多重索引被定义为非常重要的索引,因为它处理数据分析和操作,尤其是处理高维数据时。它还可以在Series和DataFrame等较低维度的数据结构中存储和处理任意数量的维度的数据。
示例:
arrays = [['it', 'it', 'of', 'of', 'for', 'for', 'then', 'then'], ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']] tuples = list(zip(*arrays)) tuples
输出:
[('it', 'one'), ('it', 'two'), ('of', 'one'), ('of', 'two'), ('for', 'one'), ('for', 'two'), ('then', 'one'), ('then', 'two')]
示例2:
arrays = [['it', 'it', 'of', 'of', 'for', 'for', 'then', 'then'], ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']] tuples = list(zip(*arrays)) index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
输出:
MultiIndex([('bar', 'one'), [('it', 'one'), ('it', 'two'), ('of', 'one'), ('of', 'two'), ('for', 'one'), ('for', 'two'), ('then', 'one'), ('then', 'two')] names=['first', 'second'])
示例3:
import pandas as pd import numpy as np pd.MultiIndex(levels=[[np.nan, None, pd.NaT, 128, 2]], codes=[[0, -1, 1, 2, 3, 4]])
输出:
MultiIndex(levels=[[nan, None, NaT, 128, 2]], codes=[[0, -1, 1, 2, 3, 4]])
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Tony Bai · Go语言第一课 -〔Tony Bai〕