BUG: matplotlib invert_xaxis crashes when using datetime
From [stackoverflow](http://stackoverflow.com/questions/16456751/matplotlib-axis-invert-xaxis-crashes-when-using-datetime), a question from more than a month ago, but still an issue I think (tested with master).

Basicly, when using `ax.invert_xaxis()` with datetime x-values, the following exception is raised:

```
RuntimeError: MillisecondLocator estimated to generate 5270400 ticks from 2012-08-01 00:00:00+00:00 to 2012-10-01 00:00:00+00:00: 
exceeds Locator.MAXTICKS* 2 (2000)
```

---

At first it may not seem an error from pandas, as you can trigger it by using pure matplotlib code, but the error comes from pandas\tseries\converter.py. And more, it is by _importing pandas that causes working matplotlib code to work no longer_:

``` python
import numpy as np
import matplotlib.pyplot as plt
import datetime

x = np.array([datetime.datetime(2012, 8, 1, 0, 0),
              datetime.datetime(2012, 9, 1, 0, 0),
              datetime.datetime(2012, 10, 1, 0, 0)], dtype=object)
y = np.array([-1,0,1])

## Working matplotlib!
fig, ax = plt.subplots()
ax.plot(x,y)
ax.invert_xaxis()
plt.show()

import pandas as pd

## Same matplotlib not working anymore after importing pandas
fig, ax = plt.subplots()
ax.plot(x,y)
ax.invert_xaxis()
plt.show()
```

---

**CAUSE of the bug**: 
When using `ax.invert_xaxis()` the left and right xlim are interchanged. Because of this the `delta` in PandasAutoDateLocator will be negative (https://github.com/pydata/pandas/blob/master/pandas/tseries/converter.py#L241).
This in turn triggers MilliSecondLocator instead of the normal AutoDateLocator, and causes the error as the datetime range is too big for MilliSecondLocator.

What I **don't understand** is why this is not happening when using pandas `plot` to create the axes object (the workaround I gave at [stackoverflow](http://stackoverflow.com/questions/16456751/matplotlib-axis-invert-xaxis-crashes-when-using-datetime/16460828#16460828)):

``` python
df = pd.DataFrame(y, index=x, columns=['test'])

## This works as expected!
fig, ax = plt.subplots()
df.plot(ax=ax)
ax.invert_xaxis()
plt.show()
```
