{"id":4536,"date":"2022-08-16T01:36:20","date_gmt":"2022-08-16T01:36:20","guid":{"rendered":"https:\/\/www.pythontutorial.net\/?page_id=4536"},"modified":"2022-08-16T01:46:25","modified_gmt":"2022-08-16T01:46:25","slug":"numpy-split","status":"publish","type":"page","link":"https:\/\/www.pythontutorial.net\/python-numpy\/numpy-split\/","title":{"rendered":"NumPy split()"},"content":{"rendered":"\n

Summary<\/strong>: in this tutorial, you’ll learn how to use the NumPy split()<\/code> function to split an array into multiple sub-arrays.<\/p>\n\n\n\n

Introduction to the NumPy split() function #<\/a><\/h2>\n\n\n\n

The split()<\/code><\/code> funciton splits an array<\/a> into multiple sub-arrays as views. The syntax of the split()<\/code><\/code> function is as follows:<\/p>\n\n\n

numpy.split(ary, indices_or_sections, axis=0<\/span>)<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
In this syntax:<\/p>\n\n\n\n
ary<\/code> is the array to be split into subarrays.<\/p>\n\n\n\n
indices_or_sections<\/code> can be an integer or a 1-D array of sorted integers. <\/p>\n\n\n\n
If it is an integer, the function splits the input array into N equal arrays along the axis. If the split is not possible, the function will raise an error.<\/p>\n\n\n\n
If indices_or_sections is a 1D array of sorted integers, the indices indicate where along the axis the function splits the array. <\/p>\n\n\n\n
When an index exceeds the dimension of the array along the axis, the function returns an empty subarray.<\/p>\n\n\n\n
The following picture shows how the split()<\/code> function splits the array with indices 2, 3, and 4. It results in 4 arrays.<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
NumPy split() function example #<\/a><\/h2>\n\n\n\n
Let’s take some examples of using the split()<\/code> function.<\/p>\n\n\n\n
1) Using the split() function to split a 1D array #<\/a><\/h3>\n\n\n\n
The following example uses the split()<\/code> function to split a 1D array with seven elements into three sub-arrays:<\/p>\n\n\n
import<\/span> numpy as<\/span> np\n\n\na = np.arange(1<\/span>,7<\/span>)\nresults = np.split(a,3<\/span>)\n\nprint(a)\nprint(results)<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
Output:<\/p>\n\n\n
[1<\/span> 2<\/span> 3<\/span> 4<\/span> 5<\/span> 6<\/span>]\n[array([1<\/span>, 2<\/span>]), array([3<\/span>, 4<\/span>]), array([5<\/span>, 6<\/span>])]<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
The following example raises an error because the split is not possible:<\/p>\n\n\n
import<\/span> numpy as<\/span> np\n\n\na = np.arange(1<\/span>,7<\/span>)\nresults = np.split(a,4<\/span>)<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
Output:<\/p>\n\n\n
ValueError: array split does not<\/span> result in<\/span> an equal division<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
In this example, the array has 6 elements therefore it cannot be split into 4 arrays of equal size. If you want to have a more flexible split, you can use the array_split()<\/code> function.<\/p>\n\n\n\n
2) Using the split() function to split a 2D array #<\/a><\/h3>\n\n\n\n
The following example uses the split()<\/code> function to split a 2D array into two subarrays:<\/p>\n\n\n
import<\/span> numpy as<\/span> np\n\na = np.array([[1<\/span>,2<\/span>],[3<\/span>,4<\/span>],[5<\/span>,6<\/span>],[7<\/span>,8<\/span>]])\nresults = np.split(a,2<\/span>)\n\nprint(a)\nprint(results)<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
Output:<\/p>\n\n\n
[[1<\/span> 2<\/span>]\n [3<\/span> 4<\/span>]\n [5<\/span> 6<\/span>]\n [7<\/span> 8<\/span>]]\n[array([[1<\/span>, 2<\/span>],\n       [3<\/span>, 4<\/span>]]), array([[5<\/span>, 6<\/span>],\n       [7<\/span>, 8<\/span>]])]<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
3) Using the NumPy split() function using indices #<\/a><\/h3>\n\n\n\n
The following example uses the split()<\/code> function to split a 1D array using an array of indices:<\/p>\n\n\n
import<\/span> numpy as<\/span> np\n\n\na = np.arange(10<\/span>,70<\/span>,10<\/span>)\nresults = np.split(a, [2<\/span>, 3<\/span>, 4<\/span>])\nprint(a)\nprint(results)<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
Output:<\/p>\n\n\n
[1<\/span> 2<\/span> 3<\/span> 4<\/span> 5<\/span> 6<\/span>]\n[array([1<\/span>, 2<\/span>]), array([3<\/span>]), array([4<\/span>, 5<\/span>, 6<\/span>])]<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
Summary #<\/a><\/h2>\n\n\n\n
  • Use NumPy split()<\/code> function to split an array into subarrays.<\/li><\/ul>\n
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