{"id":3061,"date":"2021-04-22T07:59:46","date_gmt":"2021-04-22T02:29:46","guid":{"rendered":"https:\/\/python-programs.com\/?p=3061"},"modified":"2021-11-22T18:44:56","modified_gmt":"2021-11-22T13:14:56","slug":"how-to-get-numpy-array-dimensions-using-numpy-ndarray-shape-numpy-ndarray-size-in-python","status":"publish","type":"post","link":"https:\/\/python-programs.com\/how-to-get-numpy-array-dimensions-using-numpy-ndarray-shape-numpy-ndarray-size-in-python\/","title":{"rendered":"How to get Numpy Array Dimensions using numpy.ndarray.shape & numpy.ndarray.size() in Python"},"content":{"rendered":"

In this article, we will be discussing how to count several elements in 1D, 2D, and 3D Numpy array. Moreover, we will be discussing the counting of rows and columns in a 2D array and the number of elements per axis in a 3D Numpy array.<\/p>\n

Let’s get started!<\/strong><\/em><\/p>\n

Get the Dimensions of a Numpy array using ndarray.shape()<\/h2>\n

NumPy.ndarray.shape<\/h3>\n

This module is used to get a current shape of an array, but it is also used to reshaping the array in place by assigning a tuple of arrays dimensions to it. The function is:<\/p>\n

ndarray.shape<\/pre>\n
We will use this function for determining the dimensions of the 1D and 2D array.<\/p>\n
Get Dimensions of a 2D NumPy array using ndarray.shape:<\/h3>\n
Let us start with a 2D Numpy array.<\/p>\n
\"2D<\/p>\n
\n
Code:<\/div>\n<\/div>\n
arr2D = np.<\/span>array<\/span>([[<\/span>11<\/span> ,<\/span>12<\/span>,<\/span>13<\/span>,<\/span>11<\/span>]<\/span>, <\/span>[<\/span>21<\/span>, <\/span>22<\/span>, <\/span>23<\/span>, <\/span>24<\/span>]<\/span>, <\/span>[<\/span>31<\/span>,<\/span>32<\/span>,<\/span>33<\/span>,<\/span>34<\/span>]])<\/span><\/div>\n
print<\/span>(<\/span>‘2D Numpy Array’<\/span>)<\/span><\/div>\n
print<\/span>(<\/span>arr2D<\/span>)<\/span><\/div>\n
Output:<\/div>\n
2D Numpy Array \r\n[[11 12 13 11] \r\n[21 22 23 24] \r\n[31 32 33 34]]<\/pre>\n
Get the number of rows in\u00a0this 2D NumPy array:<\/h3>\n
\"number<\/p>\n
Code:<\/p>\n
\n
numOfRows = arr2D.shape[0]\r\nprint('Number\u00a0of\u00a0Rows\u00a0:\u00a0',\u00a0numOfRows)<\/pre>\n<\/div>\n
Output:<\/div>\n
Number of Rows : 3<\/pre>\n
Get a number of columns in this 2D NumPy array:<\/h3>\n
\"number<\/p>\n
Code:<\/p>\n
\n
numOfColumns = arr2D.shape[1]\r\nprint('Number\u00a0of\u00a0Columns\u00a0:\u00a0',\u00a0numOfColumns)<\/pre>\n<\/div>\n
Output:<\/div>\n
Number of Columns: 4<\/pre>\n
Get the total number of elements in this 2D NumPy array:<\/h3>\n
\"total<\/p>\n
Code:<\/p>\n
\n
print('Total\u00a0Number\u00a0of\u00a0elements\u00a0in\u00a02D\u00a0Numpy\u00a0array\u00a0:\u00a0',\u00a0arr2D.shape[0]\u00a0*\u00a0arr2D.shape[1])<\/pre>\n<\/div>\n
Output:<\/div>\n
Total Number of elements in 2D Numpy array: 12<\/p>\n
Get Dimensions of a 1D NumPy array using ndarray.shape<\/h3>\n
Now, we will work on a 1D NumPy array.<\/p>\n
\"number<\/p>\n
Code:<\/p>\n
arr = np.<\/span>array<\/span>([<\/span>4<\/span>, <\/span>5<\/span>, <\/span>6<\/span>, <\/span>7<\/span>, <\/span>8<\/span>, <\/span>9<\/span>, <\/span>10<\/span>, <\/span>11<\/span>])<\/span><\/pre>\n
