python - 使用pd.read_csv()，指定数据为np.float32，但得到字符串

Question

当我尝试从 csv 文件读取数据时。我想将“数据”列的数据类型设置为 float ，所以我的代码是这样的:

data = pd.read_csv('data.csv', index_col=0, 
                   parse_dates=[0], 
                   skiprows=[0], names=['Data'],
                   dtype={'Data':np.float32})

但是我得到的结果仍然是字符串列表。有什么原因和解决办法吗？

[5]: data.values

[5]: array([['1188.0'],
            ['1377.0'],
            ['1279.0'],
            ['1461.0'],
            ['1146.0'],
            ['1287.0'],
            ['1259.0']], dtype=object)

Answer 1

向names参数添加值:

import pandas as pd
import numpy as np
from io import StringIO

temp="""2019-01-02,1188.0
2019-01-03,1377.0
2019-01-04,1279.0
2019-01-05,1461.0
2019-01-06,1146.0
2019-01-07,1287.0
2019-01-08,1259.0"""
#after testing replace 'pd.compat.StringIO(temp)' to 'data.csv'
df = pd.read_csv(StringIO(temp),
                 index_col=0,
                 parse_dates=[0],
                 names=['dates','Data'],
                 dtype={'Data':np.float32})

<小时/>

print (df)
              Data
dates             
2019-01-02  1188.0
2019-01-03  1377.0
2019-01-04  1279.0
2019-01-05  1461.0
2019-01-06  1146.0
2019-01-07  1287.0
2019-01-08  1259.0

print (df.dtypes)
Data    float32
dtype: object

print (df.index)
DatetimeIndex(['2019-01-02', '2019-01-03', '2019-01-04', '2019-01-05',
               '2019-01-06', '2019-01-07', '2019-01-08'],
              dtype='datetime64[ns]', name='dates', freq=None)