删除 'Day3 20200404210何锐钦/作业代码.ipynb'

Day3 20200404210何锐钦/作业代码.ipynb

@@ -1,1083 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([37.2, 37.6, 36.8])"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import numpy as np\n",
-    "\n",
-    "X = np.array([[1.2, 1.5, 1.8],\n",
-    "               [1.3, 1.4, 1.9],\n",
-    "               [1.1, 1.6, 1.7]])\n",
-    "y = np.array([5, 10, 9]).T\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "X.dot(y)\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 5, 10,  9])"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "y"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(3, 3)"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X.shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "1.04 µs ± 64.3 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)\n"
-     ]
-    }
-   ],
-   "source": [
-    "%timeit X.dot(y)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "20.1 µs ± 589 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)\n"
-     ]
-    }
-   ],
-   "source": [
-    "%%timeit\n",
-    "total = []\n",
-    "for i in range(X.shape[0]):\n",
-    "    each_price = 0\n",
-    "    for j in range(X.shape[1]):\n",
-    "        each_price += X[i,j] * y[j]\n",
-    "#         each_price = each_price + X[i,j] * y[j]\n",
-    "    total.append(round(each_price, 1))\n",
-    "total   "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 第二题"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([6, 9, 6, 1, 1, 2, 8, 7, 3, 5, 6, 3, 5, 3, 5, 8, 8, 2, 8, 1, 7, 8,\n",
-       "       7, 2, 1, 2, 9, 9, 4, 9])"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.random.seed(1)\n",
-    "X = np.random.randint(1, 10, size=30)\n",
-    "X"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[6, 9, 6],\n",
-       "       [1, 1, 2],\n",
-       "       [8, 7, 3],\n",
-       "       [5, 6, 3],\n",
-       "       [5, 3, 5],\n",
-       "       [8, 8, 2],\n",
-       "       [8, 1, 7],\n",
-       "       [8, 7, 2],\n",
-       "       [1, 2, 9],\n",
-       "       [9, 4, 9]])"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X.reshape(-1,3)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[6, 9, 6],\n",
-       "       [1, 1, 2],\n",
-       "       [8, 7, 3],\n",
-       "       [5, 6, 3],\n",
-       "       [5, 3, 5],\n",
-       "       [8, 8, 2],\n",
-       "       [8, 1, 7],\n",
-       "       [8, 7, 2],\n",
-       "       [1, 2, 9],\n",
-       "       [9, 4, 9]])"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X1 = X.reshape(-1 ,3)\n",
-    "X1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([6, 2, 3, 3, 5, 2, 7, 2, 9, 9])"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "last1 = X1[:, 2]\n",
-    "last1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([False,  True,  True,  True, False,  True, False,  True, False,\n",
-       "       False])"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "last1 <= 3"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([2, 3, 3, 2, 2])"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# 返回符合条件的位置，位置以True False来表示\n",
-    "temp1 = last1[last1 <= 3]\n",
-    "temp1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(array([1, 2, 3, 5, 7]),)"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# 返回符合条件的位置, 索引值\n",
-    "np.where(last1 <= 3)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([6, 2, 3, 3, 5, 2, 7, 2, 9, 9])"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "last1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([6, 5])"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "temp2 =  last1[(last1 > 3) & (last1 <= 6)]\n",
-    "temp2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([7, 9, 9])"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "temp3 =  last1[last1 > 6]\n",
-    "temp3"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "last1[last1 <= 3] = 0"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([6, 0, 0, 0, 5, 0, 7, 0, 9, 9])"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "last1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "last1[(last1 > 3) & (last1 <= 6)] = 1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1, 0, 0, 0, 1, 0, 7, 0, 9, 9])"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "last1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "last1[last1 > 6] = 2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1, 0, 0, 0, 1, 0, 2, 0, 2, 2])"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "last1 "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "X_train = X1[:, 0:2]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[6, 9],\n",
-       "       [1, 1],\n",
-       "       [8, 7],\n",
-       "       [5, 6],\n",
-       "       [5, 3],\n",
-       "       [8, 8],\n",
-       "       [8, 1],\n",
-       "       [8, 7],\n",
-       "       [1, 2],\n",
-       "       [9, 4]])"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X_train"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "y_train = last1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1, 0, 0, 0, 1, 0, 2, 0, 2, 2])"
-      ]
-     },
-     "execution_count": 36,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "y_train"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1, 1],\n",
-       "       [8, 7],\n",
-       "       [5, 6],\n",
-       "       [8, 8],\n",
-       "       [8, 7]])"
-      ]
-     },
-     "execution_count": 37,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X_train[y_train == 0] # 分类为0"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([False,  True,  True,  True, False,  True, False,  True, False,\n",
-       "       False])"
-      ]
-     },
-     "execution_count": 38,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "y_train == 0"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[6, 9],\n",
-       "       [5, 3]])"
-      ]
-     },
-     "execution_count": 46,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X_train[y_train == 1] # 分类为1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[8, 1],\n",
-       "       [1, 2],\n",
-       "       [9, 4]])"
-      ]
-     },
-     "execution_count": 47,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X_train[y_train == 2] # 分类为2"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 面试题"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# 奇数替换成-1 不改变arr的值\n",
