Definition of NumPy zip
As the name suggest it zipped the variable together. We can use iterable object with this function like array, list, string, dictionary etc. This function pairs the first value of the every iterable object and proceed ahead like this only. This function is also available inside the NumPy library which is used for computation on the array and single element as well. It is not mandatory to have the iterable object of the same type.
We can call this function using the ‘zip’ keyword and it takes any itearble object inside it as the input parameter. Below see the syntax to use zip function in python;
zip(object1, object2, object3, object4,.. so on)
Also see the syntax as per the python doc;
This function takes containers or an iterable object like; string, list, array, etc.
Let’s see one practice syntax for a better understating of the function see below We will discuss its working in detail in the next section;
arr1 = [val1, val2, val3] arr2 = [val1, val2, val3] result = zip(arr1, arr2)
How does zip Function Work in NumPy?
Now we know that we use this function to zip or group the variable of different array sometimes it just remove the need of user object to be created. It just functions in the same way like its name just zipped different array or list variable values together. This can take any number of an iterable object, also the length of the iterable object is also not a constraint here. If we talk about its return type it returns single objects which contain all the value zipped form the different iterable objects. We can use this function in so many places like if we want to amp the student data based on the name, city, marks, and roll number so we can use this function without creating a class for it. Let’s take one example to understand about its syntax more in detail;
- Return Type: This function returns a single object. This single object contains all the variable from all the array or iterable objects we pass into the function.
- Parameter: This function takes an iterable object of any length and any number of parameters.
Let’s see one example to understand its working in a better way;
arr1 = [ "amit", "sumit", "vishal", "mita", "geets", "sujata", “kavita”, ”lalita”, ”somore” ] arr2 = [ 001, 002, 003, 004, 005, 006, 007, 008, 009, 010, so on …] result = zip(arr1, arr2)
In the above example, we are creating two arrays. The first array containing the name of the student and the second array containing the roll number associated with the student. IF we talk about any other programming language then we need an object which will bind both the variable of the student class or else we need to create a map that will map the value of the student as key value pair this will require a lot of code. But in python, we have a zip() function which will bind the variable of two or more different array into one single array. In the last line, we are calling the zip() function and passing both the array into it as a parameter. We are holding the data into the result variable here which will be a zipped iterable object which will contain the result. Now we will talk about the real time scenario in which we cause it.
Suppose we have a student where we need to bind the data according to with roll number, marks, city, and address so we can use this function for this we need to create three array which will contain the name, roll number, marks, city, and address of the student respectively. After that, we can pass this input parameter in the zip() function. So in the output, we will have all the student data mapped with the corresponding record of the student.
studentName = ; rollNumber = ; city =; address = ; result = zip(studentName, rollNumber, city, address)
So in the end it will generate the object which will be going to contain the mapped object of the student object.
Pints to be remembered while working with zip() function in python;
- Like we zip our object into the single object we can also perform unzip of the object. This operation can be performed by using the unzip() function.
- zip() function does not bond to the length of the iterable object. The same length is not mandatory.
Examples of NumPy zip
Following are the examples are given below:
In this example, we are creating two iterable objects and just calling the zip function on them. This is for beginners to show the working.
print("demo for zip function") #creating array object arr1 = [ "value1", "value2", "value3", "value4", "value5", "value6" ] arr2 = [ 1, 2, 3, 4, 5, 6 ] #calling zip function here to bind two array elements result = zip(arr1, arr2) #here mapping result to print in formte result = set(result) #printing result print("result after zip function is ::") print(result)
In this example we are going to map the student data for name, roll number, city and grade they obtained and printing the result.
print("demo for zip function") #creating array object arr1 = [ "Amit", "Sumit", "Vinit", "Kavit", "aman", "vijay" ] arr2 = [ "mumbai", "pune", "bng", "chennai", "hyd", "deilhi" ] arr3 = [ "001", "004", "003", "009", "010", "011" ] arr4 = [ 1, 2, 3, 4, 5, 6 ] #calling zip function here to bind two array elements result = zip(arr1, arr2, arr3, arr4) #here mapping result to print in formte result = set(result) #printing result print("result after zip function is ::") print(result)
If we want to bind or zip the data of different array then we can go for zip function in python of NumPy. This function eliminates the need of class object if not required. We can easily map our data with any number of the array and this can be done very easily with the use of the zip() function.
This is a guide to NumPy zip. Here we discuss the definition and how does zip function work in numpy? along with different examples and its code implementation. You may also have a look at the following articles to learn more –