This is a rapid introduction to NumPy, pandas, and matplotlib for experienced Python programmers who are new to those libraries.
If you or your team are using or plan to use Python for data science or data analytics, then this is the right Python course for you. The course assumes that you already have had a good amount of Python training and/or experience. Your live instructor will start the class by teaching you how to use Jupyter Notebook, a great tool for writing, testing, and sharing quick Python programs. Even if you do not end up using Jupyter Notebook as your main Python IDE, you will appreciate having it as a tool in your Python toolkit. You will learn NumPy, which makes working with arrays and matrices (in place of lists and lists of lists) much more efficient, and pandas, which makes manipulating, munging, slicing, and grouping data much easier. You will also learn some simple data visualization techniques with matplotlib.
Upon successful completion of this course, the student will be able to:
- Learn to work with Jupyter Notebook
- Learn to use NumPy to work with arrays and matrices of numbers
- Learn to work with pandas to analyze data
- Learn to work with matplotlib from within pandas
Basic Python programming experience. In particular, you should be very comfortable with Working with strings, Working with lists, tuples and dictionaries, Loops and conditionals, and writing your own functions.