Financial timeseries data

In finance, it is common to be working with a CSV (comma-separated-values) "flat" file of a timeseries of many different assets with their prices, returns, or other data over time. Sometimes the data is stored in databases, but more often than not, even large banks still use spreadsheets.

In this exercise, you have been given a timeseries of trading data for Microsoft stock as a .csv file stored at the url fpath_csv. When you finish the exercise, take note of the various types of data stored in each column.

You will be using pandas to read in the CSV data as a DataFrame.