Pandas: Setting no. of max rows

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())

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.

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.

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)

to set unlimited number of rows use

None

i.e.,

pd.set_option('display.max_columns', None)

now the notebook will display all the rows in all datasets within the notebook 😉

Similarly you can set to show all columns as

pd.set_option('display.max_rows', None)

now if you use run the cell with only dataframe with out any head or tail tags
as

df

then it will show all the rows and columns in the dataframe df

I don’t know why nobody mentioned this.

You should also set 'display.min_rows'.

pd.set_option('display.min_rows', 500)  # <-add this!
pd.set_option('display.max_rows', 500)

---

If total number of rows > display.max_rows,

then, setting only display.max_rows would not work.

(Yeah, it’s confusing. This should be modified.)

I would use a context manager to set these options so that I can control which df should be affected.

with pd.option_context('display.min_rows', 50, 'max_columns', None):
    display(df)

Also, instead of display.max_rows use display.min_rows instead. This should work without setting display.max_rows.

pd.options.display.max_rows = None

This would display all the rows

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