Data Science with Plotly, NumPy, Matplotlib, and Pandas

Data Science with Plotly, NumPy, Matplotlib, and Pandas
Data Science with Plotly, NumPy, Matplotlib, and Pandas
English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 11 Hours | 4.88 GB

Learn to acquire Data with NumPy and Pandas, transform it, and visualize it with Matplotlib and Plotly

Become a Master in Data Acquisition and Visualization with Python 3 and acquire employers’ one of the most requested skills of 21st Century! An expert level Data Science can earn minimum $100000 (that’s five zeros after 1) in today’s economy.

This is the most comprehensive, yet straight-forward course for the Data Science with Python 3 on Udemy! Whether you have never worked with Data Science before, already know basics of Python, or want to learn the advanced features of Plotly and Pandas with Python 3, this course is for you! In this course we will teach you Data Science with Python 3, Jupyter, NumPy, Pandas, Matplotlib, and Plotly .

(Note, we also provide you PDFs and Jupyter Notebooks in case you need them)

With over 40 lectures and more than 11 hours of video this comprehensive course leaves no stone unturned in teaching you Data Science with Python 3, Pandas, and Plotly!

This course will teach you Data Science in a very practical manner, with every lecture comes a 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, Jupyter, Pandas, and Plotly installed on your Windows computer and Raspberry Pi.

We cover a wide variety of topics, including:

  • Basics of Scientific Python Ecosystem
  • Basics of Pandas
  • 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
  • Basics of Matplotlib
  • Installation of SciPy and Pandas
  • Linear Algebra with NumPy and SciPy
  • Data Acquisition with Python 3
  • MySQL and Python 3
  • Data Acquisition with Pandas
  • Basics of Plotly
  • Configuring Charts with Plotly
  • NumPy and Plotly
  • Matplotlib and Plotly
  • Pandas and Plotly
  • Transformations with Plotly
  • Advanced visualizations with Pandas and Plotly

What you’ll learn

  • Understand the Scientific Python Ecosystem
  • Understand Data Science, Pandas, and Plotly
  • Learn basics of NumPy Fundamentals
  • Learn Advanced Data Visualization
  • Learn Data Acquisition Techniques
  • Linear Algebra and Matrices
Table of Contents

Introduction
1 Audience and Prerequisites
2 Course Contents and Topics Overview
3 Please leave your feedback
4 Scientific Python Ecosystem
5 URLs to the important projects in SciPy ecosystem

Install and Verify Python 3 on Windows
6 Python 3 on Windows
7 Verify the installation

Python 3 on Raspberry Pi
8 What is Raspberry Pi
9 Unboxing of Raspberry Pi
10 Web URLs for the download
11 Raspbian OS Installation Part 1
12 Raspbian OS Installation Part 2
13 Remote connection with VNC
14 Linux commands used in the section
15 Python on Raspberry Pi Raspbian OS

Basics of Python 3
16 Hello World! on Windows
17 Hello World! on Raspberry Pi
18 Python Interpreter mode vs Script Mode
19 IDLE
20 RPi Vs PC vs Mac

PyPI and pip
21 Python Package Index and pip
22 pip on Windows
23 pip3 on Raspberry Pi Linux

Install NumPy and Matplotlib
24 Install NumPy and Matplotlib on a Windows Computer
25 Install NumPy and Matplotlib on Raspberry Pi

Jupyter Notebook
26 Jupyter and IPython
27 Jupyter on Windows
28 Jupyter on Raspberry Pi
29 Remote connection with PuTTy
30 Connecting to Remote Jupyter Notebook
31 A brief tour of Jupyter
32 Notes of Jupyter Installation and Remote Connection

Getting Started with NumPy
33 Introduction to NumPy
34 Ndarrays, Indexing, and Slicing
35 Ndarray Properties
36 NumPy constants
37 NumPy Datatypes

Creation of Arrays and Matplotlib
38 Ones and Zeros
39 Matrices
40 What is Matplotlib
41 Numerical Rages Visualised

Random Sampling
42 Random Sampling

Array Manipulation Routines
43 Array Manipulation Routines

Bitwise Operations
44 Bitwise Operations

Statistical Functions
45 Statistical Functions

Plotting in detail
46 Single Line Plots
47 Multi Line Plots
48 Grid Axes and Labels
49 Color Line Markers

Installing SciPy and Pandas
50 Introduction to SciPy
51 Install SciPy on Windows
52 Install SciPy on Raspberry Pi
53 What is Pandas
54 Install Pandas on Windows
55 Install Pandas on Raspberry Pi

Matrices and Linear Algebra
56 Dot Products
57 Vector Dot Products
58 Inner Products
59 QR Decomposition
60 Determinant and Solving Linear Equations Improved
61 Linear Algebra with SciPy

Data Acquisition with Python, NumPy, and Matplotlib
62 Plain Text File Handling
63 CSV File Handling
64 Handling Excel File
65 NumPy file format
66 NumPy CSV File
67 Matplotlib CBook

Python and MySQL
68 MySQL Windows Installation
69 UPDATE
70 DELETE
71 DROP
72 Getting Started with MySQL and SQL Workbench
73 Connect to MySQL with SQL Developer
74 Exploring SQL Workbench
75 pymysql on Windows
76 Connect MySQL with Python 3
77 Execute DDL
78 INSERT
79 SELECT

Series and DataFrame in Pandas
80 Pandas Series
81 Pandas Dataframe

Data Acquisition with Pandas
82 Read CSV
83 Read Excel
84 Read JSON
85 Pickles
86 Pandas and Web
87 Read SQL
88 Clipboard

Downloadable Contents
89 BONUS LECTURE