tabulate 0.7.4

Pretty-print tabular data

Pretty-print tabular data in Python, a library and a command-line utility.

The main use cases of the library are:

• printing small tables without hassle: just one function call, formatting is guided by the data itself

• authoring tabular data for lightweight plain-text markup: multiple output formats suitable for further editing or transformation

• readable presentation of mixed textual and numeric data: smart column alignment, configurable number formatting, alignment by a decimal point

Installation

To install the Python library and the command line utility, run:

pip install tabulate

The command line utility will be installed as tabulate to bin on Linux (e.g. /usr/bin); or as tabulate.exe to Scripts in your Python installation on Windows (e.g. C:\Python27\Scripts\tabulate.exe).

You may consider installing the library only for the current user:

pip install tabulate --user

In this case the command line utility will be installed to ~/.local/bin/tabulate on Linux and to %APPDATA%\Python\Scripts\tabulate.exe on Windows.

To install just the library on Unix-like operating systems:

TABULATE_INSTALL=lib-only pip install tabulate

On Windows:

set TABULATE_INSTALL=lib-only
pip install tabulate

Library usage

The module provides just one function, tabulate, which takes a list of lists or another tabular data type as the first argument, and outputs a nicely formatted plain-text table:

>>> from tabulate import tabulate

>>> table = [["Sun",696000,1989100000],["Earth",6371,5973.6],
...          ["Moon",1737,73.5],["Mars",3390,641.85]]
>>> print tabulate(table)
-----  ------  -------------
Sun    696000     1.9891e+09
Earth    6371  5973.6
Moon     1737    73.5
Mars     3390   641.85
-----  ------  -------------

The following tabular data types are supported:

• list of lists or another iterable of iterables

• list or another iterable of dicts (keys as columns)

• dict of iterables (keys as columns)

• two-dimensional NumPy array

• NumPy record arrays (names as columns)

• pandas.DataFrame

Examples in this file use Python2. Tabulate supports Python3 too.

Headers

The second optional argument named headers defines a list of column headers to be used:

>>> print tabulate(table, headers=["Planet","R (km)", "mass (x 10^29 kg)"])
Planet      R (km)    mass (x 10^29 kg)
--------  --------  -------------------
Sun         696000           1.9891e+09
Earth         6371        5973.6
Moon          1737          73.5
Mars          3390         641.85

If headers="firstrow", then the first row of data is used:

>>> print tabulate([["Name","Age"],["Alice",24],["Bob",19]],
...                headers="firstrow")
Name      Age
------  -----
Alice      24
Bob        19

If headers="keys", then the keys of a dictionary/dataframe, or column indices are used. It also works for NumPy record arrays and lists of dictionaries or named tuples:

>>> print tabulate({"Name": ["Alice", "Bob"],
...                 "Age": [24, 19]}, headers="keys")
  Age  Name
-----  ------
   24  Alice
   19  Bob

Table format

There is more than one way to format a table in plain text. The third optional argument named tablefmt defines how the table is formatted.

Supported table formats are:

• “plain”

• “simple”

• “grid”

• “fancy_grid”

• “pipe”

• “orgtbl”

• “rst”

• “mediawiki”

• “html”

• “latex”

• “latex_booktabs”

plain tables do not use any pseudo-graphics to draw lines:

>>> table = [["spam",42],["eggs",451],["bacon",0]]
>>> headers = ["item", "qty"]
>>> print tabulate(table, headers, tablefmt="plain")
item      qty
spam       42
eggs      451
bacon       0

simple is the default format (the default may change in future versions). It corresponds to simple_tables in Pandoc Markdown extensions:

>>> print tabulate(table, headers, tablefmt="simple")
item      qty
------  -----
spam       42
eggs      451
bacon       0

grid is like tables formatted by Emacs’ table.el package. It corresponds to grid_tables in Pandoc Markdown extensions:

>>> print tabulate(table, headers, tablefmt="grid")
+--------+-------+
| item   |   qty |
+========+=======+
| spam   |    42 |
+--------+-------+
| eggs   |   451 |
+--------+-------+
| bacon  |     0 |
+--------+-------+

fancy_grid draws a grid using box-drawing characters:

