In programming, data type is an important concept.
Data types are the classification or categorization of data items. It represents the kind of value that tells what operations can be performed on a particular data. Since everything is an object in Python programming, data types are actually classes and variables are instance (object) of these classes.
Following are the standard or built-in data type of Python:
Variables can store data of different types, and different types can do different things.
In this course, you will get understanding of Data types in Python including examples, illustrations, related functions, methods and operations.
You’ll learn about several basic numeric, string, and Boolean types that are built into Python. By the end of this tutorial, you’ll be familiar with what objects of these types look like, and how to represent them.
You’ll also get an overview of Python’s built-in functions. These are pre-written chunks of code you can call to do useful things. You have already seen the built-in print() function, but there are many others.
By the end of this course, you will get a clear understanding of;
-other regular data types that are string, integer, float and boolean in python.
You will definitely love this course because it is simple, easy and takes levels ahead in programming with even noticing 🙂
✓ It will help students build strong foundation of data types in Python with examples in Jupyter Notebook.
✓ Students will get better understanding of 1) Python List 2) Python Tuple, 3) Python Sets, 4) Python Dictionary.
✓ students will be able to know about the definition, syntax, usage and examples of data types in python.
✓ Students will be able to apply the learned knowledge to the practical work.
I am a BI Developer | Instructor | Facilitator graduate in Business Finance and Computer Science.
Certified in Statistics, Data Analytics, Machine Learning, and Visualization.
I have been supporting the data-driven decision, consulting, creating, implementing and automating Data Intelligence and Analytics Strategies while identifying KPIs in the process and how it affects the overall business strategy.
Blogger on Microsoft Power BI Community
Hands-on experience (Intermediate to advanced level) in using the following tools;
Business Intelligence | Analytics: Microsoft Azure Machine Learning Studio, Microsoft Power BI, Mode Analytics, Microsoft Excel / Google Spreadsheet, Python (Pandas, Openpyxl, matplotlib)
Database: SQL Server 2016 (ETL into Power BI), MYSQL
Project Management: Wrike, GetFlow, Jira.
Documentation: Confluence, Dropbox Paper, Dropbox. Adobe Acrobat PDF, Microsoft Word, and Microsoft Excel.
Diagram | Wireframe | Mockups: Balsamiq Mockups, Drawdotio, Microsoft Visio, Microsoft Excel, and Word Smart Art Graphic.
Analyzed CRM Applications: ZOHO CRM, Rethink Residential and Commercial (Built on Salesforce Platform), Podio, Plan plus, ConvergeEnterprise, dotloop, Microsoft Dynamics NAV.