-    "arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0, -1,  2, -1,  4, -1,  6, -1,  8, -1])"
-      ]
-     },
-     "execution_count": 49,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.where(arr % 2 == 1, -1, arr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[[0 1 2 3 4]\n",
-      " [5 6 7 8 9]]\n",
-      "[[1 1 1 1 1]\n",
-      " [1 1 1 1 1]]\n"
-     ]
-    }
-   ],
-   "source": [
-    "# 垂直叠加两个数组\n",
-    "a = np.arange(10).reshape(2, -1)\n",
-    "print(a)\n",
-    "b = np.repeat(1, 10).reshape(2, -1)\n",
-    "print(b)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[0, 1, 2, 3, 4, 1, 1, 1, 1, 1],\n",
-       "       [5, 6, 7, 8, 9, 1, 1, 1, 1, 1]])"
-      ]
-     },
-     "execution_count": 54,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.concatenate([a, b], axis = 1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 53,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[0, 1, 2, 3, 4, 1, 1, 1, 1, 1],\n",
-       "       [5, 6, 7, 8, 9, 1, 1, 1, 1, 1]])"
-      ]
-     },
-     "execution_count": 53,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.hstack([a, b])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 55,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[0, 1, 2, 3, 4],\n",
-       "       [5, 6, 7, 8, 9],\n",
-       "       [1, 1, 1, 1, 1],\n",
-       "       [1, 1, 1, 1, 1]])"
-      ]
-     },
-     "execution_count": 55,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.vstack([a, b])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 56,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[0, 1, 2, 3, 4, 1, 1, 1, 1, 1],\n",
-       "       [5, 6, 7, 8, 9, 1, 1, 1, 1, 1]])"
-      ]
-     },
-     "execution_count": 56,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.c_[a, b]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([2, 4])"
-      ]
-     },
-     "execution_count": 57,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# 求两个集合的交互项\n",
-    "a = np.array([1,2,3,2,3,4,3,4,5,6])\n",
-    "b = np.array([7,2,10,2,7,4,9,4,9,8])\n",
-    "np.intersect1d(a, b)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 58,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1, 2, 3, 4])"
-      ]
-     },
-     "execution_count": 58,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# 从数组a中删除数组b中的所有项\n",
-    "a = np.array([1,2,3,4,5])\n",
-    "b = np.array([5,6,7,8,9])\n",
-    "\n",
-    "np.setdiff1d(a, b)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 59,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(array([1, 3, 5, 7]),)"
-      ]
-     },
-     "execution_count": 59,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# 获取a和b元素匹配的位置\n",
-    "a = np.array([1,2,3,2,3,4,3,4,5,6])\n",
-    "b = np.array([7,2,10,2,7,4,9,4,9,8])\n",
-    "\n",
-    "np.where(a == b)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 62,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(array([1, 3, 4]),)"
-      ]
-     },
-     "execution_count": 62,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# 如何从numpy数组中提取给定范围内的所有数字\n",
-    "# 获取5到10之间的所有项目\n",
-    "a = np.array([2, 6, 1, 9, 10, 3, 27])\n",
-    "indexs = np.where((a >= 5) & (a <= 10))\n",
-    "indexs"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 63,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 6,  9, 10])"
-      ]
-     },
-     "execution_count": 63,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a[indexs]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 64,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 6,  9, 10])"
-      ]
-     },
-     "execution_count": 64,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a[(a >= 5) & (a <= 10)]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 65,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[0, 1, 2],\n",
-       "       [3, 4, 5],\n",
-       "       [6, 7, 8]])"
-      ]
-     },
-     "execution_count": 65,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# 如何交换二维numpy数组中的两列？\n",
-    "# 在数组arr中交换列0和1\n",
-    "arr = np.arange(9).reshape(3, 3)\n",
-    "arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 66,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1, 0, 2],\n",
-       "       [4, 3, 5],\n",
-       "       [7, 6, 8]])"
-      ]
-     },
-     "execution_count": 66,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr[:, [1, 0, 2]]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 69,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[3, 4, 5],\n",
-       "       [0, 1, 2],\n",
-       "       [6, 7, 8]])"
-      ]
-     },
-     "execution_count": 69,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr[[1, 0, 2], :]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 70,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[0, 1, 2],\n",
-       "       [3, 4, 5],\n",
-       "       [6, 7, 8]])"
-      ]
-     },
-     "execution_count": 70,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr = np.arange(9).reshape(3, 3)\n",
-    "arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 71,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[6, 7, 8],\n",
-       "       [3, 4, 5],\n",
-       "       [0, 1, 2]])"
-      ]
-     },
-     "execution_count": 71,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# 反转行\n",
-    "arr[::-1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 72,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[2, 1, 0],\n",
-       "       [5, 4, 3],\n",
-       "       [8, 7, 6]])"
-      ]
-     },
-     "execution_count": 72,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# 反转列\n",
-    "arr[:, ::-1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 75,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[[[ 0,  1,  2],\n",
-       "         [ 3,  4,  5]],\n",
-       "\n",
-       "        [[ 6,  7,  8],\n",
-       "         [ 9, 10, 11]]],\n",
-       "\n",
-       "\n",
-       "       [[[12, 13, 14],\n",
-       "         [15, 16, 17]],\n",
-       "\n",
-       "        [[18, 19, 20],\n",
-       "         [21, 22, 23]]],\n",
-       "\n",
-       "\n",
-       "       [[[24, 25, 26],\n",
-       "         [27, 28, 29]],\n",
-       "\n",
-       "        [[30, 31, 32],\n",
-       "         [33, 34, 35]]]])"
-      ]
-     },
-     "execution_count": 75,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr = np.arange(36).reshape(3, 2, 2, 3)\n",
-    "arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}