Agroalimentary (1.5 points)
===========================

From the Catalan government web we have downloaded the file
:download:`agroalimentary.csv` related to Catalan agroalimentary
companies. Download and study this file. We have already created a
:py:ref:`DataFrame <basics.dataframe>` with this data.

The following example shows the names of the columns of this
:py:ref:`DataFrame <basics.dataframe>` and a subdataframe example
with columns corresponding to the establishment name
(``Establiment``), the region (``Comarca``), the company type
(``Titularitat``) and the latitude (``Latitud``):

.. literalinclude:: test-agroalimentary-1.txt
   :language: python
   :lines: 4-18
	  
Save the following functions to file ``p4.py``.

#. Write function :py:func:`agro1` that takes a :py:ref:`DataFrame
   <basics.dataframe>`, ``df``, as that described and a string
   corresponding to a company type, and returns the percentage of
   companies of this type. (0.75 points)
 
   Examples:
   
   .. literalinclude:: test-agroalimentary-1.txt
      :language: python
      :lines: 22-25

   .. note:: You have more tests in file :download:`test-agroalimentary-1.txt`
	   
.. hint::
   Use selection.
   
#. Write function :py:func:`agro2` that takes a :py:ref:`DataFrame
   <basics.dataframe>`, ``df``, as that described, and a string with
   the name of a region. This function computes the most northern
   company (i.e. the one with the maximum latitude) in the given
   region, and returns a tuple with two elements: the establishment
   name and latitude of this company. (0.75 points)
 
   Examples:
   
   .. literalinclude:: test-agroalimentary-2.txt
      :language: python
      :lines: 22-26

   .. note:: You have more tests in file :download:`test-agroalimentary-2.txt`

.. hint::
   Use selection, indexing and method idxmax().

.. note:: To run your functions you don't actually need to read the given data file. But you need to download it because the given testfiles read from it to create the :py:ref:`DataFrame <basics.dataframe>`.