**Python 3 Data Science – Time Series with Pandas**

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 12 Hours | 5.35 GB

Learn NumPy, Matplotlib, Jupyter, Pandas, Plotly, Altair, Seaborn, and Time Series Analysis in a single course

Become a Master in Data Acquisition, Visualization, and Time Series Analysis with Python 3 and acquire employers’ one of the most requested skills of 21st Century! An expert level Data Science professional 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 and Time Series 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 Pandas Time Series with Python 3, this course is for you! In this course we will teach you Data Science and Time Series 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 95 lectures and more than 10 hours of video this comprehensive course leaves no stone unturned in teaching you Data Science with Python 3, Pandas, and Time Series Analysis!

This course will teach you Data Science and Time Series 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
- Dataframes and Series in Pandas
- Time Series in Pandas
- Time Series analysis with Matplotlib, Plotly, Seaborn, and Altair

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
- Time Series with Pandas
- Time Series with Plotly, Matplotlib, Altair, and Seaborn

**Table of Contents**

**Introduction**

1 Objectives, Prerequisites, and Audience

2 Course Topics Overview

3 Please Leave your feedback

4 Scientific Python Ecosystem

5 Important URLs

**Python 3 on Windows**

6 Python 3 on Windows

7 Verify Python 3 environment on Windows

**Python 3 on Raspberry Pi**

8 What is Raspberry Pi

9 Unboxing

10 Important URLs used in the Setup of Raspberry Pi

11 Raspbian OS Setup on Raspberry Pi Part 1

12 Raspbian OS Setup on Raspberry Pi Part 2

13 Remotely connect to RPi with VNC

14 Commands used in the section

15 Python 3 on Raspberry Pi

**Python 3 Basics**

16 Hello World! on Windows

17 Hello World! on Raspberry Pi

18 Interpreter vs Script Mode

19 IDLE

20 Raspberry Pi vs PC

**Python 3 and PyPI**

21 PyPI and pip

22 pip on Windows

23 pip3 on Raspberry Pi

**Installing NumPy and Matplotlib**

24 Install NumPy and Matplotlib on Windows

25 Install NumPy and Matplotlib on Raspberry Pi

**Jupyter Notebook**

26 Jupyter and IPython

27 Jupyter Installation on Windows

28 Jupyter Installation on Raspberry Pi

29 Remote connection with PuTTY

30 Connect to a remote Jupyter Notebook

31 A brief tour of Jupyter

32 Commands used in the section

**Getting Started with NumPy**

33 Introduction to NumPy

34 Ndarrays, Indexing and Slicing

35 Ndarray Properties

36 NumPy Constants

37 NumPy Datatypes

**Array creation routines**

38 Ones and Zeros

39 Matrices

40 Introduction to Matplotlib

41 Numerical Ranges and Matplotlib

**Random Sampling**

42 Random Sampling

**Array Manipulation**

43 Array Manipulation

**Bitwise Operation**

44 Bitwise Operation

**Statistical Functions**

45 Statistical Functions

**Plotting in Detail**

46 Single Line Plots

47 Multiline 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 Introduction to Pandas

54 Install Pandas on Windows

55 Install Pandas on Raspberry Pi

**Matrices and Linear Algebra**

56 Dot Products

57 Vector and Dot Products

58 Inner Products

59 QR Decomposition

60 Determinants and Solving Linear Equations

61 Linear Algebra with SciPy

**Data Acquisition with Python, NumPy, and Matplotlib**

62 Plain Text File Handling

63 CSV

64 Excel File

65 NumPy file format

66 Read a CSV file with NumPy

67 Matplotlib CBook

**Python and MySQL**

68 MySQL installation on Windows

69 UPDATE

70 DELETE

71 DROP

72 Getting Started with MySQL and SQL Workbench

73 Connect to MySQL with SQL Developer

74 Exploring MySQL Workbench

75 Pymysql installation on Windows

76 Connect to MySQL with Python 3

77 DDL

78 INSERT

79 SELECT

**Dataframes and Series in Pandas**

80 Series

81 Dataframe

**Data Acquisition with Pandas**

82 Read data from a CSV file

83 Read an excel file

84 Read from JSON

85 Pickles

86 Read data from Web

87 Read data from SQL

88 Read from Clipboard

**Time Series in Pandas**

89 Introduction to the Time Series

90 Shifting and Timezone Handling

**Time Series Analysis with More libraries**

91 Plotly

92 Plotly and Matplotlib

93 Seaborn

94 Altair

**Downloadable Resources and Code Bundle**

95 Code Bundle

96 BONUS LECTURE

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