在Python 3中在线读取CSV文件中的数据

只是作为练习来测试一些东西。我有这个巨大的CSV文件在线 我想读取所有的数据，然后把它放到一个表格里，这样我就可以进行分析并制作表格。 到目前为止，我的代码是使用其他StackOverflow问题和其他网站组合而成的，但似乎发生的是当它被阅读时，然后立即再次逐字打印出来，因此我得到：

['C']
['o']
['u']
['n']
['t']
['r']
['y']
[' ']
['N']
['a']
['m']
['e']
['', '']
['C']
['o']
['u']
['n']
['t']
['r']
['y']
[' ']
['C']
['o']
['d']
['e']
['', '']
['Y']
['e']
['a']
['r']
['', '']
['V']
['a']
['l']
['u']
['e']
[]
[]
['A']
['r']
['a']
['b']
[' ']
['W']
['o']
['r']
['l']
['d']
['', '']

到目前为止，我的代码是：

import csv
import urllib.request

url = "https://raw.github.com/datasets/gdp/master/data/gdp.csv"
webpage = urllib.request.urlopen(url)
datareader = csv.reader(webpage.read().decode('utf-8'))
data = []
for row in datareader:
    data.append(row)

for row in data:
    print(row)

我如何修改它，使它实际上逐行读取，然后甚至将该行拆分为不同的变量。我在使用之前做过这个

payRollNumber, salary, jobTitle, otherNames, \
               surname = line.strip().split(',')

---

我可以在得到行之后应用这个。有什么想法吗？

在将读取的CSV数据传递到

CSV.reader（）之前，您需要将其按行拆分：

然后，
csv.reader（）
会为您处理其余部分

您还可以负责阅读、解码和线路处理：

import csv
import io
import urllib.request

url = "https://raw.github.com/datasets/gdp/master/data/gdp.csv"
webpage = urllib.request.urlopen(url)
datareader = csv.reader(io.TextIOWrapper(webpage))

在读卡器上循环并向列表中添加行几乎没有意义；你可以这样做：

data = list(datareader)

相反，如果您只想打印列，请直接在读卡器上循环并执行以下操作：

datareader = csv.reader(io.TextIOWrapper(webpage))
for row in datareader:
    print(row)

无论哪种方式，通过自己拆分行或使用
TextIOWrapper
，代码现在生成：

['Country Name', 'Country Code', 'Year', 'Value']
['Arab World', 'ARB', '1968', '32456179321.45']
['Arab World', 'ARB', '1969', '35797666653.6002']
['Arab World', 'ARB', '1970', '39062044200.4362']
['Arab World', 'ARB', '1971', '45271917893.3429']
['Arab World', 'ARB', '1972', '54936622019.8224']
['Arab World', 'ARB', '1973', '69564884441.8264']
['Arab World', 'ARB', '1974', '132123836511.468']
['Arab World', 'ARB', '1975', '147666389454.913']
['Arab World', 'ARB', '1976', '182208407088.856']
# ... etc. ...

['Country Name', 'Country Code', 'Year', 'Value']
['Arab World', 'ARB', '1968', '32456179321.45']
['Arab World', 'ARB', '1969', '35797666653.6002']
['Arab World', 'ARB', '1970', '39062044200.4362']
['Arab World', 'ARB', '1971', '45271917893.3429']
['Arab World', 'ARB', '1972', '54936622019.8224']
['Arab World', 'ARB', '1973', '69564884441.8264']
['Arab World', 'ARB', '1974', '132123836511.468']
['Arab World', 'ARB', '1975', '147666389454.913']
['Arab World', 'ARB', '1976', '182208407088.856']
# ... etc. ...