如下所示：

import numpy as npimport pandas as pd################# 准备数据 #################a1 = np.arange(1,101)a3 = a1.reshape((2,5,10))a3'''array([[[ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [ 11, 12, 13, 14, 15, 16, 17, 18, 19, 20], [ 21, 22, 23, 24, 25, 26, 27, 28, 29, 30], [ 31, 32, 33, 34, 35, 36, 37, 38, 39, 40], [ 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]], [[ 51, 52, 53, 54, 55, 56, 57, 58, 59, 60], [ 61, 62, 63, 64, 65, 66, 67, 68, 69, 70], [ 71, 72, 73, 74, 75, 76, 77, 78, 79, 80], [ 81, 82, 83, 84, 85, 86, 87, 88, 89, 90], [ 91, 92, 93, 94, 95, 96, 97, 98, 99, 100]]])'''################# 准备标签 ################## 第 1 维的标签index1 = pd.Series(np.arange(1,11))index1 = index1.astype(str)index1 = 'A'+index1index1'''0 A11 A22 A33 A44 A55 A66 A77 A88 A99 A10'''# 第 2 维的标签index2 = pd.Series(np.arange(1,6))index2 = index2.astype(str)index2 = 'B'+index2index2'''0 B11 B22 B33 B44 B5'''# 第 3 维的标签index3 = pd.Series(np.arange(1,3))index3 = index3.astype(str)index3 = 'C'+index3index3'''0 C11 C2'''################# 展开数据 ################## 把三维数组展开value = a3.flatten()value = pd.Series(value)value.name = 'value'value'''0 11 22 3 ... 97 9898 9999 100Name: value, Length: 100, dtype: int64'''################# 展开标签 #################import itertools# index的笛卡尔乘积。注意：高维在前，低维在后prod = itertools.product(index3, index2, index1 )# 转换为DataFrameprod = pd.DataFrame([x for x in prod])prod.columns = ['C', 'B', 'A']prod.T''' 0 1 2 3 4 5 6 7 8 9 ... 90 91 92 93 94 95 96 \C C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 ... C2 C2 C2 C2 C2 C2 C2 B B1 B1 B1 B1 B1 B1 B1 B1 B1 B1 ... B5 B5 B5 B5 B5 B5 B5 A A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 ... A1 A2 A3 A4 A5 A6 A7 97 98 99 C C2 C2 C2 B B5 B5 B5 A A8 A9 A10 [3 rows x 100 columns]'''################# 最终数据 ################## 合并成一个DataFramepd.concat([prod, value], axis=1)''' C B A value0 C1 B1 A1 11 C1 B1 A2 22 C1 B1 A3 33 C1 B1 A4 44 C1 B1 A5 55 C1 B1 A6 66 C1 B1 A7 77 C1 B1 A8 88 C1 B1 A9 99 C1 B1 A10 1010 C1 B2 A1 1111 C1 B2 A2 1212 C1 B2 A3 1313 C1 B2 A4 1414 C1 B2 A5 1515 C1 B2 A6 1616 C1 B2 A7 1717 C1 B2 A8 1818 C1 B2 A9 1919 C1 B2 A10 2020 C1 B3 A1 2121 C1 B3 A2 2222 C1 B3 A3 2323 C1 B3 A4 2424 C1 B3 A5 2525 C1 B3 A6 2626 C1 B3 A7 2727 C1 B3 A8 2828 C1 B3 A9 2929 C1 B3 A10 30.. .. .. ... ...70 C2 B3 A1 7171 C2 B3 A2 7272 C2 B3 A3 7373 C2 B3 A4 7474 C2 B3 A5 7575 C2 B3 A6 7676 C2 B3 A7 7777 C2 B3 A8 7878 C2 B3 A9 7979 C2 B3 A10 8080 C2 B4 A1 8181 C2 B4 A2 8282 C2 B4 A3 8383 C2 B4 A4 8484 C2 B4 A5 8585 C2 B4 A6 8686 C2 B4 A7 8787 C2 B4 A8 8888 C2 B4 A9 8989 C2 B4 A10 9090 C2 B5 A1 9191 C2 B5 A2 9292 C2 B5 A3 9393 C2 B5 A4 9494 C2 B5 A5 9595 C2 B5 A6 9696 C2 B5 A7 9797 C2 B5 A8 9898 C2 B5 A9 9999 C2 B5 A10 100[100 rows x 4 columns]'''

以上这篇Python实现把多维数组展开成DataFrame就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。