Python 将带有逗号分隔数据和换行符的字符串转换为数据帧
我为一只股票拉1分钟的历史数据条,数据如下: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
'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