Beginner's guide to Python Pandas for Data Analysis

Udemy Beginner's guide to Python Pandas for Data Analysis

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Learn how to code with pandas library


What you'll learn
  • This course will introduce to the student how to use a Python analytical tool called Pandas. With this technology, the student will be able to import and analyze data from a variety of data sources, such as Excel, CSV, SQL Server, URLs, Big Data, and much more. With the aid of Juypter Notebook editor, the student will be able to interact with pandas library and learn to code. The pandas library will introduce to the student on how to import and export data, how to manage, manipulate, configure data, and how to filter, add, delete, concatenate, group data and visualize data with charts and much more.

Requirements
  • This course is designed with the beginner in mind; as such, we introduce the fundamentals of pandas library commands to manage data, However, my course called An Absolute Beginner’s Guide to Python is a highly recommended course or a fundamental understanding of Python language.

Description
This course will introduce to the student how to use a Python analytical tool called Pandas. With this technology, the student will be able to import and analyze data from a variety of data sources, such as Excel, CSV, SQL Server, URLs, Big Data, and much more. With the aid of Juypter Notebook editor, the student will be able to interact with pandas library and learn to code. The pandas library will introduce to the student on how to import and export data, how to manage, manipulate, configure data, and how to filter, add, delete, concatenate, group data and visualize data with charts and much more.
Who this course is for:
  • As this is a beginner guide to pandas library, it is designed for the student who wants to learn about how to manipulate, configure, manage, import, and export data from a variety of sources such as Excel, CSV, SQL databases, URLs, and many more resources. These students can be developers, database admins, beginning data scientists, financial analysts, Excel students, or anyone who works with data.
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