When to use pandas series, numpy ndarrays or simply python dictionaries?
Numpy is very fast with arrays, matrix, math.
Pandas series have indexes, sometimes it's very useful to sort or join data.
Dictionaries is a slow beast, but sometimes it's very handy too.
So, as it was already was mentioned, it depends on use case which data types and tools to use.
I am new to learning Python, and some of its libraries (numpy, pandas).
I have found a lot of documentation on how numpy ndarrays, pandas series and python dictionaries work. 
But owing to my inexperience with Python, I have had a really hard time determining when to use each one of them. And I haven't found any best-practices that will help me understand and decide when it is better to use each type of data structure.
As a general matter, are there any best practices for deciding which, if any, of these three data structures a specific data set should be loaded into?
Thanks!