#424: Shiny for Python

1

Introduction

00:00 • 3min

2

How I Got Into Programming R and Got Over to Python

02:30 • 3min

3

The Story of R Studio

05:57 • 2min

4

The Power of Shiny

08:07 • 2min

5

Shiny for Python: A Way to Create Web Applications

09:43 • 2min

6

The Future of Web Development

11:26 • 2min

7

The Differences Between Python and Jupyter Notebooks

13:48 • 4min

8

Python App for Ducks

17:20 • 2min

9

How to Use China to Do Fancy Math for GitHub

18:54 • 2min

10

Shiny for Python: An Open Source Platform for Data Scientists

20:50 • 2min

11

Shiny for Python: The Open Source Platform for Data Scientists

22:44 • 3min

12

Shiny for Python Displaces Power BI and Tableau

25:17 • 2min

13

GlareDB: An Open Source Database for Querying Distributed Data

27:12 • 2min

14

Streamlet: The Future of Python

28:49 • 5min

15

Shiny for Python

33:50 • 3min

16

The Future of Reactive Programming

36:41 • 3min

17

Reactive Programming: A Framework for Data Scientists

39:14 • 2min

18

The Importance of Reactive Programming

41:30 • 4min

19

Shiny for Python: A Data Scientist's Guide

45:25 • 2min

20

Python Data Science: The Future of Data Science

47:54 • 2min

21

Shiny for Python: An Open Source Framework for User Authentication

49:25 • 3min

22

The Future of Sleek for R

52:20 • 4min

23

The Power of Shiny for Python

56:02 • 2min

24

The Future of Web App Development

58:01 • 3min

25

How to Be a Better R and Python Developer

01:00:58 • 2min

26

How to Write Python Code

01:02:33 • 2min