This weekend I wanted to work on collecting and plotting historical option contract prices. I used the following API call to pull option contract data from Yahoo!
curl -X GET "http://finance.yahoo.com/q/op?s=AAPL&m=2016-01" | cat > aapl
Continue reading Scraping Yahoo! Finance Data with BeautifulSoup
One of my favorite things about pandas is that you can easily combine temporal data sets using different time scales. Behind the scenes, pandas will fill in the empty gaps with null values, and then quietly ignore those null values when you want to make a scatter plot or do some other computation, like a rolling mean. It takes so much tedious book-keeping out of the data analysis process.
Continue reading Concatenating and Visualizing Data in Pandas
In this post I’ll demonstrate how to open an Excel file in Python using Pandas, a (the) module for data manipulation. I love using Pandas, and I cannot recommend it enough.
This is the first in a series of posts using the small data sets from The Handbook of Small Data Sets to illustrate introductory techniques in text processing, plotting, statistics, etc. The data sets are collected in a ZIP file at publisher’s website in the link above. Someone decided to format the data files to resemble the published format to the greatest degree possible, which makes parsing the files interesting. First, we will import our modules,