Python将csv文件列读入列表，而忽略标题 [英] Python read csv file columns into lists, ignoring headers

问题描述

我有一个看起来像这样的文件'data.csv'

I have a file 'data.csv' that looks something like

ColA, ColB, ColC
1,2,3
4,5,6
7,8,9

我想打开文件列并将其读入列表，并省略该列表的第一个条目，例如

I want to open and read the file columns into lists, with the 1st entry of that list omitted, e.g.

dataA = [1,4,7]
dataB = [2,5,8]
dataC = [3,6,9]

实际上有3列以上，并且列表很长，这只是格式的一个示例.我尝试过:

In reality there are more than 3 columns and the lists are very long, this is just an example of the format. I've tried:

csv_file = open('data.csv','rb')
csv_array = []

for row in csv.reader(csv_file, delimiter=','):
    csv_array.append(row)

然后我将csv_array的每个索引分配给一个列表，例如

Where I would then allocate each index of csv_array to a list, e.g.

dataA = [int(i) for i in csv_array[0]]

但是我遇到了错误:

_csv.Error: new-line character seen in unquoted field - do you need to open the file in universal-newline mode?

感觉就像将数据保存到几个列表中一样漫长的方式...

Also it feels like a very long winded way of just saving data to a few lists...

谢谢！

这是我解决的方法:

import pandas as pd

df = pd.read_csv('data.csv', names = ['ColA','ColB','ColC']

dataA = map(int,(df.ColA.tolist())[1:3])

，然后对其余的列重复上述操作.

and repeat for the rest of the columns.

推荐答案

使用熊猫:

import pandas as pd

df = pd.DataFrame.from_csv(path)
rows = df.apply(lambda x: x.tolist(), axis=1)

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