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-.. _quickstart:
-Quickstart
-==========
-
-.. module:: tablib
-
-
-Eager to get started? This page gives a good introduction in how to get started with Tablib. This assumes you already have Tablib installed. If you do not, head over to the :ref:`Installation <install>` section.
-
-First, make sure that:
-
-* Tablib is :ref:`installed <install>`
-* Tablib is :ref:`up-to-date <updates>`
-
-
-Lets gets started with some simple use cases and examples.
-
-Creating a Dataset
-------------------
-
-A :class:`Dataset <tablib.Dataset>` is nothing more than what its name implies—a set of data.
-
-Creating your own instance of the :class:`tablib.Dataset` object is simple. ::
-
-    data = tablib.Dataset()
-    
-You can now start filling this :class:`Dataset <tablib.Dataset>` object with data.
-
-.. admonition:: Example Context
-     
-     From here on out, if you see ``data``, assume that it's a fresh :class:`Dataset <tablib.Dataset>` object.
-
-
-Adding Rows
------------
-
-Let's say you want to collect a simple list of names. ::
-
-    # collection of names
-    names = ['Kenneth Reitz', 'Bessie Monke']
-
-    for name in names:
-        # split name appropriately
-        fname, lname = name.split()
-        
-        # add names to Dataset
-        data.append([fname, lname])
-
-You can get a nice, Pythonic view of the dataset at any time with :class:`Dataset.dict`.
-
-    >>> data.dict
-    [('Kenneth', 'Reitz'), ('Bessie', 'Monke')]
-
-
-Adding Headers
---------------
-
-It's time enhance our :class:`Dataset` by giving our columns some titles. To do so, set :class:`Dataset.headers`. ::
-
-    data.headers = ['First Name', 'Last Name']
-
-Let's view the data in YAML this time. ::
-
-    >>> data.yaml
-    - {First Name: Kenneth, Last Name: Reitz}
-    - {First Name: Bessie, Last Name: Monke}
-    
-
-Adding Columns 
---------------
-
-Now that we have a basic :class:`Dataset` in place, let's add a column of **ages** to it. ::
-
-    data.append(col=['Age', 22, 20])
-    
-Let's view the data in CSV this time. ::
-
-    >>> data.csv
-    Last Name,First Name,Age 
-    Reitz,Kenneth,22 
-    Monke,Bessie,20
-
-It's that easy.
-
-Selecting Rows & Columns
-------------------------
-
-You can slice and dice your data, just like a standard Python list. ::
-
-    >>> data[0]
-    ('Kenneth', 'Reitz', 22)
-
-
-If we had a set of data consisting of thousands of rows, it could be useful to get a list of values in a column.
-To do so, we access the :class:`Dataset` as if it were a standard Python dictionary.  ::
-
-    >>> data['First Name']
-    ['Kenneth', 'Bessie']
-
-Let's find the average age. ::
-
-    >>> ages = data['Age']
-    >>> float(sum(ages)) / len(ages)
-    21.0
-
-
-
-Dynamic Columns
----------------
-
-.. versionadded:: 0.8.3
-
-Thanks to Josh Ourisman, Tablib now supports adding dynamic columns. For now, this is only supported on :class:`Dataset` objects that have no defined :class:`headers <Dataset.headers>`.
-
-Let's save our headers for later. ::
-
-    _headers = list(data.headers)
-    data.headers = None
-
-test ::
-
-    import random
-    
-    def random_grade(*args):
-        """Returns a random integer for entry."""
-        return (random.randint(60,100)/100.0)
-    
-    data.append(col=[random_grade])
-
-
-::
-    >>> data.yaml
-    - [Reitz, Kenneth, 22, 0.83]
-    - [Monke, Bessie, 21, 0.73]
-
-Now we can add our headers back.
-::
-    >>> data.headers = _headers + ['Random']
-
-Let's delete that column. 
-
-::
-    >>> del data['Grade']
-
-
-.. _seperators:
-
-Seperators
-----------
-
-
-
-Transposition
--------------
-
-Thanks to Luca Beltrame, :class:`Dataset` objects 
-::
-
-    data.transpose()
-
-
-Shortcuts
----------
-
-Population upon instantiation.
-
-
-Now, go check out the :ref:`API Documentation <api>` or begin :ref:`Tablib Development <development>`.
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