Python Tutorial: Time Series Analysis in Python

Want to learn more? Take the full course at https://learn.datacamp.com/courses/introduction-to-time-series-analysis-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Welcome to the first video of the "Introduction to Times Series Analysis Using Python" course. My name is Rob Reider. I'm an Adjunct Professor in the Math-Finance Master's program at NYU's Courant Institute, where I teach a course on Time Series Analysis. I'm also a consultant to a company called Quantopian, which has built a Python-based platform for analyzing and backtesting quantitative trading strategies. Authors of algorithms can enter into paper trading contests and be considered for an allocation of money. Authors receiving allocations are paid 10 percent of the strategy’s net profits, based on their strategy’s individual performance. Also, Quantopian hosts a community where members can ask for help, share ideas, and discuss and share code. Time series analysis deals with data that is ordered in time. Of course, there are many other types of data that are not covered in this course - for example, cross-sectional data that are taken at one point in time. Time series comes up in many contexts. Here is a time series of the frequency of Google searches for the word "diet" over a five year period. You can see an interesting pattern: it hits a low around the holidays and then spikes up at the beginning of the year when people make New Year's resolutions to lose weight. Here is another example of a time series: the average annual temperature in New York City since 1870. Notice that this time series is trending up. Many of the most interesting applications of time series analysis are financial time series. In this course, you will look at a variety of financial time series: stocks, bonds, commodities, even cryptocurrencies like Bitcoin. Here is the time series of quarterly earnings for the company H&R Block. H&R Block is in th