘制为与中心的差异。您似乎提供了每个误差条结束处的值，因此您必须重新计算到端点的距离并提供 (2, N) 形式的 numpy 数组，其中第一行包含负误差条值，第二行包含正值：

...
df.plot(width=0.1, kind='barh', stacked=True, figsize=(11, 8))
#determine x-values of the stacked bars
country_sum = df.sum(axis=1).values
#calculate differences of error bar values to bar heights 
#and transform array into necessary (2, N) form
err_vals = np.abs(np.asarray(error_value).T - country_sum[None])[::-1, :]
plt.errorbar(country_sum, np.arange(df.shape[0]), xerr=err_vals, capsize=4, color="k", ls="none")
plt.subplots_adjust(bottom=0.2)
...

示例输出：