pandas is one of today’s most celebrated data analysis libraries. A favorite of many, its versatile functionalities can be leveraged for manipulation of many types of data - numeric, text, Boolean, and more. That’s one of the features that make pandas the go-to choice for analysts, especially during the data cleaning and preprocessing stages. pandas is built on NumPy and takes advantage of its computational power and abilities. But what sets pandas apart is its ability to operate with data in an easy-to-use way, allowing you to focus almost entirely on your analytic task. In this course, you will learn how to work with this powerful Python library and its core data structures – the pandas Series and DataFrames.
Skills you will gain
What You'll Learn
This course introduces you to one of the most widely used data analysis libraries – pandas. With pandas you’ll be able to solve your analytic tasks in an easy and professional way!
- pandas - Basics15 Lesson 82 MinIntroduction to the pandas Library Free Installing and Running pandas Free Introduction to pandas Series Free Working with Attributes in Python Free Using an Index in pandas Free Label-based vs Position-based Indexing Free More on Working with Indices in Python Free Using Methods in Python - Part I Free Using Methods in Python - Part II Free Parameters vs Arguments Free The pandas Documentation Free Introduction to pandas DataFrames Free Creating DataFrames from Scratch - Part I Creating DataFrames from Scratch - Part II Additional Notes on Using DataFrames
- Data Cleaning and Data Preprocessing1 Lesson 5 Min
- pandas Series5 Lesson 21 Min
- pandas DataFrames6 Lesson 38 Min
“In this course, I will help you streamline the data cleaning and data preprocessing stages of analysis with pandas – the go-to library for data science and analytics professionals. By the end of this brief practical training, you will be able to handle the pandas Series object and DataFrames with confidence and ease.”
Worked at European Commission
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