English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 8 Hours | 3.52 GB
Learn Python 3 Data Visualization: Jupyter, NumPy, and Matplotlib in a single course, Create awesome visualizations
Become a Master in Data Visualization with Python 3 and acquire employers’ one of the most requested skills of 21st Century! A great data visualization engineer earns more than $150000 per year!
This is the most comprehensive, yet straight-forward course for the Data Visualization with Python 3 on Udemy! Whether you have never worked with Data Visualization before, already know basics of Python, or want to learn the advanced features of matplotlib and NumPy with Python 3, this course is for you! In this course we will teach you Data Visualization with Python 3, Jupyter, NumPy, and Matplotlib.
(Note, we also provide you PDFs and Jupyter Notebooks in case you need them)
This course will teach you Data Visualization in a very practical manner, with every lecture comes a full programming video and a corresponding Jupyter notebook that has Python 3 code! Learn in whatever manner is the best for you!
We will start by helping you get Python3, NumPy, matplotlib, and Jupyter installed on your Windows computer and Raspberry Pi.
We cover a wide variety of topics, including:
- Basics of Scientific Python Ecosystem
- Basics of Digital Image Processing
- Basics of NumPy and Matplotlib
- Installation of Python 3 on Windows
- Setting up Raspberry Pi
- Tour of Python 3 environment on Raspberry Pi
- Jupyter installation and basics
- NumPy Ndarrays
- Array Creation Routines
- Basic Visualization with Matplotlib
- Ndarray Manipulation
- Random Array Generation
- Bitwise Operations
- Statistical Functions
- Plotting with Matplotlib
- Other types of visualizations (bar, histograms, scatter, and bubble)
- Contours
- 3D Visualizations (plot, mesh, and surfaces)
- Advanced Concepts in Matplotlib
- and much more…..
What you’ll learn
- Prepare excellent Visualizations
- Publications and Printing quality Visualizations
- 3D Visualizations
- Image Processing with NumPy and Matplotlib
- Add Matplotlib and NumPy in resume
- Appear for interviews confidently
Table of Contents
Introduction
1 Please leave your feedback
2 Scientific Python Ecosystem
3 Introduction to Matplotlib
4 URLs to the important projects in the Scientific Python Ecosystem
Python 3 on Windows
5 Python 3 on Installation on Windows
6 Verify the Installation and the environment
Python 3 on Raspberry Pi
7 What is Raspberry Pi
8 Unboxing of Raspberry Pi 3B+
9 URLs of all the softwares used in this section
10 Raspberry Pi Raspbian OS Setup Part 1
11 Raspberry Pi Raspbian OS Setup Part 2
12 Remote Connection with VNC
13 Linux commands used in the Section
14 Python 3 on Raspberry Pi
Python 3 Basics
15 Hello World on Windows
16 Hello World on Raspberry Pi
17 Interpreter vs Script
18 A brief Tour of IDLE
19 RPi vs PC
PyPI and pip
20 Python Package Index and pip
21 pip on Windows
22 pip on Raspberry Pi
Install NumPy and Matplotlib on Windows and Raspberry Pi
23 Install NumPy and Matplotlib on Windows
24 Install NumPy and Matplotlib on Raspberry Pi
Jupyter Notebook
25 Jupyter and IPython
26 Jupyter Installation on Windows
27 Jupyter Installation on Raspberry Pi
28 Remote Connection with PuTTY
29 Connecting to Remote Jupyter Notebook
30 Jupyter Notebook Notes
Getting Started with NumPy
31 Introduction to NumPy
32 Ndarrays, Indexing, and Slicing
33 Ndarray Properties
34 NumPy Constants
35 NumPy DataTypes
Creation of Arrays and Visualizations
36 Ones and Zeros
37 Matrices
38 Numerical Ranges and Visualizations
Random Sampling
39 Random Sampling
Array Manipulation
40 Array Manipulation
Bitwise Operations
41 Bitwise Operations
Statistical Functions
42 Statistical Functions
Matplotlib and NumPy Recipes
43 Simple Plots
44 D Histograms
45 Polar Bar Graphs
46 Scatter Plots
47 Pie Charts
48 Scatter Polar Plot
49 Horizontal Bar Graphs
50 Histograms
51 Histogram of IQ of Population
52 Stacked Bar Plot
53 Countours and Points
54 Time Plots
55 MultiColor Graphs
56 D Bar Graph
57 MultiColored 3D Plots
58 D Contours
59 Multiplying Two Signals
60 Different Strokes
61 Filled Plots
62 Dashed Plots
63 Colored Plots
64 Dotted Plot
65 Polar Plot
Matplotlib and Pandas
66 What is Pandas
67 Install Pandas on Windows
68 Install Pandas on Raspberry Pi
69 Series in Pandas
70 DataFrame in Pandas
71 Pandas and Matplotlib
Downloadable Code Section
72 Downloadable Code Bundle
73 BONUS LECTURE
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