2015
Lynda
Michele Vallisneri
2:11
English

If you're going to work with big data, you'll probably be using R or Python. And if you're using Python, you'll be definitely using Pandas and NumPy, the third-party packages designed specifically for data analysis. This course provides an opportunity to learn about them. Michele Vallisneri shows how to set up your analysis environment and provides a refresher on the basics of working with data containers in Python. Then he jumps into the big stuff: the power of arrays, indexing, and DataFrames in NumPy and Pandas. He also walks through two sample big-data projects: one using NumPy to analyze weather patterns and the other 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.

Introduction
Welcome
What you need to know
Exercise files
1. Installation and Setup
Installing the Anaconda Python distribution
Writing and running Python in the iPython notebook
2. Refresher: Data Containers in Python
Python containers overview
Using Python lists and the slicing syntax
Using Python dictionaries
Comprehensions
3. Word Anagrams in Python
Word anagram overview
Loading the dictionary
Finding anagrams
Challenge
Solution
4. Introduction to NumPy
NumPy overview
Creating NumPy arrays
Doing math with arrays
Indexing and slicing
Records and dates
5. Weather Data with NumPy
Weather data overview
Downloading and parsing data files
Temperature analysis
Integrating missing data
Smoothing data
Computing daily records
Challenge
Solution
6. Introduction to Pandas
Pandas overview
Series in pandas
DataFrames in pandas
Using multilevel indices
Aggregation
7. Baby Names with Pandas
Baby name overview
Loading datasets
Name popularity
A yearly top ten
Name fads
Challenge
Solution
Conclusion
Next steps



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