Log scaled histograms readability with default display.mpl_style can be improved
I use quite frequently log scaled histograms with `histtype='step'` option.

I noticed that with the suggested `default display.mpl_style` (which I like), readability of such histograms is quite improvable.

Consider this (from ipython notebook)

```
%pylab inline

import pandas as pd
import numpy as np
import matplotlib
import matplotlib.pyplot as plt

matplotlib.rcParams['savefig.dpi'] = 300

pd.set_option('display.mpl_style', 'default')

val = np.random.normal(size=1000000)
val2 = np.random.normal(scale = .5, size=1000000)
df = pd.DataFrame({'A' : val , 'B' : val2 , 'C' : val2})

df.hist(bins = 80, log=True,histtype='step')

plt.figure()
df.A.hist(bins = 80 , log=True,histtype='step',normed=True )
df.B.hist(bins = 80 , log=True,histtype='step',normed=True )
```

![pandas_hist1](https://cloud.githubusercontent.com/assets/2300692/2658524/92125cf0-c009-11e3-9c9a-934de51c0554.png)
![pandas_hist2](https://cloud.githubusercontent.com/assets/2300692/2658528/94deb17c-c009-11e3-8538-8b7e52f198bd.png)

The secondary grid looks too thick and confusing; IMHO it damages readability. This problem shows up only with log scaled hist.

Consider the following as a comparison
![pandas_hist3](https://cloud.githubusercontent.com/assets/2300692/2658585/32c32102-c00a-11e3-97a0-1c7302651289.png)
