ENH: A new method that will more efficiently display 'tall' df
#### Is your feature request related to a problem?

I wish there was a way to preserve verticle screen space when I'm inspecting 'tall' data frames. These are data frames with many observaitons but few columns. Thus, they're _tall_. I use the word tall to avoid conflating with _long_ data.

#### Describe the solution you'd like

I believe this function accomplishes the goal:

```Python
def insp(df, n=5, parts='ht'):
  if parts == 'ht':
    display = pd.concat([df.head(n).reset_index().rename(columns={'index':'loc'}),
                         df.tail(n).reset_index().rename(columns={'index':'loc'})], 
                        axis=1,
                        keys=['head','tail'])
  if parts == 'hs':
    sep='< head | sample >'
    display = pd.concat([df.head(n).reset_index().rename(columns={'index':'loc'}),
                         df.sample(n).reset_index().rename(columns={'index':'loc'})], 
                        axis=1,
                        keys=['head','sample'])
  if parts == 'st':
    sep='< head | sample >'
    display = pd.concat([df.sample(n).reset_index().rename(columns={'index':'loc'}),
                         df.tail(n).reset_index().rename(columns={'index':'loc'})], 
                        axis=1,
                        keys=['sample','tail'])
  if parts == 'hst':
    sep1 = '< head | sample >'
    sep2 = '< sample | tail >'
    display = pd.concat([df.head(n).reset_index().rename(columns={'index':'loc'}),
                         df.sample(n).reset_index().rename(columns={'index':'loc'}),
                         df.tail(n).reset_index().rename(columns={'index':'loc'})], 
                        axis=1,
                        keys=['head','sample','tail'])
  return(display)
```

#### API breaking implications

Not applicable and/or unsure.

#### Describe alternatives you've considered

So the above function works great. Try it out. Take a look over at this colab notebook that demonstrates:

https://colab.research.google.com/drive/1mcNLlG6RVbhoXGCMdVyUryxKSgcaRPNC?usp=sharing

But, I'd propose a new method. Something like `Pandas.DataFrame.inspect()` or `Pandas.DataFrame.insp()` - to compliment the `.head()` - `.sample()` - and `.tail()` methods.

#### Additional Context

Inspired by the first suggestion in this article:
https://towardsdatascience.com/pandas-hacks-that-i-wish-i-had-when-i-started-out-1f942caa9792
(See the first 'hack' of the three).
