Introduction to Python for Data Science

The notebooks here will run through examples using popular PyData libraries.

For Mac users: my install steps for Python 3.5 and useful libraries.

Topics covered:

• Pandas to read csv and linear regression with scikit-learn
• Image analysis to count circles with openCV
• Text analysis by web scraping with BeautifulSoup and construct a count matrix with scikit-learn
• Time series analysis using FFT and curve-fitting from numpy and filtering time series with statsmodel.