print<\/span>(<\/span>‘Shape of 1D numpy array : ‘<\/span>, arr.shape<\/span>)<\/span><\/div>\n
print<\/span>(<\/span>‘length of 1D numpy array : ‘<\/span>, arr.shape<\/span>[<\/span>0<\/span>])<\/span><\/div>\n
Output:<\/div>\n
\n
\n
Shape of 1D numpy array : <\/span>(<\/span>8<\/span>,<\/span>)\r\n<\/span>length of 1D numpy array : 8<\/span><\/pre>\n<\/div>\n<\/div>\n
\n
Get the Dimensions of a Numpy array using NumPy.shape()<\/h2>\n
Now, we will see the module which provides a function to get the number of elements in a Numpy array along the axis.<\/p>\n
numpy.<\/span>size<\/span>(<\/span>arr, axis=<\/span>None<\/span>)<\/span><\/p>\n
We will use this module for getting the dimensions of a 2D and 1D Numpy array.<\/p>\n
Get Dimensions of a 2D numpy array using numpy.size()<\/h3>\n
We will begin with a 2D Numpy array.<\/p>\n
\"Dimensions<\/p>\n
Code:<\/p>\n
\n
arr2D = np.<\/span>array<\/span>([[<\/span>11<\/span> ,<\/span>12<\/span>,<\/span>13<\/span>,<\/span>11<\/span>]<\/span>, <\/span>[<\/span>21<\/span>, <\/span>22<\/span>, <\/span>23<\/span>, <\/span>24<\/span>]<\/span>, <\/span>[<\/span>31<\/span>,<\/span>32<\/span>,<\/span>33<\/span>,<\/span>34<\/span>]])\r\n<\/span>print(<\/span>'2D Numpy Array'<\/span>)\r\n<\/span>print(<\/span>arr2D<\/span>)<\/span><\/pre>\n<\/div>\n
Output:<\/p>\n
\n
2D Numpy Array<\/span><\/div>\n<\/div>\n
\n
[[<\/span>11<\/span> 12<\/span> 13<\/span> 11<\/span>]<\/span><\/div>\n<\/div>\n
\n
[<\/span>21<\/span> 22<\/span> 23<\/span> 24<\/span>]<\/span><\/div>\n<\/div>\n
\n
[<\/span>31<\/span> 32<\/span> 33<\/span> 34<\/span>]]<\/span><\/div>\n<\/div>\n<\/div>\n
Get a number of rows and columns of this 2D NumPy array:<\/h3>\n
\"number<\/p>\n
Code:<\/p>\n
\n
numOfRows = np.<\/span>size<\/span>(<\/span>arr2D, <\/span>0<\/span>)\r\n<\/span># get number of columns in 2D numpy array\r\nnumOfColumns = np.size<\/span>(<\/span>arr2D, <\/span>1)\r\n<\/span>print(<\/span>'Number of Rows : '<\/span>, numOfRows<\/span>)\r\n<\/span>print(<\/span>'Number of Columns : '<\/span>, numOfColumns<\/span>)<\/span><\/pre>\n<\/div>\n
Output:<\/div>\n
\n
\n
Number of Rows : <\/span>3\r\n<\/span>Number of Columns: 4<\/span><\/pre>\n<\/div>\n
\n
Get a total number of elements in this 2D NumPy array:<\/h3>\n
\"<\/p>\n
Code:<\/p>\n
print<\/span>(<\/span>'Total Number of elements in 2D Numpy array : '<\/span>, np.<\/span>size<\/span>(<\/span>arr2D<\/span>))<\/span><\/pre>\n
Output:<\/p>\n
Total Number of elements <\/span>in<\/span> 2D Numpy array: <\/span>12<\/span><\/pre>\n<\/div>\n<\/div>\n
\n
Get Dimensions of a 3D NumPy array using numpy.size()<\/h2>\n<\/div>\n
Now, we will be working on the 3D Numpy array.<\/p>\n
\"3D<\/p>\n
Code:<\/p>\n
\n
arr3D = np.<\/span>array<\/span>([<\/span> [[<\/span>11<\/span>, <\/span>12<\/span>, <\/span>13<\/span>, <\/span>11<\/span>]<\/span>, <\/span>[<\/span>21<\/span>, <\/span>22<\/span>, <\/span>23<\/span>, <\/span>24<\/span>]<\/span>, <\/span>[<\/span>31<\/span>, <\/span>32<\/span>, <\/span>33<\/span>, <\/span>34<\/span>]]<\/span>,\r\n<\/span>[[1<\/span>, <\/span>1<\/span>, <\/span>1<\/span>, <\/span>1<\/span>]<\/span>, <\/span>[<\/span>2<\/span>, <\/span>2<\/span>, <\/span>2<\/span>, <\/span>2<\/span>]<\/span>, <\/span>[<\/span>3<\/span>, <\/span>3<\/span>, <\/span>3<\/span>, <\/span>3<\/span>]]<\/span> ])\r\n<\/span>print(<\/span>arr3D<\/span>)<\/span><\/pre>\n<\/div>\n
