As the data cleanup is done, start with the data exploration tasks. We can use the pandas date-time capabilities to run some interesting queries.
For example, if we want to get all the records from a particular year, pass that year to the DataFrame inside square brackets. The following screenshot shows the price data from the year 2010:
We can also specify whether we want the data from a particular date.
The following screenshot shows the bitcoin price in USD from August 1, 2017:
We can also specify whether we want the data from a particular period spanning certain dates.
The following screenshot shows the data from August 1, 2017, onward:
Statistical information can also be retrieved using pandas methods. For example, to get the minimum price from this dataset, we can use the min() method, as shown in the following...
