DOC: add FAQ section on monkey-patching

doc/source/faq.rst

@@ -21,6 +21,47 @@ Frequently Asked Questions (FAQ)
    import matplotlib.pyplot as plt
    plt.close('all')
 
+.. _ref-monkey-patching:
+
+
+----------------------------------------------------
+
+Pandas is a powerful tool and already has a plethora of data manipulation
+operations implemented, most of them are very fast as well.
+It's very possible however that certain functionality that would make your
+life easier is missing. In that case you have several options:
+
+1) Open an issue on `Github <https://github.com/pydata/pandas/issues/>`_ , explain your need and the sort of functionality you would like to see implemented.
+2) Fork the repo, Implement the functionality yourself and open a PR
+   on Github.
+3) Write a method that performs the operation you are interested in and
+   Monkey-patch the pandas class as part of your IPython profile startup
+   or PYTHONSTARTUP file.
+
+   For example, here is an example of adding an ``just_foo_cols()``
+   method to the dataframe class:
+
+.. ipython:: python
+
+   import pandas as pd
+   def just_foo_cols(self):
+       """Get a list of column names containing the string 'foo'
+
+       """
+       return [x for x in self.columns if 'foo' in x]
+
+   pd.DataFrame.just_foo_cols = just_foo_cols # monkey-patch the DataFrame class
+   df = pd.DataFrame([range(4)],columns= ["A","foo","foozball","bar"])
+   df.just_foo_cols()
+   del pd.DataFrame.just_foo_cols # you can also remove the new method
+
+
+Monkey-patching is usually frowned upon because it makes your code
+less portable and can cause subtle bugs in some circumstances.
+Monkey-patching existing methods is usually a bad idea in that respect.
+When used with proper care, however, it's a very useful tool to have.
+
+
 .. _ref-scikits-migration:
 
 Migrating from scikits.timeseries to pandas >= 0.8.0
@@ -171,5 +212,3 @@ interval (``'start'`` or ``'end'``) convention:
    data = Series(np.random.randn(50), index=rng)
    resampled = data.resample('A', kind='timestamp', convention='end')
    resampled.index
-
-