在主、副 x 和 y 轴上绘制，y 轴反转

Question

我创建了这个图，在左侧“y 轴”上“观察到大肠杆菌”，在右侧“y 轴”上“模拟大肠杆菌”，在“y 轴”上“日期” x 轴。

代码是这样

# -*- coding: utf-8 -*- 
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

source = "Sample_table.csv"
df = pd.read_csv(source, encoding = 'unicode_escape')

x = df['Date_1']
y1 = df['Obs_Ec']
y2 = df['Rain']
y3 = df['Mod_Ec']

# Plot Line1 (Left Y Axis)
fig, ax1 = plt.subplots(1,1,figsize=(10,6), dpi= 80)

# Plot Line2 (Right Y Axis)
ax2 = ax1.twinx()  # instantiate a second axes that shares the same x-axis
ax2.plot(x, y2, color='tab:blue', linewidth=2.0)

# Plot Line2 (Right Y Axis)
ax3 = ax1.twinx()  # instantiate a second axes that shares the same x-axis
ax3.scatter(x, y3)

# Control limits of the y Axis
a,b = 0,80000
c,d = 0,80000
e,f = 0,35
ax1.set_ylim(a,b)
ax3.set_ylim(c,d)
ax2.set_ylim(e,f)

# Decorations
# ax1 (left Y axis)
ax1.set_xlabel('Date', fontsize=20)
ax1.set_ylabel('E. coli - cfu ml-1', color='tab:red', fontsize=20)
ax1.tick_params(axis='y',rotation=0, labelcolor='tab:red')
ax1.grid(alpha=.0)
ax1.tick_params(axis='both', labelsize=14)

# Plot the scatter points
ax1.scatter(x, y1,
       color="red",  # Color of the dots
       s=50,         # Size of the dots
       alpha=0.5,     # Alpha of the dots
       linewidths=0.5)  # Size of edge around the dots
ax1.scatter(0**np.arange(5), 0**np.arange(5))
ax1.legend(['Observed E. coli'], loc='right',fontsize=14, bbox_to_anchor=(0.2, -0.20))

ax3.scatter(x, y3,
       color="green",  # Color of the dots
       s=50,         # Size of the dots
       alpha=0.5,     # Alpha of the dots
       linewidths=0.5)  # Size of edge around the dots
ax3.scatter(0**np.arange(5), 0**np.arange(5))
ax3.legend(['Modelled E. coli'], loc='right',fontsize=14, bbox_to_anchor=(0.48, -0.20))

# ax2 (right Y axis)
ax2.set_ylabel("Rainfall - mm", color='tab:blue', fontsize=20)
ax2.tick_params(axis='y', labelcolor='tab:blue')
ax2.tick_params(axis='both', labelsize=15)
ax2.set_xticks(np.arange(1, len(x), 4))
ax2.set_xticklabels(x[0::4], rotation=15, fontdict={'fontsize':10})
ax2.set_title("SP051 - without SR (validation 2018-2020)", fontsize=22)
ax2.legend(['rainfall'], loc='right',fontsize=14, bbox_to_anchor=(1.05, -0.20))
fig.tight_layout()
plt.show()

但是这段代码给出了下面的情节：

我想改变这个情节中的三件事：

首先，将蓝线图转换为条形图。
其次，更重要的是，我想让代表降雨量的条形图显示在图的顶部
第三，我需要通过使“ax3 散点图”简单地共享左侧的“y 轴”来消除右侧“y 轴”上的黑色刻度线。

