Django with Data Science

Video description

This course will show you how to create a professional and attractive user interface (UI) in Django for data science using the Semantic UI framework. If you don’t have a programming background, this course will help you create custom analytic tools in the browser by taking you through the core concepts of pandas, NumPy, Matplotlib, and Seaborn. With a step-by-step introduction to new concepts, this Django course will gradually help you get to grips with the essentials of data science.

What You Will Learn

  • Understand the integration of Django and Python data science libraries: pandas, Matplotlib, Seaborn, and NumPy
  • Populate the database from CSV files
  • Explore the Semantic UI framework
  • Get to grips with the basics of data science

Audience

If you are a developer looking to dive into the world of data science with Django, this course is for you.

About The Author

Lukasz Makinia: Lukasz Makinia is a freelance web developer and a Lean Sigma Six Black Belt. From the beginning of his 8-year professional career, he’s related to the field of continuous improvement by providing IT and Lean Management solutions to medium and large companies. He also creates web applications mainly for data gathering and processing using Python/Django, JavaScript, React, and ML. In his free time, Luke writes articles for his blog—PyPlane.

He is associated with “Django Ninjas”—a web framework for building APIs with Django and Python 3.6+ type hints. They provide online educational courses mainly about Python/Django by the community of web developers across the globe. Their classes are project-based only, which means “teaching by doing”.

Publisher resources

Download Example Code

Table of contents

  1. Chapter 1 : Django Project
    1. How to get Visual Studio code and Anaconda
    2. Setting Up the Django Project Part I
    3. Setting Up the Django Project Part II
    4. Creating the First Model
    5. Creating Another Model
    6. Creating Our First View (with pandas Dataframes)
    7. Merging Two Dataframes
    8. Adding Static Files
    9. Creating a Chart Selection Form
    10. Adding JS to the Form
    11. Sending the Data to the View
    12. Displaying Error Messages
    13. Adding Objects
    14. Working with the Date
    15. Performing GroupBy
    16. Adding Additional Logic to the View
    17. Chart Function Part I
    18. Chart Function Part II
    19. Chart Function Part III
    20. Displaying the Chart
    21. Styling the Error Message
    22. Closing the Error Message
    23. Creating Modal with Price Statistics
    24. Adding Styling
    25. Applying a Fix to the Chart and Button Creation
    26. Creating Purchase View
    27. Creating Django Model Form
    28. Finishing Django Model Form
    29. Testing the Model Form
    30. Adding Send Confirmation
    31. Navigation to the Purchase View
    32. Remarks on the Chart View
    33. Adding Navbar
    34. Creating the CSV Model
    35. Setting Up the Upload View
    36. Creating the Django Form for File Upload
    37. Resetting the Database
    38. Chart View Fix
    39. Exploring the CSV File - Sales Data
    40. Saving CSV File via Form
    41. Opening the CSV File - Sales Data
    42. Transforming Rows of the CSV File - Sales Data
    43. Populating the Database from CSV File - Sales Data
    44. Creating Customers App and Model
    45. Creating Customer View
    46. Setting Up Customer View
    47. Finishing the Customer View
    48. Working on the Sales View Part I
    49. Working on the Sales View Part II
    50. Styling the Graphs
    51. Creating the Home View
    52. Creating Login Form and Login View
    53. Working on the Login
    54. Continue Working on the Login
    55. Final Touches for the Login
    56. Logout View
    57. Outro
  2. Chapter 2 : Python Data Science Libraries
    1. Introduction to Data Science

Product information

  • Title: Django with Data Science
  • Author(s): Lukasz Makinia
  • Release date: August 2020
  • Publisher(s): Packt Publishing
  • ISBN: 9781800564725