Algorithms For Dummies

Storing Data Using Sets, Lists, and Tuples

When working with algorithms, it’s all about the data. Python provides a host of 

methods for storing data in memory. Each method has advantages and 

disadvantages. Choosing the most appropriate method for your particular need is 

important. The following sections discuss three common techniques used for 

storing data for data science needs.

Creating sets

Most people have used sets at one time or another in school to create lists of items 

that belong together. These lists then became the topic of manipulation using 

math operations such as intersection, union, difference, and symmetric differ-

ence. Sets are the best option to choose when you need to perform membership 

testing and remove duplicates from a list. You can’t perform sequence-related 

tasks using sets, such as indexing or slicing. To see how you can work with sets, 

start a copy of IPython and type the following code:

SetA = set(['Red', 'Blue', 'Green', 'Black'])

SetB = set(['Black', 'Green', 'Yellow', 'Orange'])

SetX = SetA.union(SetB)

SetY = SetA.intersection(SetB)

SetZ = SetA.difference(SetB)

You now have five different sets to play with, each of which has some common 

elements. To see the results of each math operation, type print(‘{0}\n{1}\n{2}’.

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  PART 1