You need the transpose of mydata, otherwise x, y, z, mx, my, mz are the rows rather than the columns.

mydata = np.array([x, y, z, mx, my, mz]).T
print(mydata[:5, :])

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.

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.