Implement a human readable summary function like R (less structured than describe)
In R, the summary(data) function provides counts for categorical data of the most frequent values. For datetime and numeric values, it gives their mean, quartiles and range.

The describe function in Pandas is similar but does not provide such a human-readable data output for heterogeneous dataframes. As the output is primarily intended for human consumption, we could make a new summary() function with a new tabular layout designed solely for human consumption.
#### Examples of the R summary function

Heterogeneous columns from input data below:

```
A,1
B,2
C,3
A,1
```

```
 summary(d)
 V1          V2      
 A:2   Min.   :1.00  
 B:1   1st Qu.:1.75  
 C:1   Median :2.50  
       Mean   :2.75  
       3rd Qu.:3.50  
       Max.   :5.00  

```

Datetime example:

```
    datetime                        data       
 Min.   :2012-12-22 12:00:00   Min.   :-1.392  
 1st Qu.:2012-12-22 18:00:00   1st Qu.: 7.906  
 Median :2012-12-23 00:00:00   Median :10.836  
 Mean   :2012-12-23 00:00:00   Mean   :11.271  
 3rd Qu.:2012-12-23 06:00:00   3rd Qu.:16.362  
 Max.   :2012-12-23 12:00:00   Max.   :21.097  

```

Discussed with @jreback and he suggested that starting with a new function rather than changing describe.

This is how describe works on heterogeneous columns now, showing how it is difficult to read:

```
In [3]: df = pd.DataFrame({'A' : list('aab'), 'B' : range(3)})

In [4]: df
Out[4]: 
   A  B
0  a  0
1  a  1
2  b  2

In [5]: df.describe()
Out[5]: 
         B
count  3.0
mean   1.0
std    1.0
min    0.0
25%    0.5
50%    1.0
75%    1.5
max    2.0

In [7]: df.describe(include='all')
Out[7]: 
          A    B
count     3  3.0
unique    2  NaN
top       a  NaN
freq      2  NaN
mean    NaN  1.0
std     NaN  1.0
min     NaN  0.0
25%     NaN  0.5
50%     NaN  1.0
75%     NaN  1.5
max     NaN  2.0
```
