If you're a data scientist or anyone else whose job includes performing data analysis and data manipulation on a regular basis, you know how frustrating it can be to deal with messy, unstructured data. This is where Python libraries like Pandas come in handy. They help make data analysis and manipulation a breeze, even if your data is far from clean.
Course Overview
The Data Manipulation in Python: A Pandas Crash Course teaches you how to use Python and Pandas for data analysis and data manipulation. With this course, you'll learn how to transform, clean, and merge data with Python. The instructor, Ph.D. Samuel Hinton, will guide you through common and advanced Pandas data manipulation techniques that will help you take raw data to a final product for analysis as efficiently as possible.
The course has a rating of 4.6 out of 5 stars, based on 1758 course reviews. With this course, you'll learn how to:
- Use Python and Pandas for data analysis and data manipulation
- Transform, clean, and merge data
- Make statistical analysis and machine learning as simple as possible
- Achieve better results by spending more time problem-solving and less time data-wrangling
Course Description
The course starts with an introduction to the Pandas library and how to load and create DataFrames. You'll also learn how to display data with basic plots and different types of visualizations. Then, the course moves on to the more advanced topics of DataFrame manipulations. You'll learn how to index, label, slice, filter, and perform other basic manipulations on DataFrame objects.
As the course progresses, you'll learn advanced Pandas techniques such as multiIndexing, stacking, hierarchical indexing, pivoting, melting, and more. You'll also learn about DataFrame grouping, aggregation, imputation, and other techniques for working with advanced datasets. The course rounds out with a module dedicated to mastering time series manipulations, including techniques for resampling, rolling functions, method chaining and filtering, and more.
Why Pandas?
Python's Pandas library is the most popular Python library in data science, and it's easy to see why. With Pandas, data analysis and data manipulation become much more efficient, and you can spend more time working on problem-solving and less time on data-wrangling. Whether you're working with data for visualization, statistical analysis, or machine learning, Pandas has the tools you need to get the job done.
Moreover, data scientists at Google, Facebook, JP Morgan, and nearly every other major company that analyzes data use Pandas. This course will help you gain the skills you need to join them and advance your data analysis career.
What to Expect from the Course
The course is designed to guide beginners and intermediate users smoothly into every aspect of Pandas. The curriculum covers all the important features of Pandas in an easy-to-understand manner, so even if you're a complete beginner, you'll be able to follow along with ease.
The course includes practical exercises that are based on real-life examples. This way, you'll learn the theory and get some hands-on practice with Pandas as well, which is essential for mastering any new library or technology effectively.
Course Curriculum
The course curriculum covers the following topics:
- Loading and creating Pandas DataFrames
- Displaying your data with basic plots, and 1D, 2D and multidimensional visualizations
- Performing basic DataFrame manipulations: indexing, labeling, ordering slicing, filtering and more
- Performing advanced Pandas DataFrame manipulations: multiIndexing, stacking, hierarchical indexing, pivoting, melting and more
- Carrying out DataFrame grouping: aggregation, imputation, and more
- Mastering time series manipulations: reindexing, resampling, rolling functions, method chaining and filtering, and more
- Merging Pandas DataFrames
The Instructor: Ph.D. Samuel Hinton
The instructor for this course is Ph.D. Samuel Hinton. With over 20 years of experience as a course review content writer, he has a wealth of knowledge and expertise in the field of data science and data manipulation.
With his guidance, you'll gain a deep understanding of Pandas and its advanced features. You'll learn how to create efficient workflows for data manipulation and analysis and transform messy datasets into valuable insights.
The Bottom Line
If you're a data scientist or anyone else whose job involves working with data, the Data Manipulation in Python: A Pandas Crash Course is a must-take course. With this course, you'll learn how to use Python and Pandas to efficiently manipulate and analyze data, saving you time and increasing your productivity.
The course is designed to guide beginners and intermediate users smoothly into every aspect of Pandas and covers all the important features of Pandas in an easy-to-understand manner. Plus, the practical exercises based on real-life examples will give you hands-on experience with Pandas, critical for mastering the library effectively.
By the end of this course, you'll have the skills you need to work with complex and heterogeneous datasets, confident in your ability to produce useful results for the next stage of data analysis.
