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Easy Learning with Python Data Visualization Mastery: From Beginner to Expert
Development > Data Science
3 h
£14.99 £12.99
4.3 ★★★★★
7685 students

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Language: English

Python Data Visualization: From Novice to Pro

What you will learn:

  • Data Visualization Principles
  • Matplotlib Plotting
  • Seaborn Statistical Graphics
  • Plotly Interactive Charts
  • Folium Geographic Visualizations
  • Pandas Data Integration
  • Advanced Visualization Techniques
  • Data Storytelling
  • Dashboard Creation
  • Real-World Data Analysis
  • Interactive Dashboard Design
  • Data Visualization Best Practices

Description

Ready to transform raw data into captivating visuals that tell compelling stories?

This course, "Python Data Visualization: From Novice to Pro," isn't just another data visualization tutorial; it's your passport to mastering Python's most powerful data visualization libraries. Whether you're a complete beginner or an experienced developer aiming to elevate your skillset, we'll take you on a journey from basic plotting to creating interactive dashboards and sophisticated 3D visualizations.

We go beyond simple charts. You'll learn the art of effective data communication, mastering the selection of appropriate visualization types, employing effective color palettes, and skillfully annotating your visualizations. You'll explore techniques to transform complex datasets into easy-to-understand visual narratives that leave a lasting impression.

Why Python for Data Visualization?

Python's extensive libraries provide unparalleled flexibility and power. You'll learn how to use these tools for a broad range of scenarios, whether you're analyzing market trends, understanding scientific data, or constructing compelling reports.

Dive into these Key Areas:

  • Foundational Visualization Principles: Discover the core principles of effective chart selection and avoid common visualization pitfalls.
  • Matplotlib Mastery: Gain deep expertise in creating static, interactive, and animated plots with Matplotlib, learning its vast customization options.
  • Seaborn's Statistical Power: Master Seaborn's high-level interface for generating statistically-rich visuals, including insightful distributions and correlations.
  • Plotly's Interactive Edge: Build interactive, web-ready visualizations with Plotly, creating dynamic dashboards and stunning 3D plots.
  • Folium's Geographic Insights: Leverage Folium to visualize geographic data and create compelling interactive maps.
  • Pandas Integration: Streamline your data analysis and visualization workflows using pandas' powerful data manipulation capabilities.
  • Advanced Techniques: Explore advanced concepts such as time-series visualization, geospatial analysis and crafting statistically informative plots.
  • Data Storytelling: Learn to transform data insights into compelling visual narratives that resonate with any audience.

Become a Data Visualization Pro:

  • Confidently choose the optimal visualization technique for any data set.
  • Create a diverse range of visualizations across various libraries (Matplotlib, Seaborn, Plotly, Folium).
  • Tailor visualizations to precise design requirements.
  • Effectively communicate data insights to both technical and non-technical audiences.
  • Develop a professional portfolio of data visualization projects.

Enroll today and transform your data into impactful visuals that speak volumes. Master the art of data storytelling!

Curriculum

Introduction to Data Visualization

This introductory section lays the groundwork for your data visualization journey. "Basic Principles of Effective Visualization" equips you with the foundational understanding of choosing the right chart types and avoiding common mistakes. "Setting up the Python Environment" guides you through the essential steps to prepare your system for efficient data visualization projects.

Matplotlib Foundations

Dive into Matplotlib, the core library for Python visualizations. You'll learn to create various basic plot types – line, bar, and scatter – in "Creating Simple Plots (line, bar, scatter)". The next lecture teaches you customization techniques to enhance visuals with colours, markers, and labels, transforming plain plots into compelling graphs. "Subplots and Figure Size" shows you how to organize your plots efficiently, and "Saving Plots" teaches you to save your creations in various formats.

Seaborn for Statistical Visualizations

Seaborn simplifies the creation of statistically insightful graphs. "Introduction to Seaborn" gets you started. Learn to visualize distributions with "Distplot and Histogram" and explore "Box plot and Violin Plot" for comparing data groups. Understand relationships with "Scatter Plot and Joint Plot" and "Pair Plot", then learn to represent correlations with "Heatmap".

Plotly for Interactive Visualizations

Explore the power of Plotly for creating interactive and web-ready visualizations. "Introduction to Plotly" gets you started. You'll then create various interactive charts – line, scatter, bar, histograms, and pie/donut charts. "3D Plots" introduces a whole new dimension to your visualizations, and "Dashboards and Interactive Visualizations" teaches you to combine multiple plots into dynamic dashboards.

Advanced Data Visualization Techniques

This section delves into advanced visualization techniques. "Geospatial Data Visualization" teaches you to use maps to visualize geographic data. "Time Series Visualization" focuses on visualizing data points over time and "Statistical Charts (e.g., QQ plots, probability plots)" equips you with techniques for exploring statistical properties.

Real-World Data Visualization Projects

Put your newly-acquired skills to the test with real-world datasets. "Analyzing and Visualizing a Real-World Dataset" guides you through a complete workflow, and "Creating a Data Story Using Visualizations" teaches you to craft data visualizations that tell compelling stories.