问题
I am trying to plot 3 series with 2 on the left y-axis and 1 on the right using secondary_y
, but it’s not clear to me how to define the right y-axis scale as I did on the left with ylim=()
.
I have seen this post: Interact directly with axes
… but once I have:
import matplotlib.pyplot as plt
df = pd.DataFrame(np.random.randn(10,3))
fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
ax1.plot(df.index,df.iloc[:,[0,2]])
ax2.plot(df.index, df.iloc[:,2])
plt.show()
doesn't produce anything at all. I am using:
- Spyder 2.3.5.2
- python: 3.4.3.final.0
- python-bits: 64
- OS: Windows
- OS-release: 7
- pandas: 0.16.2
- numpy: 1.9.2
- scipy: 0.15.1
- matplotlib: 1.4.3
I found these links helpful:
tcaswell, working directly with axes
matplotlib.axes documentation
回答1:
You need to use set_ylim on the appropriate ax.
For example:
ax2 = ax1.twinx()
ax2.set_ylim(bottom=-10, top=10)
Also, reviewing your code, it appears that you are specifying your iloc
columns incorrectly. Try:
ax1.plot(df.index, df.iloc[:, :2]) # Columns 0 and 1.
ax2.plot(df.index, df.iloc[:, 2]) # Column 2.
回答2:
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(10,3))
print (df)
fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
ax1.plot(df.index,df.iloc[:,[0,2]])
ax2.plot(df.index, df.iloc[:,2])
plt.show()
回答3:
You can do this without directly calling ax.twinx():
#Plot the first series on the LH y-axis
ax1 = df.plot('x_column','y1_column')
#Add the second series plot, and grab the RH axis
ax2 = df.plot('x_column','y2_column',ax=ax1)
ax2.set_ylim(0,10)
Note: Only tested in Pandas 19.2
来源:https://stackoverflow.com/questions/34006443/unable-to-control-scale-of-second-y-axis-on-df-plot