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I use an external module (libsvm), which does not support numpy arrays, only tuples, lists and dicts. But my data is in a 2d numpy array. How can I convert it the pythonic way, aka without loops.
>>> import numpy >>> array = numpy.ones((2,4)) >>> data_list = list(array) >>> data_list [array([ 1., 1., 1., 1.]), array([ 1., 1., 1., 1.])] >>> type(data_list[0]) <type 'numpy.ndarray'> # <= what I don't want # non pythonic way using for loop >>> newdata=list() >>> for line in data_list: ... line = list(line) ... newdata.append(line) >>> type(newdata[0]) <type 'list'> # <= what I want 
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To convert from a Numpy array to list, we simply typed the name of the 2D Numpy array, and then called the Numpy tolist() method which produced a Python list as an output.
With NumPy, [ np. array ] objects can be converted to a list with the tolist() function. The tolist() function doesn't accept any arguments. If the array is one-dimensional, a list with the array elements is returned.
To convert a NumPy array (ndarray) to a Python list use ndarray. tolist() function, this doesn't take any parameters and returns a python list for an array. While converting to a list, it converts the items to the nearest compatible built-in Python type.
You can simply cast the matrix to list with matrix.tolist(), proof:
>>> import numpy >>> a = numpy.ones((2,4)) >>> a array([[ 1., 1., 1., 1.], [ 1., 1., 1., 1.]]) >>> a.tolist() [[1.0, 1.0, 1.0, 1.0], [1.0, 1.0, 1.0, 1.0]] >>> type(a.tolist()) <type 'list'> >>> type(a.tolist()[0]) <type 'list'> If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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