python - 从数据中的现有标准列添加标准偏差条？

Question

我正在根据以下数据（仅头部）绘制图表：

Date    noctiluca_ave   density_ave density_sd
0   2018-03-07  2.0 1027.514332 0.091766
1   2018-03-14  4.0 1027.339988 0.285309
2   2018-03-21  1.0 1027.346413 0.183336
3   2018-03-31  1.0 1027.372996 0.170423
4   2018-04-07  0.0 1027.292119 0.187385

如何将标准偏差 ('density_sd') 条添加到 density_ave 线？

fig, ax = plt.subplots(figsize=(10, 10))
ax.plot(hydro_weekly2 ['Date'], hydro_weekly2 ['density_ave'], label='density weekly ave', color='purple')
ax2=ax.twinx()
ax2.plot(hydro_weekly2['Date'], hydro_weekly2['noctiluca_ave'], label='noctiluca abundance' , color='r')
ax.set_ylabel('Density')
ax.set_xlabel('Date')
ax2.set_ylabel('Noctiluca abundance/cells per m3')
ax.set(title="Noctiluca Abundance and Density 2018")


lines, labels = ax.get_legend_handles_labels()
lines2, labels2 = ax2.get_legend_handles_labels()
ax2.legend(lines + lines2, labels + labels2, loc="upper left")

标签： pythonmatplotlibstandard-deviationerrorbar

Answer 1

您可以替换ax.plot为ax.errorbar()或使用ax.fill_between()来显示彩色条带。

这是一个包含玩具数据的示例，两种方法相结合：

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

N = 20
dates = pd.date_range('2018-03-07', periods=N, freq='W-WED')
hydro_weekly2 = pd.DataFrame({'Date': dates,
                              'noctiluca_ave': np.random.randint(0, 14000, N),
                              'density_ave': 1027 + np.random.randn(N).cumsum() / 5,
                              'density_sd': 0.1 + np.abs(np.random.randn(N) / 5)})
fig, ax = plt.subplots(figsize=(10, 10))
ax.errorbar(hydro_weekly2['Date'], hydro_weekly2['density_ave'], yerr=hydro_weekly2['density_sd'],
            label='density weekly ave', color='purple')
ax.fill_between(hydro_weekly2['Date'], hydro_weekly2['density_ave'] - hydro_weekly2['density_sd'],
                hydro_weekly2['density_ave'] + hydro_weekly2['density_sd'], color='purple', alpha=0.3)
ax2 = ax.twinx()
ax2.plot(hydro_weekly2['Date'], hydro_weekly2['noctiluca_ave'], label='noctiluca abundance', color='r')
ax.set_ylabel('Density')
ax.set_xlabel('Date')
ax2.set_ylabel('Noctiluca abundance/cells per m3')
ax.set(title="Noctiluca Abundance and Density 2018")
plt.show()