Misaligned X axis when plotting datetime with same frequency but different step base

[HenrikSpa]

Code Sample, a copy-pastable example if possible

import pandas as pd
import matplotlib.pyplot as plt

x1 = pd.date_range(start='2018-03-02 12:00:00', end='2019-10-21 12:00:00', freq='1h')
df1 = pd.DataFrame([0]*len(x1), index=x1, columns=['x1'])
x2 = pd.date_range(start='2017-06-04 06:00:01', end='2019-11-10 06:00:01', freq='1h')
df2 = pd.DataFrame([0]*len(x2), index=x2, columns=['x2'])

fig, axes = plt.subplots(nrows=4, ncols=1, sharex=True)
df1.plot(ax=axes[0])
df2.plot(ax=axes[1])
axes[2].plot(df1)
axes[3].plot(df2)

#Autoscale doesn't affect this issue. Just used to make all lines visible from start.
plt.autoscale(enable=True, axis='both', tight=None)

for ax in axes:
    ax.legend().remove()

# printouts
print(str(axes[0].get_xlim()))
print(str(axes[1].get_xlim()))
print(str(axes[2].get_xlim()))
print(str(axes[3].get_xlim()))
plt.show()

Problem description

The x-axes are misaligned when plotting two or more subplots and have different timestep base (in the example above, x1 starts with hour:minute:second 00:00:00 while x2 starts with 06:00:01.

UPDATE: Also, plotting df1 using axes[2].plot(df1) instead of df1.plot(ax=axes[0]) works perfectly.

If plt.autoscale is not used, the topmost plot, df1.plot(ax=axes[0]), is not visible unless one pan the axes manually.

The result from get_xlim() from the supplied code returns

(736484.2500115741, 737373.2500115741)
(736484.2500115741, 737373.2500115741)
(736484.2500115741, 737373.2500115741)
(736484.2500115741, 737373.2500115741)

If the df2.plot(ax=axes[1]) is plotted before the other three, the result of the get_xlim() is instead

(422220.0, 436572.0)
(422220.0, 436572.0)
(422220.0, 436572.0)
(422220.0, 436572.0)

This issue might be related to:
#11574, #18571 and #29705.

Expected Output

Plotting the data at the correct x axis coordinates.

Output of pd.show_versions()

[paste the output of pd.show_versions() here below this line]
INSTALLED VERSIONS

commit : None
python : 3.6.8.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-65-generic
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : sv_SE.UTF-8
LOCALE : sv_SE.UTF-8

pandas : 0.25.3
numpy : 1.17.4
pytz : 2019.3
dateutil : 2.8.1
pip : 9.0.1
setuptools : 40.8.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.2.1
html5lib : 0.999999999
pymysql : None
psycopg2 : 2.7.4 (dt dec pq3 ext lo64)
jinja2 : 2.10
IPython : None
pandas_datareader: None
bs4 : 4.6.0
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : 4.2.1
matplotlib : 3.0.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.2.0
sqlalchemy : None
tables : None
xarray : None
xlrd : 1.2.0
xlwt : None
xlsxwriter : None