.. _mlb-data:

Working with Major League Baseball Batting Data
===============================================

We'll illustrate how to import a data file as a Pandas DataFrame into the
IPython namespace using the Data Import Tool.

The Data Set
------------
Here's the data used in this example:
:download:`mlb_batting_2008.csv </_static/mlb_batting_2008.csv>`.

.. _mlb_data_open:

Step 1: Opening the Data Set
----------------------------
The Data Import Tool can be used to open a data file in the following ways:

* From the Canopy Editor, by clicking on the  *File --> Import Data* Menu
  Option and selecting the datasource you'd like to use -- a file, a URL, or the
  clipboard
* Right-clicking on the data file in the File Browser and selecting
  *Import Data*

After opening the file, you will be able to use the Data Import Tool to browse
through the data:

.. figure:: /images/use_cases/mlb_data/mlb-dit-window.png
   :align: center
   :figwidth: image

   Figure : Data Import Tool Window

.. _delete_rows_where_mlb_data:

Step 2: Deleting Rows
---------------------
To delete rows that contain records for rookie players, we can use the *Delete
Rows Where* command, utilizing the `ROOKIE` column. Under the Transforms menu,
select the appropriate command:

.. figure:: /images/use_cases/mlb_data/transform-menu-delete-where.png
   :align: center
   :figwidth: image

   Figure : Transforms Menu

Then enter a boolean expression to filter the data:

.. figure:: /images/use_cases/mlb_data/mlb-delete-rows-where-dialog.png
   :align: center
   :figwidth: image

   Figure : Delete Rows Where ``ROOKIE == True``


Step 3: Loading the DataFrame into Canopy
-----------------------------------------
Clicking on the Use DataFrame button at the bottom of the Data Import Tool
will load the dataset as a Pandas DataFrame object into Canopy's IPython
namespace. The Data Import Tool automatically uses the name of the data file,
minus the file extension, as the name of the resulting Pandas DataFrame. This
can be changed in the Configuration Pane. The console will provide messages with
some information regarding your recent import:

.. figure:: /images/use_cases/mlb_data/mlb-ipython-prompt.png
   :align: center
   :figwidth: image

   Figure : DataFrame Loaded into Canopy

We can now view the contents of Pandas DataFrame object from the IPython
terminal and use it for further numerical analysis. A trivial exercise using the
DataFrame, as shown below, would be to plot a histogram of the salaries of the
players contained in the data set:

.. figure:: /images/use_cases/mlb_data/mlb-salary-histogram.png
   :align: center
   :figwidth: image

   Figure : Histogram Plot