Python-双Y轴图，零对齐 [英] Python - dual y axis chart, align zero

问题描述

我正在尝试创建一个带有双 x 轴的水平条形图.这两个轴在比例上有很大不同，一组从-5到15(正值和负值)，另一组从100到500(所有正值).

绘制此图时，我想对齐 2 个轴，以便在同一位置显示零，并且只有负值位于此左侧.目前所有正值的集合从最左边开始，正负集合从整个图的中间开始.

我找到了 align_yaxis 示例，但我正在努力对齐 x 轴.

I'm trying to create a horizontal bar chart, with dual x axes. The 2 axes are very different in scale, 1 set goes from something like -5 to 15 (positive and negative value), the other set is more like 100 to 500 (all positive values).

When I plot this, I'd like to align the 2 axes so zero shows at the same position, and only the negative values are to the left of this. Currently the set with all positive values starts at the far left, and the set with positive and negative starts in the middle of the overall plot.

I found the align_yaxis example, but I'm struggling to align the x axes. Matplotlib bar charts: Aligning two different y axes to zero

Here is an example of what I'm working on with simple test data. Any ideas/suggestions? thanks

import pandas as pd
import matplotlib.pyplot as plt

d = {'col1':['Test 1','Test 2','Test 3','Test 4'],'col 2':[1.4,-3,1.3,5],'Col3':[900,750,878,920]}
df = pd.DataFrame(data=d)

fig = plt.figure()  # Create matplotlib figure

ax = fig.add_subplot(111)  # Create matplotlib axes
ax2 = ax.twiny()  # Create another axes that shares the same y-axis as ax.

width = 0.4

df['col 2'].plot(kind='barh', color='darkblue', ax=ax, width=width, position=1,fontsize =4, figsize=(3.0, 5.0))
df['Col3'].plot(kind='barh', color='orange', ax=ax2, width=width, position=0, fontsize =4, figsize=(3.0, 5.0))

ax.set_yticklabels(df.col1)
ax.set_xlabel('Positive and Neg',color='darkblue')
ax2.set_xlabel('Positive Only',color='orange')

ax.invert_yaxis()
plt.show()

解决方案

I followed the link from a question and eventually ended up at this answer : https://stackoverflow.com/a/10482477/5907969

The answer has a function to align the y-axes and I have modified the same to align x-axes as follows:

def align_xaxis(ax1, v1, ax2, v2):
    """adjust ax2 xlimit so that v2 in ax2 is aligned to v1 in ax1"""
    x1, _ = ax1.transData.transform((v1, 0))
    x2, _ = ax2.transData.transform((v2, 0))
    inv = ax2.transData.inverted()
    dx, _ = inv.transform((0, 0)) - inv.transform((x1-x2, 0))
    minx, maxx = ax2.get_xlim()
    ax2.set_xlim(minx+dx, maxx+dx)

And then use it within the code as follows:

import pandas as pd
import matplotlib.pyplot as plt

d = {'col1':['Test 1','Test 2','Test 3','Test 4'],'col 2' [1.4,-3,1.3,5],'Col3':[900,750,878,920]}
df = pd.DataFrame(data=d)

fig = plt.figure()  # Create matplotlib figure

ax = fig.add_subplot(111)  # Create matplotlib axes
ax2 = ax.twiny()  # Create another axes that shares the same y-axis as ax.

width = 0.4

df['col 2'].plot(kind='barh', color='darkblue', ax=ax, width=width, position=1,fontsize =4, figsize=(3.0, 5.0))
df['Col3'].plot(kind='barh', color='orange', ax=ax2, width=width, position=0, fontsize =4, figsize=(3.0, 5.0))

ax.set_yticklabels(df.col1)
ax.set_xlabel('Positive and Neg',color='darkblue')
ax2.set_xlabel('Positive Only',color='orange')

align_xaxis(ax,0,ax2,0)
ax.invert_yaxis()
plt.show()

This will give you what you're looking for

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