I have a .csv file with both string and integer - containing columns. I need to use numpy.loadtxt method to import the matrix formed from the specified columns. How can I do that? Right now I am trying to do the following:
data = np.loadtxt(open(path_to_data, "rb"), delimiter=",", skiprows=1, usecols=[1:])
Basically trying to read all columns but first, but it is giving an error:
SyntaxError: invalid syntax
Because such syntax is not allowed: usecols=[1:]
This is the syntax error:
In [153]: [1:]
File "<ipython-input-153-4bac19319341>", line 1
[1:]
^
SyntaxError: invalid syntax
It's not specific to loadtxt.
Use
data = np.loadtxt(open(path_to_data, "rb"), delimiter=",", skiprows=1, usecols=np.arange(1,n))
where n is the total number of columns.
usecols : int or sequence, optional
Which columns to read, with 0 being the first. For example,
``usecols = (1,4,5)`` will extract the 2nd, 5th and 6th columns.
The default, None, results in all columns being read.
If you don't know n, and don't want to use a preliminary file read to determine it, genfromtxt might be easier.
data = np.genfromtxt(..., delimiter=',', skiprows=1)
should load all columns, putting nan where it can't convert the string into float. If those nan are all in the first column, then
data = data[:,1:]
should give you all but the first column.
genfromtxt is a little more forgiving when it comes to converting strings to floats.