我被困住了。我想将一个简单的csv文件读取到一个Numpy数组中，似乎已经陷入困境。我是Numpy的新手，我确定我已经以某种方式弄乱了它，因为通常我可以在Python 3.4中轻松读取CSV文件。我不想使用Pandas，所以我想我会使用Numpy来提高我的技能，但是我真的一点都没有。如果有人可以使用genfromtxt告诉我我是否走在正确的轨道上，或者有什么更简单的方法向我正确的方向走，我将不胜感激。我想读取CSV文件，将datetime列设置为2014年8月4日，然后将其与其余列一起放入numpy数组中。这是我到目前为止所遇到的问题以及我在编码时遇到的错误。我可以在那里获得日期的一部分，但看不到如何将date.strftime（“％Y-％m-％d”）添加到datefunc。另外，我也看不到如何格式化SYM字符串以解决该错误。任何帮助，将不胜感激。
数据
2015-08-04 02:14:05.249392, AA, 0.0193103612, 0.0193515212, 0.0249713335, 30.6542480634, 30.7195875454, 39.640763021, 0.2131498442, 29.0406746589, 13524.5347810182, 89, 57, 99
2015-08-04 02:14:05.325113, AAPL, 0.0170506271, 0.0137941891, 0.0105915637, 27.0670313481, 21.8975963326, 16.8135861893, -19.0986405157, -23.2172064279, 21.5647072302, 33, 26, 75
2015-08-04 02:14:05.415193, AIG, 0.0080808151, 0.0073296055, 0.0076213535, 12.8278962785, 11.635388035, 12.0985236788, -9.2962105215, 3.980405659, -142.8175077335, 71, 42, 33
2015-08-04 02:14:05.486185, AMZN, 0.0235649449, 0.0305828226, 0.0092703502, 37.4081902773, 48.5487257749, 14.7162247572, 29.7810062852, -69.6877219282, -334.0005615016, 2, 92, 10
对不起，“代码”仍然在学习
import numpy as np
from datetime import datetime
from datetime import date,time
datefunc = lambda x: datetime.strptime(x.decode("utf-8"), '%Y-%m-%d %H:%M:%S.%f')
a = np.genfromtxt('/home/dave/Desktop/development/hvanal2016.csv',delimiter = ',',
converters = {0:datefunc},dtype='object,str,float,float,float,float,float,float,float,float,float,float,float,float',
names = ["date","sym","20sd","10sd","5sd","hv20","hv10","hv5","2010hv","105hv","abshv","2010rank","105rank","absrank"])
print(a["date"])
print(a["sym"])
print(a["20sd"])
print(a["hv20"])
print(a["absrank"])
错误
Python 3.4.3+ (default, Oct 14 2015, 16:03:50)
[GCC 5.2.1 20151010] on linux
Type "copyright", "credits" or "license()" for more information.
>>>
============================================================================== RESTART: /home/dave/3 9 15 my slope.py ===============================================================================
[datetime.datetime(2015, 8, 4, 2, 14, 5, 249392)
datetime.datetime(2015, 8, 4, 2, 14, 5, 325113)
datetime.datetime(2015, 8, 4, 2, 14, 5, 415193) ...,
datetime.datetime(2016, 3, 18, 1, 0, 25, 925754)
datetime.datetime(2016, 3, 18, 1, 0, 26, 26400)
datetime.datetime(2016, 3, 18, 1, 0, 26, 114828)]
Traceback (most recent call last):
File "/home/dave/3 9 15 my slope.py", line 19, in <module>
print(a["sym"])
File "/usr/lib/python3/dist-packages/numpy/core/numeric.py", line 1615, in array_str
return array2string(a, max_line_width, precision, suppress_small, ' ', "", str)
File "/usr/lib/python3/dist-packages/numpy/core/arrayprint.py", line 454, in array2string
separator, prefix, formatter=formatter)
File "/usr/lib/python3/dist-packages/numpy/core/arrayprint.py", line 328, in _array2string
_summaryEdgeItems, summary_insert)[:-1]
File "/usr/lib/python3/dist-packages/numpy/core/arrayprint.py", line 490, in _formatArray
word = format_function(a[i]) + separator
UnicodeDecodeError: 'utf-32-le' codec can't decode bytes in position 0-3: code point not in range(0x110000)
因此，您的文字部分是
b'2015-08-04 02:14:05.249392 AA 0.0193103612 ...'
