Code:
import csv
import numpy
raw_data = open('C:\\Users\\train.csv', 'rt')
data = numpy.loadtxt(raw_data, delimiter=",")
print(data.shape)
Below is the sample data used
Time Freq
8:00 91.1
8:03 91.1
8:06 91.1
8:09 91.1
8:12 91.1
8:15 91.1
8:18 91.1
8:21 91.1
8:24 91.1
8:27 91.1
8:30 91.1
Error:
ValueError: could not convert string to float: b'Time'
In [350]: txt ='''Time Freq
...: 8:00 91.1
...: 8:03 91.1
...: 8:06 91.1
...: 8:09 91.1
...: 8:12 91.1
...: 8:15 91.1
...: 8:18 91.1
...: 8:21 91.1
...: 8:24 91.1
...: 8:27 91.1
...: 8:30 91.1
...: '''
Loading as a structured array, using the first line as field names.
In [351]: data = np.genfromtxt(txt.splitlines(),names=True,dtype=None,encoding=N
...: one)
In [352]: data
Out[352]:
array([('8:00', 91.1), ('8:03', 91.1), ('8:06', 91.1), ('8:09', 91.1),
('8:12', 91.1), ('8:15', 91.1), ('8:18', 91.1), ('8:21', 91.1),
('8:24', 91.1), ('8:27', 91.1), ('8:30', 91.1)],
dtype=[('Time', '<U4'), ('Freq', '<f8')])
In [353]: data['Freq']
Out[353]: array([91.1, 91.1, 91.1, 91.1, 91.1, 91.1, 91.1, 91.1, 91.1, 91.1, 91.1])
Note that the 2nd column has been loaded as numbers, but the first as strings.
By default numpy.loadtext expects everything in the file to be a number. Time is not a number. 8:00 is not a number either. If you want to perform numerical operations on your data, you're going to need to remove the Time Freq header, and convert your times to numbers.
If you don't need to do any type of numerical analysis, you can import the data as strings. numpy.loadtxt(raw_data, delimiter=",", dtype='str') . See the docs for more info.
Alternatively, you can use genfromtxt.
numpy.loadtexthave an optional parameter telling it to skip a header line? It isn't clear from your sample data that the first two words are on their own line. Please copy and paste the sample data and format it as code (select it and presctrl-k).loadtxtloads the data as floats, and raises an error when it can't.genfromtxtputsnanwhere it can't create the float. What do you want the result to look like?