Question

我需要从我读过的CSV文件中划分空白区域

import csv

aList=[]
with open(self.filename, 'r') as f:
    reader = csv.reader(f, delimiter=',', quoting=csv.QUOTE_NONE)
    for row in reader:
        aList.append(row)
    # I need to strip the extra white space from each string in the row
    return(aList)

Answer 1

还有嵌入式格式参数：skipinitialspace（默认为false） http://docs.python.org/2/library/csv.html#csv-fmt-params

aList=[]
with open(self.filename, 'r') as f:
    reader = csv.reader(f, skipinitialspace=False,delimiter=',', quoting=csv.QUOTE_NONE)
    for row in reader:
        aList.append(row)
    return(aList)

Answer 2

在我的情况下，我只关心在使用csv.DictReader时从字段名称（也就是列标题，也就是字典键）中删除空格。

基于csv.DictReader创建一个类，并覆盖fieldnames属性以从每个字段名称中删除空格（也就是列标题，也就是字典键）。

通过获取常规的字段名列表，然后在创建新列表时迭代它，并从每个字段名称中删除空白，并将基础_fieldnames属性设置为此新列表。

>

import csv

class DictReaderStrip(csv.DictReader):
    @property                                    
    def fieldnames(self):
        if self._fieldnames is None:
            # Initialize self._fieldnames
            # Note: DictReader is an old-style class, so can't use super()
            csv.DictReader.fieldnames.fget(self)
            if self._fieldnames is not None:
                self._fieldnames = [name.strip() for name in self._fieldnames]
        return self._fieldnames

Answer 3

with open(self.filename, 'r') as f:
    reader = csv.reader(f, delimiter=',', quoting=csv.QUOTE_NONE)
    return [[x.strip() for x in row] for row in reader]

Answer 4

你可以这样做：

aList.append([element.strip() for element in row])

Answer 5

您可以在文件周围创建一个包装器对象，在CSV阅读器看到之前剥离空格。这样，您甚至可以将csv文件与cvs.DictReader一起使用。

import re

class CSVSpaceStripper:
  def __init__(self, filename):
    self.fh = open(filename, "r")
    self.surroundingWhiteSpace = re.compile("\s*;\s*")
    self.leadingOrTrailingWhiteSpace = re.compile("^\s*|\s*$")

  def close(self):
    self.fh.close()
    self.fh = None

  def __iter__(self):
    return self

  def next(self):
    line = self.fh.next()
    line = self.surroundingWhiteSpace.sub(";", line)
    line = self.leadingOrTrailingWhiteSpace.sub("", line)
    return line

然后像这样使用它：

o = csv.reader(CSVSpaceStripper(filename), delimiter=";")
o = csv.DictReader(CSVSpaceStripper(filename), delimiter=";")

我将";"硬编码为分隔符。将代码推广到任何分隔符都留给读者练习。

Answer 6

使用Pandas读取CSV（或Excel文件）并使用此自定义功能修剪它。

#Definition for strippping whitespace
def trim(dataset):
    trim = lambda x: x.strip() if type(x) is str else x
    return dataset.applymap(trim)

您现在可以将修剪（CSV / Excel）应用到您的代码中（如循环的一部分等）

dataset = trim(pd.read_csv(dataset))
dataset = trim(pd.read_excel(dataset))

Answer 7

解析后格式化单元格最节省内存的方法是通过generators。像这样：

with open(self.filename, 'r') as f:
    reader = csv.reader(f, delimiter=',', quoting=csv.QUOTE_NONE)
    for row in reader:
        yield (cell.strip() for cell in row)

但可能值得将其移至一个函数，您可以使用该函数来不断进行调整并避免即将到来的迭代。例如：

nulls = {'NULL', 'null', 'None', ''}

def clean(reader):
    def clean(row):
        for cell in row:
            cell = cell.strip()
            yield None if cell in nulls else cell

    for row in reader:
        yield clean(row)

或者它可以用于分解一个类：

def factory(reader):
    fields = next(reader)

    def clean(row):
        for cell in row:
            cell = cell.strip()
            yield None if cell in nulls else cell

    for row in reader:
        yield dict(zip(fields, clean(row)))

Answer 8

这是适用于 Python3 的 Daniel Kullmann 出色的解决方案：

import re

class CSVSpaceStripper:
    """strip whitespaces around delimiters in the file
    NB has hardcoded delimiter ";"
    """

    def __init__(self, filename):
        self.fh = open(filename, "r")
        self.surroundingWhiteSpace = re.compile(r"\s*;\s*")
        self.leadingOrTrailingWhiteSpace = re.compile(r"^\s*|\s*$")

    def close(self):
        self.fh.close()
        self.fh = None

    def __iter__(self):
        return self

    def __next__(self):
        line = self.fh.readline()
        line = self.surroundingWhiteSpace.sub(";", line)
        line = self.leadingOrTrailingWhiteSpace.sub("", line)
        return line

Answer 9

我想出了一个非常简单的解决方案：

import csv

with open('filename.csv') as f:
  reader = csv.DictReader(f)
  rows = [ { k.strip(): v.strip() for k,v in row.items() } for row in reader ]

从CSV文件中删除空格

9 个答案: