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Get started on your learning journey towards data science using Python. Equip yourself with practical skills in Python programming for the purpose of basic data manipulation and analysis.

In NumPy, you can join 2 or more arrays together using `np.concatenate`

. To do so, you will need to ensure that if you are adding a row, the rows of both arrays must be the same. Likewise for columns.

**Syntax**

np.concatenate(array1, array2)

Once again we start by creating some arrays with `.arange`

Arrays can be stacked horizontally - meaning that you can join the arrays by the sides. To do this, we need to ensure that the number of rows in all arrays that are to be joined together are the same.

Arrays can be also be stacked vertically - meaning that you can join the arrays by the top / bottom. To do this, we need to ensure that the number of columns in all arrays that are to be joined together are the same.

Rearrange the following arrays and stack them vertically with 5 columns:

myArray_1 = np.arange(20) myArray_2 = np.arange(30)

Your results should look like this:

[[ 0 1 2 3 4] [ 5 6 7 8 9] [10 11 12 13 14] [15 16 17 18 19] [ 0 1 2 3 4] [ 5 6 7 8 9] [10 11 12 13 14] [15 16 17 18 19] [20 21 22 23 24] [25 26 27 28 29]]