Getting Started With Plotly | Interactive Data Visualization in Python

Pubblicato il: 06 marzo 2026
sul canale di: Data science world
0

Plotly is a powerful interactive data visualization library used in Python, R, and JavaScript to create dynamic charts, dashboards, and analytical visualizations. It is widely used by data scientists, analysts, and developers to present data in a visually engaging and interactive way.

In this tutorial, you will learn the basics of Plotly, including how to create different types of visualizations such as line charts, bar charts, histograms, and sunburst charts. The video also demonstrates how to connect Plotly with API data, GitHub datasets, Google Sheets, and local CSV files to generate real-time visualizations.

Plotly is commonly used in data science, machine learning projects, financial analytics, and business intelligence dashboards because of its ability to create interactive and web-based charts that allow users to zoom, filter, and explore data.

Another important advantage of Plotly is that it integrates well with Dash, a framework used to build interactive web dashboards for data applications using Python.

📌 In this video:
00:00 – What is Plotly
01:02 – API Data & Line Chart
02:13 – GitHub Data & Bar Chart
03:42 – Google Sheets Data & Sunburst Chart
05:18 – Local CSV & Histogram
06:23 – Plotly High-Level Documentation

📊 Key Concepts Covered:
• Introduction to Plotly for interactive data visualization
• Creating line charts, bar charts, histograms, and sunburst charts
• Importing data from APIs, GitHub, Google Sheets, and CSV files
• Understanding Plotly’s high-level visualization API
• Building interactive and dynamic charts for data analysis
• Using Plotly for dashboards and analytics applications

This video is ideal for beginners in Data Science, Data Analytics, and Python visualization who want to learn how to create interactive charts and dashboards using Plotly.

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#Plotly #DataVisualization #Python #DataScience #DataAnalytics #MachineLearning #InteractiveCharts #Dash


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