Idea for a a plot improvement

I often see the sizes of the groups printed in survival curves. So I thought I'd have a go at implementing it.

Example script:
```python
import matplotlib.pyplot as plt
import numpy as np
from lifelines.estimation import KaplanMeierFitter


t = np.random.exponential(size=50)
kmf = KaplanMeierFitter()
kmf.fit(t)
kmf.plot(size_show=True)
plt.show()
```

And result:
![1riskexample](https://cloud.githubusercontent.com/assets/223655/5486965/af748ac4-86ac-11e4-8436-72d68f58bda5.png)

Stuff to improve:
- [x] It is hard-coded for KaplanMeier at the moment, and should be changed or moved into KaplanMeier specifically, if approved.
- [x] Make this feature a separate function, to allow for several groups in one plot.
- [x] Take several groups into account with figure size adjustments
- [x] Add group labels
- [x] Add unit tests (test with labels, and without labels)
- [ ] Document the functionality

I just pulled this locally, I think these arguments should be revered: `add_at_risk_counts(self, kwargs['ax'])`