Python for Data-Driven Engineering смотреть онлайн

Welcome to Python for Data-Driven Engineering. This introductory lesson covers variable types such as boolean, integer, float, and string. It introduces operators, conditional statements, for loops, while loops, print statements, conversion between types, try and except, input functions, string methods, time, datetime, functions, and how to get help. There are two exercises to test student's knowledge.

Data-Driven Engineering: https://apmonitor.com/dde
DDE Python Overview: https://apmonitor.com/dde/index.php/Main/PythonOverview
DDE Python Basics: https://apmonitor.com/dde/index.php/Main/PythonBasics

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.