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Introduction to Data Visualization
0/3
1. Introduction to Python for Data Visualization
05:34
2. The Importance of Data Visualization and Typess
05:37
3. Installing Required Libraries (Matplotlib, Seaborn, Plotly, etc.)
16:49
Getting Started with Matplotlib
0/4
4. Basic Plotting: Line Plots, Scatter Plots, and Bar Charts
10:21
5. Customizing Plots: Titles, Labels, and Legends
10:54
6. Working with Colors, Markers, and Line Styles
12:40
7. Creating Subplots for Multiple Charts
06:51
Advanced Matplotlib Techniques
0/5
8. Customizing Plot Axes and Ticks
09:07
9. Adding Annotations and Text to Plots
10:15
10. Creating Histograms and Density Plots
08:23
11. Working with 3D Plots in Matplotlib
12:11
12. Saving and Exporting Charts for Different Formats
09:02
Data Visualization with Seaborn
0/3
13. Creating Pair Plots, Heatmaps, and Violin Plots
12:06
14. Customizing Aesthetics with Seaborn Themes and Styles
08:17
15. Visualizing Relationships with Seaborn (Categorical, Linear, and Non-linea
07:36
Interactive Visualizations with Plotly
0/3
16. Creating Interactive Line, Bar, and Scatter Plots
10:33
17. Visualizing Geospatial Data with Plotly
12:04
18. Building Interactive Dashboards with Plotly Dash
09:15
Visualizing Data with Pandas and Other Libraries
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19. Using Pandas for Quick Data Visualization
10:39
20. Visualizing Time Series Data
06:04
21. Data Visualization with Altair and Bokeh
11:57
22. Creating Interactive Visualizations with Altair
10:35
Visualizing Large Datasets
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23. Working with Big Data: Challenges and Strategies
10:11
24. Visualizing Data with Dask and Vaex
09:16
25. Optimizing Performance for Large Data Visualizations
09:55
Visual Storytelling and Design Principles
0/3
26. Principles of Effective Data Storytelling
12:03
27. Using Color Effectively in Data Visualizations
07:24
28. Typography and Layout for Enhanced Clarity
09:02
The Ultimate Python Data Visualization Course- Step By Step
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