Javascript Adds Two Arrays

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Michael Zippo 04.11.2021

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How to concatenate NumPy arrays

NumPy is a great library to work with arrays in Python . It covers everything from creating and manipulating tables of all sizes. So it’s no surprise that NumPy comes with a utility that you can use to concatenate arrays.

The numpy.concatenate () method joins two or more arrays into a single array.

In this guide, we’ll talk about what NumPy arrays are and how you can concatenate them. We’re going to look at some examples to get you started. Let’s get started!

The structure of an array

A NumPy array is a type of array which works with the NumPy library. It looks like any other array but is stored in an ndarray object:

To work with a NumPy array, we must import the numpy library :

We are going to concatenate two arrays. An array will contain all numbers between 1 and 9 (inclusive). The second array will contain all the numbers between 10 and 18 (inclusive).

We create these arrays using the arange () method:

This code creates two arrays. Each array is a 2D array. We created these 2D arrays using the reshape () method which creates a 3 √ó 3 grid for each array:

We now have two tables to work with! Let’s concatenate them using concatenate ().

NumPy Concatenation

You can concatenate an array on two axes: by row or by column. This is done using the concatenate () method. The chained method can join 1D, 2D, 3D, 4D and arrays with a larger number of dimensions.

Concatenate by row

We will start by concatenating our two tables by row. This will align the elements of our two arrays per row and merge them into one array:

We specified a tuple inside the concatenate () function. This tuple contains the list of arrays we want to concatenate. Without any parameters, concatenate () concatenates by line.

Our code returns:

Our tables are concatenated by lines.

Concatenate by column

You can use t The concatenate method to join two tables by column.

To do this, we need to introduce a new parameter: the axis. By default, this value is 0. It corresponds to the x-axis or to the line axis. We can override this value and set it to 1. This will merge our two tables per column.

Let’s concatenate our two arrays by column:

Our code is almost the same as our last example. The difference is that we specified the axis = 1 parameter. Let’s see what happens when we run our code:

Our tables are attached by column.

Concatenate more than two arrays

The concatenate () method can concatenate any number of arrays. Let’s try to concatenate three arrays on a horizontal axis. The arrays we will be working with contain all the numbers in the range:

• 1 to 9 (inclusive).
• 10 to 18 (inclusive).
• 19 to 27 (inclusive).

Let’s define our arrays in Python:

Then we can use concatenate to bring them together:

We have specified our three arrays as a tuple in the concatenate () method. When combined, these arrays match all numbers between 1 and 27.

Let’s run our program:

Our three arrays are now assigned to the variable "Final_array." We printed this variable on the console to show that our arrays were successfully merged.

Conclusion

The NumPy concatenate () merges two or more NumPy arrays. Arrays are merged on vertical axis by default. You can merge arrays on horizontal access using the axis = 1 flag.