332 lines
7.4 KiB
Plaintext
332 lines
7.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 25,
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"id": "d99d999d",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"id": "955684bc",
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.read_excel(\"./学生信息.xls\", usecols=['学号', '姓名', '性别', '年级','班级'])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"id": "7a49db1c",
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"metadata": {},
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"outputs": [],
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"source": [
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"class_count = df.groupby(['年级', '班级']).size().reset_index(name='人数')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"id": "3e00f787",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>年级</th>\n",
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" <th>班级</th>\n",
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" <th>人数</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>26学部</td>\n",
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" <td>1班</td>\n",
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" <td>42</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>26学部</td>\n",
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" <td>2班</td>\n",
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" <td>41</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>26学部</td>\n",
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" <td>3班</td>\n",
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" <td>38</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>26学部</td>\n",
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" <td>4班</td>\n",
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" <td>40</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>26学部</td>\n",
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" <td>5班</td>\n",
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" <td>39</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>5</th>\n",
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" <td>27学部</td>\n",
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" <td>1班</td>\n",
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" <td>48</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6</th>\n",
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" <td>27学部</td>\n",
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" <td>2班</td>\n",
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" <td>47</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>7</th>\n",
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" <td>27学部</td>\n",
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" <td>3班</td>\n",
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" <td>46</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>8</th>\n",
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" <td>27学部</td>\n",
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" <td>4班</td>\n",
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" <td>48</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>9</th>\n",
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" <td>27学部</td>\n",
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" <td>5班</td>\n",
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" <td>48</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>10</th>\n",
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" <td>28学部</td>\n",
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" <td>1班</td>\n",
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" <td>49</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>11</th>\n",
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" <td>28学部</td>\n",
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" <td>2班</td>\n",
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" <td>49</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>12</th>\n",
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" <td>28学部</td>\n",
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" <td>3班</td>\n",
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" <td>49</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>13</th>\n",
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" <td>28学部</td>\n",
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" <td>4班</td>\n",
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" <td>49</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" 年级 班级 人数\n",
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"0 26学部 1班 42\n",
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"1 26学部 2班 41\n",
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"2 26学部 3班 38\n",
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"3 26学部 4班 40\n",
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"4 26学部 5班 39\n",
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"5 27学部 1班 48\n",
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"6 27学部 2班 47\n",
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"7 27学部 3班 46\n",
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"8 27学部 4班 48\n",
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"9 27学部 5班 48\n",
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"10 28学部 1班 49\n",
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"11 28学部 2班 49\n",
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"12 28学部 3班 49\n",
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"13 28学部 4班 49"
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]
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},
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"execution_count": 29,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"class_count"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "bc5324c0",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "6a622610",
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.read_excel(\"./学生信息.xls\", usecols=['学号', '姓名', '性别', '年级'])\n",
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"row_strings = set()\n",
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"for _, row in df.iterrows():\n",
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" row_str = f\"{row['学号']}{row['姓名']}{row['性别']}{row['年级']}\"\n",
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" row_strings.add(row_str)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "c2b0ab79",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(633, 4)"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"df.shape"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "e5f90213",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"633"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"len(row_strings)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"id": "0ec9fe0a",
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"metadata": {},
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"outputs": [],
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"source": [
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"df1 = pd.read_excel(\"./学生信息2.xls\", usecols=['学号', '姓名', '性别', '年级'])\n",
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"row_strings1 = set()\n",
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"for _, row in df.iterrows():\n",
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" row_str = f\"{row['学号']}{row['姓名']}{row['性别']}{row['年级']}\"\n",
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" row_strings1.add(row_str)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"id": "75d2483a",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'260434于铭达男26学部'"
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]
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},
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"execution_count": 22,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"row_strings1.pop()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"id": "e5180f79",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'260434于铭达男26学部'}"
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]
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},
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"execution_count": 24,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"row_strings - row_strings1 "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e87426b4",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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