**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

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