New article released provides introduction to analyzing stock data with Python

WEST JORDAN, Utah - Sept. 18, 2016 - PRLog -- Curtis Miller released an article online providing an introduction to analyzing stock data with Python. This article is the first in a two-part series on the topic.

The article provides some basic background knowledge on how stocks work along with a brief history of mathematics and computer science in finance. It describes how to use the Yahoo! Finance API and the Python libraries matplotlib and pandas libraries for storing and visualizing stock data.

Most of the article describes how to properly visualize stock data. Japanese candlestick charts are covered, and issues about how to create informative charts for stock data are discussed.

The article contains extensive code examples along with functions that readers may examine and borrow for their own purposes. All code is heavily commented to ease understanding.

The series was originally a lecture given by Curtis Miller at the University of Utah for a class on data science. The entire series represents a data analysis project from beginning to end, a useful introduction to data analysis topics in general.

The next article in the series will discuss formulation and evaluation of trading strategies in Python, and will be released on September 26th, 2016. It will also include practice problems for readers to strengthen their understanding and explore ideas not discussed in detail in the series.

The article was released on 9:00 AM MDT on September 19th, 2016, at: https://ntguardian.wordpress.com/2016/09/19/introduction-...