Output:<\/div>\n
\n
\n
[[[<\/span>11<\/span> 12<\/span> 13<\/span> 11<\/span>]\r\n<\/span>[21<\/span> 22<\/span> 23<\/span> 24<\/span>]\r\n<\/span>[31<\/span> 32<\/span> 33<\/span> 34<\/span>]]\r\n<\/span>[[ 1<\/span> 1<\/span> 1<\/span> 1<\/span>]\r\n<\/span>[ 2<\/span> 2<\/span> 2<\/span> 2<\/span>]\r\n<\/span>[ 3<\/span> 3<\/span> 3<\/span> 3<\/span>]]]<\/span><\/pre>\n<\/div>\n<\/div>\n
Get a number of elements per axis in 3D NumPy array:<\/h3>\n
\"number<\/p>\n
Code:<\/p>\n
\n
print<\/span>(<\/span>'Axis 0 size : '<\/span>, np.<\/span>size<\/span>(<\/span>arr3D, <\/span>0<\/span>))\r\n<\/span>print(<\/span>'Axis 1 size : '<\/span>, np.<\/span>size<\/span>(<\/span>arr3D, <\/span>1<\/span>))\r\n<\/span>print(<\/span>'Axis 2 size : '<\/span>, np.<\/span>size<\/span>(<\/span>arr3D, <\/span>2<\/span>))<\/span><\/pre>\n<\/div>\n
Output:<\/p>\n
\n
Axis <\/span>0<\/span> size : <\/span>2\r\n<\/span>Axis 1<\/span> size : <\/span>3\r\n<\/span>Axis 2<\/span> size : <\/span>4<\/span><\/pre>\n<\/div>\n
\n
Get the total number of elements in this 3D NumPy array:<\/h3>\n
\"total<\/p>\n
Code:<\/p>\n
print<\/span>(<\/span>‘Total Number of elements in 3D Numpy array : ‘<\/span>, np.<\/span>size<\/span>(<\/span>arr3D<\/span>))<\/span><\/p>\n
Output:<\/p>\n
Total Number of elements <\/span>in<\/span> 3D Numpy array : <\/span>24<\/span><\/p>\n
Get Dimensions of a 1D NumPy array using numpy.size()<\/h3>\n
Let us create a 1D array.<\/p>\n
\"Dimensions<\/p>\n
Code:<\/p>\n
arr = np.<\/span>array<\/span>([<\/span>4<\/span>, <\/span>5<\/span>, <\/span>6<\/span>, <\/span>7<\/span>, <\/span>8<\/span>, <\/span>9<\/span>, <\/span>10<\/span>, <\/span>11<\/span>])<\/span>\r\nprint<\/span>(<\/span>'Length of 1D numpy array : '<\/span>, np.<\/span>size<\/span>(<\/span>arr<\/span>))<\/span><\/pre>\n
Output:<\/p>\n
\n
\n
\n
Length of 1D numpy array : <\/span>8<\/span><\/pre>\n<\/div>\n
A complete example is as follows:<\/strong><\/div>\n
\n
\n
import<\/span> numpy <\/span>as<\/span> np\r\n<\/span>def main<\/span>()<\/span>:\r\n<\/span>print(<\/span>'**** Get Dimensions of a 2D numpy array using ndarray.shape ****'<\/span>)\r\n<\/span># Create a 2D Numpy array list of list\r\n arr2D = np.array<\/span>([[<\/span>11<\/span> ,<\/span>12<\/span>,<\/span>13<\/span>,<\/span>11<\/span>]<\/span>, <\/span>[<\/span>21<\/span>, <\/span>22<\/span>, <\/span>23<\/span>, <\/span>24<\/span>]<\/span>, <\/span>[<\/span>31<\/span>,<\/span>32<\/span>,<\/span>33<\/span>,<\/span>34<\/span>]])\r\n<\/span>print(<\/span>'2D Numpy Array'<\/span>)\r\n<\/span>print(<\/span>arr2D<\/span>)\r\n<\/span> # get number of rows in 2D numpy array\r\n numOfRows = arr2D.shape[<\/span>0<\/span>]\r\n<\/span> # get number of columns in 2D numpy array\r\n numOfColumns = arr2D.shape[<\/span>1<\/span>]\r\n<\/span>print(<\/span>'Number of Rows : '<\/span>, numOfRows<\/span>)\r\n<\/span>print(<\/span>'Number of Columns : '<\/span>, numOfColumns<\/span>)\r\n<\/span>print(<\/span>'Total Number of elements in 2D Numpy array : '<\/span>, arr2D.shape<\/span>[<\/span>0<\/span>]<\/span> * arr2D.shape<\/span>[<\/span>1<\/span>])\r\n<\/span>print(<\/span>'**** Get Dimensions of a 1D numpy array using ndarray.shape ****'<\/span>)\r\n<\/span> # Create a Numpy array from list of numbers\r\narr = np.array<\/span>([<\/span>4<\/span>, <\/span>5<\/span>, <\/span>6<\/span>, <\/span>7<\/span>, <\/span>8<\/span>, <\/span>9<\/span>, <\/span>10<\/span>, <\/span>11<\/span>])\r\n<\/span>print(<\/span>'Original Array : '<\/span>, arr<\/span>)\r\n<\/span>print(<\/span>'Shape of 1D numpy array : '<\/span>, arr.shape<\/span>)\r\n<\/span>print(<\/span>'length of 1D numpy array : '<\/span>, arr.shape<\/span>[<\/span>0<\/span>])\r\n<\/span>print(<\/span>'**** Get Dimensions of a 2D numpy array using np.size() ****'<\/span>)\r\n<\/span> # Create a 2D Numpy array list of list\r\n arr2D = np.array<\/span>([[<\/span>11<\/span>, <\/span>12<\/span>, <\/span>13<\/span>, <\/span>11<\/span>]<\/span>, <\/span>[<\/span>21<\/span>, <\/span>22<\/span>, <\/span>23<\/span>, <\/span>24<\/span>]<\/span>, <\/span>[<\/span>31<\/span>, <\/span>32<\/span>, <\/span>33<\/span>, <\/span>34<\/span>]])\r\n<\/span>print(<\/span>'2D Numpy Array'<\/span>)\r\n<\/span>print(<\/span>arr2D<\/span>)\r\n<\/span> # get number of rows in 2D numpy array\r\n numOfRows = np.size<\/span>(<\/span>arr2D, <\/span>0<\/span>)\r\n<\/span> # get number of columns in 2D numpy array\r\n numOfColumns = np.size<\/span>(<\/span>arr2D, <\/span>1<\/span>)\r\n<\/span>print(<\/span>'Number of Rows : '<\/span>, numOfRows<\/span>)\r\n<\/span>print(<\/span>'Number of Columns : '<\/span>, numOfColumns<\/span>)\r\n<\/span>print(<\/span>'Total Number of elements in 2D Numpy array : '<\/span>, np.<\/span>size<\/span>(<\/span>arr2D<\/span>))\r\n<\/span>print(<\/span>'**** Get Dimensions of a 3D numpy array using np.size() ****'<\/span>)\r\n<\/span> # Create a 3D Numpy array list of list of list\r\n arr3D = np.array<\/span>([<\/span> [[<\/span>11<\/span>, <\/span>12<\/span>, <\/span>13<\/span>, <\/span>11<\/span>]<\/span>, <\/span>[<\/span>21<\/span>, <\/span>22<\/span>, <\/span>23<\/span>, <\/span>24<\/span>]<\/span>, <\/span>[<\/span>31<\/span>, <\/span>32<\/span>, <\/span>33<\/span>, <\/span>34<\/span>]]<\/span>,\r\n<\/span>[[1<\/span>, <\/span>1<\/span>, <\/span>1<\/span>, <\/span>1<\/span>]<\/span>, <\/span>[<\/span>2<\/span>, <\/span>2<\/span>, <\/span>2<\/span>, <\/span>2<\/span>]<\/span>, <\/span>[<\/span>3<\/span>, <\/span>3<\/span>, <\/span>3<\/span>, <\/span>3<\/span>]]<\/span> ])\r\n<\/span>print(<\/span>'3D Numpy Array'<\/span>)\r\n<\/span>print(<\/span>arr3D<\/span>)\r\n<\/span>print(<\/span>'Axis 0 size : '<\/span>, np.<\/span>size<\/span>(<\/span>arr3D, <\/span>0<\/span>))\r\n<\/span>print(<\/span>'Axis 1 size : '<\/span>, np.<\/span>size<\/span>(<\/span>arr3D, <\/span>1<\/span>))\r\n<\/span>print(<\/span>'Axis 2 size : '<\/span>, np.<\/span>size<\/span>(<\/span>arr3D, <\/span>2<\/span>))\r\n<\/span>print(<\/span>'Total Number of elements in 3D Numpy array : '<\/span>, np.