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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 five 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.

Peter Mortensen
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beets
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    [Here](https://pandas.pydata.org/pandas-docs/stable/user_guide/options.html) is the user guide 'options and settings' from pandas with examples you are looking for. – MogaGennis May 14 '21 at 23:18

21 Answers21

1257

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.

TruncatedColumnDisplay

Peter Mortensen
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Wouter Overmeire
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    Tried myself and get the same with IDLE, works fine with pylab. I raised an [issue](https://github.com/pydata/pandas/issues/1714) for this. – Wouter Overmeire Jul 31 '12 at 18:42
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    display.height: deprecated, use `display.height` instead... I'm in dead loop. – Frozen Flame Jun 15 '14 at 03:24
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    Nowadays options can also be set as [assignments to attributes of `pd.options`](http://pandas.pydata.org/pandas-docs/stable/options.html#overview), e.g. `pd.options.display.max_rows = 999` – unutbu Jun 07 '15 at 00:19
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    The 'display.height' property is deprecated. – Greg M. Krsak Mar 22 '16 at 16:47
  • You could also set max_* to None: `pd.set_option('display.max_rows', None) pd.set_option('display.max_columns', None)` – Melroy van den Berg Jan 15 '17 at 16:55
  • Surely the context manager approach is superior, as it restores the initial values afterward. – BallpointBen Sep 04 '18 at 21:28
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    You may want to use the [option_context](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.option_context.html) 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. – Mike Williamson Oct 05 '18 at 23:16
  • display.height is gone. Using display.max_rows is sufficient. I will update the answer accordingly. – Ben Feb 18 '19 at 12:12
  • Also `np.set_printoptions(linewidth = 120)` if you print numpy array – user3226167 Aug 23 '19 at 07:23
  • I was not able to get `pandas.util.terminal.get_terminal_size()` to work, but `IPython.utils.terminal.get_terminal_size()` did work--inside PyCharm. In a Terminal window, `os.get_terminal_size()` works. – Carl Parker Jul 15 '20 at 17:31
  • It helped me to get pandas working correctly with git bash. pd.set_option('display.width', 0). Without the parameter, pandas could not determine window size. – Shtefan Mar 29 '21 at 00:15
  • I work fulltime, this is my most-viewed StackExchange answer. I come here at least once a week. Never bothered to memorize it. But after years of coming here, I want to say: Thank you! – Corey Levinson May 08 '22 at 14:15
255

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: pandas.set_option.

Peter Mortensen
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Robert Rose
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    This one works for me. It seems that pandas miscalculates the output width for some reason, and breaks columns unnecessarily. – zbyszek Jul 24 '15 at 17:44
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    I literally have to do this every day... Is there a way to set this globally somewhere? – citynorman Oct 08 '18 at 21:04
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    @citynorman see `pandas\core\config_init.py` to permanently set it. – Jarad Jul 07 '19 at 03:14
  • With Anaconda I found `config_init.py` under `C:\ProgramData\Anaconda3\Lib\site-packages\pandas\core`. Additionally, I had to run the text editor as Administrator in order to save changes to the file. – Francisco C Oct 21 '21 at 17:15
  • Dude, i've been looking for this damn command for MONTHS!!!! Thanks!!!!!!!!!!!! – Ghost May 11 '22 at 18:29
185

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

with pd.option_context('display.max_rows', None, 'display.max_columns', None):
    print (df)

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

jezrael
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    In order to set no limits, `None` can be used (instead of 999, etc.). – Eric O Lebigot Sep 14 '17 at 19:27
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    `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. – azizj Sep 20 '17 at 12:43
  • But there is difference, need some number like `-1` or `500`, not None. – jezrael Sep 20 '17 at 12:45
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    Using -1 crashes, and 500 did not do anything either – azizj Sep 20 '17 at 13:07
  • Hmmm, then I have no idea :( – jezrael Sep 20 '17 at 13:22
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    +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). – bluenote10 Mar 19 '19 at 12:09
  • Just to add my little usage note: I paired this with the top secret built-in pager (!) in Python's standard library `pydoc.pager`, which lets you view a wide pandas DataFrame if you set the `PAGER` env variable to `less -S`. I thought it needed `max_colwidth` set to `None` too but on closer inspection the above answer works just fine :—) There is a weird bug where you need to page exactly one column to the right to get a very wide DF to display without wrapping, not sure if that can be fixed with pandas options context settings though. – Louis Maddox Aug 06 '20 at 20:32
140

Only using these three 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)

It was for Anaconda, Python 3.6.5, Pandas 0.23.0, and Visual Studio Code 1.26.

Peter Mortensen
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arispen
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    All the more upvoted posts above use properties that are renamed and or disabled in the newest versions of pandas. All the 800 upvotes up there belong here. The pipy/pypi cheese shop sketch naming just clicked. – Eric Leschinski Jun 17 '20 at 00:44
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    `pd.set_option('max_colwidth', 100)` if you want to specify a max-width – Elder Druid Oct 06 '20 at 21:19
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    Newer versions of Pandas now take `None` argument for no max colwidth instead of `-1` – Andreas Klintberg Jan 20 '21 at 19:45
  • The correct syntax would be: `pd.set_option('max_colwidth', None)` Reason: `FutureWarning: Passing a negative integer is deprecated in version 1.0 and will not be supported in future version. Instead, use None to not limit the column width.` – Gergely M Dec 01 '21 at 13:49
68

Set the column maximum width using:

pd.set_option('max_colwidth', 800)

This particular statement sets the maximum width to 800 pixels per column.

Peter Mortensen
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pX0r
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    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). – Peter Leimbigler Mar 19 '18 at 20:38
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    This is the only one that worked for me for Pandas 0.23.2. – devinbost Sep 27 '18 at 19:23
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    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. – cmo Oct 17 '18 at 22:40
29

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.).

