在Python中读取scipy / numpy中的csv文件

问题描述

我无法在python中阅读由制表符分隔的csv文件。我使用以下函数：

I am having trouble reading a csv file, delimited by tabs, in python. I use the following function:

def csv2array(filename, skiprows=0, delimiter='\t', raw_header=False, missing=None, with_header=True):
    """
    Parse a file name into an array. Return the array and additional header lines. By default,
    parse the header lines into dictionaries, assuming the parameters are numeric,
    using 'parse_header'.
    """
    f = open(filename, 'r')
    skipped_rows = []
    for n in range(skiprows):
        header_line = f.readline().strip()
        if raw_header:
            skipped_rows.append(header_line)
        else:
            skipped_rows.append(parse_header(header_line))
    f.close()
    if missing:
        data = genfromtxt(filename, dtype=None, names=with_header,
                          deletechars='', skiprows=skiprows, missing=missing)
    else:
    if delimiter != '\t':
        data = genfromtxt(filename, dtype=None, names=with_header, delimiter=delimiter,
                  deletechars='', skiprows=skiprows)
    else:
        data = genfromtxt(filename, dtype=None, names=with_header,
                  deletechars='', skiprows=skiprows)
    if data.ndim == 0:
    data = array([data.item()])
    return (data, skipped_rows)

问题是genfromtxt抱怨我的文件，例如错误：

the problem is that genfromtxt complains about my files, e.g. with the error:

Line #27100 (got 12 columns instead of 16)

我不知道这些错误是从哪里来的。有任何想法吗？

I am not sure where these errors come from. Any ideas?

以下是导致问题的示例文件：

Here's an example file that causes the problem:

#Gene   120-1   120-3   120-4   30-1    30-3    30-4    C-1 C-2 C-5 genesymbol  genedesc
ENSMUSG00000000001  7.32    9.5 7.76    7.24    11.35   8.83    6.67    11.35   7.12    Gnai3   guanine nucleotide binding protein alpha
ENSMUSG00000000003  0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Pbsn    probasin

写一个通用的csv2array函数？感谢。

Is there a better way to write a generic csv2array function? thanks.

推荐答案

查看python CSV模块：

Check out the python CSV module: http://docs.python.org/library/csv.html

import csv
reader = csv.reader(open("myfile.csv", "rb"),
                    delimiter='\t', quoting=csv.QUOTE_NONE)

header = []
records = []
fields = 16

if thereIsAHeader: header = reader.next()

for row, record in enumerate(reader):
    if len(record) != fields:
        print "Skipping malformed record %i, contains %i fields (%i expected)" %
            (record, len(record), fields)
    else:
        records.append(record)

# do numpy stuff.

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