By beets


2012-07-29 07:44:51 8 Comments

Is there a way to widen the display of output in either interactive or script-execution mode?

Specifically, I am using the describe() function on a Pandas dataframe. When the dataframe is 5 columns (labels) wide, I get the descriptive statistics that I want. However, if the dataframe has any more columns, the statistics are suppressed and something like this is returned:

>> Index: 8 entries, count to max  
>> Data columns:  
>> x1          8  non-null values  
>> x2          8  non-null values  
>> x3          8  non-null values  
>> x4          8  non-null values  
>> x5          8  non-null values  
>> x6          8  non-null values  
>> x7          8  non-null values  

The "8" value is given whether there are 6 or 7 columns. What does the "8" refer to?

I have already tried dragging the IDLE window larger, as well as increasing the "Configure IDLE" width options, to no avail.

My purpose in using Pandas and describe() is to avoid using a second program like STATA to do basic data manipulation and investigation.

Python/IDLE 2.7.3
Pandas 0.8.1
Notepad++ 6.1.4 (UNICODE)
Windows Vista SP2

13 comments

@user11052564 2019-02-28 22:21:03

If you don't want to mess with your display options and you just want to see this one particular list of columns without expanding out every dataframe you view, you could try:

df.columns.values

@Wouter Overmeire 2012-07-29 18:02:02

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(), 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.


Update: Pandas 0.23.4 onwards

pandas.set_printoptions(...) is deprecated. Instead, use pandas.set_option. 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, eg 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)

@Wouter Overmeire 2012-07-31 18:42:27

Tried myself and get the same with IDLE, works fine with pylab. I raised an issue for this.

@Frozen Flame 2014-06-15 03:24:32

display.height: deprecated, use display.height instead... I'm in dead loop.

@unutbu 2015-06-07 00:19:49

Nowadays options can also be set as assignments to attributes of pd.options, e.g. pd.options.display.max_rows = 999

@Greg M. Krsak 2016-03-22 16:47:33

The 'display.height' property is deprecated.

@danger89 2017-01-15 16:55:35

You could also set max_* to None: pd.set_option('display.max_rows', None) pd.set_option('display.max_columns', None)

@Dave Kielpinski 2018-07-17 22:04:34

doesn't work. see second answer

@BallpointBen 2018-09-04 21:28:43

Surely the context manager approach is superior, as it restores the initial values afterward.

@devinbost 2018-09-27 19:24:09

Didn't work for me in Pandas 0.23.2.

@Mike Williamson 2018-10-05 23:16:12

You may want to use the option_context so that the option changes are local to the thing you're working with. This prevents accidentally printing out 400 pages of junk on your next call to .head() or whatever.

@Ben 2019-02-18 12:12:49

display.height is gone. Using display.max_rows is sufficient. I will update the answer accordingly.

@killian95 2019-04-05 22:52:44

I come back to this answer many times in a year. Thanks Wouter.

@OPV 2019-04-14 09:38:30

It does not work, all properties

@William Pourmajidi 2018-11-23 10:11:59

import pandas as pd
pd.set_option('display.max_columns', 100)
pd.set_option('display.width', 1000)

SentenceA = "William likes Piano and Piano likes William"
SentenceB = "Sara likes Guitar"
SentenceC = "Mamoosh likes Piano"
SentenceD = "William is a CS Student"
SentenceE = "Sara is kind"
SentenceF = "Mamoosh is kind"


bowA = SentenceA.split(" ")
bowB = SentenceB.split(" ")
bowC = SentenceC.split(" ")
bowD = SentenceD.split(" ")
bowE = SentenceE.split(" ")
bowF = SentenceF.split(" ")

# Creating a set consisted of all words

wordSet = set(bowA).union(set(bowB)).union(set(bowC)).union(set(bowD)).union(set(bowE)).union(set(bowF))
print("Set of all words is: ", wordSet)

# Initiating dictionary with 0 value for all BOWs

wordDictA = dict.fromkeys(wordSet, 0)
wordDictB = dict.fromkeys(wordSet, 0)
wordDictC = dict.fromkeys(wordSet, 0)
wordDictD = dict.fromkeys(wordSet, 0)
wordDictE = dict.fromkeys(wordSet, 0)
wordDictF = dict.fromkeys(wordSet, 0)

for word in bowA:
    wordDictA[word] += 1
for word in bowB:
    wordDictB[word] += 1
for word in bowC:
    wordDictC[word] += 1
for word in bowD:
    wordDictD[word] += 1
for word in bowE:
    wordDictE[word] += 1
for word in bowF:
    wordDictF[word] += 1

