2] 2"print(xs[-1])# Negative indices count from the end of the list; prints "2"xs[2] ='foo'# Lists can contain elements of different typesprint(xs)# Prints "[3, 1, 'foo']"xs.append('bar')# Add a new element to the end of the listprint(xs)# Prints "[3, 1, 'foo', ...
x=5 #assigns the value 5 to the variable x x+=1 #statement adds 1 to x (is equivalent to x=x+1) x-=1 #statement subtracts 1 from x (is equivalent to x=x-1) x*=2 #multiplies x by 2(is equivalent to x=x*2) x%=3 #equivalent to x=x%3, returns remainder x/=3 #equ...
# Elementwise difference; both produce the array # [[-4.0 -4.0] # [-4.0 -4.0]] print(x - y) print(np.subtract(x, y)) # Elementwise product; both produce the array # [[ 5.0 12.0] # [21.0 32.0]] print(x * y) print(np.multiply(x, y)) # Elementwise division; both produce...
6],[7,8]], dtype=np.float64) # Elementwise sum; both produce the array # [[ 6.0 8.0] # [10.0 12.0]] print(x + y) print(np.add(x, y)) # Elementwise difference; both produce the array # [[-4.0 -4.0] # [-4.0 -4.0]] print(x - y) print(np.subtract(x,...
subtract(x, y)) # Elementwise product; both produce the array # [[ 5.0 12.0] # [21.0 32.0]] print(x * y) print(np.multiply(x, y)) # Elementwise division; both produce the array # [[ 0.2 0.33333333] # [ 0.42857143 0.5 ]] print(x / y) print(np.divide(x, y)) # Element...
With NumPy arrays, you can do things like inner and outer products, transposition, and element-wise operations. NumPy also contains a number of useful methods for reading text and binary data files, fitting polynomial functions, many mathematical functions (sine, cosine, square root, and so on)...
You also subtract the height of the frame containing the sliders from the height of the preview to avoid cropping the contained image. While the application displays the image that you specify on the command line after starting up, nothing seems to change when you move the sliders. It’s ...
logical_not Compute truth value of not x element-wise. Equivalent to -arr. Table 4-4. Binary universal functions FunctionDescription add Add corresponding elements in arrays subtract Subtract elements in second array from first array multiply Multiply array elements divide, floor_divide Divide or flo...
add(x,y) print("Addition of x and y:\n", z) # Subtract `x` and `y` z = np.subtract(x,y) print("Subtraction of y from x:\n", z) # Multiply `x` and `y` z = np.multiply(x,y) print("Element-wise multiplication of x and y:\n", z) Powered By Remember how ...
>>> a == b #Elementwise comparison array([[False , True, True], [ False,False ,False ]], dtype=bool) >>> a< 2 #Elementwise comparison array([True, False, False], dtype=bool) >>> np.array_equal(a, b) #Arraywise comparison Powered By Copying Arrays >>>h = a.view()#Cr...