It has nothing to do with Python or NumPy specifically; that's a feature of ipython to run external programs, in this case, the head utility from the standard suite of *NIX command line utilities. head -4 just reads the first four lines of the file provided and echoes them to the terminal.

Suppose you want to output the first and last 10 rows of the iris data set.

In R:

data(iris)
head(iris, 10)
tail(iris, 10)

In Python (scikit-learn required to load the iris data set):

import pandas as pd
from sklearn import datasets
iris = pd.DataFrame(datasets.load_iris().data)
iris.head(10)
iris.tail(10)

Now, as previously answered, if your data frame is too large for the display you use in the terminal, a summary is output. To visualize your data in a terminal, you could either expend the terminal or reduce the number of columns to display, as follows.

iris.iloc[:,1:2].head(10)

EDIT. Changed .ix to .iloc. From the pandas documentation,

Starting in 0.20.0, the .ix indexer is deprecated, in favor of the more strict .iloc and .loc indexers.

Under Python 3.x, you can do this nicely:

>>> head, *tail = [1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
>>> head
1
>>> tail
[1, 2, 3, 5, 8, 13, 21, 34, 55]

A new feature in 3.x is to use the * operator in unpacking, to mean any extra values. It is described in PEP 3132 - Extended Iterable Unpacking. This also has the advantage of working on any iterable, not just sequences.

It's also really readable.

As described in the PEP, if you want to do the equivalent under 2.x (without potentially making a temporary list), you have to do this:

it = iter(iterable)
head, tail = next(it), list(it)

As noted in the comments, this also provides an opportunity to get a default value for head rather than throwing an exception. If you want this behaviour, next() takes an optional second argument with a default value, so next(it, None) would give you None if there was no head element.

Naturally, if you are working on a list, the easiest way without the 3.x syntax is:

head, tail = seq[0], seq[1:]