The Ultimate Python Data Visualization Course- Step By Step
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.25 GB | Duration: 4h 34m
Master Data Visualization with Python: A Complete Step-by-Step Guide to Unlocking the Power of Your Data
What you'll learn
Introduction to Python for Data Visualization
Installing Required Libraries (Matplotlib, Seaborn, Plotly, etc.)
Basic Plotting: Line Plots, Scatter Plots, and Bar Charts
Customizing Plots: Titles, Labels, and Legends
Creating Subplots for Multiple Charts
Adding Annotations and Text to Plots
Saving and Exporting Charts for Different Formats
Customizing Aesthetics with Seaborn Themes and Styles
Creating Pair Plots, Heatmaps, and Violin Plots
Visualizing Relationships with Seaborn (Categorical, Linear, and Non-linear)
Creating Interactive Line, Bar, and Scatter Plots
Building Interactive Dashboards with Plotly Dash
Visualizing Time Series Data
Optimizing Performance for Large Data Visualizations
Principles of Effective Data Storytelling
Using Color Effectively in Data Visualizations
Requirements
No Prior Experience Required
Description
Unlock the power of your data with 'The Ultimate Python Data Visualization Course- Step By Step.' This comprehensive course is designed to take you from a beginner to an expert in Python data visualization. You'll learn how to create stunning and informative visuals that communicate your data's story effectively.Starting with the basics, you'll delve into Python's powerful libraries like Matplotlib, Seaborn, and Plotly. Each section of the course builds on the previous one, ensuring a solid understanding of core concepts before moving on to more advanced techniques. You'll work on real-world projects and practical examples that bring theory to life and equip you with skills you can apply immediately.This Course Include:Introduction to Data VisualizationIntroduction to Python for Data VisualizationThe Importance of Data Visualization and TypessInstalling Required Libraries (Matplotlib, Seaborn, Plotly, etc.)Getting Started with MatplotlibBasic Plotting: Line Plots, Scatter Plots, and Bar ChartsCustomizing Plots: Titles, Labels, and LegendsWorking with Colors, Markers, and Line StylesCreating Subplots for Multiple ChartsAdvanced Matplotlib TechniquesCustomizing Plot Axes and TicksAdding Annotations and Text to PlotsCreating Histograms and Density PlotsWorking with 3D Plots in MatplotlibSaving and Exporting Charts for Different FormatsData Visualization with SeabornCreating Pair Plots, Heatmaps, and Violin PlotsCustomizing Aesthetics with Seaborn Themes and StylesVisualizing Relationships with Seaborn (Categorical, Linear, and Non-linear)Interactive Visualizations with PlotlyCreating Interactive Line, Bar, and Scatter PlotsVisualizing Geospatial Data with PlotlyBuilding Interactive Dashboards with Plotly DashVisualizing Data with Pandas and Other LibrariesUsing Pandas for Quick Data VisualizationVisualizing Time Series DataData Visualization with Altair and BokehCreating Interactive Visualizations with AltairVisualizing Large DatasetsWorking with Big Data: Challenges and StrategiesVisualizing Data with Dask and VaexOptimizing Performance for Large Data VisualizationsVisual Storytelling and Design PrinciplesPrinciples of Effective Data StorytellingUsing Color Effectively in Data VisualizationsTypography and Layout for Enhanced ClarityDesigned for data analysts, business professionals, and aspiring data scientists, this course provides the tools to make data-driven decisions with confidence. Unlock your data's potential with this comprehensive, step-by-step guide and become a visualization expert.Enroll now in this transformative journey and start making your data speak volumes!
Overview
Section 1: Introduction to Data Visualization
Lecture 1 Introduction to Python for Data Visualization
Lecture 2 The Importance of Data Visualization and Typess
Lecture 3 Installing Required Libraries (Matplotlib, Seaborn, Plotly, etc.)
Section 2: Getting Started with Matplotlib
Lecture 4 Basic Plotting: Line Plots, Scatter Plots, and Bar Charts
Lecture 5 Customizing Plots: Titles, Labels, and Legends
Lecture 6 Working with Colors, Markers, and Line Styles
Lecture 7 Creating Subplots for Multiple Charts
Section 3: Advanced Matplotlib Techniques
Lecture 8 Customizing Plot Axes and Ticks
Lecture 9 Adding Annotations and Text to Plots
Lecture 10 Creating Histograms and Density Plots
Lecture 11 Working with 3D Plots in Matplotlib
Lecture 12 Saving and Exporting Charts for Different Formats
Section 4: Data Visualization with Seaborn
Lecture 13 Creating Pair Plots, Heatmaps, and Violin Plots
Lecture 14 Customizing Aesthetics with Seaborn Themes and Styles
Lecture 15 Visualizing Relationships with Seaborn (Categorical, Linear, and Non-linear)
Section 5: Interactive Visualizations with Plotly
Lecture 16 Creating Interactive Line, Bar, and Scatter Plots
Lecture 17 Visualizing Geospatial Data with Plotly
Lecture 18 Building Interactive Dashboards with Plotly Dash
Section 6: Visualizing Data with Pandas and Other Libraries
Lecture 19 Using Pandas for Quick Data Visualization
Lecture 20 Visualizing Time Series Data
Lecture 21 Data Visualization with Altair and Bokeh
Lecture 22 Creating Interactive Visualizations with Altair
Section 7: Visualizing Large Datasets
Lecture 23 Working with Big Data: Challenges and Strategies
Lecture 24 Visualizing Data with Dask and Vaex
Lecture 25 Optimizing Performance for Large Data Visualizations
Section 8: Visual Storytelling and Design Principles
Lecture 26 Principles of Effective Data Storytelling
Lecture 27 Using Color Effectively in Data Visualizations
Lecture 28 Typography and Layout for Enhanced Clarity
Anyone interested in Python programming, Python scripting, machine learning, data science and data visualization.,Those who are interested to learn data science or data visualization application.
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