Interactive Data Visualization with Plotly in Python: A Comprehensive Guide
Learn how to use Plotly in Python to create interactive visualizations for data analysis, dashboards, and scientific research. This beginner-friendly guide covers installation, core concepts, and step-by-step examples using both Plotly Express and graph objects. You will learn to make line charts, bar charts, scatter plots, histograms, pie charts, and custom figures, as well as how to handle missing data and errors.
Follow along as we build a small interactive dashboard and explore best practices for labeling, sharing, and debugging your visualizations. Whether you are new to data visualization or looking to enhance your Python skills, these practical examples will help you get started with Plotly quickly and effectively.
00:00 Introduction to Plotly
00:19 Real-world uses
00:26 Installing Plotly
00:36 Importing modules
00:49 Core concepts overview
01:13 First line plot example
01:41 Creating a bar chart
01:59 Making a scatter plot
02:19 Multi-line plots
02:43 Customizing labels and legends
03:04 Scatter plots with color and size
03:38 Building a histogram
04:04 Creating a pie chart
04:31 Combining line and bar in one figure
05:02 Facet plots for grouped data
05:35 Interactive plots with dropdowns
06:29 Handling missing values
07:25 Error handling with wrong column names
08:04 Displaying plots in notebooks
08:43 Best practices and tips
09:12 Building an interactive dashboard
11:10 Dashboard review and conclusion
#Python #DataVisualization #Plotly
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