Created
June 5, 2018 12:37
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Save eiel/4fb26abcfd38da6fa728e6cb544ca4ae to your computer and use it in GitHub Desktop.
統計モデリング勉強会 環境構築 docker run --rm -p 8888:8888 -v "$HOME":/home/jovyan/work jupyter/datascience-notebook
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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H51++ZvCu3gOtLbyQNBAqpudtD5l9AV\n/0nxidNMvwidfbq7ik+OIAFFSXsT0jnuwg8rDtBb5dtud8hRoXORsDgLHEECSvbXJYT4xzLI\nkFW6p/gquFuv4CGspxAkoGOX1+sHn1xZFtxZ8b0MovYdhbYXk+vOESSgIqNCP2sb772aUQWH\nvYc95rgnsSYmtztHkICKP/TivfP6dGRVQlyof+OmAYE/MJkcQQIqvikiduZVYVbD43WTYlez\n+IDEIUhAyZpAsTOrFtM6LH6d+vY0Ra4ozApBAirOZy522pLhZaq8xOam+q/XN7ZMUnZaBAno\naPfCPb750nCYbR3NqvIrjZ+p3FLZaREkoONGeImJaxa9YlzItoxtHsLh2ASTsu/uECSg5OGU\nhkHle+xjXMX7TcVO43GKzosggar0fV3sdFf2Ns0IEjjtxrRXm7yzgdUZDf82tonYaThB0XkR\nJHBWXEDFgRNf9Wr7mHUhvF3GU9Y23qjsCQ4IEjjpst9w/saTCaUY7/cWtSt/zPJ4tFwHZadF\nkMBJo2oKb+ri9MqsB2nD/U766i9X07+i8F8QggROqi/euzzDfx3bQjId+GzoZ4rfChNBAidV\nnSd2Sn7JtA62ECRwUut3hfaBxza2hfzb6SndXp8h122gs0OQwEmLA4U7Ic8oxPSWec/52BjR\n/+0qXkuVmg9BAiel1ql6gOMezzR+zbqSLFabvuebz43bFZoQQQJn3XlVF1DeGLSCdR1ZVRkt\ntH2aSm9HDYIEzruwdslOlzgcm+m2eO9N7n/GdGVmRJBAhRLIZaFzmCi0yB2CBE54snvxylOs\ni8jBfcMuobPWV6FTABEkyLv1hY3lg0mLK6zryO6l7tbG3LybQhMiSJBnPxk/sPye4uuXd73f\n1n6vofc57k7v/KcVmhBBgrwylxlpbR+UmsK4khxsK+ZZo4qp3B9KzYcgQV4dJVeFzuTabAvJ\nUUrcnHm/pik3HYIEefSzj9j5LpRpHS4BQYK82q0Xjx0tKM+2EFeAIEFePfIVbxgbFc22EAkJ\n/WoUrDPypvwTIUiQZ+OC+TXszFM841lXkpstvo0/XfdR1ZDjss+EIEGepb1haj9+cNV8LnJB\nX3a3A0bzx2NTu1SU/a5NCBI4IW5I1CuTLrOuIldzSgm77e54/Sz3VAgSqNcbmR/eGkyWeyoE\nCdSry0Cx02y83FMhSJAn6Wd2usSiQZLGNhDa9BDZl5NAkCAP0mcEEB2pHMe6DhuOGTZZ20/z\n/yP3VAgS5EF0wOIraX8NNm5gXYgNY30+Pp96cpRxmewzIUjguO3G/db2gxCXui42O/OiwoSQ\n8grcVhZBAse9Ld5w+ZHPT2wLscOF3deVmAZBAsdFxoqd6p+yLMOVIEjguFajxE75RUzrcCEI\nEjhunLhu/nndAcaV2Cnj6Hfrz8k6A4IEjrvgPYNvHr3UwDXuLmbLnookpABpflHGKRAkyINV\nni0+WzmpdJhya2s744D321c57liTUjIeTUKQIC9ORFcPbhir0JpxzmrQw9o8Dh8u3xwIEqjd\ndd0hobOgtHyTIEigdvvJQ6Gz1SjfRzoECdQuPnO1ozUF5JsEQQIHXdi8Q/ZTQKlKL7RQ6LzZ\nRr5JECRwyOE6xNuk73aLdR2OmBFgPdy13LBDvjkQJHDEUb9u8RkpOyPC77OuxAEZfUydpo5t\nYlwg4xwIEjgisrP18/rdsA9YV+KQ//Vr2GzYCTlnQJDAAdd1B4XO7IpsC3E5CBI4YB8RL0Da\n4sm2EJeDIIEDjpHbQmdNANtCXA6CBA5IKSCuIhLdim0heZSRKNfICBI4YnzoSb5ZZ/wf60ry\nYFNDHxLUPUGWsREkcERqJ9/oBTNfNsxgXUgefGwcuOXoypf89ssxOIIEDjGv7Fqldp99rMvI\ng+OG7/nG3LO8HLcfQ5BAI4Y1Eto7pm0yjI4ggUa0fF/sVPtMhtERJNCIFmPEjixLHyFIoBHv\nRQptooccKy0jSGCn1FUjuo2Nc4/VTnJy1LCWb8x9yspx1zEECezzdzW/dgOiPFq502nf/zbd\n+N62k+tb+e6VY3AECeySWjmKv5wvoUJn1pXk3YYXPYh/p5OyjI0ggV2+ChDOrjmmO8y4Emek\nybYOOIIEdundQ+xU+YRpHa4KQQK7dBwqdqJkv4ukW0KQwC7vdBI7ZeczrcNVIUhgl43ewvLE