Data Manipulation with Python, Pandas, R ,SQL and Alteryx

سرفصل های دوره

Unlock the Power of Data: Master Comprehensive Data Manipulation Techniques with Python, Pandas, R, SQL, and Alteryx

1. Introduction

1. Introduction.html

2. Overview of Data Manipulation.html

3. Introduction to Data Manipulation.html

4. Role of Data Manipulation in Data Analysis.html

5. Introduction to Data Manipulation Tools.html

6. Overview of Python, R, SQL, Pandas and Alteryx.html

7. Installing Required Software and Libraries.html

2. Python Environment Setup

1. Introduction to Jupyter Notebook

2. Installing Jupyter Notebook

3. Running Jupyter Notebook Server

4. Common Jupyter Notebook Commands

5. Jupyter Notebook Components

6. The Notebook Dashboard

7. Notebook User Interface

8. Creating a new Notebook

3. Python Fundamentals

1. Python Expressions

2. Python Statements

3. Python Comments

4. Python Data Types

5. Casting Data Types

6. Python Variables

7. Python List

8. Python Tuples

9. Python Dictionaries

10. Python Operators

11. Python Conditional Statements

12. Python Loops

13. Python Functions

4. Python and Pandas for Data Manipulation

1. Python for Data Manipulation.html

2. Introduction to Pandas.html

3. Introduction to Pandas Library.html

4.1 us baby names.zip

4. Tabular Data

5. Exploring Pandas DataFrame

6. Manipulating Pandas DataFrame

7. What is data cleaning

8.1 crime boston.zip

8. Data Cleaning process

9. Series and DataFrame.html

10. Loading Data into DataFrame.html

11. Data Manipulation with Pandas.html

12. Data Cleaning with Pandas.html

13. Data Wrangling and Transformation.html

14. Aggregation and Grouping.html

15. Merge, Join, and Concatenate.html

5. R for Data Manipulation

1. Basics for Data Manipulation.html

2. Introduction to R and RStudio.html

3. Installing R on Windows

4.1 Download+and+install+R+on+Mac (1).pdf

4. Installing R on Macs.html

5. Installing R Studio on Windows

6.1 Download+and+install+R+Studio (1).pdf

6. Installing R Studio on Macs.html

7. Exploring R Studio Interface

8. Creating a new project in R Studio

9. Real-world Data Manipulation Project Using Python and Pandas.html

10. What are packages.html

11. How to install Packages

12. Loading Packages

13.1 sydneybeaches.csv

13. Importing data into R Studio

14. Reading CSV data with R

15. Selecting a subset of data

16. Performing multiple operations with Pipe Operator

17. Cleaning Columns

18. Creating new columns from existing Columns

19. Create another R Project.html

20.1 chocolate.csv

20. Load data into new project

21. What is data wrangling.html

22. Perform data wrangling

23. Create a scatter plot

24. Create a bar graph

25. Basic Data Types in R.html

26. Control Structures and Functions in R.html

27. Data Manipulation with dplyr in R.html

28. Introduction to dplyr package.html

29. Filtering and Selecting Data with dplyr.html

30. Arrange, Mutate, Summarize and Group By functions.html

31. Data Manipulation with tidyr in R.html

32. Introduction to tidyr package.html

33. Reshape data with gather and spread functions.html

34. Unite and separate columns.html

6. MySQL Database Server Server

1. What is MySQL

2. MySQL Installation on Windows

3. What is MySQL Workbench

4. MySQL Installation on Macs

5. MySQL Workbench installation on Macs

6. Basic Database Concepts

7. What is a Schema

8. Database Schema

9. MySQL Data Types

10. Real-world Data Manipulation Project Using R.html

7. SQL for Data Manipulation

1. SQL Basics.html

2. Introduction to SQL.html

3. SQL Operators.html

4. CREATE Database

5. CREATE Table

6.1 insert+data+into+tables (1).zip

6. INSERT Data into Table

7. SELECT Statement

8. UPDATE Statement

9. DELETE Statement

10. SQL Indexes.html

11. Introduction to MySQL Table Joins.html

12. MySQL INNER Join

13. MySQL LEFT Join

14. MySQL RIGHT Join

15. MySQL SELF Join

16. Introduction to MySQL Views

17.1 create+replace+view.zip

17.2 create+view.zip

17. Creating Views

18. Querying Views

19.1 alter+view.zip

19. Modifying Views

20. Dropping Views

21. Introduction to Sub queries

22. Nested Sub queries

23. What are derived Tables

24. Grouping Rows of Data using GROUP BY Clause

25. Filtering Groups of Data using HAVING Clause

26. Sorting Data using ORDER BY Clause

27. Filtering Rows of Data using WHERE Clause

28. Introduction to aggregate Functions

29. The AVG Function

30. The COUNT Function

31. The SUM Function

32. The MIN Function

33. The MAX Function

34. Filtering data using BETWEEN Command

35. Filtering data using IN Command

36. Filtering data using LIKE Command

37. Filtering data using UNION Command

8. Alteryx for Data Manipulation

1. Introduction to Alteryx.html

2. Overview of Alteryx.html

3. Creating a basic workflow

4. Connecting to Data

5. Viewing Data

6. Real-world Data Manipulation Project Using SQL.html

7. Transforming Data

8. Adding a new column

9. Filtering Data

10. Blend and Analyze Data

11. Alteryx User Interface and Workflow Canvas.html

12. Splitting Columns

13. Analyzing data based on a column

14. Data Import and Export in Alteryx.html

15. Reading Data into Alteryx from Various Sources.html

16. Writing Data from Alteryx to Various Formats.html

17. Data Manipulation with Alteryx.html

18. Data Preprocessing and Cleaning in Alteryx.html

19. Handling Missing Data.html

20. Formatting Data.html

21. Data Wrangling with Alteryx.html

22. Data Transformation in Alteryx.html

23. Pivoting and Unpivoting Data.html

24. Data Binning and Grouping.html

25. Creating Calculated Fields.html

26. Predictive Analysis Tools in Alteryx.html

27. Spatial and Time Series Analysis.html

28. Creating Macros in Alteryx.html

29. Real-world Data Manipulation Project Using Alteryx.html

9. Data Manipulation Pipeline with Python, Pandas, R, SQL, and Alteryx

1. Designing Effective Data Manipulation Pipelines.html

2. Use Case Integrating All Tools in a Single Workflow.html

10. Capstone Project Full Integration

1. Real-World Project requiring the use of Python, Pandas, R, SQL, and Alteryx.html

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تولید کننده: Udemy-Training