简单地用next()迭代一次

with open(filename) as file:

    csvreaded = csv.reader(file)
    header = next(csvreaded)

    for row in csvreaded:
        empty_list.append(row) #your csv list without header  

或者在reader对象的末尾使用[1:]

with open(filename) as file:

    csvreaded = csv.reader(file)
    header = next(csvreaded)

    for row in csvreaded[1:]:
        empty_list.append(row) #your csv list without header  

执行row=1不会改变任何东西，因为您只是用循环的结果覆盖了它。

您希望执行下一步(读取器)跳过一行。

您的reader变量是一个可迭代对象，通过对它进行循环，您可以检索行。

要让它在循环之前跳过一项，只需调用next(reader, None)并忽略返回值。

你也可以稍微简化你的代码;使用打开的文件作为上下文管理器来自动关闭它们:

with open("tmob_notcleaned.csv", "rb") as infile, open("tmob_cleaned.csv", "wb") as outfile:
   reader = csv.reader(infile)
   next(reader, None)  # skip the headers
   writer = csv.writer(outfile)
   for row in reader:
       # process each row
       writer.writerow(row)

# no need to close, the files are closed automatically when you get to this point.

如果你想将头文件未处理地写入输出文件，这也很简单，将next()的输出传递给writer.writerow():

headers = next(reader, None)  # returns the headers or `None` if the input is empty
if headers:
    writer.writerow(headers)

解决这个问题的另一种方法是使用DictReader类，它“跳过”标题行，并使用它来允许命名索引。

给定"foo.csv"如下所示:

FirstColumn,SecondColumn
asdf,1234
qwer,5678

像这样使用DictReader:

import csv
with open('foo.csv') as f:
    reader = csv.DictReader(f, delimiter=',')
    for row in reader:
        print(row['FirstColumn'])  # Access by column header instead of column number
        print(row['SecondColumn'])

受到马丁·彼得的回应的启发。

如果你只需要从csv文件中删除头，你可以更有效地工作，如果你使用标准的Python文件I/O库，避免使用csv Python库:

with open("tmob_notcleaned.csv", "rb") as infile, open("tmob_cleaned.csv", "wb") as outfile:
   next(infile)  # skip the headers
   outfile.write(infile.read())

简单地用next()迭代一次

with open(filename) as file:

    csvreaded = csv.reader(file)
    header = next(csvreaded)

    for row in csvreaded:
        empty_list.append(row) #your csv list without header  

或者在reader对象的末尾使用[1:]

with open(filename) as file:

    csvreaded = csv.reader(file)
    header = next(csvreaded)

    for row in csvreaded[1:]:
        empty_list.append(row) #your csv list without header