Drop rows with missing values

In pandas, :meth:Series.isna and :meth:Series.notna can be used to filter the rows.

.. ipython:: python

outer_join[outer_join["value_x"].isna()] outer_join[outer_join["value_x"].notna()]

pandas provides :ref:a variety of methods to work with missing data <missing_data>. Here are some examples:

Drop rows with missing values

.. ipython:: python

   outer_join.dropna()

Forward fill from previous rows

.. ipython:: python

outer_join.ffill()

Replace missing values with a specified value

Using the mean:

.. ipython:: python

   outer_join["value_x"].fillna(outer_join["value_x"].mean())