During programming, there will be instances when you will need to convert existing lists to arrays in order to perform certain operations on them (arrays enable mathematical operations to be performed on them in ways that lists do not).
Lists can be converted to arrays using the built-in functions in the Python numpy library.
numpy
provides us with two functions to use when converting a list into an array:
numpy.array()
numpy.asarray()
numpy.array()
This function of the numpy
library takes a list as an argument and returns an array that contains all the elements of the list. See the example below:
import numpy as np my_list = [2,4,6,8,10] my_array = np.array(my_list) # printing my_array print my_array # printing the type of my_array print type(my_array)
numpy.asarray()
This function calls the numpy.array()
function inside itself. See the definition below:
def asarray(a, dtype=None, order=None):
return array(a, dtype, copy=False, order=order)
The main difference between
np.array()
andnp.asarray()
is that thecopy
flag isfalse
in the case ofnp.asarray()
, andtrue
(by default) in the case ofnp.array()
.
This means that np.array()
will make a copy of the object (by default) and convert that to an array, while np.asarray()
will not.
The code below illustrates the usage of np.asarray()
:
import numpy as np my_list = [2,4,6,8,10] my_array = np.asarray(my_list) # printing my_array print my_array # printing the type of my_array print type(my_array)
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