Shiny for Python Masterclass: Build Dashboards using Shiny

Arrange your app layout with columns in Shiny Express, use default widths, place cards and text, and leverage the 12-column bootstrap model with negative values to create spaces.

Explore scatter plots in plotly express using the iris dataset to compare petal length and petal width, add color by discrete species, adjust size, and tweak templates for dashboard visuals.

Learn to create histograms that show the distribution of sepal length in the iris dataset, customize bins and colors by species, and render Plotly graphs in shiny dashboards.

Learn how to create a scatter map box in Plotly Express using Mapbox to visualize population across cities with latitude and longitude, adjust zoom, and hover city names.

Explore how Plotly Express templates change color schemes and grid lines on an iris scatter plot, using ggplot, seaborn, simple white, and plotly themes.

Build a basic Gapminder dashboard in shiny with a title, a year dropdown, and an interactive, zoomable graph showing GDP versus life expectancy, color-coded by continent.

Build a Gapminder dashboard in shiny for python by importing pandas and plotly express, preparing data, adding a year dropdown widget, and visualizing life expectancy against GDP with continent coloring.

Build an interactive Titanic dashboard in Shiny for Python with dropdowns for embarkation and gender, displaying age distribution histograms, a survival pie chart, and fare box plots that update automatically.

Learn to preprocess Titanic data with pandas, fill missing embarked values with unknown, and create dropdowns for port of embarkment and gender using shiny UI cards and a grid layout.

Build interactive dashboards in Shiny for Python by adding histograms, a pie chart, and reactive filtering with port and gender widgets, rendering plots with Plotly Express.

Build a two-column Shiny for Python dashboard showing a histogram and a pie chart, using decorators and preprocessed data (survived counts) to render Plotly graphs.

Build a shiny for Python dashboard for US cities with a year slider. Use pandas and Plotly Express to render a map with a state dropdown and cyborg theme.

Connect the year and state dropdowns to a top ten cities by population bar chart using reactive calculations and Plotly, delivering a dynamic dashboard with a dark-themed bar visualization.

Build the iris dashboard using shiny python part 2 by adding a scatter plot in a main area card, filtered by a species dropdown using a reactive function.

Add a second card split into four equal columns and populate histograms for sepal width and sepal length using Plotly Express in a Shiny Python dashboard.

Add the two missing histograms to the app layout in this exercise. Review the solution video to learn how the histograms are implemented.

Adjust the dashboard theme by applying the minty theme from shiny swatch, updating visuals with ggplot2 templates, and exploring orange, gray, white color schemes for improved aesthetics.

Build the Spotify dashboard in Shiny for Python, featuring a heatmap of correlations and bar charts by genre, plus histograms of popularity, tempo, and duration with Plotly visuals.

Import libraries and prepare the Spotify dashboard data to focus on audio features, then create reactive filters and Plotly charts for correlation heatmaps and mean values.

Add histograms for track popularity and tempo by genre to your Shiny dashboard, using Plotly visuals in a card layout.

Add a duration histogram to the dashboard by creating a render_plotly function that returns a plotly express histogram from the existing dataframe, with X set to duration.

Build a Shiny dashboard in Python by rendering a Plotly histogram from a filtered data frame. Learn using a decorator, a dedicated function, and a card-based, column layout.

Review and revise a python shiny dashboard, tweaking interactive widgets that control five graphs, including a seven-feature heatmap, an average bar chart, and histograms of popularity, tempo, and duration.

Create a single-select dropdown with a unique id and a list of choices using Shiny's input select widget. Render the selected value with a decorator to display the output.

Learn to implement a multiselect dropdown in Shiny for Python using the select tiles input, define a unique id, enable multiple selections, and render the chosen values.

Learn to implement a checkbox group in a Shiny app with Shiny Express, including unique IDs and choices. Discover inline horizontal options, rendering and exporting selected values using render text.