Calling Series methods
A typical workflow in pandas will have you going back and forth between executing statements on Series and DataFrames. Calling Series methods is the primary way to use the abilities that the Series offers.
Both Series and DataFrames have a tremendous amount of power. We can use the built-in dir function to uncover all the attributes and methods of a Series. In the following code, we also show the number of attributes and methods common to both Series and DataFrames. Both of these objects share the vast majority of attribute and method names:
>>> s_attr_methods = set(dir(pd.Series))
>>> len(s_attr_methods)
471
>>> df_attr_methods = set(dir(pd.DataFrame))
>>> len(df_attr_methods)
458
>>> len(s_attr_methods & df_attr_methods)
400
As you can see there is a lot of functionality on both of these objects. Don't be overwhelmed by this. Most pandas users only use a subset of the functionality and get...
