我尝试过使用test = np.loadtxt('filename.txt')加载文本文件,但一直遇到这个问题:could not convert string to float: [。该文件不包含任何标头。任何帮助都将不胜感激。谢谢。 原文 关注 分享 反馈 Jiv提问于2020-09-29 20:50 1 个回答 高票数最新 Adrian Keister回答于202
# load from the file if comments start with #array1 = np.loadtxt(file1, comments ='#')print('Array1:', array1)# load from the file and ignore all the characters after ?array2 = np.loadtxt(file2, comments ='?')print('Array2:', array2)# load from the file and ignore all th...
问使用numpy loadtxt加载文本文件时出现问题EN(1) save 函数是以二进制的格式保存数据。 格式: ...
>>> np.loadtxt('a.txt') Traceback (most recent call last): File "<stdin>", line 1, in<module> File "/usr/lib/python3/dist-packages/numpy/lib/npyio.py", line 930, in loadtxt items = [conv(val) for (conv, val) in zip(converters, vals)] File "/usr/lib/python3/dist-packa...
could not convert string to float: '-1.0000,0.0000,0.0000,-0.0008,0.0000,0. 1. 2. 遇到这种问题,那其实是因为在loadtxt的时候没有设置delimiter参数,原因是之前savetxt的时候设置了delimiter参数,当然也可以不设置这个参数,当不设置参数时候,默认的分隔符是’ ',即空格...
“ datafile1.csv”:# Comment 1# Comment 2x,y,z 1,2,34,5,67,8,9...# End of File Comment我认为适用于这种情况的脚本如下所示:import numpy as npFH = np.loadtxt('datafile1.csv',comments='#',delimiter=',',skiprows=1)但是,我遇到了一个错误:ValueError: could not convert string to flo...
type ValueError: could not convert string to float: 上面的数据因为缺失的原因,导致了加载使用的loadtxt无法使用 outfile = r'./data_1.csv' x = np.genfromtxt(outfile, delimiter=',', names= True) print(x) [(1., 123., 1.4, 23.) (2., 110., nan, 18.) (3., nan, 2.1, 19.)] ...
ValueError: could not convertstringtofloat:b'name' 为此,我们可以跳过第一行,用法如下 >>> np.loadtxt('a.txt', skiprows = 1) array([[ 1., 2.], [ 3., 4.]]) 除此之外,该函数还提供了很多的参数,常用的有以下几个 #修改分隔符 >>> np.loadtxt('a.txt', delimiter='\t') array([[...
我们将重点放在genfromtxt函数上。 In a nutshell, genfromtxt runs two main loops. 第一个循环以字符串序列转换文件的每一行。第二个循环将每个字符串转换为适当的数据类型。这种机制比单一循环慢,但提供了更多的灵活性。特别的, genfromtxt考虑到缺失值的情况, 其他更简单的方法如loadtxt无法做到这点. 注意...
ValueError: could not convert string to float: '"Live' but that's a different issue; you might want to try either importnumpyasnpnp.loadtxt(f,delimiter=",",unpack=True,encoding="utf-8-sig",skiprows=1) if you don't care about the column names, or usenp.genfromtxtwithnames=Trueto ca...