我有一个使用np.genfromtxt()
函数从csv文件加载的元组数组。
import numpy as np
import re
from matplotlib.dates import strpdate2num
def convert_string_to_bigint(x):
p = re.compile(r'(\d{4})/(\d{1,2})/(\d{1,2}) (\d{1,2}):(\d{2}):\d{2}')
m = p.findall(x)
l = list(m[0])
l[1] = ('0' + l[1])[-2:]
l[2] = ('0' + l[2])[-2:]
return long("".join(l))
#print convert_string_to_bigint("2012/7/2 14:07:00")
csv = np.genfromtxt ('sr00-1min.txt', delimiter=',', converters={0:convert_string_to_bigint})
csv文件中的数据样本:
2015/9/2 14:54:00,5169,5170,5167,5168
2015/9/2 14:55:00,5168,5169,5166,5166
2015/9/2 14:56:00,5167,5170,5165,5169
2015/9/2 14:57:00,5168,5173,5167,5172
2015/9/2 14:58:00,5172,5187,5171,5182
2015/9/2 14:59:00,5182,5183,5171,5176
2015/9/2 15:00:00,5176,5183,5174,5182
加载后,它看起来像这样:
[(201509021455L, 5168.0, 5169.0, 5166.0, 5166.0)
(201509021456L, 5167.0, 5170.0, 5165.0, 5169.0)
(201509021457L, 5168.0, 5173.0, 5167.0, 5172.0)
(201509021458L, 5172.0, 5187.0, 5171.0, 5182.0)
(201509021459L, 5182.0, 5183.0, 5171.0, 5176.0)
(201509021500L, 5176.0, 5183.0, 5174.0, 5182.0)]
我想将它转换为numpy 2d数组。它应该是这样的:
[[201509021455L, 5168.0, 5169.0, 5166.0, 5166.0]
[201509021456L, 5167.0, 5170.0, 5165.0, 5169.0]
[201509021457L, 5168.0, 5173.0, 5167.0, 5172.0]
[201509021458L, 5172.0, 5187.0, 5171.0, 5182.0]
[201509021459L, 5182.0, 5183.0, 5171.0, 5176.0]
[201509021500L, 5176.0, 5183.0, 5174.0, 5182.0]]
我使用下面的代码来解决这个问题,但它看起来非常难看。有人能告诉我如何以优雅的方式转换它吗?
pool = np.asarray([x for x in csv if x[0] > 201508010000])
sj = np.asarray([x[0] for x in pool])
kpj = np.asarray([x[1] for x in pool])
zgj = np.asarray([x[2] for x in pool])
zdj = np.asarray([x[3] for x in pool])
spj = np.asarray([x[4] for x in pool])
output = np.column_stack((sj,kpj,zgj,zdj,spj))
print output.shape
答案 0 :(得分:2)
在convert_string_to_bigint
中,更改
return long("".join(l))
到
return float("".join(l))
然后genfromtxt
会将所有值识别为浮点数,并返回一个浮点数dtype的二维数组:
In [23]: np.genfromtxt ('sr00-1min.txt', delimiter=',', converters={0:convert_string_to_bigint}).shape
Out[23]: (7, 5)
而不是混合dtype的1D 结构化数组。