| 1. Anaconda Installation.mp4 | 133.9 MB | ||
| 2. Introduction to Jupyter Notebook interface.mp4 | 59.2 MB | ||
| 3. Introduction to Matplotlib.mp4 | 19.1 MB | ||
| 3.1 1. Introduction to Matplotlib.ipynb | 11.6 KB | ||
| 3.2 1. Introduction to Matplotlib.pdf | 26.4 KB | ||
| 4. Line Chart Plot.mp4 | 137.2 MB | ||
| 4.1 2. Line Chart Plot.ipynb | 173.2 KB | ||
| 4.2 2. Line Chart Plot.pdf | 263.8 KB | ||
| 4.3 class.csv | 409.6 B | ||
| 5. Plotting a Bar Chart.mp4 | 125.4 MB | ||
| 5.1 3. Plotting a Bar Charts.ipynb | 106.8 KB | ||
| 5.2 3. Plotting a Bar Charts.pdf | 223.6 KB | ||
| 6. Histogram and Scatter Plot.mp4 | 53.7 MB | ||
| 6.1 4. Histogram and Scatter Plot.ipynb | 71.4 KB | ||
| 6.2 4. Histogram and Scatter Plot.pdf | 155.3 KB | ||
| 7. Stack Plot and Pie Plot.mp4 | 86 MB | ||
| 7.1 5. Stack Plot and Pie Plot.ipynb | 107.9 KB | ||
| 7.2 5. Stack Plot and Pie Plot.pdf | 150 KB | ||
| 8. Subplots.mp4 | 126.2 MB | ||
| 8.1 6. Plotting Subplots.ipynb | 158.8 KB | ||
| 8.2 6. Plotting Subplots.pdf | 225.6 KB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 23 total files | |||
Mastering Data Visualization in Analytics using Python
https://DevCourseWeb.com
Published 4/2024
Created by Ganeshraj Shetty
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 8 Lectures ( 1h 14m ) | Size: 742 MB
Unlocking Insights: Advanced Data Visualization Techniques with Python
What you'll learn:
Introduction to Matplotlib and its capabilities for creating various types of plots.
Plotting with Matplotlib: Line plots, Scatter plots, Bar plots, Pie Chart, Stack Plot and Histogram.
Customizing plots: Changing colors, Styles, Markers, and Line widths.
Adding Titles, Labels, and Legends to plots for better interpretation.
Working with multiple subplots and figures to create complex visualizations.
Saving plots in image formats (e.g., PNG) for publication or sharing.
Best practices for creating clear, informative, and aesthetically pleasing visualizations.
Practical examples and case studies nstrating real-world applications of data visualization with Matplotlib.
Requirements:
Basics of Mathematics and Python Programming
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