Python matplotlib 2轴组件

Question

我有一些数据无法复制，但它只是一个简单的读取CSV文件：

pumpDf = pd.read_csv('C:\\Python Scripts\\data.csv', index_col='Date', parse_dates=True)


pumpDf = pumpDf.truncate(before='12/17/2017', after='12/31/2017')


print(pumpDf.head())
print(pumpDf.tail())

                             DP   pump30
Date
2017-12-17 00:00:07.238  9.9969  81.9101
2017-12-17 00:00:07.255  9.9969  81.9101
2017-12-17 00:00:07.275  9.9969  81.9101
2017-12-17 00:00:07.292  9.9861  81.9101
2017-12-17 00:00:07.311  9.9861  82.2360

我试图将两个数据点绘制在不同的y轴上。知道如何修改这段代码吗？

import matplotlib.pyplot as plt

pumpDf.plot()
plt.show()

我正在尝试使用matplotlib.org中的代码来完成这项任务，但我对如何合并我的pandas数据框而不是numpy数组感到困惑。 # Create some mock data此代码从此处复制

matplotlib.org/devdocs/gallery/api/two_scales

import numpy as np
import matplotlib.pyplot as plt


def two_scales(ax1, time, data1, data2, c1, c2):
    """

    Parameters
    ----------
    ax : axis
        Axis to put two scales on

    time : array-like
        x-axis values for both datasets

    data1: array-like
        Data for left hand scale

    data2 : array-like
        Data for right hand scale

    c1 : color
        Color for line 1

    c2 : color
        Color for line 2

    Returns
    -------
    ax : axis
        Original axis
    ax2 : axis
        New twin axis
    """
    ax2 = ax1.twinx()

    ax1.plot(time, data1, color=c1)
    ax1.set_xlabel('time (s)')
    ax1.set_ylabel('exp')

    ax2.plot(time, data2, color=c2)
    ax2.set_ylabel('sin')
    return ax1, ax2


# Create some mock data
t = np.arange(0.01, 10.0, 0.01)
s1 = np.exp(t)
s2 = np.sin(2 * np.pi * t)

# Create axes
fig, ax = plt.subplots()
ax1, ax2 = two_scales(ax, t, s1, s2, 'r', 'b')


# Change color of each axis
def color_y_axis(ax, color):
    """Color your axes."""
    for t in ax.get_yticklabels():
        t.set_color(color)
    return None
color_y_axis(ax1, 'r')
color_y_axis(ax2, 'b')
plt.show()

Answer 1

来自the docs：

pumpDf.DP.plot()
pumpDf.pump30.plot(secondary_y=True)

Answer 2

根据您的示例数据，使用DataFrame.plot或pyplot.plot方法非常简单。诀窍是使用ax.twinx的双轴。

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax2 = ax.twinx()

df.DP.plot(ax=ax)
df.pump30.plot(ax=ax2, color='r')

fig.show()

也可以像这样创建相同的图像：

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax2 = ax.twinx()

ax.plot(df.index, df.DP)
ax2.plot(df.index, df.pump30, color='r')

fig.show()

Answer 3

这里有详细说明： https://matplotlib.org/examples/api/two_scales.html

他们展示的cond片段是：

import numpy as np
import matplotlib.pyplot as plt

fig, ax1 = plt.subplots()
t = np.arange(0.01, 10.0, 0.01)
s1 = np.exp(t)
ax1.plot(t, s1, 'b-')
ax1.set_xlabel('time (s)')
# Make the y-axis label, ticks and tick labels match the line color.
ax1.set_ylabel('exp', color='b')
ax1.tick_params('y', colors='b')

ax2 = ax1.twinx()
s2 = np.sin(2 * np.pi * t)
ax2.plot(t, s2, 'r.')
ax2.set_ylabel('sin', color='r')
ax2.tick_params('y', colors='r')

fig.tight_layout()
plt.show()