Update examples to be v.0.3.0+ compliant

Hi @reiinakano , here's my PR! 👍

This commit solves Issue #62 and updates Jupyter notebook examples to be compliant with the latest version. Some things to note:

Summary

Demos that used the plotters API were removed. Some examples demonstrate by showing how to do it with the factory, and by the plotters API. Since both of them are deprecated, I just removed the other and focused on the updated way to do it.
__Add a .gitignore file to untrack .ipynb_checkpoints__ I think they're not needed so I have git ignore them.
Explicitly pass a parameter to cmap to avoid matplotlib deprecation warning. This seems a bit weird for me. My environment has matplotlib 2.0.2 and of course scikit-plot 0.3.1. When I call plot_roc_curve or plot_precision_curve, I encounter a deprecation warning on the use of spectral or spectral_r.

So whenever I do this:

import matplotlib.pyplot as plt
from sklearn.naive_bayes import GaussianNB
from sklearn.datasets import load_digits as load_data
import scikitplot as skplt

X, y = load_data(return_X_y=True)
nb = GaussianNB()
nb.fit(X,y)
y_probas = nb.predict_proba(X)

skplt.metrics.plot_precision_recall_curve(y, y_probas)
plt.show()

This appears:

 MatplotlibDeprecationWarning: The spectral and spectral_r colormap was deprecated in version 2.0. Use nipy_spectral and nipy_spectral_r instead.
  warnings.warn(message, mplDeprecation, stacklevel=1)

Although I checked the code in the repo and it's actually supplying nipy_spectral. Hmmm, not sure if it's just an environment problem for me. Either way, I solve it by explicitly passing the cmap parameter instead.

I committed a lot (almost per file), I can rebase my commits after your suggestion/revisions/review. Thank you so much! Sorry if this PR took me a long time, thesis happened. 😞

reiinakano / scikit-plot

Update examples to be v.0.3.0+ compliant #69

Summary