December 2015
Beginner to intermediate
202 pages
4h
English
Content preview from Python Business Intelligence CookbookBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Standardizing dates in Pandas
Along with Social Security numbers, there are almost infinite ways to write dates. In order to compare them properly, or use them in your own systems, you need to put them into a single format. This recipe handles commonly seen date formats in the United States, and dates with missing information.
Getting ready
Import Pandas and create a new DataFrame to work with:
import pandas as pd lc = pd.DataFrame({ 'people' : ["cole o'brien", "lise heidenreich", "zilpha skiles", "damion wisozk"], 'age' : [24, 35, 46, 57], 'ssn': ['6439', '689 24 9939', '306-05-2792', '992245832'], 'birth_date': ['2/15/54', '05/07/1958', '19XX-10-23', '01/26/0056'], 'customer_loyalty_level' : ['not at all', 'moderate', 'moderate', 'highly loyal']}) ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.