Python Set for Data-Driven Engineering
A Python set is an unordered collection of unique elements. It is useful because it can perform mathematical set operations such as union, intersection, and difference. Additionally, sets are faster to search than lists or dictionaries because they are implemented using hash tables, which have a constant average-case time complexity for operations such as membership testing and element insertion. Sets are also useful for filtering out duplicates in a list or removing elements from a list that meet certain criteria.
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1️⃣ Python Basics
Data-driven engineering relies on information, often stored in the form of characters (strings) and numbers (integers and floating point numbers). It is essential to import, export, and get data into the correct form so that information can be extracted. This series includes an introduction to Python Basics as foundational elements.
2️⃣ Python Tuple
Tuple (e.g. (i,x,e)) is immutable (does not change) as an efficient storage mechanism for constant sets of values.
3️⃣ Python List
List (e.g. [i,x,e]) is a mutable set of values where it is possible to add elements, remove elements, sort.
4️⃣ Python Set
Set (e.g. {i,x,e}) is a data structure that is similar to list but not sorted and has no duplicate values.
5️⃣ Python Dictionary
Dictionary (e.g. {'i':i,'x':x,'e':e}) is a data structure with a reference value based on key.
6️⃣ NumPy
NumPy expands upon the basic Python functions to create an array. Matrix and vector operations are designed as a foundation for numerical calculations.
7️⃣ Pandas
Pandas reads, cleanses, calculates, rearranges, and exports data. It is a library for working with data with common high-level functions that simplify the processing steps of analytics and informatics.
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