Grouping with anonymous functions with a DatetimeIndex

Using DataFrames with a DatetimeIndex opens the door to many new and different operations as seen with several recipes in this chapter.

In this recipe, we will show the versatility of using the .groupby method for DataFrames that have a DatetimeIndex.

How to do it…

1. Read in the Denver crime hdf5 file, place the REPORTED_DATE column in the index, and sort it:

   >>> crime = (pd.read_hdf('data/crime.h5', 'crime') 
   ...    .set_index('REPORTED_DATE') 
   ...    .sort_index()
   ... )
   

2. The DatetimeIndex has many of the same attributes and methods as a pandas Timestamp. Let's take a look at some that they have in common:

   >>> common_attrs = (set(dir(crime.index)) & 
   ...     set(dir(pd.Timestamp)))
   >>> [attr for attr in common_attrs if attr[0] != '_']
   ['tz_convert', 'is_month_start', 'nanosecond...