![]() A 2D array is built up of multiple 1D arrays. If we’re dealing with a 2D Numpy array, it’s more complicated. If we’re dealing with a 1D Numpy array, looping over all elements can be as simple as: for x in my_array : The capital of germany is berlin Loop over Numpy array – np.nditer() # Definition of dictionary europe = # Iterate over europe for x, y in ems(): print("the capital of ", str(x), " is ", str(y)) On each iteration, "the capital of x is y" will be printed out, where x is the key and y is the value of the pair. Room 4: 9.5 Loop over dictionary – items() In Python 3, we need the items() method to loop over a dictionary. If one also wants to access the index information, so where the list element we are iterating over is located, we can use enumerate().Īs an example, have a look at how the for loop was converted by creating an areas list: # areas list areas = # Change for loop to use enumerate() and update print() for x, y in enumerate(areas) : print("room ", str(x), ": ", str(y)) Using a for loop to iterate over a list only gives us access to every list element in each run, one after the other. ![]() In the following topic, we’ll see a brief of different processes of iteration. They are iterable containers from which you can get an iterator from. Lists, tuples, dictionaries, strings, and sets are all iterable objects. Python has several language features to make it easier to perform the iteration task.Īs an object, the iterator counts a number of values that can be iterated upon. In a way, we can say repeated execution of a set of statements is what iteration is all about. ![]() IntroductionĪn iteration is an object that repeats identical or similar tasks without making errors. ![]()
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