如何更改numpy recarray的某些列的dtype？

Question

假设我有一个如下所示的重组:

import numpy as np

# example data from @unutbu's answer
recs = [('Bill', '31', 260.0), ('Fred', 15, '145.0')]
r = np.rec.fromrecords(recs, formats = 'S30,i2,f4', names = 'name, age, weight')

print(r)
# [('Bill', 31, 260.0) ('Fred', 15, 145.0)]

假设我想将某些列转换为浮点数.我该怎么做呢？我应该换成一个ndarray,然后再回到recarray吗？

Answer 1

以下是astype用于执行转换的示例:

import numpy as np
recs = [('Bill', '31', 260.0), ('Fred', 15, '145.0')]
r = np.rec.fromrecords(recs, formats = 'S30,i2,f4', names = 'name, age, weight')
print(r)
# [('Bill', 31, 260.0) ('Fred', 15, 145.0)]

的age是D型细胞<i2:

print(r.dtype)
# [('name', '|S30'), ('age', '<i2'), ('weight', '<f4')]

我们可以改为<f4使用astype:

r = r.astype([('name', '|S30'), ('age', '<f4'), ('weight', '<f4')])
print(r)
# [('Bill', 31.0, 260.0) ('Fred', 15.0, 145.0)]

Answer 2

基本上有两个步骤.我的绊脚石是找到如何修改现有的dtype.我就这样做了:

# change dtype by making a whole new array
dt = data.dtype
dt = dt.descr # this is now a modifiable list, can't modify numpy.dtype
# change the type of the first col:
dt[0] = (dt[0][0], 'float64')
dt = numpy.dtype(dt)
# data = numpy.array(data, dtype=dt) # option 1
data = data.astype(dt)