TablePrinter

NOTE: You might be able to use the built-in pandas.DataFrame.to_latex() or to_markdown() calls now... Though it bears mentioning that this may require additional dependencies to work properly (PyTablePrinter does not have any dependencies).

Convert dictionaries of data into nicely printed tables in LaTeX or Markdown.

Installation

You can either clone this repository and use it locally, or install from pypi:

pip install pytableprinter

Use this Python library to easily print markdown tables of data that are either lists of dictionaries or dictionaries of dictionaries. For instance:

data = [
    {
        "has_sequel": True,
        "author": "Margaret Atwood",
        "title": "Oryx & Crake",
        "rating": 5
    },
    {
        "author": "Kurt Vonnegut",
        "title": "Galapagos",
        "rating": 5
    }
]

Usage

from tableprinter import *
tp = TablePrinter(data)
print tp.to_markdown()

You can supply extra arguments to the TablePrinter constructor to get different results. For instance, specify the order of columns to include:

TablePrinter(data, col_order=['title', 'author'])

Specifying column titles that have no corresponding datum in the dictionaries of data will result in empty columns (but will not fail to render):

TablePrinter(data, col_order=['title', 'rating', 'has_sequel' 'favorite'])

title	rating	has_sequel	favorite
Oryx & Crake	5	True
Galapagos	5

You can also provide 2-tuples instead of a simple list for col_order. The first will be used as the lookup key, and the second string will be used as the table title.

TablePrinter(data, col_order=[
    ("title",       "The Title Of The Book"),
    ("rating",      "Rating"),
    ("has_sequel",  "Sequel?"),
    ("favorite",    "Favorite?")
])

The Title Of The Book	Rating	Sequel?	Favorite?
Oryx & Crake	5	True
Galapagos	5

You can even mix the two, with something like:

TablePrinter(data, col_order=[
    ("title",        "The Title Of The Book"),
    "rating",
    ("has_sequel",   "Sequel?"),
    "favorite"
])

...and for my final trick...

The latest, neatest trick is the implementation of functions as columns as well. If you provide a 3-tuple and the last item is a function, you can run a function on each datum like so:

("rating percentage", "Rating %", lambda d: str(100. * d['rating']/5.0) + "%")

(This, of course, returns a percentage rating, using the rating field, as calculated out of a possible 5.)

...	Rating %
...	80%