Udemy - Mastering Data Visualization in Analytics using Python

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Udemy - Mastering Data Visualization in Analytics using Python (Size: 742.3 MB)
  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

Description


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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