python - 将键值对读入 Pandas

Question

Pandas 使读取 CSV 文件变得非常容易:

pd.read_table('data.txt', sep=',')

对于具有键值对的文件，Pandas 是否有类似的东西？我想到了这个:

pd.DataFrame([dict([p.split('=') for p in l.split(',')]) for l in open('data.txt')])

如果不是内置的，那么也许是更惯用的东西？

感兴趣的文件如下所示:

symbol=ESM3,exchange=GLOBEX,timestamp=1365428525690751,price=1548.00,quantity=551
symbol=ESM3,exchange=GLOBEX,timestamp=1365428525697183,price=1548.00,quantity=551
symbol=ESM3,exchange=GLOBEX,timestamp=1365428525714498,price=1548.00,quantity=551
symbol=ESM3,exchange=GLOBEX,timestamp=1365428525734967,price=1548.00,quantity=551
symbol=ESM3,exchange=GLOBEX,timestamp=1365428525735567,price=1548.00,quantity=555
symbol=ESM3,exchange=GLOBEX,timestamp=1365428525735585,price=1548.00,quantity=556
symbol=ESM3,exchange=GLOBEX,timestamp=1365428525736116,price=1548.00,quantity=556
symbol=ESM3,exchange=GLOBEX,timestamp=1365428525740757,price=1548.00,quantity=556
symbol=ESM3,exchange=GLOBEX,timestamp=1365428525748502,price=1548.00,quantity=556
symbol=ESM3,exchange=GLOBEX,timestamp=1365428525748952,price=1548.00,quantity=557

它在每一行上都有完全相同的键，并且顺序相同。没有空值。要生成的表是:

  exchange    price quantity symbol         timestamp
0   GLOBEX  1548.00    551\n   ESM3  1365428525690751
1   GLOBEX  1548.00    551\n   ESM3  1365428525697183
2   GLOBEX  1548.00    551\n   ESM3  1365428525714498
3   GLOBEX  1548.00    551\n   ESM3  1365428525734967
4   GLOBEX  1548.00    555\n   ESM3  1365428525735567
5   GLOBEX  1548.00    556\n   ESM3  1365428525735585
6   GLOBEX  1548.00    556\n   ESM3  1365428525736116
7   GLOBEX  1548.00    556\n   ESM3  1365428525740757
8   GLOBEX  1548.00    556\n   ESM3  1365428525748502
9   GLOBEX  1548.00    557\n   ESM3  1365428525748952

(我可以在引入 quantity 后使用 rstrip() 删除 \n。)

Answer 1

如果您事先知道键名并且名称总是以相同的顺序出现，那么您可以使用转换器来截断键名，然后使用 names 参数来命名列:

import pandas as pd

def value(item):
    return item[item.find('=')+1:]

df = pd.read_table('data.txt', header=None, delimiter=',',
                   converters={i:value for i in range(5)},
                   names='symbol exchange timestamp price quantity'.split())
print(df)

关于您发布的数据产量

  symbol exchange         timestamp    price quantity
0   ESM3   GLOBEX  1365428525690751  1548.00      551
1   ESM3   GLOBEX  1365428525697183  1548.00      551
2   ESM3   GLOBEX  1365428525714498  1548.00      551
3   ESM3   GLOBEX  1365428525734967  1548.00      551
4   ESM3   GLOBEX  1365428525735567  1548.00      555
5   ESM3   GLOBEX  1365428525735585  1548.00      556
6   ESM3   GLOBEX  1365428525736116  1548.00      556
7   ESM3   GLOBEX  1365428525740757  1548.00      556
8   ESM3   GLOBEX  1365428525748502  1548.00      556
9   ESM3   GLOBEX  1365428525748952  1548.00      557