I have a problem viewing the following DataFrame:

n = 100
foo = DataFrame(index=range(n))
foo['floats'] = np.random.randn(n)
foo

The problem is that it does not print all rows per default in ipython notebook, but I have to slice to view the resulting rows. Even the following option does not change the output:

pd.set_option('display.max_rows', 500)

Does anyone know how to display the whole array?

Set display.max_rows:

pd.set_option('display.max_rows', 500)

For older versions of pandas (<=0.11.0) you need to change both display.height and display.max_rows.

pd.set_option('display.height', 500)
pd.set_option('display.max_rows', 500)

See also pd.describe_option('display').

You can set an option only temporarily for this one time like this:

from IPython.display import display
with pd.option_context('display.max_rows', 100, 'display.max_columns', 10):
    display(df) #need display to show the dataframe when using with in jupyter
    #some pandas stuff

You can also reset an option back to its default value like this:

pd.reset_option('display.max_rows')

And reset all of them back:

pd.reset_option('all')

Personally, I like setting the options directly with an assignment statement as it is easy to find via tab completion thanks to iPython. I find it hard to remember what the exact option names are, so this method works for me.

For instance, all I have to remember is that it begins with pd.options

pd.options.<TAB>

Most of the options are available under display

pd.options.display.<TAB>

From here, I usually output what the current value is like this:

pd.options.display.max_rows
60

I then set it to what I want it to be:

pd.options.display.max_rows = 100

Also, you should be aware of the context manager for options, which temporarily sets the options inside of a block of code. Pass in the option name as a string followed by the value you want it to be. You may pass in any number of options in the same line:

with pd.option_context('display.max_rows', 100, 'display.max_columns', 10):
    some pandas stuff

You can also reset an option back to its default value like this:

pd.reset_option('display.max_rows')

And reset all of them back:

pd.reset_option('all')

It is still perfectly good to set options via pd.set_option. I just find using the attributes directly is easier and there is less need for get_option and set_option.

It was already pointed in this comment and in this answer, but I’ll try to give a more direct answer to the question:

from IPython.display import display
import numpy as np
import pandas as pd

n = 100
foo = pd.DataFrame(index=range(n))
foo['floats'] = np.random.randn(n)

with pd.option_context("display.max_rows", foo.shape[0]):
    display(foo)

pandas.option_context is available since pandas 0.13.1 (pandas 0.13.1 release notes). According to this,

[it] allow[s] you to execute a codeblock with a set of options that revert to prior settings when you exit the with block.

As @hanleyhansen noted in a comment, as of version 0.18.1, the display.height option is deprecated, and says “use display.max_rows instead”. So you just have to configure it like this:

pd.set_option('display.max_rows', 500)

See the Release Notes — pandas 0.18.1 documentation:

Deprecated display.height, display.width is now only a formatting option does not control triggering of summary, similar to < 0.11.0.

pd.set_option('display.max_rows', 500)
df

Does not work in Jupyter!
Instead use:

pd.set_option('display.max_rows', 500)
df.head(500)

As in this answer to a similar question, there is no need to hack settings. It is much simpler to write:

print(foo.to_string())