问用反向y轴绘制主次x轴和y轴的图

EN

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'])

# the xticklabels are empty strings until after the canvas is drawn
# needing this may also depend on the version of pandas and matplotlib
ax.get_figure().canvas.draw()

# 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, 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
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
ax2.vlines(x=df_filtered.Date_1, ymin=0, ymax=df_filtered.Rain, color='deepskyblue')

# cosmetics
ax2.set_ylim(0, 60)
ax2.invert_yaxis()  # reverse the secondary y axis so it starts at the top
ax2.set_ylabel('Rain (mm)')
ax2.legend(['Rainfall'], loc='upper right', ncol=1, bbox_to_anchor=(1.01, 1.09))

#1 Import Library

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

#2 IMPORT DATA  
sfData=pd.read_excel('data/streamflow validation.xlsx',sheet_name='Sheet1')

#3 Define Data
x = sfData['Year']
y1 = sfData['Observed']
y2 = sfData['Simulated']
y3 = sfData['Areal Rainfall']

# Or we can use loc for defining the data
x = list(sfData.iloc[:, 0])
y1 = list(sfData.iloc[:, 1])
y2 = list(sfData.iloc[:, 2])
y3 = list(sfData.iloc[:, 3])

#4 Plot Graph
fig, ax1 = plt.subplots(figsize=(12,10))
# increase space below subplot
fig.subplots_adjust(bottom=0.3)
# Twin Axes
# Secondary axes
ax2 = ax1.twinx()
ax2.bar(x, y3, width=15, bottom=0, align='center', color = 'b', data=sfData)
ax2.set_ylabel(('Areal Rainfall(mm)'),
            fontdict={'fontsize': 12})
# invert y axis
ax2.invert_yaxis()
# Primary axes
ax1.plot(x, y1, color = 'r', linestyle='dashed', linewidth=3, markersize=12)
ax1.plot(x, y2, color = 'k', linestyle='dashed', linewidth=3, markersize=12)

#5 Define Labels
ax1.set_xlabel(('Years'),
           fontdict={'fontsize': 14})
ax1.set_ylabel(('Flow (m3/s)'),
               fontdict={'fontsize': 14})

#7 Set limit 
ax1.set_ylim(0, 45)
ax2.set_ylim(800, 0)
ax1.set_xticklabels(('Jan 2003', 'Jan 2004', 'Jan 2005', 'Jan 2006', 'Jan 2007', 'Jan 2008', 'Jan 2009' ),
                    fontdict={'fontsize': 13})
for tick in ax1.get_xticklabels():
    tick.set_rotation(90)

#8 set title
ax1.set_title('Stream Flow Validation 1991', color = 'g')

#7 Display legend
legend = fig.legend()
ax1.legend(['Observed', 'Simulated'], loc='upper left', ncol=2, bbox_to_anchor=(-.01, 1.09))
ax2.legend(['Areal Rainfall'], loc='upper right', ncol=1, bbox_to_anchor=(1.01, 1.09))

#8 Saving the graph
fig.savefig('output/figure1.png')
fig.savefig('output/figure1.jpg')