Data Manipulation in Python: A Pandas Crash Course

In the real-world, data is anything but clean, which is why Python libraries like Pandas are so valuable. If data manipulation is setting your data analysis workflow behind then this course is the key to taking your power back. Own your data, don't let your data own you.

When data manipulation and preparation accounts for up to 80% of your work as a data scientist, learning data munging techniques that take raw data to a final product for analysis as efficiently as possible is essential for success. Data analysis with Python library Pandas makes it easier for you to achieve better results, increase your productivity, spend more time problem-solving and less time data-wrangling, and communicate your insights more effectively. This course prepares you to do just that.

With Pandas DataFrame, prepare to learn advanced data manipulation, preparation, sorting, blending, and data cleaning approaches to turn chaotic bits of data into a final pre-analysis product. This is exactly why Pandas is the most popular Python library in data science and why data scientists at Google, Facebook, JP Morgan, and nearly every other major company that analyzes data use Pandas. If you want to learn how to efficiently utilize Pandas to manipulate, transform, pivot, stack, merge and aggregate your data for preparation of visualization, statistical analysis, or machine learning, then this course is for you.

Here's what you can expect when you enrolled with your instructor, Ph. D. Samuel Hinton:Learn common and advanced Pandas data manipulation techniques to take raw data to a final product for analysis as efficiently as possible.