Many real-world data sets contain strings, integers, time-stamps and unstructured data. How do you store data like this so that you can manipulate it and easily retrieve important information? The answer is in a pandas DataFrame! In this course, you‘ll learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames. With pandas, you‘ll always be able to convert your data into a form that permits you to analyze it easily. You‘ll also learn more about NumPy, how it stores data, and its relation to the pandas DataFrame.