\nWw1nGVdCwT8p1IdEkMAu5pcqHbU0Wwq9y7oSZ93qF0qMVRZRPiCGIIF97nbWlY0sZoiR49Rp\nJV0sXmPF0V2T/d6imyQECex17D+xX51nXYTT2jZ6wjd/eq+kOiyLIKXs327j94EggUyu6sRr\nqQa2oDquokGavJ1/XBRACKkleVgPQQKZbDVlCJ2vi1IdV9EgkdGWh5+IZ6f+DYi/1M4fBAlk\nop4glfOPtzyu1fWW2BBBAplc04tv7Qa0pDqu4kG6RcZa+x2l/oOAILmW02t+cP+9DKJ2DZP5\n5pDXKqrDKh6kS+Qra3+8SWJDBMmVHKlFCvqTSHnvCq6YSyWqf3l4x4f5ernx7m8+SOn+0639\n6IISGyJILuSkf1dLhk40L3qNdSV03H6nCDFVW+LOB2RJjwMJt8eUfWTpnvRtL7EhguRC2rW2\nfjxPqdWPdSXUJLn5KUJEsIbjvvHVSy3ThyC5jgeZq1d9Fci2ENemaJCWzYmN6dkx0vKLWVB0\no9SGCJLrOJ15B9YD+KVIYHSK0IMMyW8jSK7jKhGvzd5qSGdbiUvDuXZgQ6mPhPbd+mzrcG0I\nEtiwwO83vvnBtJ51JXQd/u+M9fRuz84qSGejop77l3NeJAv3XfRJdcyDjZ2mTWplmMK6EKqu\nRenL1C3gS23RVVZBOkyeH8W8I+6pGLwiuZLtfes1HijLzVCYSa5S9wzHpS/1onWnc1ZBSj5+\nXOK7eGsH8poXkmRtF/o/ojMgPiOBFrUUF0VK9t5MZ0Clg2Q+F7du3bZLNrZCkEBeT2/tEvYF\nnQGVDVLi8GBhX0KJSY+ltkOQQF5NJghtRn5K+yIVDdK1MFKuV+zMmeN7FCHVpe4vjSCBvGIr\nCYu4/GS8RWdARYPUx5R5DUj6Al2MxIYIkou4uOrj1ZdZFyGHW4G9+TVQjhSW+jN0hKJBCo1+\n1u9WXGJDBMklPBlgCHoh0Bgjx/2EWPujaJHuMVGG12j9f1M0SKapz/oTPSQ2RJBcwhtFt1oe\nN4f0ZV2IHO4v7t9pzE5qwykapJJdn/U7lJLYEEFyBX8YDlnbvfqjjCtxA4oGKUY364nQe/iB\ndSGU3CBIrmB8A7FTa6rkdsApHKSkCOIX1WvwoJ6RPqSRVFQQJFcQ/abY6TKQaR1uQdnjSCmf\n1DDwh5FMdZdIXtuCILmCYW3ETtOxTOtwC4qfIpR85tChBFuXzCNIruAHnxvW9rLnL4wrcQM4\n1w5ykx7RhL9e52a9epRX3HElGWc37rtHYRwECXJ1ubp/l+Gv+NVSyTpcOdlagfjqPQY9dHog\nBAlyl/LNwLaDvnP3OyJJ2GIacp57tDEsyunlKBAk0K70sGHW9mL+L50dCkEC7frdcFvoDGoj\nvaFtCBJo17eFxc7CSs4OhSCBdm3IL+6PnFnL2aEQJNCuq/pdQidygLNDIUiQszQV76x7qke4\n9Zjzp6Z4Z0dCkCAHaXNqeHpUm6nGC5H+5W7dwCGLp0V6fu30SAgSZJfSMmhK3LbpIZHJrCuR\nW+qiDhXqDXL69QhBgpxMC/mbb64UncC4EPeBIEF2peYI7aJQ6buGwFMIEmRzjwiXxnLx5Abb\nStwHggTZJJEjQufpTcbAFgQJsiu8WGhXFMS9xeyEIEF2Y0pZz0FLKk9r1Tf1Q5Aguwe1w76I\nP7W8XLW7rCtRyMNlQ3vOkLo/ik0IEuTg4chgQoKGauV2b3uLBHfsGaEb4cSVwAgS5OzmddYV\nKOZKgb78kee4/B/lfQwECTTvvVrC4bL/5s/7mRwIEmhetY+F9mHmyeB5gCCB5hX7SuwUyPvN\nkhAk0Lxa04Q2Sfd7nsdAkEDzJlQQlqSfFZz3a7AQJHhOSoLqL554zp2i7W5yXMZSDyfuJ4sg\nwb/sbmgihoiNrMtQ1qnqHhEvBXvPdWIIBAmyWmPsvePKnqHGeawLUVbG9tkffHfTmREQJMgi\nqeAUa7vM8zzjStwNggRZfJn5cbsq7i3mGAQJsni/pdjp86bkdvA8BAmyGNdM7PTsybIMN4Qg\nQRYr/R9Z24wysxlX4m4QJMjiUdHB1ksJpvtp59xvOhAkyGqHb7MVe77vbFrNuhAmzv931Oyd\nebsoCUGCfzn9WnES2vEg6zJYyBhlCGsTYap/OS9PRpDgeU9YF8DIhAI/Wx4vNayclx8AggRg\nddtzjbVNCl6Uh2cjSABWKwuKy8oO6JiHZyNIAFZzq4qdafXy8GwECcDq22Bxf92Q9nl4NoIE\nYHXNuNnaPir6aR6ejSABCGJC91keE9uGPczDkxEkEP3Wu1bVbmtZV8FQarSu9lvN84efzsuT\nESQQfGjoNGt+T+/uWl42/9BH0WPW5u1+nwgSWP1g+olvjgdNYV2Je0KQwKrJQKH9vJCWX5Ly\nDkECK6+fhfYSOcO2EDeFIAEvXb9T6CRm3q0PHIIggVWphUK725DIthA3hSCB1agK1h95RptW\nrCtxTwgSWCWWe2FPasaJTgXiWVfiApIdf1VGkEBwvZPO5E3qOXX/R1XImFvJQIoMdjBLCBJk\nur19yyXWNbCX8WqB6b8dXla5jGOrViBIAFl94fcX3zyq082hpyFIAFnVHym024wOvblDkACy\nyrxr32Pi0F3HECSArJ4FaZ8jT0OQALJqIL6122rCWzuAPFvmd4JvHtbq7tDTECTguGs7z2aw\nrsFVZHT1n7rrz6WVyt5w6GkIEmyqSHQkcDaiJMiYX9lIig1JcuxZCJLmfW9472T6pQX+g1gX\n4jpS7jr+FARJ4+4HTrO2u/WO/yXAUwiS1q32TxE6rQazLcS9IUhaN+NFsTO6NdM63ByCpHVz\nqoudd/Oy5DWIECSt2224Ym0zwiczrsStIUhal1GrdTLfTsx3lXUp7gxB0ryzJcpPXjmnqfcP\nrAtxMU8Orfztnt1bI0iQOL5BcM2+p1iX4WL+W4iEGLzH2LvuKoIEkIO5nh8nccmrgt+0c3sE\nCSC7277/tbZ/GnfY9wQECSC75SHiqYdt7DxMjSABZDepkdgZ3s6+JyBIANnNriF2+tq5BgqC\nBJDdXsPf1jalhJ33wUSQALIzN2jEX0qR1j/YzuuSECRNO7/uq4NprItwSVfCQ4fMHR0eZG88\nECQNu9qaFChOwuJY1+GSHs/tXKVVrN3XmyNI2nWvfP2jHHd7qIedh0pAAoKkXbGlhZ/yO1UZ\nF6IGCJJ2Vf1IaM+QBLaFqAGCpF2Za4qaDdvYFqIGCJJ2Ff9SaO+S/WwLUQMESbu6dxDa5X5P\n2BaiBgiSdh00zuObI4U+YF2JCiBIGrbc68VRkzp7vI5DshLOrPn+mNn2ZgiSliW837pR/82s\nq3BlZxuTgiGkiu0PkQgSQK6uF21xkuMuv5nvmK0tESSAXA2IsC5Da+7Y3NaWCBJArkLEIwS7\nDbaW1UeQAHLzhOwVOrfICRubIkgAuTF7iHtizpCLNjZFkAByFdlfaGcVt7UHHEECyNUm40q+\n2e0339aWCJI2pR1bs9PBmztq0mzjS+MmtTcMsXlIFkHSpLXFSZDRY9Aj1nW4viPvNWsywI4r\nHxEkLfreOOEWl/JTyVZ2nPsCdkGQNCg5eKq1Pee7knEl6oEgadAWr4dCp3cXtoWoCIKkQYsr\niJ2ZdZjWoSYIkgZ9XVjsjI9kWoeaIEgadJYctLbmmmMYV6IeCJIWdap20/JoHu97iXUlqoEg\naVHiCwXfmTeudr6fWBfiNszn4hLSpTZwPkh/x3236Lu4vx0eRQqCJLPUJV2qNht1gXUZbmNF\nMWIiIZ9LHHZzMkjnhpQlgrLvns9DgblAkMCVzPGYfIG78omPxCoxTgXpVrSRBHcbP3fF3PHd\nChFj9K08VZkDBAlcyBWv5db2R8PJXLdxJki/BhteP5T5amc+9LohmNZq7AgSuJB5pcW/8ohJ\nuW7jTJBMjc/+698TGpscHitnCBK4kPdeFju9eua6jTNBmvD8boz0CQ6PlTMECVzImMylT7r2\nz3UbZ/fa7c7sZHzi8Di5Q5DAhazLJyx9khzy31y3cTZI+vceW9szDWgeXUKQwIWklO2eamnS\n+xe+n/s2TgapNanwu+Xl6FNvz9w/hzkOQZLRtRMprEtwN0dDKk/+ZnpEgERWnD4gu6a4fuTx\nRqTpGfueaz4Xt27dNltnpiBIckmbHkKIsfUp1nW4mZvvNyxSd9gViS2cP7Ph4QgjCVxm3zMT\nhwcLh29LTHostR2CJBPzq4ELTt/c1ib/YdaVqI3zQXoS60lCvrfridfCSLlesTNnju9RhFRP\nlNgQQZLJSu+/+MbcpTbrStTG6SDFldMNPFSPtLW1gB6vj2mV2EtfoIuR2BBBkklbcf/tWfIX\n20JUx9kg9SCltnNcxiwv3zm2nxga/azfrbjEhgiSTMr9R+wErGNah/o4GyTdO8Kf/Kl6duz+\nNk191p/oIbEhgiSTSguF1pxvI9tCVMfZIG3N7GR8bPuJJbs+63coJbEhgiSTHq8K7R86XNJH\nlzNBOpjtO9n/5V9idLPE2/4+/ICMltgQQZLJLr31lejBi+1ZV6I2zgTJY+5z35gr9XbNIimC\n+EX1GjyoZ6QPaSQVldyD9AAJc8okY5/vtswqU/4660LcVK5/f84EaTCptynLP2+qRwbZeGbK\nJzUM/GEkU90lktft5hKk5NjSOl3p2GQHaoXn/NK6sGfNsbmf6gK5k/r7c+oz0reBpFLMhhM3\nkm+c2BBTiQR+a08xZw4dSrB1jkrOQXpUv9jc/fvnFq2PJauBAcm/P+d2NjzgTzgRhc6g964r\n5yCNK3GDb64XH0dtIgC7Sf79ObvXLmP/9OiXI1+Onn4gI4/l5STHIJlDF4vfDcXa76A46b8/\nVstxnY2Keu5fEgf2e6pRTkG6TY4LnePkNoUKABwi/ffHKkiHyfOjIEjg0uQNknlVuxqVBQ6N\nkXz8uMR3pd/aLS6Mt3agOOm/P2eDNIsQH39B3srLEXY2gOuRdWdDsZbnHHquMxf2PapfbB52\nfwMrkn9/zgbJtM+RZzp5YbflHVMAACAASURBVB8OyDrh3tianoVb/8K6DHcm2wFZi2K/O/BE\nChf24RShPLpWvsysLd/1MU5mXYh7k+UUId7IgQ48ERf2sdP+ReuPdKN+F+tK1MnZID1o+dqW\n+AQr20