Creating and using a DatetimeIndex

The pandas Index is a powerful way to handle time series data, so it is valuable to know how to build one yourself. Pandas provides the pd.to_datetime() function for just this task. For example, if passed the list of strings ['2015-01-01 091234','2015-01-01 091234'] and a format specification variable, such as format='%Y-%m-%d %H%M%S, pandas will parse the string into the proper datetime elements and build the datetime objects.

In this exercise, a list of temperature data and a list of date strings has been pre-loaded for you as temperature_list and date_list respectively. Your job is to use the .to_datetime() method to build a DatetimeIndex out of the list of date strings, and to then use it along with the list of temperature data to build a pandas Series.

Prepare a format string, time_format, using '%Y-%m-%d %H:%M' as the desired format.
Convert date_list into a datetime object by using the pd.to_datetime() function. Specify the format string you defined above and assign the result to my_datetimes.
Construct a pandas Series called time_series using pd.Series() with temperature_list and my_datetimes. Set the index of the Series to be my_datetimes.

Exercise

Creating and using a DatetimeIndex

Instructions