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snowykte0426snowykte0426
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2025-03-26
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‎Pandas_Data.ipynb‎

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"id": "9de38cbf3c631c24",
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'pd' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001B[31m---------------------------------------------------------------------------\u001B[39m",
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"\u001B[31mNameError\u001B[39m Traceback (most recent call last)",
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"\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[1]\u001B[39m\u001B[32m, line 1\u001B[39m\n\u001B[32m----> \u001B[39m\u001B[32m1\u001B[39m df5 = \u001B[43mpd\u001B[49m.read_excel(\u001B[33m'\u001B[39m\u001B[33m./sheet.xlsx\u001B[39m\u001B[33m'\u001B[39m)\n\u001B[32m 2\u001B[39m df6 = pd.read_excel(\u001B[33m'\u001B[39m\u001B[33m./sheet.xlsx\u001B[39m\u001B[33m'\u001B[39m, header=\u001B[32m0\u001B[39m)\n\u001B[32m 4\u001B[39m \u001B[38;5;28mprint\u001B[39m(df5)\n",
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"\u001B[31mNameError\u001B[39m: name 'pd' is not defined"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" 통계표명: 아황산가스(SO2) Unnamed: 2 Unnamed: 3 Unnamed: 4 Unnamed: 5 \\\n",
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"0 단위: ppm NaN NaN NaN NaN \n",
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"1 NaN 2014 2015 2016.000 2017.000 2018.000 \n",
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"2 서울 0.006 0.005 0.005 0.005 0.004 \n",
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"3 부산 0.007 0.006 0.005 0.005 0.005 \n",
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"4 대구 0.004 0.003 0.003 0.003 0.003 \n",
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"5 인천 0.007 0.006 0.006 0.006 0.005 \n",
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"6 광주 0.004 0.003 0.003 0.003 0.003 \n",
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"7 대전 0.004 0.004 0.003 0.003 0.002 \n",
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"8 울산 0.008 0.007 0.007 0.006 0.006 \n",
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"9 세종 - - 0.004 0.003 0.003 \n",
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"10 출처: 환경부「대기환경연보」 NaN NaN NaN NaN \n",
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"\n",
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" Unnamed: 6 Unnamed: 7 Unnamed: 8 Unnamed: 9 Unnamed: 10 \n",
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"0 NaN NaN NaN NaN NaN \n",
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"1 2019.000 2020.000 2021.000 2022.000 2023.000 \n",
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"2 0.004 0.003 0.003 0.003 0.003 \n",
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"3 0.005 0.004 0.003 0.003 0.003 \n",
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"4 0.003 0.002 0.002 0.002 0.002 \n",
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"5 0.005 0.004 0.003 0.003 0.003 \n",
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"6 0.003 0.003 0.003 0.003 0.003 \n",
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"7 0.002 0.002 0.003 0.003 0.003 \n",
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"8 0.005 0.004 0.003 0.003 0.003 \n",
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"9 0.003 0.003 0.003 0.003 0.003 \n",
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"10 NaN NaN NaN NaN NaN \n",
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"\n",
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"\n",
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" 통계표명: 아황산가스(SO2) Unnamed: 2 Unnamed: 3 Unnamed: 4 Unnamed: 5 \\\n",
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"0 단위: ppm NaN NaN NaN NaN \n",
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"1 NaN 2014 2015 2016.000 2017.000 2018.000 \n",
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"2 서울 0.006 0.005 0.005 0.005 0.004 \n",
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"3 부산 0.007 0.006 0.005 0.005 0.005 \n",
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"4 대구 0.004 0.003 0.003 0.003 0.003 \n",
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"5 인천 0.007 0.006 0.006 0.006 0.005 \n",
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"6 광주 0.004 0.003 0.003 0.003 0.003 \n",
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"7 대전 0.004 0.004 0.003 0.003 0.002 \n",
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"8 울산 0.008 0.007 0.007 0.006 0.006 \n",
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"9 세종 - - 0.004 0.003 0.003 \n",
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"10 출처: 환경부「대기환경연보」 NaN NaN NaN NaN \n",
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"\n",
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" Unnamed: 6 Unnamed: 7 Unnamed: 8 Unnamed: 9 Unnamed: 10 \n",
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"0 NaN NaN NaN NaN NaN \n",
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"1 2019.000 2020.000 2021.000 2022.000 2023.000 \n",
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"2 0.004 0.003 0.003 0.003 0.003 \n",
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"3 0.005 0.004 0.003 0.003 0.003 \n",
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"4 0.003 0.002 0.002 0.002 0.002 \n",
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"5 0.005 0.004 0.003 0.003 0.003 \n",
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"6 0.003 0.003 0.003 0.003 0.003 \n",
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"7 0.002 0.002 0.003 0.003 0.003 \n",
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"8 0.005 0.004 0.003 0.003 0.003 \n",
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"9 0.003 0.003 0.003 0.003 0.003 \n",
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"10 NaN NaN NaN NaN NaN \n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"C:\\Users\\snowy\\PyCharmMiscProject\\.venv\\Lib\\site-packages\\openpyxl\\styles\\stylesheet.py:237: UserWarning: Workbook contains no default style, apply openpyxl's default\n",
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" warn(\"Workbook contains no default style, apply openpyxl's default\")\n",
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"C:\\Users\\snowy\\PyCharmMiscProject\\.venv\\Lib\\site-packages\\openpyxl\\styles\\stylesheet.py:237: UserWarning: Workbook contains no default style, apply openpyxl's default\n",
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" warn(\"Workbook contains no default style, apply openpyxl's default\")\n"
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]
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}
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],
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"execution_count": 9
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-03-26T02:05:57.098408Z",
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"start_time": "2025-03-26T02:05:57.086783Z"
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}
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},
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"cell_type": "code",
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"source": [
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"df7 = pd.read_json('./test.json')\n",
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"df8 = pd.read_json('./test.json', typ='series')\n",
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"\n",
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"print(df7)\n",
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"print('\\n')\n",
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"print(df8)"
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],
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"id": "cc151111c8d7b709",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" users\n",
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"0 {'userId': 1, 'firstName': 'AAAAA', 'lastName'...\n",
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"1 {'userId': 2, 'firstName': 'BBBB', 'lastName':...\n",
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"2 {'userId': 3, 'firstName': 'CCCCC', 'lastName'...\n",
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"3 {'userId': 4, 'firstName': 'DDDDD', 'lastName'...\n",
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"4 {'userId': 5, 'firstName': 'EEEEE', 'lastName'...\n",
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"\n",
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"\n",
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"users [{'userId': 1, 'firstName': 'AAAAA', 'lastName...\n",
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"dtype: object\n"
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]
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}
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],
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"execution_count": 1
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"execution_count": 10
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}
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],
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"metadata": {

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