01-pandas-Series.ipynb

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     "ename": "NameError",
     "evalue": "name 'obj2' is not defined",
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     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[0;32mIn [7]\u001b[0m, in \u001b[0;36m<cell line: 13>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[38;5;66;03m# 直接运算 筛选\u001b[39;00m\n\u001b[1;32m     12\u001b[0m obj \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m2\u001b[39m\n\u001b[0;32m---> 13\u001b[0m np\u001b[38;5;241m.\u001b[39mexp(\u001b[43mobj2\u001b[49m)\n\u001b[1;32m     14\u001b[0m obj2 \u001b[38;5;241m=\u001b[39m obj[obj \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m     17\u001b[0m \u001b[38;5;28mprint\u001b[39m(obj)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'obj2' is not defined"
     ]
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from pandas import Series, DataFrame\n",
    "\n",
    "# 创建 Series 解构并赋值索引，索引默认从 0 开始\n",
    "obj = pd.Series([1,2,3,4], index = ['a', 'b', 'c', 'd'])\n",
    "\n",
    "# 通过索引访问\n",
    "obj.a\n",
    "\n",
    "# 直接运算 筛选\n",
    "obj * 2\n",
    "np.exp(obj2)\n",
    "obj2 = obj[obj > 1]\n",
    "\n",
    "\n",
    "print(obj)\n",
    "print(obj2)\n",
    "\n",
    "\n",
    "'b' in obj2\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "db34d26d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ohio      35000\n",
      "Texas     71000\n",
      "Oregon    16000\n",
      "Utah       5000\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 通过字典创建 Series\n",
    "\n",
    "sdata = {'Ohio': 35000, 'Texas': 71000, 'Oregon': 16000, 'Utah': 5000}\n",
    "obj3 = pd.Series(sdata)\n",
    "\n",
    "print(obj3)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "92628fce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ohio           NaN\n",
       "Oregon     32000.0\n",
       "Texas     142000.0\n",
       "Utah           NaN\n",
       "asd            NaN\n",
       "nn             NaN\n",
       "dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Series 自动对齐数据\n",
    "\n",
    "obj4 = Series({'nn': 'NaN', 'Texas': 71000, 'Oregon': 16000, 'asd': False})\n",
    "\n",
    "obj3 + obj4 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8772483c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a      NaN\n",
       "b    71000\n",
       "c    16000\n",
       "e    False\n",
       "dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 赋值更改索引\n",
    "\n",
    "obj4.index = ['a', 'b', 'c', 'e']\n",
    "\n",
    "obj4\n"
   ]
  },
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