# Printing Term frequency

print("SentenceA TF: ", wordDictA)
print("SentenceB TF: ", wordDictB)
print("SentenceC TF: ", wordDictC)
print("SentenceD TF: ", wordDictD)
print("SentenceE TF: ", wordDictE)
print("SentenceF TF: ", wordDictF)

print(pd.DataFrame([wordDictA, wordDictB, wordDictB, wordDictC, wordDictD, wordDictE, wordDictF]))

OutPut:

   CS  Guitar  Mamoosh  Piano  Sara  Student  William  a  and  is  kind  likes
0   0       0        0      2     0        0        2  0    1   0     0      2
1   0       1        0      0     1        0        0  0    0   0     0      1
2   0       1        0      0     1        0        0  0    0   0     0      1
3   0       0        1      1     0        0        0  0    0   0     0      1
4   1       0        0      0     0        1        1  1    0   1     0      0
5   0       0        0      0     1        0        0  0    0   1     1      0
6   0       0        1      0     0        0        0  0    0   1     1      0

@William Pourmajidi 2018-11-23 10:12:28

You just need these two: (Check the above example) import pandas as pd pd.set_option('display.max_columns', 100) pd.set_option('display.width', 1000)

@arispen 2018-07-26 14:10:51

Only using these 3 lines worked for me:

pd.set_option('display.max_columns', None)  
pd.set_option('display.expand_frame_repr', False)
pd.set_option('max_colwidth', -1)

Anaconda / Python 3.6.5 / pandas: 0.23.0 / Visual Studio Code 1.26

@Marek Bernád 2018-10-02 18:34:20

this only one of all worked for me... gg

@arispen 2018-10-17 14:23:07

@MarekBernád true, the same was in my case

@Geanderson Esteves 2018-12-18 01:14:27

This was also the only solution that worked on my environment

@OPV 2019-04-14 09:41:06

How to set min-width for cell, column?

@debaonline4u 2018-08-27 14:14:20

I used these settings when scale of data is high.

# environment settings: 
pd.set_option('display.max_column',None)
pd.set_option('display.max_rows',None)
pd.set_option('display.max_seq_items',None)
pd.set_option('display.max_colwidth', 500)
pd.set_option('expand_frame_repr', True)

You can refer the documentationhere

@OPV 2019-04-14 09:41:50

How to set min-width for cell, column?

@serv-inc 2018-03-23 16:52:02

It seems like all above answers solve the problem. One more point: instead of pd.set_option('option_name'), you can use the (auto-complete-able)

pd.options.display.width = None

See Pandas doc: Options and Settings:

Options have a full “dotted-style”, case-insensitive name (e.g. display.max_rows). You can get/set options directly as attributes of the top-level options attribute:

In [1]: import pandas as pd

In [2]: pd.options.display.max_rows
Out[2]: 15

In [3]: pd.options.display.max_rows = 999

In [4]: pd.options.display.max_rows
Out[4]: 999

[...]

for the max_... params:

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. [emphasis not in original]

for the width param:

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.

@jezrael 2015-10-27 18:04:34

If you want to set options temporarily to display one large DataFrame, you can use option_context:

with pd.option_context('display.max_rows', -1, 'display.max_columns', 5):
    print df

Option values are restored automatically when you exit the with block.

@Eric O Lebigot 2017-09-14 19:27:46

In order to set no limits, None can be used (instead of 999, etc.).

@Aziz Javed 2017-09-20 12:39:08

This does not seem to work, at least for Python 3.6

@jezrael 2017-09-20 12:40:13

@AzizJaved - Can you explain more? For me it working perfectly.

@Aziz Javed 2017-09-20 12:43:41

with pd.option_context('display.max_rows', None, 'display.max_columns', None): print(energy) didn't work. It did not change the number of columns I wanted to see. However, Wouter Overmeiere's solution did work.

@jezrael 2017-09-20 12:45:18

But there is difference, need some number like -1 or 500, not None.

@Aziz Javed 2017-09-20 13:07:03

Using -1 crashes, and 500 did not do anything either

@jezrael 2017-09-20 13:22:02

Hmmm, then I have no idea :(

@bluenote10 2019-03-19 12:09:45

+1 for suggesting a context manager, but -1 for the max_rows value ;). Setting 'display.max_rows' to -1 seems to mess up the formatting completely (for my data no crash, but it prints certain rows multiple times now).

