Tutorials
Hands-On Python
Hands-On Python
  • Hands-On Python Tutorial For Real-World Business Analytics Problems
  • Preface
    • Section I. A Note From The Author
    • Section II. Tutorial Overview
    • Section III. What Is The Preflight Checklist?
    • Section IV. Supplimentery Material
  • Preflight Checklist
    • Section V. Select Your Difficulty Setting
    • Section VI. Download Anaconda
    • Section VII. Download PyCharm (Optional)
    • Section VIII. Download SQL Server Developer Edition
    • Section IX. Configure Database Environment
    • Section X. Download The Source Code
    • Section XI. Starting JupyterLab
    • Section XII. How To Get Help With This Tutorial
  • Language Basics
    • Lesson 1. Obligatory Hello World
    • Lesson 2. Code Comments
    • Lesson 3. Data Types
    • Lesson 4. Variables
    • Lesson 5. String Concatenation
    • Lesson 6. Arithmetic Operators
    • Lesson 7. Making Decisions
    • Lesson 8. Control Flow With if-elif-else
    • Lesson 9. Control Flow With while
    • Lesson 10. Data Structures Part I: List
    • Lesson 11. Data Structures Part II: Tuples
    • Lesson 12. Data Structures Part III: Dictionaries
    • Lesson 13. Looping With for
    • Lesson 14. Functions
    • Lesson 15. Importing Modules
    • Lesson 16. Python Programming Standards
  • Advanced Topics
    • Lesson 17. Functional Programing With map
    • Lesson 18. Generators
    • Lesson 19. Comprehensions
    • Lesson 20. Basic File Operations
    • Lesson 21. Working With Data In Numpy
    • Lesson 22. Working With Data In Pandas
    • Lesson 23. Working With JSON
    • Lesson 24. Making File Request Over HTTP And SFTP
    • Lesson 25. Interacting With Databases
    • Lesson 26. Saving Objects With Pickle
    • Lesson 27. Error Handling
    • Lesson 28. Bringing It All Together
  • Solutions To Real World Problems
    • Lesson 29. Download A Zip File Over HTTP
    • Lesson 30. Looping Over Files In A Directory
    • Lesson 31. Convert Comma Delmited Files To Pipe Delimited
    • Lesson 32. Combining Multiple CSVs Into One File
    • Lesson 33. Load Large CSVs Into Data Warehouse Staging Tables
    • Lesson 34. Efficiently Write Large Database Query Results To Disk
    • Lesson 35. Working With SFTP In The Real World
    • Lesson 36. Executing Python From SQL Server Agent
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  1. Preflight Checklist

Section XI. Starting JupyterLab

JupyterLab is started from the command line.

  1. Search for and open the program Anaconda Prompt.

  2. Change directories to wherever you placed the source code folder then change directories to tutorial-python\Notebooks.

  3. Type jupyter lab

Jupyter Lab will open in a browser window. You will also notice that the Anaconda Prompt window did not close. That is your kernel, and you need to keep that bad boy open. If you close Anaconda Prompt, your JupyterLab instance will become unresponsive and die.

It is possible to bring it back to life without closing your browser window. Just follow the previous steps for starting JupyterLab and your instance will pull a Ra's al Ghul and you can keep truckin’.

A security feature of JupyterLab is you cannot navigate outside of the directory you opened the program in. So whenever you start JupyterLab, make sure you are in a directory low enough that you will have access to all the assets you need to perform your work.

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Last updated 3 years ago