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Questions and Answers
What is one reason programming is essential for Data Science?
What is one reason programming is essential for Data Science?
What does REPL stand for?
What does REPL stand for?
Read-Eval-Print Loop
Compiled languages are executed directly without conversion to binary.
Compiled languages are executed directly without conversion to binary.
False
Which of the following is a characteristic of an interpreted language?
Which of the following is a characteristic of an interpreted language?
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The command to test if Python is installed correctly is 'python ______'
The command to test if Python is installed correctly is 'python ______'
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What is the file extension for a Jupyter Notebook?
What is the file extension for a Jupyter Notebook?
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Match the Python characteristics with their descriptions:
Match the Python characteristics with their descriptions:
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What does the following code print? 'print("Hello World!")'
What does the following code print? 'print("Hello World!")'
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Python allows for multiline comments using triple quotes.
Python allows for multiline comments using triple quotes.
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What are variables in programming?
What are variables in programming?
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Study Notes
Programming for Data Science
- Data Engineering is improved by programming.
- Programming allows access to pre-built analytics libraries.
- Customization, Scalability, Automation and Integration are key benefits of programming for Data Science.
Why Python?
- Cross Platform
- Used for Data Science, AI, IoT, Web and Scripting.
- Can be used in various modes (REPL/Shell, Program, Interactive).
- Flexible paradigm: Structural, Functional, and Object Oriented.
- Large ecosystem of libraries.
Programming Languages Overview
- Genesis: Progression from Binary and Assembly to 3rd and 4th Generation Languages.
- Purpose Driven: Languages designed for specific tasks.
- General Purpose: Languages like Java and JavaScript designed for a wide range of applications.
Compiled vs Interpreted Languages
- Interpreted Languages execute line by line directly.
- Compiled Languages translate code into binary for a specific operating system.
- Hybrid languages combine elements of both.
Programming Paradigms
- Structural or Procedural (Pascal, Fortran) prioritize sequential execution.
- Object Oriented emphasizes data and methods in objects.
- Functional utilizes functions as primary building blocks.
Installing Python
- Download Python from the official website (https://www.python.org/downloads/).
- Select the option to "add python into system path" during installation.
- Download Visual Studio Code (https://code.visualstudio.com/download).
Testing Python
- Open a terminal or command line tool.
- Type "python --version" to check if Python is installed correctly.
- Type "code." to test if VS Code is installed correctly.
Running Python
- Interactive Shell or REPL Interpreter: Execute code line by line.
- Python File: Create a file with the ".py" extension and run from the terminal using "python filename.py".
- Jupyter Notebook: Combines interactive and program file modes.
- Cells allow for code execution and Markdown documentation. Files have the ".ipynb" extension.
Writing in Python
- Space Sensitivity: Code blocks are defined by indentation using spaces.
- Case Sensitivity: Variable names like "MyName", "myName" and "myname" are different.
- Scope Sensitivity: Variables defined within functions are only accessible within those functions.
Comments in Python
- Single Line Comments: Use the "#" symbol.
- No Multiline Comments: Instead, use multiple single line comments or a docstring for multiline documentation.
Hello World!
- The
print("message")
function outputs a message to the user. -
print ("Hello World!")
will display the text "Hello World!" on the screen.
Variables
- Variables are like labeled boxes that store values.
- Think of them as containers holding specific types of data.
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Description
Explore the essential role of programming in data engineering and data science. Understand why Python is a favored language due to its flexibility and vast library ecosystem. Learn about the evolution of programming languages and the distinction between compiled and interpreted languages.