@hamx0r 2016-04-02 13:26:39

According to the docs for v0.18.0, if you're running on a terminal (ie not iPython notebook, qtconsole or IDLE), it's a 2-liner to have Pandas auto-detect your screen width and adapt on the fly with how many columns it shows:

pd.set_option('display.large_repr', 'truncate')
pd.set_option('display.max_columns', 0)

@Greg Sadetsky 2018-02-08 17:41:56

This worked for me, thank you! I'm using Pandas 0.22.0 (latest as of Feb 8 2018) using the built-in Terminal app on OS X 10.11.6

@OPV 2019-04-14 09:41:38

How to set min-width for cell, column?

@pX0r 2015-11-19 08:43:35

Set column max width using:

pd.set_option('max_colwidth', 800)

This particular statement sets max width to 800px, per column.

@Peter Leimbigler 2018-03-19 20:38:39

Scrolling down in descending vote order, this is the first answer that worked for me to get pandas to not truncate the plaintext output of DataFrames. (pandas 0.22, iTerm2 3.0.13, OS X 10.12).

@devinbost 2018-09-27 19:23:42

This is the only one that worked for me for Pandas 0.23.2.

@cmo 2018-10-17 22:40:10

How come you didn't have to specify it as display.max_colwidth? That is how it is listed in the documentation. I agree that only max_colwidth works and is shorter to write, but I was surprised.

@OPV 2019-04-14 09:40:18

How to set min width?

@Wilfred Hughes 2015-03-16 10:04:56

You can set the output display to match your current terminal width:

pd.set_option('display.width', pd.util.terminal.get_terminal_size()[0])

@Matthias Fripp 2016-04-28 00:19:57

@wouter-overmeire says that pandas does this automatically, but that doesn't seem to be the case, at least not with 0.18.0. However, if you use pd.set_option('display.width', None) in a terminal, "pandas will correctly auto-detect the width".

@danger89 2016-07-12 13:08:04

Exactly! It doesn't do it by default. Setting it on None, it just ignore the width at all. Maybe it's a bug in Pandas or maybe it has to do with the gnome terminal..? Thanks Wilfred Hughes!

@John Zwinck 2016-07-13 19:22:39

@mfripp: display.width=None is treated as "unlimited" not "auto." Meaning it will be up to your terminal program to wrap long lines--typically with ugly results.

@Matthias Fripp 2016-07-14 03:21:49

@john-zwinck: I have to disagree. In the OS X Terminal, this adapts correctly, i.e., shows enough columns to fill the window width, then starts a new row below, where it shows more columns: import pandas as pd; pd.set_option('display.width', None); pd.DataFrame(1.00001, index=range(10), columns=range(100)). What environment are you working in?

@John Zwinck 2016-07-14 14:45:52

@mfripp: Linux.

@Matthias Fripp 2016-07-15 19:54:19

@john-swinck: The command above automatically adjusts the display width on Ubuntu 15.04, accessed via SSH from a couple of different terminal programs on my Mac. I haven't tried it from the Ubuntu desktop itself, but this suggests the problem is between your terminal app and pandas, not inherent to pandas or Linux.

@I_am_Groot 2017-06-21 00:03:16

AttributeError: module 'pandas.util' has no attribute 'terminal'

@SebMa 2018-06-22 09:30:22

@BhishanPoudel You can do this instead : pd.options.display.width = None

@Ajay 2018-07-11 18:31:33

@BhishanPoudel This answer is a few years old, and I ran into the same problem as you. As of writing this, using pandas version 0.23.1, the module is now pd.io.formats.terminal.get_terminal_size()

@OPV 2019-04-14 09:41:26

How to set min-width for cell, column?

@Robert Rose 2014-08-20 22:19:24

Try this:

pd.set_option('display.expand_frame_repr', False)

From the documentation:

display.expand_frame_repr : 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. [default: True] [currently: True]

See: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.set_option.html

@zbyszek 2015-07-24 17:44:59

This one works for me. It seems that pandas miscalculates the output width for some reason, and breaks columns unnecessarily.

@citynorman 2018-10-08 21:04:23

I literally have to do this every day... Is there a way to set this globally somewhere?

@Mingfei 2018-12-06 02:26:54

It works for me for pandas v0.23.4. Thanks a lot!

@bmu 2012-07-29 10:56:01

You can adjust pandas print options with set_printoptions.

