{"id":27543,"date":"2022-08-30T21:05:09","date_gmt":"2022-08-30T15:35:09","guid":{"rendered":"https:\/\/python-programs.com\/?p=27543"},"modified":"2022-08-30T21:05:09","modified_gmt":"2022-08-30T15:35:09","slug":"python-numpy-matrix-itemset","status":"publish","type":"post","link":"https:\/\/python-programs.com\/python-numpy-matrix-itemset\/","title":{"rendered":"Python Numpy matrix.itemset() Function"},"content":{"rendered":"
NumPy Library\u00a0<\/strong><\/p>\n NumPy is a library in python that is created to work efficiently with arrays in python. It is fast, easy to learn, and provides efficient storage. It also provides a better way of handling data for the process. We can create an n-dimensional array in NumPy. To use NumPy simply have to import it into our program and then we can easily use the functionality of NumPy in our program.<\/p>\n NumPy is a Python library that is frequently used for scientific and statistical analysis. NumPy arrays are grids of the same datatype\u2019s values.<\/p>\n Numpy matrix.itemset() Function:<\/strong><\/p>\n We can set the items in a given matrix using the matrix.itemset() method of the Numpy module by passing the index number and the item as arguments.<\/p>\n Syntax:<\/strong><\/p>\n Return Value:<\/strong><\/p>\n A new matrix containing item is returned by the itemset() function.<\/p>\n For 2-Dimensional (2D) Matrix\u00a0<\/strong><\/p>\n Approach:<\/strong><\/p>\n Below is the implementation:<\/strong><\/p>\n Output:<\/strong><\/p>\n For 3-Dimensional (3D) Matrix\u00a0<\/strong><\/p>\n Approach:<\/strong><\/p>\n Below is the implementation:<\/strong><\/p>\n Output:<\/strong><\/p>\n NumPy Library\u00a0 NumPy is a library in python that is created to work efficiently with arrays in python. It is fast, easy to learn, and provides efficient storage. It also provides a better way of handling data for the process. We can create an n-dimensional array in NumPy. To use NumPy simply have to import …<\/p>\n matrix.itemset(index, item)<\/pre>\n
Numpy matrix.itemset() Function in Python<\/h2>\n
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# Import numpy module using the import keyword\r\nimport numpy as np\r\n \r\n# Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing \r\n# some random 2D matrix as arguments to it and store it in a variable\r\ngvn_matrx = np.matrix('[2, 1; 6, 3]')\r\n \r\n# Pass the index(row, column) and item\/value as an argument to the itemset() function and \r\n# apply it to the given matrix.\r\n# Here it inserts the given item at the specified index in a matrix(inserts 50 at 0th row, 1st col).\r\n# Store it in another variable\r\ngvn_matrx.itemset((0, 1), 50)\r\n# Print the given matrix after inserting an item at the specified index\r\nprint(\"The given matrix after inserting an item {50} at the specified index(0th row, 1st col):\")\r\nprint(gvn_matrx)<\/pre>\n
The given matrix after inserting an item {50} at the specified index(0th row, 1st col):\r\n[[ 2 50]\r\n [ 6 3]]<\/pre>\n
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# Import numpy module using the import keyword\r\nimport numpy as np\r\n \r\n# Create a matrix(3-Dimensional) using the matrix() function of numpy module by passing \r\n# some random 3D matrix as an argument to it and store it in a variable\r\ngvn_matrx = np.matrix('[2, 4, 1; 8, 7, 3; 10, 9, 5]')\r\n \r\n# Pass the index(row, column) and item\/value as an argument to the itemset() function and \r\n# apply it to the given matrix.\r\n# Here it inserts the given item at the specified index in a matrix(inserts 100 at 1st row, 2nd col).\r\n# Store it in another variable\r\ngvn_matrx.itemset((1, 2), 100)\r\n# Print the given matrix after inserting an item at the specified index\r\nprint(\"The given matrix after inserting an item {100} at the specified index(1st row, 2nd col):\")\r\nprint(gvn_matrx)<\/pre>\n
The given matrix after inserting an item {100} at the specified index(1st row, 2nd col):\r\n[[ 2 4 1]\r\n [ 8 7 100]\r\n [ 10 9 5]]<\/pre>\n","protected":false},"excerpt":{"rendered":"