/EhX3MXNTtFzqv9mBbiFo5GyTyjO0n4sI+Zn7MJ3YWhDOtQ7WcvtS8Z59Mtp+IC/uY\nWRcgdpaUY1qHail6ZgMu7GPmLyIepujfjm0hauVMkK4nWv73jO0nUriwD/KoVlfr4fgT3itZ\nV6JOzgSJtHTwM5KzF/ZB3h3O32bbzdMLArvg9CpZOBOkbtMt/3vGvic7cWFfpsvD6hZp+P5N\n++YD0cnWJkJCpkv+BwzyzA3var4nIGL6N5MrhxyVvQyVSTlxjXUJ6uV8kPj/xD3Z9yfVdwxS\nQbpfuD8/ZWq3sripArgMZ4OUPvBVjvu7NCENaX6qkQrSf0KEc53u5sNioeAynA3SdDKM49ro\nBgzUT6dXlGSQ+md+GGs2huKMAE5xNkhVOnPcFV0fjouuQa8oySD17CV2Xn6P4owATnE2SPkW\ncdxSspXjFhSgV5RkkCbVElpz2HyKMwI4xdkg+VmC1MPX8rF/vi+9oiSDdNIgrP/+pZfUDdQA\nFOX0W7vXuBv5Olk6fStQq8nG7u8JPp9c4S5M9rDjPjIACnE2SNNIvSJkB8ct9xhJryjpIJk/\nDyEmUuwrivOp24VRzap2WZLKugx1czZIyb28/fm19AtXlbri1VE2ThFKT4g7hzNd7PVTvjrj\n5r1T8EWavyB4Hq0zG35Pc76WZ3CuHT2XfMfz/9G5Ua0z60pUzQ1PEQKHvF9TePE+QM4yrkTV\nECS1i5wgdkK/ZlqHyiFIaldnptgpv5hpHSqHIKldF3HFmYdeWNNORgiS2q30FS4ynxKMhTVl\nhCCpnbllyZ9TuFsTjLjGXE5uHKQdA5o0G4qr+2x6NMjDGESKr2Vdh7q5bZDMQ4ztJ417yThb\n9mLcX9LONceoHueDbNw2SPP8dvPNSuNm2asBsMldg2QuPkvo9I+UvRoAm9w1SBeIuNb4Jk+c\ndQfsuWuQTpBbQmcveSJ7OQC2uGuQkgy/CZ1lIbJXA2CTuwaJa97R+pYupeYA2asBsMltg3Q0\n31uXOe5ki6J2rDkOIDe3DRK3vwoJKUga49oACZv6N2r9vh13gAOnuW+QOPOx79eckb0UN5b2\nukfnSaNe9FrOuhAtcOMggQ0TCh3hm3nGg6wr0QAESbWS/cSXog7d2RaiCQiSau0n94TOMqn7\nXgMdCJJqbTOI53ysp7kILuQMQVKthMyzqD6qxrYQTUCQ1KvqO9bmQelYtnVoAoKkXr96vHeb\n447UK3+PdSUa4PZBuhHbqkrnuY/lrMZtxYWR4gVIm6us69ACdw/SnqDw0XOHhIbjzhQ5STv4\n1brzrIvQBjcPUlKh/vw11HcbNcRVScCSmwdpTgnhjsx/6/fKWA6ALW4epG79xE51LIICLLl5\nkNoNFzuNJslWDIBtbh6kQW2FNiN4hXzVANjk5kHaYfzT2v7X97aM5QDY4uZB4t4IWZXMJX3s\nOVfWegBscPcgpb7vbQghhZbKWo77Odm3ZnCD8bjZpXLcPUgcd++3lYewIte//eD90pyVk8uX\nwHX4inH/IEE2V/NN5JvkVrUzWJeiGQiSCk0OFwJ0xbCbcSXagSCpUId3xU61T5nWoSUIkgq1\nGi12XpzBtA4tQZBUaHBroU3xX8O2EA1BkFRoj7gw+rRA/BiVop4g3U2RoRA3NdB/weX0k+8Z\ncNtYxagkSElDihFj5fnY2yvImB1EdKTiJtZ1aIg6gnS9bPjSP3dN9e+KJIkyzu68xroGTVFH\nkLrVfsQ3J/Itk6MaAJtUEaRE41ahM6KhHNUA2KSKIP1OkoUO1hQFRhAkAApUEaRE4zahM7KB\nHNUA2KSKIHFd61h3Nvzl94Us5QDYoo4gXS9TedmR36YX6ILd39ylLdtx2b3y1BEkLnFwEWKo\nNBc5Ol6PeJt0nXGHaqWpJEgWickyFOJu4gt0PpGR+tsL5ZNYV6I16gkSWLRqa31RflB+FOtK\ntAZBUpNE8bRvbkEptoVoD4KkJkeIuHDQDn0620o0B0FSkzPkstD5yZttIdqDIKlJeqFFQmdg\nJNtCtAdBUpUpQcf55ifTj6wr0Rp1BSl17ZjoGYcoF+NO0rp795o/q5PhQ9aFaI6qgnQ6PH/z\nt2rrolNp1+NG1narWqv3b6yr0B41Belhqbb8Tqt9ITG06wGwQU1B+rSo9dRVbpMRV1mDwtQU\npHbiAqPmQt9SrQbAJjUFqd50sVNlHs1iAGxTU5A6DBTa9IKrqFYDYJOagrQo+K61Xe2JC3JA\nYWoK0pPwRpcszc8FJtCux03gfmvsqClI3OX6pog2YYZRmry+72DHUFL8tdOsy9AqVQWJM++c\nPeq/5ykX4x5Wm175fs+KKN+drAvRKHUFSbuu+1l3WZoHicfSQGEIkjrMLiu8n33kjztQMIEg\nqUPPXmInahzTOjQLQVKHN/qInZbvM61DsxAkdZhaTWhTCy1nW4hWIUjqcN7zS2s7uSAW4mJC\nlUG6+d0Hs7dr7GDSPON7e67s6GXE7ZfZUGOQ5noHvxThUf0UtXLcwsYIAzE13M26DK1SYZCW\neiy1vBrdbFcskV5BbiE5AfejZkZ9QUoN/tjaPqmg1VPugAH1BWmvXvy4PaU2pWoAbFJfkJ7e\nte+rYnSKAbBNfUHaZRDPNptVnVI1ADapL0jJ+Zda24yI92iVA2CL+oLEzcgfZ3lM7lvgCrV6\nXN31m6wr0DwVBsk8QhfRs2Nwkb306nFp92OCCAke+ZB1HdqmwiBx3PGPeg5dppU/rLvVyi0/\nFf9FWG2cVcWSKoOkKTHCbS5vlxrDuhJNQ5DcXHrBr4TOosJsC9E4BMnNXSXieieHCc77ZghB\ncnPXyUmhc5DcZ1uJtiFIbi4jdLHQmYP7L7OEILm78cWsx8v+Dp5ua0uQkYqDFD+oXoUOi1R/\n07HHkSEztsVNCWyJayhYUm+QvvZsOm3xkMC6dynU49JSP6rm4VljThrrOrRNtUGKN33KN9fD\nX3O+HJeXhhSxptogDWgqtLv0V50dCsAm1QYpYpbQmvNvcHYoAJtUG6RKn4udwrgPJshPtUFq\nM1hob+n3OTsUgE2qDdKX+S9a2/fCNLbAHTDBIkgp+7fbuIcRhSClvxS28RF3fojpF2dHcl2p\n3w1qO/BrHD9yBYoGafJ2/nFRACGk1mGpDWkcR3o4yEPvSypuc3ogl3Wtlt8rw7v4V7/MuhBQ\nOEhktOXhJ+LZqX8D4n9WYkM6pwjd27fxrIrf15nr1b9laf5pXCuddSnAIEjl/OMtj2t1vSU2\nxLl2dtjiKSxKccPnB8aVAIMg3SJjrf2ORSU2RJDsMEY85My1Hsa0DuApHqRLRLiic7xJYkME\nyQ4Du4idN6OZ1gE8xYOU7i+c7h9dUGJDBMkOT5dkboBFztlTNkg9DiTcHlOWXwn1pG97iQ0R\nJDsc1QsLjh007GdcCSgdJMEajvvGVy/126cZpJ1jOvVbrMqrsN8O2Wx53Fr0TdaFgMJBWjYn\nNqZnx8htHLeg6EapDekFKaWHISqme5Gif1Aaz5WkvmsMfCHIMOAJ60KA2SlCD6SP79AL0rtF\njlgen/QOuk1pQJdyefXHqy6yLgJ4qj3XTnDL+LO1TasYS2dAgBypPEjr/MWXvnFN6AwIkCNW\nQTobFSXxXWpB+qK02PmsGp0BAXLEKkiHidQo1IK02TtZ6AxtRWdAgByxClLy8eMS36UWpEf+\nwoWySSHz6QwIkCPX+Yxk3hH3VAy1vXbzvZamc9yZulXUtY94/8DG9fpuZ10FPKN0kMzn4tat\n23Yph++c8yJZUDuCOse3QN0y+mbXaI3nEqYYWk2a1tE4xMy6EMikbJAShwcLOSkx6bHUdjTP\nbPhn/Yz/Sl5F6H7Wm37km9/8FrKuBDIpGqRrYaRcr9iZM8f3KEKqJ0psiHPtJNV7V2hnYN18\nl6FokPqYVom99AW6GIkNESQp6Qbx+vl4gsUvXYWiQQrNcuFMt+ISGyJIUh6QA0LnKjnDthJ4\nStEgmaY+60/0kNgQQZIU+LXQbjNp5Y7Trk/RIJXs+qzfQer9vRxBSlHPnSH71bIuwZXRqh3r\nSiCTokGK0c0SD+c8/MC6EEpuqAfJvKSaiRR5RyWngF8r0vwEx53rWuAk60ogk6JBSoogflG9\nBg/qGelDGklFhXaQzL3yfbjj8JfVSqhkCbhzkcS/IKl1hHUd8JSyx5FSPqlh4A8jmeoukVyL\njXaQVnkd4pvkhlLXt7uV8z+sOc26BshC8VOEks8cOpRga5Vd2kFqMVBof9er6wwHcBmuc65d\nVrSDVFTczZVhVPEKxsASiyDNamBrC+pB+kZoM0xbqY4LIGIRpP42B6D+1m6Q0O7DWzuQhzaC\ntNLbetrqk0buf+Dl/Fex/znGugjIRhtBMr/lN3nX0RU1iud0/YY7SYsxFIsso+t8l3Uh8Bxt\nBIkzL6piJKH9btEdVXlDCvH3TTtSKQpXIrkYFkFKsnlYVJZThO5QH1JxZ/XCXse/vSXX1wTl\naWP3t1rMLyt2Og5gWgdkgyC5k/HNxE5MR6Z1QDYIkjuZXVXsdMctkVyM5oJ0PU2ukRVwWCfs\n+U4M+IpxJfAcbQXpZCd/4vGiG99ytVPFBMvjPy9VTmVdCfybpoK017fV+pNb3zPOkGNwRdxv\n5RE1oJ1ftQusC4HnaClIqWXeth5+WWM4KsPoyjDHje02YhVej1yOloL0Pw9xCbAm78kwOmia\nloL0aXWx835LGUYHTdNSkD5DkEAuWgrSVg/xLKFGw2UYHTRNS0FKK9/LurPhe8MJGUaX274+\ntat0WYmTVV2UloLE/eEXtfLoloHG2XIMLrMZhpdnLoj26Ywddq5JU0HiEroHEZ9Gm2UZW16/\nGNfxzcnQ8awrgRxpK0gWiRlyjSyrluLJdcsK2FqBCZjQXJDcVIG1QnuL4Dpzl4QguQfPX4T2\nMdnHthDIGYLkHip+IrQHdDfYFgI502SQjg9r1rBfnJwzUPdB6Xt8Y+4UyboSyJEWgzTf2GTs\n1E6mPu602+FeeMTOlIz4bn7ue76tumkwSL8aVvDN/oCP5JuDvltd9SZvUkdlt5VWDw0GqfVb\nQrugkOQdMVzOPzs24zIkl6XBIPmLe5KvENynC2jRXpDMRnEh/Ydkv2yTgNZoL0hc2EKhPYQ9\nyUCNBoM0PPyxte3RUL45aLob2zC4evRfrMsASRoM0j+lmhznuKtv+xyQbw6KLoSVmbTy0+ae\nq1kXAlI0GCTuYnNSIIRUcvz/OAvm+lGP+HaGN3bZuTItBonjzq//7qibHI7drztvbc01xzGu\nBKRoM0hu5PMKYmdUK6Z1gDQEycU9XfootinTOkCapoN0fbfrf+74yfeR0On4NttCQJKGg/RD\neUJI4cUuvpzI45APrO1+43bGlYAU7QZpmXHUydTzs3zGyj6Tc9YbB/+VdmVxQB/WhYAUzQbp\nn/yfWdtNBle/djuuMtGRgBnudYat5mg2SMtCxL/M+q7+ksRxN3aeQYxcnGaDNC7zLpIDuso9\nFWiAZoM0KfNMu95vyj0VaIBmg/Szt7AQeFqpT+WeKs8uT3olaoh7rS2hWZoNUmrFLvzqv+ZR\nAbflniqv1uWrOnh8e9Ob7nzXW83QbJC4YyFVP1r3aWPfLbLPlEfxHlP4Y1yHC+EkOzeg3SBx\nN0bWKVijX4L8E+VRtLg75JvMcxvAhWk4SK6unHgl72P9braFgB0QJJcV+r3Y8fmZaR1gDwQp\n7dd5c+Jc8RYPtacI7RWsm+8GNB+kfWVNVWp4Ft+m1Hz2m1xK+CGMLOPi59UChyCdyt/7Dsfd\nH+rlegs43C/fIJ7jHnxgxDs7N6D1IHVtLvznvvtLCk3ogCstSHB5Y+H1rOsAO2g8SGbfdUJn\np8EVd2+cWrl49xPWRYA9NB6kJCKuSn+ZnFVmRlAnjQcp3fg/oXOI/KPMjPZ5vHPJWte/DB6e\n0XiQuKbiSgijqyo0oV1WBBnLB+hevcO6DrCb1oO0zfg533xnWqPQhPb4yjjzMcftr/pCKutK\nwF5aDxK31KtK3/4RxtlKzWeHJ4WEW6DdDFzMuBKwm+aDxF2Y8Xq3KacVm84OWz3E//dDWrMt\nBOyHILmeL0uKnbku9cENpCBIooOfDf3MRc5uWFdAPCfowwZsCwH7IUhWDzrrq71cXd/pvrLT\n5uyGQbi83FxzNONKwG4IktXL5Y5aHo+Vb6/stLl4O4y/3DB9uN8V1pWAvRAk3m/GeGt70rhL\n0Xlz8biN16sTB1YM2Mq6ELAbgsQb30jsNHaN9RHMG95p8uq0m6zLAPshSLz+PcTOa30VnRdU\nA0HijWsidiLHKDpvdvt6lA9qOOUh4yrAYQgS71eTcO73WQ/G905ZYHxl0ZqJJcJvsC0DHIYg\nWbWowu8nS6jSXNlpn3fYsJxv7tVpx7YOcBiCZJXU0lj/9frGFonKTvu8vi2F9iA5z7YQcBSC\nJNox7e2pvyo96fMiPhY7BV3pZHSwA4L0L/dXx05a95jN3BZV5oudIt8wqwHyBEHKakNgQNPG\n+UOZ3QAi84bL1/X7WZUAeYMgZbHbFPuE4x4P8z7CYnaL1d4nrW2/ChmMKoA8QpCyaNRLaDu+\nzGJ2C3On4GVXnhx83QurfbsbBOmZ+/rfhM5GL1YvCKmx/oSQunhj53YQpGfOkYtC5yhhsOxI\n6oEVP1zguPSEvUnKTw7OQpCeSdL9IXS2mJS/ifhPxXUl/HUdcaKqm0KQsqgzRGjfUP4Eh83G\n9xM57mCtquz2vYMzEKQsNhsXmDkuY4bJ8Z+Jk8xlhlvbpKIzlZ4aqECQsvrCu3TXV0v4rVJ8\n4sPkmtD5oJ7icwMNCNK/XFvwzqBFt7mz3320+qqS8/7oJ3a+LqrktEANgpTdw576wi8GmkYq\nuMfhV6N4z8D5FZWbFChCkLJ7uTT/M/kxcKhyU973Es9SbdZHuUmBIgQpm60ep6xtnCFBuUmH\nFbEuv/KRx1/KzQkUIUjZxGQuFFz+M+UmTens2WXyiAgf5fdzABUIUjZdBoqdVsqsz3hjUoe6\nby5P/aFvw7bj/lZkRqAPQcqmb1exU2u6EtPtKFhp6Ixe/vVxYpBbQ5Cy+aaAcMH5GcPvCsx2\ns8AQfu/gtaqdFJgMZIMgZZNSqQX/6nC5RgslZptUUdjLfoicUmI6kAmClN258IJdhnXwaXj7\n+PcbZF+EpNUIsVPiC7mnAhkhSDl4smJg+6Hr9oSTYH/S/KK8czWcInaqzZV3IpAVgpSbQz7R\nVzjuWJNS8t7u/LU3hTbFb4Os84C8EKTcNO5mbR5XHibrNGt8hHePc/1d4t5MkEcIUi5u6sT7\n9y0sJd8kKcfOpbcovTWdezDL9B/5pgH5IUi5OEjEV4jtBrNMU1zoYCQkf0xvo3cJfaFlMk0C\nykCQcnGKXBY66/2kN8yzs8GRcXcufl2y0eVfvtyHC2PdHIKUi/RgcdXTXq1kmqFNszS+uRr8\niUwTgIIQpNzMDLAuivW1YcvhTWdlWJ7rln6v0JkUQX9wUBqClJuMt02dp41vamztR3xI2Drq\n4/9OkoXOT/mojw2KQ5By979+DaKGtg9akchdHGv8mvboT/dmrA2gPTQoD0GSts14yNrOCqB9\nmOeh93qhM+glyiMDAwiStH4dhDYl/1qKo6ate/+NiR3KWW9wucuT5sjACIIkrfk4sVN7Fr1B\nL9TI1zK6sTEgZOKGb9/xUHBpCJANgiTt5cw/80rzJbdzRGrlprcsTXzpGvX8C7fEKXaqgCBJ\nm1JJ2PN9Xh+3+/ATOmOuCBCuHDyoO0FnQGAPQZJ23W8sf4bQ/dr5iYF4DqJSVs/XxU5FBVdX\nAXkhSDZsyldv2rLRIfo2B1OS1pdpkEJhyPbDxU7TWAqjgUtAkGw5H1M/rEXJTtYzV68Vcv41\n5ML1t7uI3dILnR4NXASCZI/zRFy3cUJd5wa60y8/IflNwsqTWw3nnKwLXAaCZI+tJvFSitWF\nnBrnVrmqK8+dWurp8yc/aPAQ5ysDF4Eg2WO3Ttxht7zovh/O5H1x/ejqD/nmlJeuUvNS+sFp\nVIoDV6B0kMzn4tat23bJxlauFqR7nj9a28cV9fp8pMymPA6T7COeFTSn2MJxS8/SqQ1cgrJB\nShweTKxKTJK8ks3VgsT1L8vfLskcQSY/4i6NMObxIOoZIt506Tcdjb1/4EIUDdK1MFKuV+zM\nmeN7FCHVEyU2dLkgPWgUOHzFwrpkpPWr8UUcz8HjJb2bdCXi/S126vGuTmUUDVIfU+bNFtIX\n6GIkNnS5IHFpC1oUDy/eVvjinsc2R59/rkKhnrGv64oL169PqkK1OGBP0SCFRj/rdysusaHr\nBckqYrbYCYuZ/cURR56ZVrnlPUszyKsGf8ZRfAF6J+6Ba1A0SKapz/oTPSQ2dNEgNfxQaP+j\n86oVpnvpiv3PXO13h28e1tH1jts0Pv8rCt5VExShaJBKdn3W7yC1XJyLBmn4i9ZmuZGc5rgz\nDSo+sutZabsWLnylndBPKRPi6fvCYhmWgAC2FA1SjG6WeDzm4QdE6i5eLhqkc17TLI8pgUU6\n8l/dK2rXJUq/lzVWCtf7/SZ89crgNLmWyQOWFA1SUgTxi+o1eFDPSB/SSCoqLhokbq13w8mL\nXiE1rO/TuHdLd2s5NM7GU/7yi7ZsPSLU95j1y2ofyVwisKHscaSUT2oY+MNIprpLJD8luGqQ\nuDMxDSvWyi/s/N7s49F/TFvja6m5bp0Wv/Fohzb8K9ABfWPrHr/t+nhF6gSlKX6KUPKZQ4cS\nbB2Gcdkg8TZ7WaNzzieyjqU5GjIq7ey9HDdcGkp8ie5t61u53gHGZC5jTeC7ytUJSsK5dg67\nK6xWMqh+hPUeYbP1noRUWPrcNnu335rlOfMGd4r4WrdKjSb5Kvt6jsXuOpVCkBw3MoRfoqtq\nw/z8/u+9PvoZlw9O9uk3681OYw9wd+MWbrhys7veYCL6mZZvJ+s+0Vs/Hf2uWz1v0y2mdYOM\nWAXpbFSUxHddO0hpbxmaDX3L6LfD0k8v36cg/wI1lRTrM6SxvnE+z3B/Q4Ga2x+njvIJ5E8I\nqju47gT+ScNqMa0ZZMYqSIeJ1CiuHSSO2zn65ejS1vPudhlP6/7guBOeFfmzNt7WdUvjuB6m\nlpb+8LbN2luan41N3rA035qwWpCqsQpS8vHjEt919SDxZhbjdzEsKRdb1PK5541WUxtw3A2v\n3oGWIJWc6PUTx01o+quR32K+PmjAgNrGOazrBVnhM1JePapUL57jPi9oXG35ovgXHzbmuC9D\nb5LDXJpuV+e+HLfR5wzh/2PxOKhj1y4TT7MuF+TFLEj/JDz3D3+HBjzl4wZB4q62IIXDTcR6\nM3K/H6MGc9yUBhn6Xzmz55bRrS2fpMJb8ldNpPUp4gb/X8BZzII0+vlR0jesemoScYsL3+K/\nm781oj1/aVGFnoYjHDc3/Bx/Fl6DmL78jZxPBhjGfBFbNWgf6zJBAa4TpKz2uEeQeCdDIhb/\ntrqqjj/v7rCuVwVLs9ozaJ6liQ96qVnppmOuMy4QFIEgOev6gDL6wKZBbS5bPg6V1/G3UUoO\nJ6/OW9Lf9xVcBqsdigapVhahagmShaXY03X0ZWt6BVXw6zHx7eLFFveoUrbTdzjNW0MUDZJe\n7/mUQUVB4pn3L5nzy6O0b/tGvv5ZzqfegZopGqTRfs921anmrR0Ap3CQUmvWfnrNAYIEaqLs\nzoZ47xGZXQQJ1EThvXb37mT2dkyX2AxBAjfjmqcIIUjgZhAkAApYBGlWA1tbIEjgZlgEqb/N\nARAkcDMIEgAFCBIABQgSAAUsgpR02dYWCBK4Gez+BqAAQQKgAEECoABBAqAAQQKgwDWDdIAA\nuJkDDv+Zyx8k7sjB5/2PfPQVW6V7MC6gczjjAj4kSxlXkH8I4wIat8r2lyly6ObcAgWClN0N\nwvoWXbXtutOljGKbMi7gD2LfXXPlU2gV4wJ69aI4GILEBoKEIDkPQUKQECQKECQECUGiAEFC\nkBAkChAkBAlBogBBQpAQJAoQJAQJQaIAQUKQECQKECQECUGi4I7uLItps6j/GeMCprRkXMBh\nwxPGFRRlfW/4fv0oDsYkSNw5JrNmcTWZcQEPbzAugP3v4EI64wISEykOxiZIACqDIAFQgCAB\nUIAgAVCAIAFQgCABUIAgAVCAIAFQgCABUIAgAVCAIAFQgCABUIAgAVCAIAFQgCABUIAgAVDA\nIEhJMSVNhftcU35ii8ThJTxKdfidbRnvkT4MC9jUOJ9/018ZFnDyjVBjUMc/2FSQ+r6+ltDL\nMjeNMpQPUkoEeWVqtCmM5uWJ9rpTirSd8LrR6xjLMg4YrEFiVMAXpMz4EYU89jAr4IRfwQ9W\nTA41bmNRQXyEnxikLHNTKUP5IH1CPrI8riTDFZ+Z4waReZbHtaQNwzLSalS3BolNATfz1XzI\ncQn5BjL7CbxGtlsej5JIBhXc866d4CkEKcvcVMpQPkg1/KyrbpQNNis+NTc0KtXyaPYuybCM\nGbrN1iCxKWAW2cI3ZmYFcC8S/nfA5S/FoII7w1M5MUhZ5qZShuJBSjZEWdtehNnqG09MDdiV\ncdZ7QBIfJEYFtPRO5Z7c43usfgI9yXHL4219a0YVCEHKMjedMhQP0hkirCYWS+KUnjrTZ5Y3\neMzKiCp81xokRgWUDP+zgY6UWcbuFxEfUH339T+jfPYxqkAIUpa56ZSheJAOkUHWdhZZp/TU\noh0eDdOYlbGMrOGsQWJUgF/JwsPXfFaCfMPuF3EqnBBSYi+rH4EQpCxz0ymDQZAGW9uZZL3S\nUwu+9Yy4w6yMmwXbcZlBYlKAJ1luebyWLzSd1S8iPqz47I1LK/vHMfoRZAbp6dx0ylA8SAmk\np7UdT7YqPTXP/AFpMcUHlQAABChJREFUdZ9dGd3zXRSDxKiAQIN1peIu5BirX0RdnyuWx0dF\ni6ayqUAIUpa56ZSheJBSjJHWtge5qPTUFuZoMiSdXRmbyITLly//RXpcvsfo51DLYN1nNpDs\nYVTAA52w6vlb5ASbCoQgZZmbThnK7/5+0Yf/b2JGkeKKz2wRQ6axLGM4yTSa0c9hMNnHNy3I\nJUYF3CL1rG1XcpBNBeLu7yxzUylD+SAtIRMtj5+TDxWfmT8UG8O0jPiNvO9Ji40nGf0cDupe\nesJxB/TVmP0iwkynLY9JBfM/YVOBGKQsc1MpQ/kgpTciHT7srqvK4q4iZciQ0VaJLMuwfkZi\nVcBQUuPDvt4evzIrYJ0+cNwXU8PIAgYV7LD86g2hlod/ss5NpQwGJ60+GFHSVHTQHeUntvy/\nzfQ3yzKEIDEqwLyoupd/m/3sCuD2dixkDGj2M4sKpmf+/hP+NTeNMnAZBQAFCBIABQgSAAUI\nEgAFCBIABQgSAAUIEgAFCBIABQgSAAUIEgAFCBIABQgSAAUIEgAFCBIABQgSAAUIEgAFCBIA\nBQgSAAUIEgAFCBIABQgSAAUIEgAFCBIABQgSAAUIEgAFCBIABQgSAAUIEgAFCBIABQgSAAUI\nEgAFCBIABQgSAAUIkjszvMi6AhAhSO7gJGmZ478jSC4DQXIHCJLLQ5DcAYLk8hAkdyAEqQd5\nMKqkR7FPzJb+zxFehfokWYN0Y2AJU1CH/RwXp+vBb9xav5tpsdqEILkDIUg9Sct3ft/TgnzB\ncbsNRab9541GJkuQbpX0H/3VtGKeOzjuHRLHcWvIe6zL1SIEyR0IQepD+Fecc6Qdx7Uillcg\nbiCxBGmA8YCle8mvNsc9KFXuycPi5R+zLVabECR3kBmkLfwXPjW4DO8yfO+wJUjmoIjrvJbk\nAcdt18WO0O9lWqpWIUjuIDNI8fwX/pW5K6Q530u2BOkGyfSX5V8GeppGsixUuxAkd5AZpAT+\nC0uQzpD21n/XvcglkBqbBUmWfzhEyHGGdWoYguQOng/SZeEV6YH1FanGs+0y6oUENjIzKVHr\nECR38HyQ0jzK8r09/M6GIC/+pYi7xT/MIt8vI58yK1PLECR38HyQuEjrXrvXrHvtyFhL91Zo\nO4477d2G45r6nGFaq0YhSO4gW5A26YLfn9XuJX9LkG6WIL2/nFbC9D/LGzvfC5Y0eTbIYFyu\nFiFI7iBbkLjvq3oUik4qXtPSvT6guLHAy39w3MfkE/77k8hshqVqFYIEQAGCBEABggRAAYIE\nQAGCBEABggRAAYIEQAGCBEABggRAAYIEQAGCBEABggRAAYIEQAGCBEABggRAAYIEQAGCBEAB\nggRAAYIEQAGCBEABggRAAYIEQAGCBEABggRAAYIEQAGCBEABggRAAYIEQAGCBEABggRAAYIE\nQMH/AdbxbTdnEAfiAAAAAElFTkSuQmCC", | |
"text/plain": [ | |
"plot without title" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"x <- seq(-pi, pi, length=100)\n", | |
"plot( sin(x) )" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "R", | |
"language": "R", | |
"name": "ir" | |
}, | |
"language_info": { | |
"codemirror_mode": "r", | |
"file_extension": ".r", | |
"mimetype": "text/x-r-source", | |
"name": "R", | |
"pygments_lexer": "r", | |
"version": "3.4.1" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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