October 2017
Intermediate to advanced
532 pages
16h 10m
English
Content preview from Pandas Cookbook
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How to do it...
- Read in the Denver crime dataset, place the REPORTED_DATE in the index, and sort it:
>>> crime_sort = pd.read_hdf('data/crime.h5', 'crime') \ .set_index('REPORTED_DATE') \ .sort_index()
- Find the last full month of data:
>>> crime_sort.index.max()Timestamp('2017-09-29 06:16:00')
- As we don't quite have all of September's data, let's drop it from our dataset:
>>> crime_sort = crime_sort[:'2017-8']>>> crime_sort.index.max()Timestamp('2017-08-31 23:52:00')
- Let's count the number of crimes and traffic accidents for every month:
>>> all_data = crime_sort.groupby([pd.Grouper(freq='M'), 'OFFENSE_CATEGORY_ID']).size()>>> all_data.head()REPORTED_DATE OFFENSE_CATEGORY_ID 2012-01-31 aggravated-assault 113 all-other-crimes 124 arson ...
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