BUG: OverflowError when plotting with sharex=True
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---

I have two datasets from different sources. They span more or less the same time, contain different data, sampled at different rate.

I am trying to plot these on two subplots with a shared x axis.

Making sample data:
```python
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

time1 = pd.date_range(
    '2020-11-08T09:31:06', '2020-12-01T22:59:59', freq='S', tz='UTC'
)

df1 = pd.DataFrame(
    np.sin(2 * np.pi * 1e-5 * np.arange(time1.size)),
    index=time1,
    columns=['x1']
)

time2 = pd.date_range(
    '2020-11-08T09:32:00', '2020-12-01T22:58:00', freq='D', tz='UTC'
)

df2 = pd.DataFrame(
    np.sin(2 * np.pi * 1e-1 * np.arange(time2.size)),
    index=time2,
    columns=['x2']
)
```

Minimal plotting example:
```python
fig, (ax1, ax2) = plt.subplots(2, sharex=True)
fig.subplots_adjust(0, 0, 1, 1, hspace=0.15)


df1.x1.plot(ax=ax1, legend=False)

df2.x2.plot(ax=ax2, legend=False)
```

I get `OverflowError` and a very long traceback but I think the problem is how the `sharex=True` is handled. When I set `sharex=False`, the error goes away and it plots fine but unaligned.

#### Output of ``pd.show_versions()``

I get `ImportError: Can't determine version for pip`
But:
Pandas: 1.2.3
Matplotlib: 3.3.2

<details>

[paste the output of ``pd.show_versions()`` here leaving a blank line after the details tag]

</details>
