将混合格式的.DAT转换为.CSV(或其他任何格式) [英] Converting mixed-format .DAT to .CSV (or anything else)

问题描述

我有大量的DAT文件需要转换(最终转换为唯一的文件类型). DAT在字段之间具有混合的空白，并且列标题位于不同的行上.有什么建议吗?

I have a large collection of DAT files that need to be converted (eventually to a unique file type). The DAT's have a mixed amount of whitespace between fields, and the column headers are on different lines. Any advice?

                    ALT_RAD
                                               ALT_RAD2
                 DIRECT        D_GLOBAL        U_GLOBAL          Zenith
Year Mn Dy Hr Mi        DIFFUSE2            D_IR            U_IR
2004  9  1  0  1    1.04   79.40   78.67  303.58   61.06  310.95  85.142
2004  9  1  0  2    0.71   74.36   73.91  303.80   57.82  310.92  85.171
2004  9  1  0  3    0.67   71.80   71.64  304.25   56.84  310.98  85.199
2004  9  1  0  4    0.75   74.35   74.83  304.21   59.68  310.89  85.227

我有一个基本的脚本:

import sys
with open(sys.argv[1], r) as input_file:
    newLines = []
    for line in input_file:
            newLines.append(newLine)

我肯定会更改以解决混合空格，但是我不知道如何使用不正确的列标题.

Which I will certainly change to account for mixed whitespace, but I don't know how to work with the wonky column headers.

最终我希望标题是:

Year Month Day Hour Minute Direct Diffuse2 D_Global D_IR U_Global U_IR Zenith

推荐答案

使用所有应有的轻蔑对待输入文件中的那些标题行. (或者换句话说，阅读并丢弃它们.)

Treat those header lines in the input file with all the disdain they deserve. (Or, in other words, read them and discard them.)

headers='Year Month Day Hour Minute Direct Diffuse2 D_Global D_IR U_Global U_IR Zenith'
with open ( 'temp.dat') as input_file:
    with open ('temp_2.csv', 'w') as output_file:
        output_file.write('"%s"\n'%'","'.join(headers.split()))
        for count, line in enumerate(input_file):
            if count<4: continue
            outLine = ','.join(line.split())
            output_file.write(outLine + '\n')

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