Time Series Analysis:Hands-On Projects & Advanced Techniques

سرفصل های دوره

Hands-On Time Series with Python: Accessing, Manipulating, Visualizing Data, Master Advanced Techniques & Build Projects

1. Introduction

1. Introduction

2. Jupyter Shortcuts.html

3. Understanding Data Types and Structures in Python.

4. Understanding Python Data Structure Wrap up.

2. Python Refresher

1. String Functions in Python Part 1

2. String Functions in Python Part 2

3. String Functions in Python Part 3

4. String Functions in Python Part 4

5. String Functions in Python Part 5

6. Lists.

7. Tuples.

8. Sets.

9. Dictionaries.

10. Control Flow IF.

11. For Loop Part 1.

12. For Loop Part 2.

13. While Loop Part 1.

14. While Loop Part 2.

15. While Loop Best Practices.

16. Introduction to Functions in Python.

17. Functions in Python and Arguments.

18. Function Tips & Tricks Recursion.

19. Function Tips & Tricks Functions Decorators and Higher Order Functions.

20. Functions Tips & Tricks Lambda Functions.

21. Function Tips & Tricks Functions Caching & Memoization.

22. Error Handling in Python.

23. Files and Modules in Python.

3. Object Oriented Programming (OOP) In Python Refresher

1. Creating Simple Class.

2. Overviewing Constructor.

3. Learning How to creating Dunder Methods

4. Learning about Inheritance.

5. Knowing What is the Encapsulation

6. Learning also about Multiple Inheritance.

7. Knowing What is the Overriding

8. Learning about Decorators.

9. Learning How to use Build-in Decorators

4. Project 1 Python Pandas + PostgreSQL

1. PostgreSQL Downloading & Installing.

2. Create Database.

3. Restore Database.

4. Using CMD & Python pip.PyPi to Install Jupyter Lab & Pandas.

5. Create a CSV File Using PostgreSQL

6. Fetchmany and Fetchall

7. Runnig SQL Query Using Python Panadas Module.

8. Using Python Pandas Package to load PostgreSQL the Data Output file.

9. Data Analysis Process Overview.

10. Pandas Methods.

11. Pandas data visualization.

12. Pandas Data Analysis.

13. Sampling Error.

5. Project 2 Scrape the Web & Saving Data to a Database

1. How to Scrape a website

2. Scrape a Table inside a Webpage using Pandas and LXML Python Modules!

3. Visualization of the Scarped Data.

4. Save The Scraped Data to a Database.

6. Project 3 Python Automation AFC (OS Python Module)

1. Download & Install of Sublime Text Editor.

2. Project Walkthrough.

3. Project Arrange Folder Content.

7. Project 4 Python Automation Project MPF (PyPDF2 Python Module)

1. Project Walkthrough.

2. Project Solution.

8. Project 5 Python Automation Business Email List (smtplib Python Module)

1. Part 1

2. Part 2

3. Part 3

9. Python Numpy Library

1. Numpy Intro.

2. Numpy.shape & Numpy.size

3. Creating Numpy nd arrays using Numpy functions.

4. Numpy.unique( ) & Array slicing.

5. Numpy Calculations and Operators.

6. Numpy Aggregations.

7. Numpy Reshape and Transposing.

8. Comparing Numpy Arrays.

9. Numpy Arrays Images Processing.

10. Accessing, Manipulating & Filtering DataFrames

1. Data manipulation using DataFrames.

2. Accessing Data Using DataFrames.

3. Data aggregation and summarization.

4. Create New Columns, Drop Unnecessary Ones, and Perform Various Data Manipulation

5. Essential Techniques for Peeking at & Describing our Data in Python.

6. Filtering Data.

11. Data Visualization in Python

1. Introduction to Data Visualization in Python.

2. Histograms a Powerful Tool for Visualizing the Distribution of Data.

3. Visualizing Trends using a Real-World Financial Data.

4. Determining and Choosing the Appropriate Plot Type.

12. Time Series Data Analysis using Python

1.1 benchmark data.csv

1.2 financial data.csv

1. Datasets used in this Section..html

2. Introduction to Time Series Analysis.

3. Creating, Converting Datetimes from Strings & Manipulating Datetime Data.

4. Accessing Datetime Attributes, Comparing Datetimes, & Making Relative Datetime.

5. Understanding Time Series Growth Rates & Comparing Stock Prices with a Benchmark

6. Changing Time Series Frequency By Up-Sampling & Interpolation.

7. Changing Time Series Frequency By Down-Sampling.

8. Window Functions in Time Series Analysis.

9. Stocks Prices Series Analysis with Lags.

13. Project 6 Time Series Analysis of Betcoin Historical Data dataset

1. Introduction to this Project.

2. Data Preprocessing and Cleaning.

3. Visualizing Time Series Data.

4. Creating Forecasting Models.

5. Predicting Future Bitcoin Prices.

14. Bonus

1. Thanks.html

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تولید کننده: Udemy