Python 将带有逗号分隔数据和换行符的字符串转换为数据帧

Python 将带有逗号分隔数据和换行符的字符串转换为数据帧,python,python-3.x,pandas,Python,Python 3.x,Pandas,我为一只股票拉1分钟的历史数据条,数据如下: '2018-06-11 09:31:00,968.250,965.000,968.000,965.250,17220,1160\n2018-06-11 09:32:00,965.250,964.250,965.250,964.750,17872,611\n2018-06-11 09:33:00,965.000,963.250,965.000,963.500,18851,547\n' 它是一个字符串,其中每行由新行字符分隔,每个字段由逗号分隔。当我使

我为一只股票拉1分钟的历史数据条,数据如下:

'2018-06-11 09:31:00,968.250,965.000,968.000,965.250,17220,1160\n2018-06-11
09:32:00,965.250,964.250,965.250,964.750,17872,611\n2018-06-11
09:33:00,965.000,963.250,965.000,963.500,18851,547\n'

它是一个字符串,其中每行由新行字符分隔,每个字段由逗号分隔。当我使用print()函数时,它看起来很好,但我想将其转换为一个数据帧。非常感谢您的帮助。

将字符串馈送到以下位置时,此操作非常有效:

import pandas as pd
from io import StringIO

mystr = StringIO("""2018-06-11 09:31:00,968.250,965.000,968.000,965.250,17220,1160\n2018-06-11 09:32:00,965.250,964.250,965.250,964.750,17872,611\n2018-06-11 09:33:00,965.000,963.250,965.000,963.500,18851,547\n""")

df = pd.read_csv(mystr, index_col=0, header=None)
df.index = pd.to_datetime(df.index)

print(df)

                          1       2       3       4      5     6
0                                                               
2018-06-11 09:31:00  968.25  965.00  968.00  965.25  17220  1160
2018-06-11 09:32:00  965.25  964.25  965.25  964.75  17872   611
2018-06-11 09:33:00  965.00  963.25  965.00  963.50  18851   547

print(df.dtypes)

1    float64
2    float64
3    float64
4    float64
5      int64
6      int64
dtype: object