BrenBarn
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29

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

Furthermore, 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
Peter Mortensen
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bmu
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  • 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! – beets Jul 30 '12 at 02:10
23

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

pd.set_option('display.width', pd.util.terminal.get_terminal_size()[0])
Wilfred Hughes
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    @wouter-overmeire says that [pandas does this automatically](http://stackoverflow.com/a/11711637/3830997), 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"](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.set_option.html). – Matthias Fripp Apr 28 '16 at 00:19
  • 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! – Melroy van den Berg Jul 12 '16 at 13:08
  • @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. – John Zwinck Jul 13 '16 at 19:22
  • @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? – Matthias Fripp Jul 14 '16 at 03:21
  • @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. – Matthias Fripp Jul 15 '16 at 19:54
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    AttributeError: module 'pandas.util' has no attribute 'terminal' – BhishanPoudel Jun 21 '17 at 00:03
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    @BhishanPoudel You can do this instead : `pd.options.display.width = None` – SebMa Jun 22 '18 at 09:30
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    @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()` – Ajay Jul 11 '18 at 18:31
  • Hi Wilfred, I have faced with the following error using version 3.7.4 of python: `AttributeError: module 'pandas.util' has no attribute 'terminal' ` – Mostafa Ghadimi Aug 25 '19 at 08:31
22

I used these settings when the scale of the data was 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 to the documentation here.

Peter Mortensen
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debaonline4u
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17

The below line is enough to display all columns from a dataframe.

pd.set_option('display.max_columns', None)
Peter Mortensen
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zeeshan
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    Welcome to SO! When you post a new answer to a question and there are some more answers, try to show the Pros. There is still one answer `pd.set_option('display.max_columns', 0)` Which ones are the benefits of yours? – David García Bodego Nov 05 '19 at 06:54
14

According to the documentation for v0.18.0, if you're running in a terminal (i.e., not IPython notebook, qtconsole or IDLE), it's a two-liner to have Pandas autodetect 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)
Peter Mortensen
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hamx0r
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    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 – Greg Sadetsky Feb 08 '18 at 17:41
9

It seems like all the previous 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 documentation: 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_... parameters:

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 parameter:

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.

Peter Mortensen
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serv-inc
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8
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 consisting 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
Peter Mortensen
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William Pourmajidi
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  • 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) – William Pourmajidi Nov 23 '18 at 10:12
7

You can simply do the following steps,

  • You can change the options for the Pandas max_columns feature as follows:

    import pandas as pd
    pd.options.display.max_columns = 10
    

    (This allows 10 columns to display, and you can change this as you need.)

  • Like that, you can change the number of rows that you need to display as follows (if you need to change maximum rows as well):

    pd.options.display.max_rows = 999
    

    (This allows to print 999 rows at a time.)

Please kindly refer to the documentation to change different options/settings for Pandas.

Peter Mortensen
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Amila Viraj
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5

You can use this custom function for displaying things for a Pandas Dataframe.

def display_all(df):     # For any Dataframe df
   with pd.option_context('display.max_rows',1000): # Change number of rows accordingly
      with pd.option_context('display.max_columns',1000): # Change number of columns accordingly
          display(df)

display_all(df.head()) # Pass this function to your dataframe and voilà!

You don't have to use pd.set_option for the whole notebook just using for a single cell.

Peter Mortensen
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loving_guy
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4

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
AreToo
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2

You can also try in a loop:

for col in df.columns: 
    print(col) 
lifeisbeautiful
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  • An explanation would be in order. E.g., how does that answer the question *"Is there a way to widen the display of output in either interactive or script-execution mode?"* – Peter Mortensen Jun 06 '21 at 20:25
2
pd.options.display.max_columns = 100

You can specify the numbers of columns as per your requirement in max_columns.

2

The below will increase the width when NumPy arrays are printed.

It gave good results in Jupyter Notebook.

import numpy as np
np.set_printoptions(linewidth=160)
Peter Mortensen
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rahul-ahuja
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0

None of these answers were working for me. A couple of them would indeed print all the columns, but it would look sloppy. As in all the information was there, but it wasn't formatted correctly. I'm using a terminal inside of Neovim so I suspect that to be the reason.

This mini function does exactly what I need, just change df_data in the two places it is for your dataframe name (col_range is set to what pandas naturally shows, for me it is 5 but it could be bigger or smaller for you).

import math
col_range = 5
for _ in range(int(math.ceil(len(df_data.columns)/col_range))):
    idx1 = _*col_range
    idx2 = idx1+col_range
    print(df_data.iloc[:, idx1:idx2].describe())
Peter Mortensen
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Al-Baraa El-Hag
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0

It is not the answer strictly speaking, but let's remember we can df.describe().transpose() or even df.head(n).transpose(), or df.tail(n).transpose().

I also find it easier to read headers as a column when they are structured:

header1_xxx,

header2_xxx,

header3_xxx,

I think terminals and applications handle the vertical scrolling more naturally, if this is necessary after transposing.

Headers are commonly larger than their values, having all of them in one column (index) minimizes their impact on the total table width.

Finally other df descriptions can be merged as well, here is a possible idea:

def df_overview(df: pd.DataFrame, max_colwidth=25, head=3, tail=3):
    return(
        df.describe([0.5]).transpose()
        .merge(df.dtypes.rename('dtypes'), left_index=True, right_index=True)
        .merge(df.head(head).transpose(), left_index=True, right_index=True)
        .merge(df.tail(tail).transpose(), left_index=True, right_index=True)
        .to_string(max_colwidth=max_colwidth, float_format=lambda x: "{:.4G}".format(x))
    )
Peruz
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