<\/span>size<\/span>(<\/span>arr3D<\/span>))\r\n<\/span>print(<\/span>'Dimension by axis : '<\/span>, arr3D.shape<\/span>)\r\n<\/span>print(<\/span>'**** Get Dimensions of a 1D numpy array using numpy.size() ****'<\/span>)\r\n<\/span> # Create a Numpy array from list of numbers\r\narr = np.array<\/span>([<\/span>4<\/span>, <\/span>5<\/span>, <\/span>6<\/span>, <\/span>7<\/span>, <\/span>8<\/span>, <\/span>9<\/span>, <\/span>10<\/span>, <\/span>11<\/span>])\r\n<\/span>print(<\/span>'Original Array : '<\/span>, arr<\/span>)\r\n<\/span>print(<\/span>'Length of 1D numpy array : '<\/span>, np.<\/span>size<\/span>(<\/span>arr<\/span>))\r\n<\/span>if __name__<\/span> == <\/span>'__main__'<\/span>:\r\n<\/span>main()<\/span><\/pre>\n<\/div>\n
<\/div>\n
Output:<\/div>\n
<\/div>\n<\/div>\n
\n
\n
**** Get Dimensions of a 2D numpy array using ndarray.shape ****\r\n<\/span>2D Numpy Array\r\n[[11<\/span> 12<\/span> 13<\/span> 11<\/span>]\r\n<\/span>[21<\/span> 22<\/span> 23<\/span> 24<\/span>]\r\n<\/span>[31<\/span> 32<\/span> 33<\/span> 34<\/span>]]\r\n<\/span>Number of Rows : 3\r\n<\/span>Number of Columns : 4\r\n<\/span>Total Number of elements in<\/span> 2D Numpy array : <\/span>12\r\n<\/span>**** Get Dimensions of a 1D numpy array using ndarray.shape ****\r\nOriginal Array : [<\/span> 4<\/span> 5<\/span> 6<\/span> 7<\/span> 8<\/span> 9<\/span> 10<\/span> 11<\/span>]\r\n<\/span>Shape of 1D numpy array : (<\/span>8<\/span>,<\/span>)\r\n<\/span>length of 1D numpy array : 8\r\n<\/span>**** Get Dimensions of a 2D numpy array using np.size<\/span>()<\/span> ****\r\n<\/span>2D Numpy Array\r\n[[11<\/span> 12<\/span> 13<\/span> 11<\/span>]\r\n<\/span>[21<\/span> 22<\/span> 23<\/span> 24<\/span>]\r\n<\/span>[31<\/span> 32<\/span> 33<\/span> 34<\/span>]]\r\n<\/span>Number of Rows : 3\r\n<\/span>Number of Columns : 4\r\n<\/span>Total Number of elements in<\/span> 2D Numpy array : <\/span>12\r\n<\/span>**** Get Dimensions of a 3D numpy array using np.size<\/span>()<\/span> ****\r\n<\/span>3D Numpy Array\r\n[[[11<\/span> 12<\/span> 13<\/span> 11<\/span>]\r\n<\/span>[21<\/span> 22<\/span> 23<\/span> 24<\/span>]\r\n<\/span>[31<\/span> 32<\/span> 33<\/span> 34<\/span>]]\r\n<\/span>[[ 1<\/span> 1<\/span> 1<\/span> 1<\/span>]\r\n<\/span>[ 2<\/span> 2<\/span> 2<\/span> 2<\/span>]\r\n<\/span>[ 3<\/span> 3<\/span> 3<\/span> 3<\/span>]]]\r\n<\/span>Axis 0<\/span> size : <\/span>2\r\n<\/span>Axis 1<\/span> size : <\/span>3\r\n<\/span>Axis 2<\/span> size : <\/span>4\r\n<\/span>Total Number of elements in<\/span> 3D Numpy array : <\/span>24\r\n<\/span>Dimension by axis : (<\/span>2<\/span>, <\/span>3<\/span>, <\/span>4<\/span>)\r\n<\/span>**** Get Dimensions of a 1D numpy array using numpy.size<\/span>()<\/span> ****\r\n<\/span>Original Array : [<\/span> 4<\/span> 5<\/span> 6<\/span> 7<\/span> 8<\/span> 9<\/span> 10<\/span> 11<\/span>]\r\n<\/span>Length of 1D numpy array : 8<\/span><\/pre>\n<\/div>\n
\n
I hope you understood this article well.<\/strong><\/em><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"
In this article, we will be discussing how to count several elements in 1D, 2D, and 3D Numpy array. Moreover, we will be discussing the counting of rows and columns in a 2D array and the number of elements per axis in a 3D Numpy array. Let’s get started! Get the Dimensions of a Numpy …<\/p>\n
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