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今年研究生数模的时候用到了,113.xlsx 是325个样本数据,每个样本数据126个初步筛选的特征 文章目录 按列读按行读 按列读 import xlrd import numpy as np def excel2matrix(path): data = xlrd.open_workbook(path) table = data.sheets()[0] nrows = table.nrows # 行数 ncols = table.ncols # 列数 datamatrix = np.zeros((nrows, ncols)) for i in range(ncols): cols = table.col_values(i) datamatrix[:, i] = cols return datamatrix pathX = '113.xlsx' # 113.xlsx 在当前文件夹下 x = excel2matrix(pathX) print(x) print(x.shape)输出 [[0.01719892 0.86457238 0.01742387 … 1. 1. 0.9999603 ] [0.0319469 0.86909879 0.01730402 … 0.99351703 0.99445369 0.99997023] [0.02805216 0.87040528 0.01724861 … 0.99051946 0.99251572 0.99993467] … [0.63507299 0.03643383 0.99306191 … 0.03441377 0.01650907 0.00848835] [0.64464586 0.05750134 0.99653096 … 0.03317541 0.01337929 0.00424418] [0.64765852 0.09031475 1. … 0.03193705 0.01024951 0. ]] (325, 126) 简单,但是很有用的一个小东西 按行读当然你可以按行读 import xlrd import numpy as np def excel2matrix(path): data = xlrd.open_workbook(path) table = data.sheets()[0] nrows = table.nrows # 行数 ncols = table.ncols # 列数 datamatrix = np.zeros((nrows, ncols)) for i in range(nrows): rows = table.row_values(i) datamatrix[i,:] = rows return datamatrix pathX = '113.xlsx' # 113.xlsx 在当前文件夹下 x = excel2matrix(pathX) print(x) print(x.shape)输出 [[0.01719892 0.86457238 0.01742387 … 1. 1. 0.9999603 ] [0.0319469 0.86909879 0.01730402 … 0.99351703 0.99445369 0.99997023] [0.02805216 0.87040528 0.01724861 … 0.99051946 0.99251572 0.99993467] … [0.63507299 0.03643383 0.99306191 … 0.03441377 0.01650907 0.00848835] [0.64464586 0.05750134 0.99653096 … 0.03317541 0.01337929 0.00424418] [0.64765852 0.09031475 1. … 0.03193705 0.01024951 0. ]] (325, 126) |
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