Reputation: 916
So, this should be a really straightforward thing but for whatever reason, nothing I'm doing to convert an array of strings to an array of floats is working.
I have a two column array, like so:
Name Value
Bob 4.56
Sam 5.22
Amy 1.22
I try this:
for row in myarray[1:,]:
row[1]=float(row[1])
And this:
for row in myarray[1:,]:
row[1]=row[1].astype(1)
And this:
myarray[1:,1] = map(float, myarray[1:,1])
And they all seem to do something, but when I double check:
type(myarray[9,1])
I get
<type> 'numpy.string_'>
Upvotes: 5
Views: 11469
Reputation: 609
The type of the objects in a numpy array is determined at the initialsation of that array. If you want to change that later, you must cast the array, not the objects within that array.
myNewArray = myArray.asType(float)
Note: Upcasting is possible, for downcasting you need the astype method.
For further information see:
http://docs.scipy.org/doc/numpy/reference/generated/numpy.array.html
http://docs.scipy.org/doc/numpy/reference/generated/numpy.chararray.astype.html
Upvotes: 0
Reputation: 46578
Numpy arrays must have one dtype
unless it is structured. Since you have some strings in the array, they must all be strings.
If you wish to have a complex dtype
, you may do so:
import numpy as np
a = np.array([('Bob','4.56'), ('Sam','5.22'),('Amy', '1.22')], dtype = [('name','S3'),('val',float)])
Note that a
is now a 1d structured array, where each element is a tuple of type dtype
.
You can access the values using their field name:
In [21]: a = np.array([('Bob','4.56'), ('Sam','5.22'),('Amy', '1.22')],
...: dtype = [('name','S3'),('val',float)])
In [22]: a
Out[22]:
array([('Bob', 4.56), ('Sam', 5.22), ('Amy', 1.22)],
dtype=[('name', 'S3'), ('val', '<f8')])
In [23]: a['val']
Out[23]: array([ 4.56, 5.22, 1.22])
In [24]: a['name']
Out[24]:
array(['Bob', 'Sam', 'Amy'],
dtype='|S3')
Upvotes: 7