October 2017
Intermediate to advanced
532 pages
16h 10m
English
Content preview from Pandas Cookbook
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Indexes support the set operations, union, intersection, difference, and symmetric difference:
>>> c1 = columns[:4]>>> c1Index(['INSTNM', 'CITY', 'STABBR', 'HBCU'], dtype='object')>>> c2 = columns[2:6]>>> c2Index(['STABBR', 'HBCU', 'MENONLY'], dtype='object')>>> c1.union(c2) # or `c1 | c2`Index(['CITY', 'HBCU', 'INSTNM', 'MENONLY', 'RELAFFIL', 'STABBR'], dtype='object')>>> c1.symmetric_difference(c2) # or `c1 ^ c2`Index(['CITY', 'INSTNM', 'MENONLY'], dtype='object')
Indexes share some of the same operations as Python sets. Indexes are similar to Python sets in another important way. They are (usually) implemented using hash tables, which make for extremely fast access when selecting rows or columns from a DataFrame. As they ...
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