In Pandas, there is a certain data type for time series data. This is a normal Pandas DataFrame or Series where the index is a column of the datetime
objects. It has to be this kind of object for Pandas to recognize it as dates and for it to understand what to do with the dates. To show you how it works, let us read in a time series dataset.
The first data that we are reading in is the mean measured daily temperature at Fisher River near Dallas, USA from 1st January, 1988 to 31st December, 1991. The data can be downloaded from DataMarket in several formats ( https://datamarket.com/data/set/235d/ ), and it can also be acquired from http://ftp.uni-bayreuth.de/math/statlib/datasets/hipel-mcleod . Here, I have the data in CSV format. The data comes from the Time Series Data Library ( https://datamarket.com/data/list/?q=provider:tsdl ) and originated in Hipel and McLeod (1994).
The data has two columns: the first with the date and the second with the mean measured temperature...