Shiny For Python Masterclass: Build Dashboards From Data

Posted By: ELK1nG

Shiny For Python Masterclass: Build Dashboards From Data
Published 12/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.76 GB | Duration: 5h 28m

Transform Your Data into Interactive Web Apps with Shiny -Leverage Plotly and Pandas to Build Stunning Dashboards

What you'll learn

Learn how to develop beautiful web apps and dashboards using the Shiny Library in Python.

Learn how to create effective and compelling visuals using plotly express.

Learn how to tackle any dashboard project given the dataset.

Learn how to add reactivity and interactivity to your Shiny Dashboards.

Requirements

You should have Python installed on your computer and be able to run your python code in an IDE of your choice.

A beginner level knowledge of python is adequate (i.e. you are comfortable with the common python objects such as lists, strings, tuples, dictionaries and python functions).

Description

Do you want to build interactive, dynamic web applications using Python without becoming a full-fledged web developer? Look no further! Shiny for Python makes it easy to turn your data analysis workflows into professional-grade dashboards and web apps—all powered by Python.In this course, you’ll master Shiny for Python, a framework that brings the power of interactivity to your data visualizations and analyses. From creating simple applications to developing complex, feature-rich dashboards, this course will guide you through the essential concepts, tools, and techniques step by step.Whether you're a data scientist, analyst, or Python enthusiast, this course equips you with the skills to build beautiful, functional applications that deliver insights and engage users.What You'll Learn:Shiny Basics:Create your first "Hello World" Shiny app in Python.Advanced Features:Leverage reactivity for real-time app updates.Integrate popular libraries like Pandas and Plotly.User Experience Design:Craft intuitive and visually appealing dashboards.Optimize layouts for different screen sizes.Real-World Use Cases:Build apps for data exploration, reporting, and real-time monitoring.Who This Course Is For:Data Scientists: Take your analysis beyond the Jupyter notebook, add interactivity to your analyses, and share insights seamlessly.Python Developers: Build powerful web apps without learning JavaScript or HTML.Business Analysts: Create self-service dashboards for stakeholders.Students & Enthusiasts: Learn a high-demand skill in the growing field of data science and become a freelance consultant.Why Take This Course?No prior web development experience is required!Hands-on coding exercises and real-world projects.Practical examples tailored for data science, business analytics, and research applications.Tips and tricks to create performant, polished dashboards.By the end of this course, you’ll be confident in designing and deploying Shiny-powered Python apps that bring your data to life. Let’s build something amazing together!

Overview

Section 1: Introduction

Lecture 1 Install libraries

Lecture 2 Hello world!

Lecture 3 Lets make the hello world app more beautiful with a Card element

Lecture 4 How to set a theme in Shiny

Lecture 5 EXERCISE: Make the dashboard look like this

Lecture 6 Hint to exercise

Section 2: Quick Plotly Express Refresher (Optional Section)

Lecture 7 Scatterplot

Lecture 8 Boxplot and Violin plot

Lecture 9 Histogram

Lecture 10 Bar Charts

Lecture 11 Plotly Templates

Section 3: Gapminder Dashboard (Basic version)

Lecture 12 What we will build– Gapminder Dashboard

Lecture 13 Get the Data

Lecture 14 Lets build the Gapminder dashboard using Shiny For Python

Section 4: US Cities Population Dashboard

Lecture 15 What we will build– US Cities Dashboard using Shiny for Python

Lecture 16 Get the Data

Lecture 17 Add slider and dropdown widget Redo

Lecture 18 Add mapbox chart Redo

Lecture 19 Add Barchart

Section 5: Iris Dashboard

Lecture 20 Introduction to what we will build - Iris Dashboard

Lecture 21 Get the Data

Lecture 22 Build Iris Dashboard using SHiny Python _Part 1 Add sidebar and dropdown widget

Lecture 23 Build the iris dashboard using Shiny Python Part 2 Add scatterplot

Lecture 24 Build the Iris Dashboard using Shiny Python Part 3 - Add two histograms

Lecture 25 Exercise- Add the Histograms to the layout

Lecture 26 Solution to Exercise

Lecture 27 Adjust the size parameter of the plot

Lecture 28 Lets adjust the theme of the dashboard

Section 6: Spotify Dashboard built using Shiny for Python

Lecture 29 What we will build – Spotify Dashboard

Lecture 30 Get the Data

Lecture 31 Data processing for the dashboard

Lecture 32 Add the correlation heatmap and bar charts

Lecture 33 Add the histograms for Track popularity and Track tempo for the different genres

Lecture 34 EXERCISE: Add Histogram to the dashboard for track duration

Lecture 35 SOLUTION

Lecture 36 Code revision

Section 7: Reference: Widgets in Shiny

Lecture 37 Dropdown widget in Shiny (input_select)

Lecture 38 Multiselect Dropdown in Shiny

Lecture 39 Checkbox Group in Shiny

Section 8: Reference: Plotly Express for Data Visualization

Lecture 40 Scatterplots in Plotly Express

Lecture 41 Histogram in Plotly Express

Lecture 42 Sunburst Chart in Plotly Express

Section 9: Reference: Pandas for Data Wrangling Crash Course

Lecture 43 Basics of Pandas

Lecture 44 Arithmetic operations in Pandas

Lecture 45 Statistical operations in Pandas

Lecture 46 Select subset of Data using the select_dtype function

Lecture 47 Rename columns and rows in Pandas

Lecture 48 Dropping rows and columns in a DataFrame

Lecture 49 Select subset of data using LOC function

Lecture 50 Select subset of dataframe using ILOC

Lecture 51 Groupby Part 1

Lecture 52 Groupby Part 2

Lecture 53 Reshape data using Melt

Lecture 54 How to filter a dataframe using isin function

Lecture 55 Filter a dataframe using boolean operators

Lecture 56 Advanced filtering using OR and AND operators

The course is for students with a knowledge of Python that are interested in creating web apps and dashboards using only python.