Pretty-print tabular data in Python, a library and a command-line utility.
The main use cases of the library are:
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:
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 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
pretty attempts to be close to the format emitted by the PrettyTables
library:
>>> print(tabulate(table, headers, tablefmt="pretty"))
+-------+-----+
| 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 as an html.escape'd str
with a .reprhtml_ method so that Jupyter Lab and Notebook display the HTML
and a .str property so that the raw HTML remains accessible:
>>> 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
---- ----
To disable this feature use disable_numparse=True.
>>> print(tabulate.tabulate([["Ver1", "18.0"], ["Ver2","19.2"]], tablefmt="simple", disable_numparse=True))
---- ----
Ver1 18.0
Ver2 19.2
---- ----
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
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 |
pretty tables:
>>> print(tabulate(table, headers, tablefmt="pretty"))
+------+-----+
| 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
(default: simple)
Such features as decimal point alignment and trying to parse everything
as a number imply that tabulate:
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 3.8.1 in Windows 10 x64:
=========================== ========== ===========
Table formatter time, μs rel. time
=========================== ========== ===========
csv to StringIO 12.4 1.0
join with tabs and newlines 15.7 1.3
asciitable (0.8.0) 208.3 16.7
tabulate (0.8.7) 492.1 39.5
PrettyTable (0.7.2) 945.5 76.0
texttable (1.6.2) 1239.5 99.6
=========================== ========== ===========
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.md) 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 3.6, run:
tox -e py27,py36
in the root of the project source tree.
To enable NumPy and Pandas tests, run:
tox -e py27-extra,py36-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, Sébastien Celles, Yago González, Andrew Gaul, Wim Glenn, Jean Michel Rouly, Tim Gates, John Vandenberg, Sorin Sbarnea, Wes Turner, Andrew Tija, Marco Gorelli, Sean McGinnis.