Can't plot pd.Timedelta (or numpy.timedelta64) versus time
Hello,

I did

```python
import numpy as np
import pandas as pd
from matplotlib.pyplot as plt

idx = pd.date_range('20140101', '20140201')
df = pd.DataFrame(index=idx)
df['col0'] = np.random.randn(len(idx))
s_idx = pd.Series(idx, index=idx) # need to do this because we can't shift index
diff_idx = (s_idx-s_idx.shift(1)).fillna(pd.Timedelta(0))
df['diff_dt'] = diff_idx
df['diff_dt'].plot()
```

but it raises `Empty 'Series': no numeric data to plot`

```python
In [78]: df.dtypes
Out[78]:
col0               float64
diff_dt    timedelta64[ns]
dtype: object


In [79]: type(df['diff_dt'][1])
Out[79]: pandas.tslib.Timedelta
```

I don't understand if data inside `diff_dt` columns are `numpy.timedelta64` or `pd.Timedelta`

```python
df['diff_dt'].map(lambda x: x.value)
```

raises `AttributeError: 'numpy.timedelta64' object has no attribute 'value'`

but it seems that I can get `value`for a given data (let's say row 10)

```python
In [97]: df['diff_dt'][10].value
Out[97]: 86400000000000
```

I don't understand why...

But I also don't understand how I could plot diff_dt column without doing an uggly:

```
df['diff_dt'].map(lambda x: x/np.timedelta64(1, 'ns')).plot()
```

But I don't know how I could automatically get this `np.timedelta64(1, 'ns')`

Maybe Pandas could plot Timedelta (or `np.timedelta64`) out of the box ?
because that's interesting to know for example if sampling period is constant.

Kind regards
