Arithmetic operations on NumPy array of strings

Question

I have a code that looks like this:

import numpy as np

data =[['2015-07-21 22:18:04', -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, 10.1, -999.25, -999.25],
       ['2015-07-21 22:18:05', -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25,
        -999.25, -999.25, 10.1, -999.25, -999.25],
       ['2015-07-21 22:18:06', -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25,
        -999.25, -999.25, 10.1, -999.25, -999.25]]

arr = np.array(data)
depth = arr[:, 1]

print(type(depth))

diff = [depth[i] - depth[i - 1] for i in range(len(depth))][1:]
diff_index = [i for i, item in enumerate(diff) if item > 0]
data = [data[row] for row in diff_index]

When I run my code, I get the following error msg:

    diff = [depth[i] - depth[i - 1] for i in range(len(depth))][1:]
TypeError: unsupported operand type(s) for -: 'numpy.str_' and 'numpy.str_'

I've never used numpy before, so I am confused. I couldn't find online documentation that can help me, but its probably because I don't know most of numpy stuff.

I want to select the i-th element from the numpy array, and perform arithmetic operations. How can one fix my code so that it will do the job?

hpaulj · Accepted Answer · 2018-03-05 04:14:55Z

In [364]: data =[['2015-07-21 22:18:04', -999.25, -999.25, -999.25, -999.25, -99...
     ...: arr = np.array(data)
     ...: depth = arr[:, 1]
     ...: 
In [365]: type(depth)       # type doesn't tell us anything important
Out[365]: numpy.ndarray
In [366]: depth.dtype       # but dtype does
Out[366]: dtype('<U19')
In [367]: arr
Out[367]: 
array([['2015-07-21 22:18:04', '-999.25', '-999.25', '-999.25',
        '-999.25', '-999.25', '-999.25', '-999.25', '-999.25', '-999.25',
        '-999.25', '-999.25', '-999.25', '10.1', '-999.25', '-999.25'],...],
      dtype='<U19')

Because the first numbers are strings (dates), everything is strings:

In [368]: depth
Out[368]: array(['-999.25', '-999.25', '-999.25'], dtype='<U19')

We can convert the arr array into float without the the first column:

In [369]: arr[:,1:].astype(float)
Out[369]: 
array([[-999.25, -999.25, -999.25, -999.25, -999.25, -999.25, -999.25,
        -999.25, -999.25, -999.25, -999.25, -999.25,   10.1 , -999.25,
        -999.25],
 ...])

Or just depth:

In [370]: depth=arr[:,1].astype(float)
In [371]: diff = [depth[i] - depth[i - 1] for i in range(len(depth))][1:]
In [372]: diff
Out[372]: [0.0, 0.0]

But since this is an array, we don't have to use list calculations:

In [373]: depth
Out[373]: array([-999.25, -999.25, -999.25])
In [374]: depth[1:]-depth[:-1]
Out[374]: array([0., 0.])

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