import numpy as np<\/pre><\/div>\n\n\n\nWe\u2019re going to concatenate two arrays. One array will contain all the numbers between 1 and 9 (inclusive). The second array will contain all the numbers between 10 and 18 (inclusive).
<\/p>\n\n\n\n
Let\u2019s create these arrays using the arange()<\/code> method:<\/p>\n\n\n\nfirst_array = np.arange(1, 10).reshape(3, 3)\nsecond_array = np.arange(10, 19).reshape(3, 3)\n\nprint(first_array)\nprint(second_array)<\/pre><\/div>\n\n\n\nThis code creates two arrays. Each array is a 2d array. We have made these arrays 2d by using the reshape()<\/code> method which creates a 3×3 grid for each array:
<\/p>\n\n\n\n[[1 2 3]\n [4 5 6]\n [7 8 9]]\n[[10 11 12]\n [13 14 15]\n [16 17 18]]<\/pre><\/div>\n\n\n\nWe now have two arrays with which we can work! Let\u2019s concatenate them using concatenate()<\/code>.<\/p>\n\n\n\nNumPy Concatenation<\/h2>\n\n\n\n
You can concatenate an array on two axes: by row or by column. This is accomplished using the concatenate()<\/code> method. The concatenate method can merge 1d, 2d, 3d, 4d, and arrays with a higher number of dimensions.<\/p>\n\n\n\nConcatenate by Row<\/h3>\n\n\n\n
We\u2019ll start by concatenating our two arrays by row. This will align the items in our two arrays by row and merge them into one array:
<\/p>\n\n\n\n
final_array = np.concatenate((first_array, second_array))\nprint(final_array)<\/pre><\/div>\n\n\n\nWe have specified a tuple inside the concatenate()<\/code> function. This tuple contains the list of arrays that we want to concatenate. Without any parameters, concatenate()<\/code> concatenates by row.
<\/p>\n\n\n\nOur code returns:
<\/p>\n\n\n\n
[[ 1 2 3]\n [ 4 5 6]\n [ 7 8 9]\n [10 11 12]\n [13 14 15]\n [16 17 18]]<\/pre><\/div>\n\n\n\nOur arrays are concatenated by rows.<\/p>\n\n\n\n
Concatenate by Column<\/h3>\n\n\n\n
You can use the concatenate method to merge two arrays by column.
<\/p>\n\n\n\n
To do this, we need to introduce a new parameter: axis. By default, this value is 0. This corresponds to the x axis, or the row axis. We can override this value and set it to 1. This will merge our two arrays by column.
<\/p>\n\n\n\n
Let\u2019s concatenate our two arrays by column:<\/p>\n\n\n\n
final_array = np.concatenate((first_array, second_array), axis=1)\nprint(final_array)<\/pre><\/div>\n\n\n\nOur code is almost the same as our last example. The difference is that we have specified the axis=1 parameter. Let\u2019s see what happens when we run our code:<\/p>\n\n\n\n
[[ 1 2 3 10 11 12]\n [ 4 5 6 13 14 15]\n [ 7 8 9 16 17 18]]<\/pre><\/div>\n\n\n\nOur arrays are merged by column. <\/p>\n\n\n\n
Concatenating More Than Two Arrays<\/h2>\n\n\n\n
The concatenate()<\/code> method can concatenate any number of arrays. Let\u2019s try to concatenate three arrays on a horizontal axis. The arrays with which we will be working contain all numbers in the range of:
<\/p>\n\n\n\n