Python Data Analysis (2020)

Data science is transforming the way that government and industry leaders look at both specific problems and the world at large. Curious about how data analysis actually works in practice? In this course, instructor Michele Vallisneri shows you how, explaining what it takes to get started with data science using Python.

Michele demonstrates how to set up your analysis environment and provides a refresher on the basics of working with data structures in Python. Then, he jumps into the big stuff: the power of arrays, indexing, and tables in NumPy and pandas—two popular third-party packages designed specifically for data analysis. He also walks through two sample big-data projects: using NumPy to identify and visualize weather patterns and using pandas to analyze the popularity of baby names over the last century. Challenges issued along the way help you practice what you've learned.

Learning objectives
Describe how to install and start Python, and load necessary libraries.
Explain examples of uses for lists and ranges in Python.
Explain string processing methods in Python.
Describe the characteristics and specifications of NumPy arrays.
Explain examples of uses for NumPy methods in generating and analyzing data.
Use matplotlib to create xy plots.
Describe the characteristics and specifications of DataFrames in pandas.