Why does using ax.twiny shift the figure mapped to second axes rightward?

Question

I'm trying to allow my figure to share the same y axis, but have different scales along x axis. The problem is that when I try to map the second figure to the second axes ( ax1 = ax.twiny ), the figure seems to move forward to the right from where it should be. Here is a minimal working example that demonstrates my problem.

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
import pandas as pd

r = [0,1,2,3,4]
raw_data = {'greenBars': [20, 1.5, 7, 10, 5], 'orangeBars': [5, 15, 5, 10, 15],'blueBars': [2, 15, 18, 5, 10]}
df = pd.DataFrame(raw_data)
totals = [i+j+k for i,j,k in zip(df['greenBars'], df['orangeBars'], df['blueBars'])]
greenBars = [i / j * 100 for i,j in zip(df['greenBars'], totals)]

f, ax = plt.subplots(1, figsize=(6,6))
ax.barh(r, greenBars, color='#b5ffb9', edgecolor='white', height=0.85)
df = pd.DataFrame({'group':['A', 'B', 'C', 'D', 'E'], 'values':[300,250,150,50,10] })
ax1 = ax.twiny() 
ax1.hlines(y=groups, xmin=0, xmax=df['values'], color='black', linewidth=1.5);

plt.show()

where my expected outcome is to have the ax1.hlines move left-ward to the frame (as shown by the arrows in the image below). Does anybody have any suggestions as to how to fix this behaviour?

Answer 1

barh usually sets lower limit at 0 while plot or others set at a little less value for aesthetic. To fix this, manually set xlim for ax1 :

... 

f, ax = plt.subplots(1, figsize=(6,6))
ax.barh(r, greenBars, color='#b5ffb9', edgecolor='white', height=0.85)
df = pd.DataFrame({'group':['A', 'B', 'C', 'D', 'E'], 'values':[300,250,150,50,10] })
ax1 = ax.twiny() 
ax1.hlines(y=df['group'], xmin=0, xmax=df['values'], color='black', linewidth=1.5);

# this is added
ax1.set_xlim(0)
plt.show()

Output: