Pandas: Setting No. of Max Rows

Pandas: Setting no. of max rows

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')

pandas pd.options.display.max_rows not working as expected

Final answer as of pandas v0.25.1

• To display all the rows, set max_rows greater than the number of rows in the DataFrame.
• To display more than 10 rows when the dataframe is truncated, set min_rows greater than 10.
• With more than 200 rows of data, if max_rows is 200 and min_rows is 20, 10 from the head and 10 from the tail will be displayed.
• With more than 200 rows of data, if max_rows is 200 and min_rows is None, 100 from the head and 100 from the tail will be displayed.

Discovery & Notes:

Both pd.set_option('display.max_rows', x) and pd.options.display.max_rows = x (where x is some number), should work.

• FYI: the default is 10 rows, as per pandas.set_option
• Options and settings
• This is also in Jupyter Lab

Other useful pandas options:

pd.set_option('display.max_columns', 200)
pd.set_option('display.max_rows', 100)
pd.set_option('display.min_rows', 100)
pd.set_option('display.expand_frame_repr', True)

get.options to return the current value:

pd.get_option("display.max_rows")

Update:

• After some discovery testing, the setting only displays more rows, if the setting is greater than the number of rows in the DataFrame.
• If pd.set_option('display.max_rows', 100), but the DataFrame has 200 rows, only 10 will show up.
• If pd.set_option('display.max_rows', 200), but the DataFrame has 100 rows, all 100 will display.

Per the pandas docs:

• display.max_rows: default=60
• This sets the maximum number of rows pandas should output when printing out various output. For example, this value determines whether the repr() for a dataframe prints out fully or just a truncated or summary repr. ‘None’ value means unlimited.
• display.min_rows: default=10
• The numbers of rows to show in a truncated repr (when max_rows is exceeded). Ignored when max_rows is set to None or 0. When set to None, follows the value of max_rows.
• display.large_repr: default=truncate
• For DataFrames exceeding max_rows/max_cols, the repr (and HTML repr) can show a truncated table (the default), or switch to the view from df.info() (the behaviour in earlier versions of pandas). allowable settings, [‘truncate’, ‘info’]

How to set the maximum rows of pandas dataframe displayed in pycharm console

To see just ten rows:

import pandas as pd
pd.set_option('display.max_rows',10)

This will fix your PD to show only first 10 rows always, no matter if you print dataframe to see more.

If you want to vary from time to time the use

df.head(10)

How do I expand the output display to see more columns of a Pandas DataFrame?

Update: Pandas 0.23.4 onwards

This is not necessary. Pandas autodetects the size of your terminal window if you set pd.options.display.width = 0. (For older versions see at bottom.)

pandas.set_printoptions(...) is deprecated. Instead, use pandas.set_option(optname, val), or equivalently pd.options.<opt.hierarchical.name> = val. Like:

import pandas as pd
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)

Here is the help for set_option:

set_option(pat,value) - Sets the value of the specified option

Available options:
display.[chop_threshold, colheader_justify, column_space, date_dayfirst,
         date_yearfirst, encoding, expand_frame_repr, float_format, height,
         line_width, max_columns, max_colwidth, max_info_columns, max_info_rows,
         max_rows, max_seq_items, mpl_style, multi_sparse, notebook_repr_html,
         pprint_nest_depth, precision, width]
mode.[sim_interactive, use_inf_as_null]

Parameters
----------
pat - str/regexp which should match a single option.

Note: partial matches are supported for convenience, but unless you use the
full option name (e.g., *x.y.z.option_name*), your code may break in future
versions if new options with similar names are introduced.

value - new value of option.

Returns
-------
None

Raises
------
KeyError if no such option exists

display.chop_threshold: [default: None] [currently: None]
: float or None
        if set to a float value, all float values smaller then the given threshold
        will be displayed as exactly 0 by repr and friends.
display.colheader_justify: [default: right] [currently: right]
: 'left'/'right'
        Controls the justification of column headers. used by DataFrameFormatter.
display.column_space: [default: 12] [currently: 12]No description available.

display.date_dayfirst: [default: False] [currently: False]
: boolean
        When True, prints and parses dates with the day first, eg 20/01/2005
display.date_yearfirst: [default: False] [currently: False]
: boolean
        When True, prints and parses dates with the year first, e.g., 2005/01/20
display.encoding: [default: UTF-8] [currently: UTF-8]
: str/unicode
        Defaults to the detected encoding of the console.
        Specifies the encoding to be used for strings returned by to_string,
        these are generally strings meant to be displayed on the console.
display.expand_frame_repr: [default: True] [currently: True]
: boolean
        Whether to print out the full DataFrame repr for wide DataFrames
        across multiple lines, `max_columns` is still respected, but the output will
        wrap-around across multiple "pages" if it's width exceeds `display.width`.
display.float_format: [default: None] [currently: None]
: callable
        The callable should accept a floating point number and return
        a string with the desired format of the number. This is used
        in some places like SeriesFormatter.
        See core.format.EngFormatter for an example.
display.height: [default: 60] [currently: 1000]
: int
        Deprecated.
        (Deprecated, use `display.height` instead.)