In [3]: df.describe()
Out[3]: 
<class 'pandas.core.frame.DataFrame'>
Index: 8 entries, count to max
Data columns:
x1    8  non-null values
x2    8  non-null values
x3    8  non-null values
x4    8  non-null values
x5    8  non-null values
x6    8  non-null values
x7    8  non-null values
dtypes: float64(7)

In [4]: pd.set_printoptions(precision=2)

In [5]: df.describe()
Out[5]: 
            x1       x2       x3       x4       x5       x6       x7
count      8.0      8.0      8.0      8.0      8.0      8.0      8.0
mean   69024.5  69025.5  69026.5  69027.5  69028.5  69029.5  69030.5
std       17.1     17.1     17.1     17.1     17.1     17.1     17.1
min    69000.0  69001.0  69002.0  69003.0  69004.0  69005.0  69006.0
25%    69012.2  69013.2  69014.2  69015.2  69016.2  69017.2  69018.2
50%    69024.5  69025.5  69026.5  69027.5  69028.5  69029.5  69030.5
75%    69036.8  69037.8  69038.8  69039.8  69040.8  69041.8  69042.8
max    69049.0  69050.0  69051.0  69052.0  69053.0  69054.0  69055.0

However this will not work in all cases as pandas detects your console width and it will only use to_string if the output fits in the console (see the docstring of set_printoptions). In this case you can explicitly call to_string as answered by BrenBarn.

Update

With version 0.10 the way wide dataframes are printed changed:

In [3]: df.describe()
Out[3]: 
                 x1            x2            x3            x4            x5  \
count      8.000000      8.000000      8.000000      8.000000      8.000000   
mean   59832.361578  27356.711336  49317.281222  51214.837838  51254.839690   
std    22600.723536  26867.192716  28071.737509  21012.422793  33831.515761   
min    31906.695474   1648.359160     56.378115  16278.322271     43.745574   
25%    45264.625201  12799.540572  41429.628749  40374.273582  29789.643875   
50%    56340.214856  18666.456293  51995.661512  54894.562656  47667.684422   
75%    75587.003417  31375.610322  61069.190523  67811.893435  76014.884048   
max    98136.474782  84544.484627  91743.983895  75154.587156  99012.695717   

                 x6            x7  
count      8.000000      8.000000  
mean   41863.000717  33950.235126  
std    38709.468281  29075.745673  
min     3590.990740   1833.464154  
25%    15145.759625   6879.523949  
50%    22139.243042  33706.029946  
75%    72038.983496  51449.893980  
max    98601.190488  83309.051963  

Further more the API for setting pandas options changed:

In [4]: pd.set_option('display.precision', 2)

In [5]: df.describe()
Out[5]: 
            x1       x2       x3       x4       x5       x6       x7
count      8.0      8.0      8.0      8.0      8.0      8.0      8.0
mean   59832.4  27356.7  49317.3  51214.8  51254.8  41863.0  33950.2
std    22600.7  26867.2  28071.7  21012.4  33831.5  38709.5  29075.7
min    31906.7   1648.4     56.4  16278.3     43.7   3591.0   1833.5
25%    45264.6  12799.5  41429.6  40374.3  29789.6  15145.8   6879.5
50%    56340.2  18666.5  51995.7  54894.6  47667.7  22139.2  33706.0
75%    75587.0  31375.6  61069.2  67811.9  76014.9  72039.0  51449.9
max    98136.5  84544.5  91744.0  75154.6  99012.7  98601.2  83309.1

@beets 2012-07-30 02:10:27

I prefer to use the max_columns method mentioned by lodagro, but I'm glad you mentioned the precision keyword since that will help clean up the stats that are displayed. Thanks!

@fantabolous 2014-07-08 01:26:49

+1 for display.precision. Thanks!

@OPV 2019-04-14 09:41:15

How to set min-width for cell, column?

@BrenBarn 2012-07-29 08:03:35

You can use print df.describe().to_string() to force it to show the whole table. (You can use to_string() like this for any DataFrame. The result of describe is just a DataFrame itself.)

The 8 is the number of rows in the DataFrame holding the "description" (because describe computes 8 statistics, min, max, mean, etc.).

@beets 2012-07-30 02:01:28

Worked great. And to_string() sounds like a useful method to know. Thanks.

@Rafael Marques 2019-02-25 18:50:11

This is an excellent solution. I wish it would get higher on this page.

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