Gain insights into Plotly and Dash to create interactive data visualizations and web dashboards with Python. Explore visualization, customization, and interactivity, mastering complex datasets and dashboard apps.

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Discover the compelling universe of Plotly and Dash, versatile Python libraries that enable interactive data visualization and web dashboard applications. These tools are essential for anyone seeking to effectively communicate data narratives and build interactive data visualizations.

You'll explore Plotly’s robust data visualization capabilities. You’ll create plots for univariate, bivariate and multivariate analysis before customizing and adding interactivity, using real world datasets. Then, you’ll build upon and use these skills when learning Dash as you build and customize analytical dashboard apps. You’ll journey through Dash's structure, from understanding layouts and HTML components to mastering Dash styling using CSS. You’ll learn the significance of callback functions, enhancing user interactivity, and experience the power of Dash's DataTable component.

By the end of this course, you'll be able to create engaging visualizations with Plotly and develop interactive web applications using Dash.

Mastering Plotly and Dash Data Visualization with Python

## Bar chart
Here we explore the concept of a bar chart and where it is most useful.

A **bar chart** is a type of graph used to display and compare the frequency, total, or average values of categorical data values. It consists of rectangular bars, with the height or length of each bar representing the value of the data for a specific category. Bar charts are used to compare data between categories and to visualize patterns, trends, and relationships in data.


# Bar chart
Here we explore the concept of a bar chart and where it is most useful.

A **bar chart** is a type of graph used to display and compare the frequency, total, or average values of categorical data values. It consists of rectangular bars, with the height or length of each bar representing the value of the data for a specific category. Bar charts are used to compare data between categories and to visualize patterns, trends, and relationships in data.


Extend your knowledge on bivariate analysis, learning how to create more plots to visualize a continuous variable against a categorical variable.

Continuous vs. Categorical Bivariate Analysis: ECDF & Violin Plot

Introduction and Univariate Analysis

Exploratory Data Analysis - Bivariate and Multivariate Analysis

Customizing Plots

Advanced Customization

Interactivity in Plotly

Visualizing Machine Learning Models with Plotly

Global Energy Consumption Visualization

Introducing Dash

Dash Layout

Dash Styling

Dash Callbacks

User Interactivity in Dash

Tabular data in Dash DataTable

Global Energy Consumption Dashboard

Conclusion

Continuous vs. Categorical Bivariate Analysis: ECDF & Violin Plot

Bar chart