Reading data from CSVs and other delimited files

In this recipe, you will use the pandas.read_csv() function, which offers a large set of parameters that you will explore to ensure the data is properly read into a time series DataFrame. In addition, you will learn how to specify an index column, parse the index to be of the type DatetimeIndex, and parse string columns that contain dates into datetime objects.

Generally, using Python, data read from a CSV file will be in string format (text). When using the read_csv method in pandas, it will try to infer the appropriate data types (dtype), and, in most cases, it does a great job at that. However, there are situations where you will need to explicitly indicate which columns to cast to a specific data type. For example, you will specify which column(s) to parse as dates using the parse_dates parameter in this recipe.

Getting ready

You will read a CSV file containing hypothetical box office numbers for a movie. The file is provided in the...