下面是我要创建的绘图示例，但我将使用散点图代替线条，如上图所示：

数据

数据可以在这里下载：link for the data

data = {'Date_1': ['1/17/2018', '2/21/2018', '3/21/2018', '4/18/2018', '5/17/2018', '6/20/2018', '7/18/2018', '8/8/2018', '9/19/2018', '10/24/2018', '11/21/2018', '12/19/2018', '1/16/2019', '2/20/2019', '3/20/2019', '4/29/2019', '5/30/2019', '6/19/2019', '7/19/2019', '8/21/2019', '9/18/2019', '10/16/2019', '1/22/2020', '2/19/2020'],
        'FLOW_OUTcms': [0.00273, 0.01566, 0.02071, 0.00511, 0.00777, 0.00581, 0.00599, 0.00309, 0.00204, 0.04024, 0.00456, 0.0376, 0.00359, 0.00301, 0.01515, 0.02796, 0.00443, 0.03602, 0.0071, 0.00255, 0.00159, 0.00319, 0.04443, 0.04542],
        'Rain': [0.0, 30.4, 2.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 8.7, 0.0, 0.0, 0.1, 0.1, 0.0, 0.0, 0.1, 0.0, 1.1, 0.1, 33.3, 0.0],
        'Mod_Ec': [10840, 212, 1953, 2616, 2715, 2869, 3050, 2741, 5479, 1049, 2066, 146, 6618, 7444, 992, 2374, 6602, 82, 5267, 3560, 4845, 1479, 58, 760],
        'Obs_Ec': [2500, 69000, 13000, 3300, 1600, 2400, 2300, 1400, 1600, 1300, 10000, 20000, 2000, 2500, 2900, 1500, 280, 260, 64, 59, 450, 410, 3900, 870]}

df = pd.DataFrame(data)

Answer 1

直接用pandas.DataFrame.plot
最好将雨绘制为散点图，然后添加垂直线，而不是使用条形图。出现这种情况是因为条形图刻度为 0 索引，而不是日期范围索引，因此很难在两种类型的刻度位置之间对齐数据点。
- 从外观上讲，我认为只添加雨大于 0 的点会更好看，因此可以过滤数据框以仅绘制这些点。

绘制 x 和 y 的主图并将其分配给坐标轴 ax
从 ax 创建第二个 x 轴并将其分配给 ax2
将次要 y 轴绘制到 ax2 上并将绘图分配给第三个轴，ax3，用于自定义次要轴。

测试于 python 3.8.11、pandas 1.3.3、matplotlib 3.4.3

import pandas as pd

# starting with the sample dataframe, convert Date_1 to a datetime dtype
df.Date_1 = pd.to_datetime(df.Date_1)

# plot E coli data
ax = df.plot(x='Date_1', y=['Mod_Ec', 'Obs_Ec'], figsize=(12, 8), rot=0, color=['blue', 'red'])

# center the xtick labels on the ticks
xticklabels = [t.get_text() for t in ax.get_xticklabels()]
xticks = ax.get_xticks()
ax.set_xticks(xticks)
ax.set_xticklabels(xticklabels, ha='center')

# cosmetics
ax.set_xlim(df.Date_1.min(), df.Date_1.max())
ax.set_ylim(0, 70000)
ax.set_ylabel('E. coli')
ax.set_xlabel('Date')
ax.legend(['Observed E. coli', 'Modelled E. coli'], loc='upper left', ncol=2, bbox_to_anchor=(-.01, 1.09))

# create twinx for rain
ax2 = ax.twinx()

# filter the rain column to only show points greater than 0
df_filtered = df[df.Rain.gt(0)]

# plot data with on twinx with secondary y as a scatter plot
ax3 = df_filtered.plot(kind='scatter', x='Date_1', y='Rain', marker='d', ax=ax2, color='deepskyblue', secondary_y=True, legend=False)

# add vlines to the scatter points
ax3.vlines(x=df_filtered.Date_1, ymin=0, ymax=df_filtered.Rain, color='deepskyblue')

# cosmetics
ax3.set_ylim(0, 60)
ax3.invert_yaxis()  # reverse the secondary y axis so it starts at the top
ax3.set_ylabel('Rain (mm)')
ax3.legend(['Rainfall'], loc='upper right', ncol=1, bbox_to_anchor=(1.01, 1.09))

在主、副 x 和 y 轴上绘制，y 轴反转

Plot on primary and secondary x and y axis with a reversed y axis

python

pandas

matplotlib

yaxis

x-axis

数据