>>> print tabulate(table, headers, tablefmt="fancy_grid")
╒════════╤═══════╕
│ item   │   qty │
╞════════╪═══════╡
│ spam   │    42 │
├────────┼───────┤
│ eggs   │   451 │
├────────┼───────┤
│ bacon  │     0 │
╘════════╧═══════╛

psql is like tables formatted by Postgres’ psql cli:

>>> print tabulate.tabulate()
+--------+-------+
| item   |   qty |
|--------+-------|
| spam   |    42 |
| eggs   |   451 |
| bacon  |     0 |
+--------+-------+

pipe follows the conventions of PHP Markdown Extra extension. It corresponds to pipe_tables in Pandoc. This format uses colons to indicate column alignment:

>>> print tabulate(table, headers, tablefmt="pipe")
| item   |   qty |
|:-------|------:|
| spam   |    42 |
| eggs   |   451 |
| bacon  |     0 |

orgtbl follows the conventions of Emacs org-mode, and is editable also in the minor orgtbl-mode. Hence its name:

>>> print tabulate(table, headers, tablefmt="orgtbl")
| item   |   qty |
|--------+-------|
| spam   |    42 |
| eggs   |   451 |
| bacon  |     0 |

rst formats data like a simple table of the reStructuredText format:

>>> print tabulate(table, headers, tablefmt="rst")
======  =====
item      qty
======  =====
spam       42
eggs      451
bacon       0
======  =====

mediawiki format produces a table markup used in Wikipedia and on other MediaWiki-based sites:

>>> print tabulate(table, headers, tablefmt="mediawiki")
{| class="wikitable" style="text-align: left;"
|+ <!-- caption -->
|-
! item   !! align="right"|   qty
|-
| spam   || align="right"|    42
|-
| eggs   || align="right"|   451
|-
| bacon  || align="right"|     0
|}

html produces standard HTML markup:

>>> print tabulate(table, headers, tablefmt="html")
<table>
<tr><th>item  </th><th style="text-align: right;">  qty</th></tr>
<tr><td>spam  </td><td style="text-align: right;">   42</td></tr>
<tr><td>eggs  </td><td style="text-align: right;">  451</td></tr>
<tr><td>bacon </td><td style="text-align: right;">    0</td></tr>
</table>

latex format creates a tabular environment for LaTeX markup:

>>> print tabulate(table, headers, tablefmt="latex")
\begin{tabular}{lr}
\hline
 item   &   qty \\
\hline
 spam   &    42 \\
 eggs   &   451 \\
 bacon  &     0 \\
\hline
\end{tabular}

latex_booktabs creates a tabular environment for LaTeX markup using spacing and style from the booktabs package.

Column alignment

tabulate is smart about column alignment. It detects columns which contain only numbers, and aligns them by a decimal point (or flushes them to the right if they appear to be integers). Text columns are flushed to the left.

You can override the default alignment with numalign and stralign named arguments. Possible column alignments are: right, center, left, decimal (only for numbers), and None (to disable alignment).

Aligning by a decimal point works best when you need to compare numbers at a glance:

>>> print tabulate([[1.2345],[123.45],[12.345],[12345],[1234.5]])
----------
    1.2345
  123.45
   12.345
12345
 1234.5
----------

Compare this with a more common right alignment:

>>> print tabulate([[1.2345],[123.45],[12.345],[12345],[1234.5]], numalign="right")
------
1.2345
123.45
12.345
 12345
1234.5
------

For tabulate, anything which can be parsed as a number is a number. Even numbers represented as strings are aligned properly. This feature comes in handy when reading a mixed table of text and numbers from a file:

>>> import csv ; from StringIO import StringIO
>>> table = list(csv.reader(StringIO("spam, 42\neggs, 451\n")))
>>> table
[['spam', ' 42'], ['eggs', ' 451']]
>>> print tabulate(table)
----  ----
spam    42
eggs   451
----  ----

Number formatting

tabulate allows to define custom number formatting applied to all columns of decimal numbers. Use floatfmt named argument:

>>> print tabulate([["pi",3.141593],["e",2.718282]], floatfmt=".4f")
--  ------
pi  3.1416
e   2.7183
--  ------

Usage of the command line utility

Usage: tabulate [options] [FILE ...]