display.line_width: [default: 80] [currently: 1000]
: int
        Deprecated.
        (Deprecated, use `display.width` instead.)

display.max_columns: [default: 20] [currently: 500]
: int
        max_rows and max_columns are used in __repr__() methods to decide if
        to_string() or info() is used to render an object to a string.  In case
        python/IPython is running in a terminal this can be set to 0 and Pandas
        will correctly auto-detect the width the terminal and swap to a smaller
        format in case all columns would not fit vertically. The IPython notebook,
        IPython qtconsole, or IDLE do not run in a terminal and hence it is not
        possible to do correct auto-detection.
        'None' value means unlimited.
display.max_colwidth: [default: 50] [currently: 50]
: int
        The maximum width in characters of a column in the repr of
        a Pandas data structure. When the column overflows, a "..."
        placeholder is embedded in the output.
display.max_info_columns: [default: 100] [currently: 100]
: int
        max_info_columns is used in DataFrame.info method to decide if
        per column information will be printed.
display.max_info_rows: [default: 1690785] [currently: 1690785]
: int or None
        max_info_rows is the maximum number of rows for which a frame will
        perform a null check on its columns when repr'ing To a console.
        The default is 1,000,000 rows. So, if a DataFrame has more
        1,000,000 rows there will be no null check performed on the
        columns and thus the representation will take much less time to
        display in an interactive session. A value of None means always
        perform a null check when repr'ing.
display.max_rows: [default: 60] [currently: 500]
: int
        This sets the maximum number of rows Pandas should output when printing
        out various output. For example, this value determines whether the repr()
        for a dataframe prints out fully or just a summary repr.
        'None' value means unlimited.
display.max_seq_items: [default: None] [currently: None]
: int or None

        when pretty-printing a long sequence, no more then `max_seq_items`
        will be printed. If items are ommitted, they will be denoted by the addition
        of "..." to the resulting string.

        If set to None, the number of items to be printed is unlimited.
display.mpl_style: [default: None] [currently: None]
: bool

        Setting this to 'default' will modify the rcParams used by matplotlib
        to give plots a more pleasing visual style by default.
        Setting this to None/False restores the values to their initial value.
display.multi_sparse: [default: True] [currently: True]
: boolean
        "sparsify" MultiIndex display (don't display repeated
        elements in outer levels within groups)
display.notebook_repr_html: [default: True] [currently: True]
: boolean
        When True, IPython notebook will use html representation for
        Pandas objects (if it is available).
display.pprint_nest_depth: [default: 3] [currently: 3]
: int
        Controls the number of nested levels to process when pretty-printing
display.precision: [default: 7] [currently: 7]
: int
        Floating point output precision (number of significant digits). This is
        only a suggestion
display.width: [default: 80] [currently: 1000]
: int
        Width of the display in characters. In case python/IPython is running in
        a terminal this can be set to None and Pandas will correctly auto-detect the
        width.
        Note that the IPython notebook, IPython qtconsole, or IDLE do not run in a
        terminal and hence it is not possible to correctly detect the width.
mode.sim_interactive: [default: False] [currently: False]
: boolean
        Whether to simulate interactive mode for purposes of testing
mode.use_inf_as_null: [default: False] [currently: False]
: boolean
        True means treat None, NaN, INF, -INF as null (old way),
        False means None and NaN are null, but INF, -INF are not null
        (new way).
Call def:   pd.set_option(self, *args, **kwds)

---

Older version information. Much of this has been deprecated.

As @bmu mentioned, Pandas auto detects (by default) the size of the display area, a summary view will be used when an object repr does not fit on the display. You mentioned resizing the IDLE window, to no effect. If you do print df.describe().to_string() does it fit on the IDLE window?

The terminal size is determined by pandas.util.terminal.get_terminal_size() (deprecated and removed), this returns a tuple containing the (width, height) of the display. Does the output match the size of your IDLE window? There might be an issue (there was one before when running a terminal in Emacs).

Note that it is possible to bypass the autodetect, pandas.set_printoptions(max_rows=200, max_columns=10) will never switch to summary view if number of rows, columns does not exceed the given limits.

---

The 'max_colwidth' option helps in seeing untruncated form of each column.

How do I display more rows of a Dataframe in Jupyter Notebook?

This code will not work on jupiter!!!

pd.set_option('display.max_rows', 500)
data1.sex

if you want to see all rows :

pd.options.display.max_rows = None
data1.sex

If you just want to see 60 rows:

pd.set_option('display.max_rows', 60)
data1.sex.head(60)

Retaining pandas dataframe rows which have maximum number of item occurrences in a column

You can get the max count of cluster value through df['cluster'].value_counts() then use isin to filter cluster column

c = df['cluster'].value_counts()

out = df[df['cluster'].isin(c[c.eq(c.max())].index)]

print(out)

      name cluster
0     john       1
1      joe       2
3  richard       1
4      sam       2

Show the entire output when pandas dataframe is big (when many nan values in multiple columns need to be shown)

You can try:

DataFrame.to_string()

Or:

DataFrame.to_markdown()

Or:

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

Now you could decide to just display NaN values like this:

-by column:

df[df['column name'].isna()]

-or for entire dataframe:

df[df.isna().any(axis=1)]

---

Related Topics