Python 3 Data Science – Time Series with Pandas

Python 3 Data Science – Time Series with Pandas
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