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
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
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.
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
By default, only pandas.DataFrame tables have an additional column
called row index. To add a similar column to any other type of table,
pass showindex="always"
or showindex=True
argument to
tabulate()
. To suppress row indices for all types of data, pass
showindex="never"
or showindex=False
. To add a custom row
index column, pass showindex=rowIDs
, where rowIDs
is some
iterable:
>>> print(tabulate([["F",24],["M",19]], showindex="always")) - - -- 0 F 24 1 M 19 - - --
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"
- "github"
- "grid"
- "fancy_grid"
- "pipe"
- "orgtbl"
- "jira"
- "presto"
- "psql"
- "rst"
- "mediawiki"
- "moinmoin"
- "youtrack"
- "html"
- "latex"
- "latex_raw"
- "latex_booktabs"
- "textile"
- "testrail"
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
github
follows the conventions of Github flavored Markdown. It
corresponds to the pipe
format without alignment colons:
>>> print(tabulate(table, headers, tablefmt="github")) | 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 │ ╘════════╧═══════╛
presto
is like tables formatted by Presto cli:
>>> print(tabulate(table, headers, tablefmt="presto")) item | qty --------+------- spam | 42 eggs | 451 bacon | 0
psql
is like tables formatted by Postgres' psql cli:
>>> print(tabulate(table, headers, tablefmt="psql")) +--------+-------+ | 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 |
jira
follows the conventions of Atlassian Jira markup language:
>>> print(tabulate(table, headers, tablefmt="jira")) || 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 |}
moinmoin
format produces a table markup used in MoinMoin
wikis:
>>> print(tabulate(table, headers, tablefmt="moinmoin")) || ''' item ''' || ''' quantity ''' || || spam || 41.999 || || eggs || 451 || || bacon || ||
youtrack
format produces a table markup used in Youtrack
tickets:
>>> print(tabulate(table, headers, tablefmt="youtrack")) || item || quantity || | spam | 41.999 | | eggs | 451 | | bacon | |
textile
format produces a table markup used in Textile format:
>>> print(tabulate(table, headers, tablefmt="textile")) |_. item |_. qty | |<. spam |>. 42 | |<. eggs |>. 451 | |<. bacon |>. 0 |
html
produces standard HTML markup:
>>> print(tabulate(table, headers, tablefmt="html")) <table> <tbody> <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> </tbody> </table>
latex
format creates a tabular
environment for LaTeX markup,
replacing special characters like _
or \
to their LaTeX
correspondents:
>>> print(tabulate(table, headers, tablefmt="latex")) \begin{tabular}{lr} \hline item & qty \\ \hline spam & 42 \\ eggs & 451 \\ bacon & 0 \\ \hline \end{tabular}
latex_raw
behaves like latex
but does not escape LaTeX commands
and special characters.
latex_booktabs
creates a tabular
environment for LaTeX markup
using spacing and style from the booktabs
package.
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 ---- ----
tabulate
allows a custom column alignment to override the above. The
colalign
argument can be a list or a tuple of stralign
named arguments.
Possible column alignments are: right
, center
, left
, decimal
(only for numbers), and None
(to disable alignment). Omitting an alignment
uses the default. For example:
>>> print(tabulate([["one", "two"], ["three", "four"]], colalign=("right",)) ----- ---- one two three four ----- ----
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 -- ------
floatfmt
argument can be a list or a tuple of format strings,
one per column, in which case every column may have different number formatting:
>>> print(tabulate([[0.12345, 0.12345, 0.12345]], floatfmt=(".1f", ".3f"))) --- ----- ------- 0.1 0.123 0.12345 --- ----- -------
By default, tabulate
removes leading and trailing whitespace from text
columns. To disable whitespace removal, set the global module-level flag
PRESERVE_WHITESPACE
:
import tabulate tabulate.PRESERVE_WHITESPACE = True
To properly align tables which contain wide characters (typically fullwidth
glyphs from Chinese, Japanese or Korean languages), the user should install
wcwidth
library. To install it together with tabulate
:
pip install tabulate[widechars]
Wide character support is enabled automatically if wcwidth
library is
already installed. To disable wide characters support without uninstalling
wcwidth
, set the global module-level flag WIDE_CHARS_MODE
:
import tabulate tabulate.WIDE_CHARS_MODE = False
Most table formats support multiline cell text (text containing newline characters). The newline characters are honored as line break characters.
