06_Numpy_Array_Manipulation.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Numpy Array Manipulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## np.reshape(): Reshape an array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "[[1 2 3]\n",
      " [4 5 6]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Create a 1D array\n",
    "arr = np.array([1, 2, 3, 4, 5, 6])\n",
    "\n",
    "# Reshape the array to a 2x3 matrix\n",
    "reshaped_arr = np.reshape(arr, (2, 3))\n",
    "print(reshaped_arr)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## np.concatenate(): Concatenate arrays along a specified axis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2]\n",
      " [3 4]\n",
      " [5 6]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Create two arrays\n",
    "arr1 = np.array([[1, 2], [3, 4]])\n",
    "arr2 = np.array([[5, 6]])\n",
    "\n",
    "# Concatenate along the first axis (rows)\n",
    "concatenated_arr = np.concatenate((arr1, arr2), axis=0)\n",
    "print(concatenated_arr)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## np.split(): Split an array into multiple sub-arrays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[array([1, 2]), array([3, 4]), array([5, 6])]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Create an array\n",
    "arr = np.array([1, 2, 3, 4, 5, 6])\n",
    "\n",
    "# Split the array into three sub-arrays\n",
    "sub_arrays = np.split(arr, 3)\n",
    "print(sub_arrays)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## np.transpose(): Transpose an array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 3]\n",
      " [2 4]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Create a 2D array\n",
    "arr = np.array([[1, 2], [3, 4]])\n",
    "\n",
    "# Transpose the array\n",
    "transposed_arr = np.transpose(arr)\n",
    "print(transposed_arr)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## np.flatten(): Flatten a multi-dimensional array to a 1D array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3 4]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Create a 2D array\n",
    "arr = np.array([[1, 2], [3, 4]])\n",
    "\n",
    "# Flatten the array\n",
    "flattened_arr = arr.flatten()\n",
    "print(flattened_arr)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## np.vstack(): Stack arrays vertically"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2]\n",
      " [3 4]\n",
      " [5 6]\n",
      " [7 8]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Create two arrays\n",
    "arr1 = np.array([[1, 2], [3, 4]])\n",
    "arr2 = np.array([[5, 6], [7, 8]])\n",
    "\n",
    "# Vertically stack the arrays\n",
    "stacked_arr = np.vstack((arr1, arr2))\n",
    "print(stacked_arr)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## np.hstack(): Stack arrays horizontally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 5 6]\n",
      " [3 4 7 8]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Create two arrays\n",
    "arr1 = np.array([[1, 2], [3, 4]])\n",
    "arr2 = np.array([[5, 6], [7, 8]])\n",
    "\n",
    "# Horizontally stack the arrays\n",
    "stacked_arr = np.hstack((arr1, arr2))\n",
    "print(stacked_arr)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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