diff --git a/奥运奖牌榜——周艺颖.ipynb b/奥运奖牌榜——周艺颖.ipynb
new file mode 100644
index 0000000..e4101b4
--- /dev/null
+++ b/奥运奖牌榜——周艺颖.ipynb
@@ -0,0 +1,109 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "a6e78756",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[{'name': '美国', 'medal': '39'}, {'name': '中国', 'medal': '38'}, {'name': '日本', 'medal': '27'}, {'name': '英国', 'medal': '22'}, {'name': '俄罗斯奥委会', 'medal': '20'}, {'name': '澳大利亚', 'medal': '17'}, {'name': '荷兰', 'medal': '10'}, {'name': '法国', 'medal': '10'}, {'name': '德国', 'medal': '10'}, {'name': '意大利', 'medal': '10'}]\n",
+      "   Unnamed: 0    name  medal\n",
+      "0           0      美国     39\n",
+      "1           1      中国     38\n",
+      "2           2      日本     27\n",
+      "3           3      英国     22\n",
+      "4           4  俄罗斯奥委会     20\n",
+      "5           5    澳大利亚     17\n",
+      "6           6      荷兰     10\n",
+      "7           7      法国     10\n",
+      "8           8      德国     10\n",
+      "9           9     意大利     10\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import requests\n",
+    "from bs4 import BeautifulSoup\n",
+    "import pandas as pd\n",
+    "data = []\n",
+    "countries = []\n",
+    "gold_medals = []\n",
+    "r = requests.get(\"https://tiyu.baidu.com/tokyoly/home/tab/奖牌榜/from/pc\")\n",
+    "soup = BeautifulSoup(r.content,'html.parser')\n",
+    "Every_country_name =soup.find('div',class_='rank-list').find_all('div',class_='rcountry')\n",
+    "\n",
+    "for i in Every_country_name:\n",
+    "  country = i.find('span',class_='name')\n",
+    "  countries.append(country.string)\n",
+    "Every_gold_medal = soup.find('div',class_='rank-list').find_all('div',class_='integral')\n",
+    "for j in Every_gold_medal:\n",
+    " gold_medal = j.find('div',class_='item-gold')\n",
+    " gold_medals.append(gold_medal.string.replace('\\n','').rstrip())\n",
+    "for m in range(10):\n",
+    " data.append({'name':countries[m],\n",
+    "  'medal':gold_medals[m]})\n",
+    "print(data)\n",
+    "table = pd.DataFrame(data)\n",
+    "table.to_excel(\"奥运会金牌数.xlsx\")\n",
+    "\n",
+    "Olympic_game = pd.read_excel(\"奥运会金牌数.xlsx\")\n",
+    "print(Olympic_game)\n",
+    "plt.bar(Olympic_game.name,Olympic_game.medal,color='orange') \n",
+    "plt.rcParams['font.sans-serif']=['SimHei']\n",
+    "plt.xticks(rotation=90)       \n",
+    "plt.xlabel(\"国家\")                   # 给x轴命名\n",
+    "plt.ylabel(\"奖牌数\")         # 给y轴命名\n",
+    "plt.title(\"东京奥运会奖牌榜\")       # 给该柱状图命名\n",
+    "plt.tight_layout()                           # 设置为紧凑型布局，不然x轴head显示不全\n",
+    "plt.show()    # 出图"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b5291721",
+   "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": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}