Multiline cells are supported for data rows and for header rows.
Further automatic line breaks are not inserted. Of course, some output formats such as latex or html handle automatic formatting of the cell content on their own, but for those that don't, the newline characters in the input cell text are the only means to break a line in cell text.
Note that some output formats (e.g. simple, or plain) do not represent row delimiters, so that the representation of multiline cells in such formats may be ambiguous to the reader.
The following examples of formatted output use the following table with a multiline cell, and headers with a multiline cell:
>>> table = [["eggs",451],["more\nspam",42]] >>> headers = ["item\nname", "qty"]
plain
tables:
>>> print(tabulate(table, headers, tablefmt="plain")) item qty name eggs 451 more 42 spam
simple
tables:
>>> print(tabulate(table, headers, tablefmt="simple")) item qty name ------ ----- eggs 451 more 42 spam
github
tables:
>>> print(tabulate(table, headers, tablefmt="github")) | item | qty | | name | | |--------|-------| | eggs | 451 | | more | 42 | | spam | |
grid
tables:
>>> print(tabulate(table, headers, tablefmt="grid")) +--------+-------+ | item | qty | | name | | +========+=======+ | eggs | 451 | +--------+-------+ | more | 42 | | spam | | +--------+-------+
fancy_grid
tables:
>>> print(tabulate(table, headers, tablefmt="fancy_grid")) ╒════════╤═══════╕ │ item │ qty │ │ name │ │ ╞════════╪═══════╡ │ eggs │ 451 │ ├────────┼───────┤ │ more │ 42 │ │ spam │ │ ╘════════╧═══════╛
pipe
tables:
>>> print(tabulate(table, headers, tablefmt="pipe")) | item | qty | | name | | |:-------|------:| | eggs | 451 | | more | 42 | | spam | |
orgtbl
tables:
>>> print(tabulate(table, headers, tablefmt="orgtbl")) | item | qty | | name | | |--------+-------| | eggs | 451 | | more | 42 | | spam | |
jira
tables:
>>> print(tabulate(table, headers, tablefmt="jira")) | item | qty | | name | | |:-------|------:| | eggs | 451 | | more | 42 | | spam | |
presto
tables:
>>> print(tabulate(table, headers, tablefmt="presto")) item | qty name | --------+------- eggs | 451 more | 42 spam |
psql
tables:
>>> print(tabulate(table, headers, tablefmt="psql")) +--------+-------+ | item | qty | | name | | |--------+-------| | eggs | 451 | | more | 42 | | spam | | +--------+-------+
rst
tables:
>>> print(tabulate(table, headers, tablefmt="rst")) ====== ===== item qty name ====== ===== eggs 451 more 42 spam ====== =====
Multiline cells are not well supported for the other table formats.
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 FPFMT, --float FPFMT floating point number format (default: g) -f FMT, --format FMT set output table format; supported formats: plain, simple, github, grid, fancy_grid, pipe, orgtbl, rst, mediawiki, html, latex, latex_raw, latex_booktabs, tsv, testrail (default: simple)
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
The following mini-benchmark was run in Python 3.5.2 on Windows
================================= ========== =========== Table formatter time, μs rel. time ================================= ========== =========== csv to StringIO 14.5 1.0 join with tabs and newlines 20.3 1.4 asciitable (0.8.0) 355.1 24.5 tabulate (0.8.2) 830.3 57.3 tabulate (0.8.2, WIDE_CHARS_MODE) 1483.4 102.4 PrettyTable (0.7.2) 1611.9 111.2 texttable (0.8.8) 1916.5 132.3 ================================= ========== ===========
The full version history can be found at the changelog.
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.
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, Jan Schulz, Simon Percivall, Javier Santacruz López-Cepero, Sam Denton, Alexey Ziyangirov, acaird, Cesar Sanchez, naught101, John Vandenberg, Zack Dever, Christian Clauss, Benjamin Maier, Andy MacKinlay, Thomas Roten, Jue Wang, Joe King, Samuel Phan, Nick Satterly, Daniel Robbins, Dmitry B, Lars Butler, Andreas Maier, Dick Marinus.