Pandas for Beginners - A Quick Guide

If you work in any functional areas of data analysis, machine learning, and artificial intelligence, you will want to be familiar with or master Pandas. Pandas is a popular Python library used for data analysis and manipulation, commonly used with data analysis, artificial intelligence, and machine learning. Pandas enables quick and efficient data manipulation, aggregation, pivoting, and flexible time series.
This course will introduce you to the basics of data analysis using the Pandas library. You will learn to work with two primary data structures in Pandas, Series and Data Frame. Then, we will take a look at how to read data from a file and explore input data using indexing and filtering, at which point you will be ready for data preprocessing. Next, we will focus on handling missing values and duplicate rows and transforming data into a more efficient format. You will also discover how to manipulate data and data processing. Finally, we will dive into creating simple plots to visualize the data.
By the end of this course, you can use OOPs paradigm to create class hierarchies with the OOP design process. You can design and implement Python programs for complex issues and make good use of the features like classes and inheritance.
What You Will Learn
Learn basic data analysis with Pandas' open-source Python library
Use the two primary Pandas data structures, Series and DataFrame
Process varied data types and manipulate data with string function
Organize input with index and filter, preprocess data with Pandas
Format and process different kinds of data most efficiently
Manipulate, aggregate, and pivot data flexibly and efficiently
Audience
This course targets beginner Python...

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