（我正在使用，b因为Py3会genfromtxt以字节串形式打开文件）。
但是您指定一个,定界符。我看不到逗号。
让我们只尝试基本负载，而不是花哨的业务。
In [97]: txt=b"""2015-08-04 02:14:05.249392 AA 0.0193103612 0.0193515212 0.0249713335 30.6542480634 30.7195875454 39.640763021 0.2131498442 29.0406746589 13524.5347810182 89 57 99
2015-08-04 02:14:05.325113 AAPL 0.0170506271 0.0137941891 0.0105915637 27.0670313481 21.8975963326 16.8135861893 -19.0986405157 -23.2172064279 21.5647072302 33 26 75
"""
In [98]: txt=txt.splitlines()
In [99]: data=np.genfromtxt(txt,dtype=None)
In [100]: data
Out[100]:
array([ (b'2015-08-04', b'02:14:05.249392', b'AA', 0.0193103612, 0.0193515212, 0.0249713335, 30.6542480634, 30.7195875454, 39.640763021, 0.2131498442, 29.0406746589, 13524.5347810182, 89, 57, 99),
(b'2015-08-04', b'02:14:05.325113', b'AAPL', 0.0170506271, 0.0137941891, 0.0105915637, 27.0670313481, 21.8975963326, 16.8135861893, -19.0986405157, -23.2172064279, 21.5647072302, 33, 26, 75)],
dtype=[('f0', 'S10'), ('f1', 'S15'), ('f2', 'S4'), ('f3', '<f8'), ('f4', '<f8'), ('f5', '<f8'), ('f6', '<f8'), ('f7', '<f8'), ('f8', '<f8'), ('f9', '<f8'), ('f10', '<f8'), ('f11', '<f8'), ('f12', '<i4'), ('f13', '<i4'), ('f14', '<i4')])
日期时间信息在2个字段中：
In [101]: data[['f0','f1']]
Out[101]:
array([(b'2015-08-04', b'02:14:05.249392'),
(b'2015-08-04', b'02:14:05.325113')],
dtype=[('f0', 'S10'), ('f1', 'S15')])
您的datefunction确实可以使用字节子字符串
In [102]: datefunc(b'2015-08-04 02:14:05.249392')
Out[102]: datetime.datetime(2015, 8, 4, 2, 14, 5, 249392)
但是它需要2个字段（由''分隔符定义）。因此，我们需要找出一种将这两个子字符串解析为一个而不是拆分为两个字段的方法。
也许我会尝试将示例更改txt为真正使用,定界符（但不要在日期和时间之间）并设置有效的方法。
使用定,界文本，我得到：
In [117]: data=np.genfromtxt(txt,delimiter=',',dtype=None,usecols=[0,1,2,3])
In [118]: data.dtype
Out[118]: dtype([('f0', 'S26'), ('f1', 'S5'), ('f2', '<f8'), ('f3', '<f8')])
In [119]: data['f0']
Out[119]:
array([b'2015-08-04 02:14:05.249392', b'2015-08-04 02:14:05.325113',
b'2015-08-04 02:14:05.415193', b'2015-08-04 02:14:05.486185'],
dtype='|S26')
In [120]: [datefunc(d) for d in data['f0']]
Out[120]:
[datetime.datetime(2015, 8, 4, 2, 14, 5, 249392),
datetime.datetime(2015, 8, 4, 2, 14, 5, 325113),
datetime.datetime(2015, 8, 4, 2, 14, 5, 415193),
datetime.datetime(2015, 8, 4, 2, 14, 5, 486185)]
我使用它usecols是因为全文在第一行有14个字段，在其他行有13个字段。
如果指定dtype（而不是easy None），则可以使用以下datetime对象替换1st字段中的字符串：
In [122]: data=np.genfromtxt(txt,delimiter=',',dtype='O,S5,f,f',usecols=[0,1,2,3])
In [123]: data
Out[123]:
array([ (b'2015-08-04 02:14:05.249392', b' AA', 0.01931036077439785, 0.019351521506905556),
(b'2015-08-04 02:14:05.325113', b' AAPL', 0.01705062761902809, 0.01379418931901455),....],
dtype=[('f0', 'O'), ('f1', 'S5'), ('f2', '<f4'), ('f3', '<f4')])
In [124]: data['f0']
Out[124]:
array([b'2015-08-04 02:14:05.249392', b'2015-08-04 02:14:05.325113',
b'2015-08-04 02:14:05.415193', b'2015-08-04 02:14:05.486185'], dtype=object)
....
In [126]: data['f0']=[datefunc(d) for d in data['f0']]
In [127]: data
Out[127]:
array([ (datetime.datetime(2015, 8, 4, 2, 14, 5, 249392), b' AA', 0.01931036077439785, 0.019351521506905556),
(datetime.datetime(2015, 8, 4, 2, 14, 5, 325113), b' AAPL', 0.01705062761902809, 0.01379418931901455),...],
dtype=[('f0', 'O'), ('f1', 'S5'), ('f2', '<f4'), ('f3', '<f4')])
并通过转换器，您的通话（或多或少）可以正常工作
In [133]: data=np.genfromtxt(txt,dtype='object,S5,float,float',
converters = {0:datefunc},delimiter=',',usecols=[0,1,2,3])
In [134]: data
Out[134]:
array([ (datetime.datetime(2015, 8, 4, 2, 14, 5, 249392), b' AA', 0.0193103612, 0.0193515212),
(datetime.datetime(2015, 8, 4, 2, 14, 5, 325113), b' AAPL', 0.0170506271, 0.0137941891),...],
dtype=[('f0', 'O'), ('f1', 'S5'), ('f2', '<f8'), ('f3', '<f8')])
the numpy datetime64使用此字符串。这些类型可以使用numpy数字。
In [154]: datefunc(b'2015-08-04 02:14:05.249392')
Out[154]: datetime.datetime(2015, 8, 4, 2, 14, 5, 249392)
In [155]: np.datetime64(b'2015-08-04 02:14:05.249392')
Out[155]: numpy.datetime64('2015-08-04T02:14:05.249392-0700')
通过将此csv导入Numpy datetime64中，我可以使用此功能：
In [175]: data=np.genfromtxt(txt,dtype='M8[us],S5,float,float',
delimiter=',',usecols=[0,1,2,3])
In [176]: data
Out[176]:
array([ (datetime.datetime(2015, 8, 4, 9, 14, 5, 249392), b' AA', 0.0193103612, 0.0193515212),
(datetime.datetime(2015, 8, 4, 9, 14, 5, 325113), b' AAPL', 0.0170506271, 0.0137941891),...],
dtype=[('f0', '<M8[us]'), ('f1', 'S5'), ('f2', '<f8'), ('f3', '<f8')])
请参阅以获取日期时间单位：http : //docs.scipy.org/doc/numpy/reference/arrays.datetime.html#datetime-units
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