FILE                      a filename of the file with tabular data;
                          if "-" or missing, read data from stdin.

Options:

-h, --help                show this message
-1, --header              use the first row of data as a table header
-o FILE, --output FILE    print table to FILE (default: stdout)
-s REGEXP, --sep REGEXP   use a custom column separator (default: whitespace)
-f FMT, --format FMT      set output table format; supported formats:
                          plain, simple, grid, fancy_grid, pipe, orgtbl,
                          rst, mediawiki, html, latex, latex_booktabs, tsv
                          (default: simple)

Performance considerations

Such features as decimal point alignment and trying to parse everything as a number imply that tabulate:

• has to “guess” how to print a particular tabular data type

• needs to keep the entire table in-memory

• has to “transpose” the table twice

• does much more work than it may appear

It may not be suitable for serializing really big tables (but who’s going to do that, anyway?) or printing tables in performance sensitive applications. tabulate is about two orders of magnitude slower than simply joining lists of values with a tab, coma or other separator.

In the same time tabulate is comparable to other table pretty-printers. Given a 10x10 table (a list of lists) of mixed text and numeric data, tabulate appears to be slower than asciitable, and faster than PrettyTable and texttable

===========================  ==========  ===========
Table formatter                time, μs    rel. time
===========================  ==========  ===========
join with tabs and newlines        25.0          1.0
csv to StringIO                    32.1          1.3
tabletext (0.1)                   565.1         22.6
asciitable (0.8.0)                777.0         31.1
tabulate (0.7.4)                 1369.6         54.8
PrettyTable (0.7.2)              3828.3        153.3
texttable (0.8.1)                4005.2        160.3
===========================  ==========  ===========

Version history

• 0.7.4: Bug fixes. fancy_grid and html formats. Command line utility.

• 0.7.3: Bug fixes. Python 3.4 support. Iterables of dicts. latex_booktabs format.

• 0.7.2: Python 3.2 support.

• 0.7.1: Bug fixes. tsv format. Column alignment can be disabled.

• 0.7: latex tables. Printing lists of named tuples and NumPy record arrays. Fix printing date and time values. Python <= 2.6.4 is supported.

• 0.6: mediawiki tables, bug fixes.

• 0.5.1: Fix README.rst formatting. Optimize (performance similar to 0.4.4).

• 0.5: ANSI color sequences. Printing dicts of iterables and Pandas’ dataframes.

• 0.4.4: Python 2.6 support.

• 0.4.3: Bug fix, None as a missing value.

• 0.4.2: Fix manifest file.

• 0.4.1: Update license and documentation.

• 0.4: Unicode support, Python3 support, rst tables.

• 0.3: Initial PyPI release. Table formats: simple, plain, grid, pipe, and orgtbl.

How to contribute

Contributions should include tests and an explanation for the changes they propose. Documentation (examples, docstrings, README.rst) should be updated accordingly.

This project uses nose testing framework and tox to automate testing in different environments. Add tests to one of the files in the test/ folder.

To run tests on all supported Python versions, make sure all Python interpreters, nose and tox are installed, then run tox in the root of the project source tree.

On Linux tox expects to find executables like python2.6, python2.7, python3.4 etc. On Windows it looks for C:\Python26\python.exe, C:\Python27\python.exe and C:\Python34\python.exe respectively.

To test only some Python environements, use -e option. For example, to test only against Python 2.7 and Python 3.4, run:

tox -e py27,py34

in the root of the project source tree.

To enable NumPy and Pandas tests, run:

tox -e py27-extra,py34-extra

(this may take a long time the first time, because NumPy and Pandas will have to be installed in the new virtual environments)

See tox.ini file to learn how to use nosetests directly to test individual Python versions.

Contributors

Sergey Astanin, Pau Tallada Crespí, Erwin Marsi, Mik Kocikowski, Bill Ryder, Zach Dwiel, Frederik Rietdijk, Philipp Bogensberger, Greg (anonymous), Stefan Tatschner, Emiel van Miltenburg, Brandon Bennett, Amjith Ramanujam.