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Section 4 is done

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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"x = np.linspace(0, 10, 10)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"y = np.sin(x)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x, y)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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Ap/Tjwy1ygCIR2QisAe5W1ZBPKJW19by1s5rrpg91fe6JNxZMzCRK4EV7SjE+1NzSyj3LtzFqUB9uzHf/Sf2nV+eR2ieOb/91A/VNtuR2d1ydh6Kqr6jqWFUdrao/c/b9UFVfaHfOf6rqnR2uW6uqE1V1svP1j4GO3R/+9uEhz9yTae7/T+SN9OQEZo4cyEsbD9vwSuMzz31wiJ1Vp7ijcBwxQVD5OiUpjnuun8TOqlP8asV2t8MJau7/axnA02a8tLiM/BEDyB4UfHNPurJwchZ7jpxmS3mt26GYMFDf1MJvVu5gyrAUCnKDZ5TjpePSufmC4fzxnb2s233U7XCCliWUILGxrIZdVaeCvjO+owV5WURHiXXOG594dO0+KmrruXPB+KArPvqvV+QwIjWJ7z2zkZP1TW6HE5QsoQSJpcUHSYiN4opJvV/3JJBS+8Rx4eiBvLTJmr1M79ScaeJ+PxaA7K2kuBh+85kplNfU8f9eDPkuW7+whBIE6ptaeGHDYQpzM+kXxHNPurJo0mAOHqtjU5mNgjHnLhAFIHtr2vAB3H7peSwtLmNFaYXb4QQdSyhBYNXWSmrrm7l+eu+W+HVLQW4msdFipVjMOfuoAORU/xeA7K1vzhlD7uB+/OtzmzlyqsHtcIKKJZQg8Gzb3JPRwfeY743+SbFcPCaNlzeV09pqzV7m7LUVgPxOAApA9lZcTBT3fmYKJxuaueu5zdbU244lFJdV1dbzxo5qrp02lOgQmHvSlYWTszhcU88HB467HYoJMTucApBfmDWCoQMCUwCyt8ZmJHNHwThWbqnkmWJbG6iNJRSXtc09uXZap3UxQ8bcnAziYqJstJc5a/csd6cAZG/dMnskM0em8uMXt9jaQA5LKC5qm3syfcQARqX1dTucXklOiOWycWm8vLmcFmv2Ml5av+8Yq7Z6CkAOCHAByN6KihJ+dcNkAL77zEZr7sUSiqs2ldWwMwTnnnRl4aTBVJ9s4P29x9wOxYSA9gUgb5k90u1wzsmw1CR+uGgC7+89xh/f3ut2OK6zhOKipcVlxMdE8ekQm3vSlTk56STGRttoL+OVlVsqKd5/nG/PG0tiXLTb4ZyzG6YPZd6EDH65YjvbKyK7UKolFJc0NHvWPSnMC825J51JiothTk46y0sqbP0I063mllbuWbGdUWl9uCHEn9BFhP+6diLJCTF8+68baGyO3N99SyguWb21ipq6prBp7mqzcNJgjp5uZN0eq3dkuvbcB4fYVXWKOwqCowBkbw3qG89/XTuRLeW1/Hb1TrfDcU3o/0uGqKXFZWT2S+DC0YPcDsWnLh2XRt/4GF60lRxNF4K1AGRvzc/N5IbpQ7n/9V0U74/M4fOWUFzwj7knQ0J67klnEmKjmTchg+UlFRH96G+6FswFIHvrh4smkNU/ke8+vYEzjc1uhxNwPSYUERkrIqtFpMR5PUlE/t3/oYWvv284REurcl2YNXe1WTgpi9r6Zt7eVe12KCbInDjTyP1rdnH5+PSgLADZW8kJsfz6xsnsP3aGn7+y1e1wAs6bJ5Q/AHcBTQCqugnPcr29JiKFIrJdRHaJyJ2dHP+iiFSLyAZn+3K7Y4tFZKezLfZFPIHQNvdk2vAURof43JOuXDQmjX4JMby00SY5mo974PXdTgHIcW6H4jcXjBrIl2aP5E/vHuD17VVuhxNQ3iSUJFV9v8O+Xj/LiUg08H/AAmACcJOITOjk1L+q6hRne8i5NhX4ETATmAH8SEQG9DamQNh8qIYdladCthCkN+JioijIzeTVLZW2ZKr5yOETdTyydh/XTh3K+MzgLgDZW98rGMfYjL7csXQTJ840uh1OwHiTUI6IyGhAAUTkesAXHz1nALtUdY+qNgJPAVd5eW0BsFJVj6nqcWAlUOiDmPwu3OaedGXR5MGcamjmjR3W7GU87l25A4DvzA/+ApC9lRAbza9vmELVyQaeKYqcWl/eJJR/Bn4PjBeRQ8C/AF/zwb2HAAfbvS5z9nV0nYhsEpGlItL2sd7baxGRW0WkSESKqqvd/ePWNvekIDeT/onhMfekKxeOHkhqnzir7WUA2F5xkmc/KGPxrBEMSUl0O5yAmDi0PzlZ/SJq3ZQeE4rzBDEXSAPGq+qnVHWfD+7d2fCOjsVwXgSyVXUSsAp47Cyu9exUfVBV81U1Py0t7ZyD9YXXtlZx4kxT2HbGtxcTHUVhXiartlRG5GgX83G/XLGNPnEx3H5paBWA7K3C3EyKDxyn6mS926EEhDejvFJE5JvAT4CfichvReS3Prh3GdC+I2Eo8LHJC6p6VFXbVrD5AzDd22uD0dLiMjL6xfOp88Jr7klXFk7Koq6phde2RVbHpPk4TwHIqpAsANlbBXkZqHrKzEQCb5q8XgGygc1Acbutt9YDY0RkpIjE4Rk59kL7E0SkfUfDlUDbOLwVwHwRGeB0xs939gWtqpP1vB4G656cjZkjB5KWHG+jvSJYOBSA7I1xGcmMGJjEitLISCgxXpyToKrf8fWNVbVZRL6OJxFEAw+raqmI/BgoUtUXgG+KyJV4RpUdA77oXHtMRH6CJykB/FhVg7rE7fMfHvbMPZkW/s1dbaKjhCvyMnlq/UFONTTTN96bXzcTTtoKQP7XtRNDugDkuRIRCnMz+ePbe6mpawr7vlNvnlCeEJGviEiWiKS2bb64uaq+oqpjVXW0qv7M2fdDJ5mgqnepaq6qTlbVy1R1W7trH1bV85ztEV/E4y9tc0+mDk/hvPTwnHvSlYWTB9PQ3MqqCHnkN/8QTgUge2N+bibNrcqaCGj69SahNAK/BNbxj+auIn8GFW5KDtWyvfJk2BWC9Mb04QPI6p9gJe0j0LMflDkFIMeHRQHIczV1WArpyfEsLwn/0V7e/Ct/BzhPVbNVdaSzjfJ3YOHk2Q/KiIuJYuGkwW6HEnBRUcKnJ2bxxo5qas40uR2OCZC6xhbuXbmTqcNTKMjNcDscV0VFCfNzM3hjRzV1jeE90debhFIK2ILJ56ihuYW/bzjE/AkZYd9+2pWFkwfT1KKs2BL+n9CMx0cFIAvDrwDkuSjM9Yx4fHNneE/09SahtAAbROT3bUOGfTRsOCKs2eaZexKJzV1tJg/tz7DURJvkGCFOnGnk/td3MWd8OjPDsADkuZg5KpX+ibFhP8nRm2E3f3c2cw7a5p5cNMbdSZVuEhE+PXEwf3hrD8dON5IaYXMRIs39r+/mVEMzdxSOdzuUoBEbHcWcnHRWbamkqaWV2DDtU/JmpvxjnW2BCC7UVZ9sYM32aq6ZGjlzT7qycFIWLa0aER2TkezQiToedQpAjstMdjucoFKQm0ltfTPv7QnqGQ690mVCEZGnna+bnVpaH9sCF2Loet5Z9+T66Z2WGYsouYP7MXJQHxvtFeZ+u8qz/G0kFIA8WxePSSMxNprlpeHb9NvdE8q3nK8LgUWdbKYbbXNPpgxL4bx0+6QmIiyalMW7e45SfbKh5wtMyKlr9BQ/vW7a0IgpAHk2EuOiuWRsGq+WVtLa2mnpwZDXZUJR1bY0eruq7m+/AbcHJrzQVXq4lm0VJyOiEKS3Fk4eTKvCspLw/YQWyd7YUU1dUwsLw3xpht4oyMug6mQDG8pOuB2KX3jTMzSvk30LfB1IuFlaXEZcdBRXRuDck66MzUhmbEZfXtxozV7haHlJOSlJscwY6ZNCGmHp8vEZxEQJK8K0L7G7PpSvichmYFyH/pO9gPWhdKOxuZXnNxxiXm4G/ZMic+5JVxZOGsz6fccpr6lzOxTjQ43NrazeWsW8nIywHcHkC/0TY5k1eiArSitQDb9mr+7+5f+Cp6/kBT7edzJdVW8OQGwh67VtVRyP8LknXWlrDnnZ5qSElXd2H+FkQzMLJma6HUrQK8zLZN/RM2yvPOl2KD7XXR9KjaruU9WbOvShhO+YNx9ZWlxGenI8F0XIuidnY1RaXyZk9bNJjmFm+eYK+sbHMNt+53s0b0IGIrCiJPwKptqzqY955p5Ucc20IRFdEK87CydnseHgCQ4es4o+4aC5pZWVWyu5fHw68TGRV6L+bKUnJzB9+ACWh+Gs+e76UOIDGUi4+GjuSQSte3K2FjkDFV7ebE8p4eD9fcc4drqRBXnW3OWtgtxMtpbXcuBoeH2o6u4j9DoAEXkiQLGEhWc/OMTkof0Zk2FzT7oyLDWJycNSbJJjmFheUkFCbBSXjIvc8kJnqyDXk3zDrbZXdwklTkQWAxeKyLUdN1/cXEQKRWS7iOwSkTs7Of4dEdnijC5bLSIj2h1rEZENzvZCx2vdUHq4hq3ltdYZ74VFk7IoOVTL3iOn3Q7F9EJrq7KitIJLxqaRFGcrcnpr+MAkcrL6RVRCuQ24AEjhk7PkF/b2xiISDfwfnjktE4CbRGRCh9M+BPJVdRKwFLin3bE6VZ3ibFf2Nh5faJt7smiyzT3pyRUTPaO9XrI5KSHtw4MnqKxtYEGeTWY8W4W5mRQfOE7VyXq3Q/GZ7kZ5va2qXwPuUNUlHbZbfHDvGcAuVd2jqo3AU8BVHWJYo6ptjYzvAkH70d8z9+Qw8yZkkJJk1XR7MjglkfwRA2y0V4hbUVpBbLRw2fh0t0MJOQV5GajCyjBaHtvbNeW/KSJLne0bIuKL2XpDgIPtXpc5+7ryJWBZu9cJIlIkIu+KyNU+iKdX1myv4tjpRmvuOgsLJ2WxvfIkO8NwPH4kUFWWlZQz+7xBEbt4XG+My0hmxMAkVpRGVkK5H5jufL0fmAY84IN7d1bPvdOpoyJyM5CPZ237NsNVNR/4HHCfiIzu4tpbncRTVF3tv9XSlhaXkZYcz0VjbBy+t66YmIUIvGhPKSGp9HAtB4/V2eiucyQiFOZmsnbXEWrqwmN5bG8SyvmqulhVX3O2JcD5Prh3GTCs3euhwCca1EVkLvBvwJWq+lGZWlU97HzdA7wOTO3sJqr6oKrmq2p+Wpp/RqEcPdXAmm1VXDPV5p6cjfR+CVwwciAvbToclmUowt2K0gqiBObmRPaa8b0xPzeT5lZlzbYqt0PxCa+WAG7/6V9ERuFZFri31gNjRGSkiMQBn8VT5uUjIjIV+D2eZFLVbv+AtnkyIjIImA1s8UFM5+T5DYdpblWus7knZ23h5Cz2VJ9ma7k1e4WaZSUVzBw5kIF9bcrauZo6LIX05PiwWXjOm4TyfWCNiLwuIm8ArwHf7e2NVbUZ+DqwAtgKPK2qpSLyYxFpG7X1S6Av8EyH4cE5QJGIbATWAHerqmsJZWlxGZOG9rcV6s7BgrwsoqOEF21OSkjZVXWSXVWnrHZXL0VFCfNzMzyl/xt98TndXT0OHFfV1SIyBhiHp99jW/ump95Q1VeAVzrs+2G77+d2cd1aYKIvYuit0sM1bCmv5cdX5bodSkhK7RPHhaM9zV53FIxDJLKXSg4VbZ+o50+whNJbhblZ/OndA7y5s/qjCY+hyqsGf1VtUNVNqrrRV8kkXDxbfMgz98TWPTlniyYN5uCxOjaV1bgdivHSspIKpg1PIbN/gtuhhLyZo1LpnxgbFpMcrQe5FxqbW/n7hkPMnZDOgD429+RcFeRmEhstVoolRBw4eobSw7U2mdFHYqOjmJOTzuqtVTS1tLodTq9YQumF1525J9YZ3zv9k2K5aEwaL28qD9u1tsNJ2yfpQhsu7DMFuZnU1DXx3p7QXh3Eq4QiIkNE5EIRubht83dgoeDZD8oY1Deei8daUbzeWjQ5i8M19Xx48LjboZgeLCspJ3dwP4alJrkdSti4eEwaibHRId/s1WNCEZFfAO8A/45nxNf3ge/5Oa6gd/RUA6u3VnHN1MG25KkPzM3JIC4mihc32iTHYFZRU88HB07YZEYfS4yL5pKxaaworQjpp3Rv/hJeDYxT1StUdZGzBUUxRje9sNGZe2KlVnwiOSGWy8al8fLmclpC+H+ocPfqFmvu8peCvAyqTjawoeyE26GcM28Syh7ACvV0sLS4jIlD+jM+s5/boYSNhZMGU32ygff3hnY7cjhbtrmC89L7cl66zbnytcvHZxATJawI4UmO3iSUM8AGEfm9iPy2bfN3YMFsy+FaSg/buie+NicnncTYaBvtFaSOnmrgvb1HKQzxuRLBqn9iLLNGD2RFaUXDfJrMAAAgAElEQVTIliLyJqG8APwEWAsUt9si1rMflBEbLVxp6574VFJcDJfnpLO8pILmEB8+GY5Wba2kVa25y58K8zLZd/QM20O0AnePCUVVHwOe5B+J5C/OvojU1NLK3z88xJzxGTb3xA8WTcri6OlG1u056nYopoNlJRUMS00kd7A18/rLvAkZiMCKktAsae/NKK9LgZ14Vle8H9gRycOG39hezVFb98RvLh2XTt/4GF6y0V5BpaauiXd2HaEwN9PK4/hRenIC04cPYHmIDh/2psnr18B8Vb1EVS8GCoB7/RtW8FpaXMagvnFcMs7mnvhDQmw08yZksLy0gsZma/YKFmu2VdHUohTa7Hi/K8jNZGt5LQePnen55CDjTUKJVdXtbS9UdQcROurr2OlGVm+r5OopQ2zuiR8tnJRFTV0Tb+/y34Jo5uwsKykno188U4eluB1K2GsrEBmKkxy9+atYJCJ/FJFLne0PRGin/AsbDtHUYnNP/O2iMWn0S7Bmr2BxprGZN3Z4KuFGRVlzl78NH5hETla/kFwjxZuE8jWgFPgm8C08C1nd5s+ggtXSD8rIG9KPnCzrlPSnuJgoCnIzeXVLJfVNob9GRKh7Y3s19U2tNrorgApzMyk+cJyqk/Vuh3JWvBnl1aCqv1HVa1X1GlW9NxJL2G8tr6XkUK0VggyQhZMHc6rB88nYuGtZSQWpfeKYkZ3qdigRoyAvA1VYuSW0Rnt1mVBE5Gnn62YR2dRxC1yIweHZYs/ck6umDHE7lIhw4eiBDEiK5aVN1uzlpobmFl7bVsW8nAxirN8wYMZlJDNiYBIrSsMkoeBp3gJYCCzqZOs1ESkUke0isktE7uzkeLyI/NU5/p6IZLc7dpezf7uIFPginq40tbTy9w2HuXx8Oqk29yQgYqOjKMzLYvXWyrBYGjVUvbPrCKcamim0pX4DSkQozM1k7a4j1NQ1uR2O17pMKKra9tHwdlXd334Dbu/tjUUkGs/clgXABOAmEZnQ4bQvAcdV9Tw8Q5V/4Vw7AfgskAsUAvc77+cXb+6o5sipBq6fPsxftzCdWDQ5izONnk/Ixh3LNleQHB/D7NGD3A4l4szPzaS5VVkTQr//3jzDzutk3wIf3HsGsEtV96hqI/AUcFWHc64C2mblLwXmiGdW1VXAU07/zl5gl/N+frG0uIyBfeK41OaeBNTMkQNJS47nxY1W28sNTS2trNxayZycdOJirLkr0KYOSyE9OT6kRnt114fyNRHZDIzv0H+yF9jsg3sPAQ62e13m7Ov0HFVtBmqAgV5e2/Zz3CoiRSJSVF19bh28V08dwg8Kx9vckwCLjhKuyMtkzfYqTjU0ux1OxHl/7zFOnGmyyYwuiYoS5udm8MaO6pAZ7djdX8i/4OkreZ6P951MV9V/8sG9OxvQ3rHEZlfneHOtZ6fqg6qar6r5aWnn9oRRkJvJjedbc5cbFk4eTENzK6tCbLRLOFhWUk5irGfhJ+OOwtws6ppaeDNERjt214dSo6r7gP8GjrXrP2kSkZk+uHcZ0P6v9FCgY9vGR+eISAzQHzjm5bUmDEwfPoDMfglW0j7AWluVFaWVXDoujcQ4v3VPmh7MHJVK/8TYkKnt5U0bzgPAqXavTzv7ems9MEZERopIHJ5O9hc6nPMCsNj5/nrgNfUsFPAC8FlnFNhIYAzwvg9iMkEmKkr49KQs3thRHVKjXULdBweOU32ywSYzuiw2Ooo5Oems3lpFUwgs6eBNQhFtt9qLqrYCMb29sdMn8nVgBbAVeFpVS0XkxyLStsTwH4GBIrIL+A5wp3NtKfA0nln7y4F/VtXQaGQ0Z23hpCyaWpRXQ+RTWjhYVlJBXHQUl49PdzuUiFeQm0lNXRPv7Qn+lUy9SQx7ROSb/OOp5HY8ywL3mqq+ArzSYd8P231fD9zQxbU/A37mizhMcJsyLIWhAxJ5aVM5N+RbX5a/qSrLSyr41JhBJCdEZB3YoHLxmDQSY6NZUer5Nwlm3jyh3AZcCBzC03cxE7jVn0EZ056IsHDSYN7edYRjpxvdDifslRyq5dCJOmvuChKJcZ6BEStKK2htDe6lgb2p5VWlqp9V1XRVzVDVz6lq6My0MWFh4aQsWlo1pMbkh6plJeVERwnzcjLcDsU4CvIyqDrZwIayE26H0q0em7xEJA34CpDd/nxVvcV/YRnzcbmD+zFyUB9e2nSYz80c7nY4YautueuCUam2xHUQuXx8BjFRwoqSCqYNH+B2OF3ypsnreTzDdVcBL7fbjAkYT7NXFu/uOUr1yYgrdh0wO6tOsefIaZvMGGT6J8Yya/RAVpRW0G6MVNDxJqEkqeoPVPVpVX22bfN7ZMZ0sHDSYFrV0yRj/GPZ5gpEoGCCNXcFm8K8TPYdPcOOylM9n+wSbxLKSyJyhd8jMaYH4zKTGZPe11Zy9KPlpRVMHz6A9H4JbodiOpg3IQMRgrof0ZuE8i08SaVORGpF5KSI1Po7MGM6s2jyYNbvP0Z5TZ3boYSd/UdPs7W81kZ3Ban05ASmDx8Q1GvNezPKK1lVo1Q1UVX7Oa9tDVzjioWTslCFl23hLZ9b5nzytYQSvApyM9lSXsvBY2fcDqVTPSYUEbm4sy0QwRnT0ai0vkzI6mcrOfrB8pIKJg7pz9ABSW6HYrpQkOtJ9sH6lOJNk9f3223/AbwI/KcfYzKmWwsnZ7Hh4Img/ZQWispr6thw8IQ9nQS54QOTyMnqF7T9KN40eS1qt80D8gCrJW5cs3DiYABe3mxPKb7S9gdqgSWUoFeYm0nxgeNUnax3O5RPOJcVo8rwJBVjXDF8YBKTh/a3kvY+tLykgrEZfRmV1tftUEwPCvIyUIWVQbhGkDd9KP8jIr91tv8F3gI2+j80Y7q2cNJgSg7Vsqc6eMfkh4ojpxpYv++YTWYMEeMykhkxMIkVpSGYUIAioNjZ1gE/UNWb/RqVMT24aspgYqKEP717wO1QQt6rpZW0qjV3hQoRoTA3k7W7jgTdGkHdrSm/2vl2gqo+5mx/VtV3AhSbMV1K75fApydl8UzRQVtvvpeWl1YwYmAS4zOT3Q7FeGl+bibNrcqabcFVp7e7J5QsEbkEuFJEporItPZboAI0pitLZo/kZEMzS4sOuh1KyKo508TaXUcozMtERNwOx3hp6rAU0pPjg274cHcJ5Yd4VkgcCvwG+HW77Ve9uamIpIrIShHZ6Xz9RPlMEZkiIutEpFRENonIZ9ode1RE9orIBmeb0pt4TGiaMiyFqcNTeGzd/qBfJyJYrdpaSXOrssD6T0JKVJQwPzeD17dXU98UPIvVdplQVHWpqi4A7lHVyzpsl/fyvncCq1V1DLDaed3RGeALqpoLFAL3iUhKu+PfV9Upzrahl/GYELVk9kj2HjnN6zuC69E/VCwvrSCrfwKThvR3OxRzlgpzs6hrauHNHdVuh/IRb+ah/MQP970KeMz5/jHg6k7uu0NVdzrfHwaqgDQ/xGJC2IK8TDL7JfDIO/vcDiXknG5o5s0d1RTkZhIVZc1doWbmqFT6J8ayPIiavc5lHoovZKhqOYDzNb27k0VkBhAH7G63+2dOU9i9IhLfzbW3ikiRiBRVVwdPJje+ERsdxednjeCtnUfYWXnS7XBCyprtVTQ0t9rs+BAVGx3FnJx0Vm+toqml1e1wAD8mFBFZJSIlnWxXneX7ZAFPAEtUte2/2l3AeOB8IBX4QVfXq+qDqpqvqvlpafaAE45umjGc+JgoHlm7z+1QQsrykgoG9Y3j/OxUt0Mx56ggN5Oauibe23PM7VAALxOKiHxKRJY436eJyMierlHVuaqa18n2PFDpJIq2hNFpA7iI9MOzOuS/q+q77d67XD0agEeAGd78HCY8pfaJ4+opQ3jugzJOnGl0O5yQUN/UwpptVcybkEm0NXeFrIvHpJEYGx00o728mSn/IzxPAHc5u2KBP/Xyvi8Ai53vF+NZZrjjfeOAvwGPq+ozHY61JSPB0/9S0st4TIhb8qls6ptaeWq9DSH2xts7j3C6scWau0JcYlw0l4xNY0VpRVCMdPTmCeUa4ErgNHzUQd7bGVB3A/NEZCcwz3mNiOSLyEPOOTcCFwNf7GR48J9FZDOwGRgE/LSX8ZgQNz6zH7NGDeTxtftoDpL25GC2rKSCfgkxzBo10O1QTC8V5GVQdbKBDWUn3A6FGC/OaVRVFREFEJE+vb2pqh4F5nSyvwj4svP9n+jiScgHw5ZNGFoyO5tbnyhmRWkln55k8yq60tTSyqqtlcydkEFcjFvjcoyvXD4+g5goYUVpBdOGf2JKX0B589v0tIj8HkgRka8Aq4A/+DcsY87enJwMhqUm8sg7e90OJai9u+coNXVNFOZac1c46J8Yy6zRA1lRUoGqu81e3sxD+RWwFHgWGAf8UFX/x9+BGXO2oqOExbOyKdp/nM1lNW6HE7SWlVSQFBfNxWNt1GO4KMzLZN/RM+yodLf6tlfPu6q6EvgJ8HOgWERsnKEJSjeeP4w+cdH2lNKFllbl1dIKLhufTkJstNvhGB+ZNyEDEVxfydGbUV5fFZFKYBP/KGVf5O/AjDkX/RJiuX76UF7cdDgoV7RzW/H+4xw51WjNXWEmPTmB6cMHuD582JsnlO8BuaqaraqjVHWkqo7yd2DGnKvFF2bT1KL82dZK+YRlJeXExURx2fhui1OYEFSQm8mW8loOHjvjWgzeJJTdeAo1GhMSRqX15bJxafz5vf00NAdPJVa3qSorSiq4eEwafeO9GeBpQkmB89Tp5lOKNwnlLmCtiPy+3VLAv/V3YMb0xpLZIzlyqpGXNpa7HUrQ2FRWw+GaepvMGKaGD0wiJ6ufq/0o3iSU3wOvAe/yj6WAi/0ZlDG9ddGYQZyX3pdH1u51fShlsFhWUkFMlDAvJ8PtUIyfFOZmUnzguGv9h94klGZV/Y6qPtJuKeDHer7MGPeICF+8MJuSQ7UU7T/udjiuU1WWl5Qza/RA+ifFuh2O8ZOCvAxUYeWWSlfu701CWeOUgM9yVlpMtWHDJhRcO20I/RJibAgxsL3yJPuOnrHmrjA3LiOZEQOTWFEavAnlczj9KPyjucuGDZuglxQXw00zhrOitJJDJ+rcDsdVyzZXIALzJ1hCCWciQmFuJut2H6Gmring9/dmpvzITjYbNmxCwudnjUBVeXzdPrdDcdXykgrOz04lLbnLtehMmJifm0lTi7JmW+CXxfZmYmOsiHxTRJY629dFxBphTUgYOiCJgtxMnnr/IGcam90OxxV7qk+xvfKkTWaMEFOHpZCeHO/K8GFvmrweAKYD9zvbdGefMSFhyeyR1NQ18bcPD7kdiiva1hy3/pPIEBUlzM/N4PXt1dQ3BXYeljcJ5XxVXayqrznbEjxL7xoTEs7PHkDu4H48+s6+iBxCvLykgsnDUhickuh2KCZACnOzqGtq4c0d1QG9rzcJpUVERre9EJFRgE0/NiFDRFgyeyQ7q07x9q4jbocTUIdO1LGprMaauyLMzFGp9E+M/ejpNFC8SSjfxzN0+HUReQPPJMfv9uamztDjlSKy0/na6aowItLSbrXGF9rtHyki7znX/9VZLtiYLi2anMWgvnE88s4+t0MJqLZZ0wusuSuixEZHMScnndVbq2gK4Aqm3ozyWg2MAb7pbONUdU0v73snsFpVxwCrndedqVPVKc52Zbv9vwDuda4/Dnypl/GYMBcfE83nZo7gtW1V7D1y2u1wAmZ5STnjM5PJHtTrhVZNiCnIzaSmron39hwL2D27TCgicr6IZAKoagMwBfgx8EsfTGy8Cmibbf8YcLW3F4qIAJfjWfTrrK83kevmC4YTGy08tnaf26EERNXJeor2H7fO+Ah18Zg0EmOjAzraq7snlN8DjQAicjFwN/A4UAM82Mv7ZqhqOYDztata2gkiUiQi74pIW9IYCJxQ1bYxoGXAkK5u5MzyLxKRourqwHZQmeCSnpzAwkmDeaboILX1gZ/0FWivllaiCgvystwOxbggMS6aS8am8eqWClpbAzMYpbuEEq2qbc9KnwEeVNVnVfU/gPN6emMRWSUiJZ1sV51FfMNVNR/PbP37nMEB0sl5Xf7XUtUHVTVfVfPT0mzJ00i3ZHY2pxtbeKaozO1Q/G55SQWjBvVhbEZft0MxLinIy6CytoENZScCcr9uE4qItC2aMAdPZ3ybHhdTUNW5qprXyfY8UCkiWQDO106ndKrqYefrHuB1YCpwBEhpF9tQ4HBP8RgDMGloCtNHDOCxtftoCdCnNjecONPIuj1HKcjLxNNKbCLR5eMziImSgDV7dZdQngTeEJHngTrgLQAROQ9Ps1dvvAAsdr5fDDzf8QQRGSAi8c73g4DZwBb1TCRYA1zf3fXGdGXJ7GwOHDvDay6UpgiUlVsqaWlVG90V4fonxjJr9EBWlFQEZA5WlwlFVX+GZ3jwo8Cn9B/RRAHf6OV97wbmichOYJ7zGhHJF5GHnHNygCIR2YgngdytqlucYz8AviMiu/D0qfyxl/GYCFKQm0lW/4SwrkK8vKSCISmJTBzS3+1QjMsK8zLZd/QMOypP+f1e3TZdqeq7nezb0dubqupRPM1oHfcXAV92vl8LTOzi+j3AjN7GYSJTbHQUX5iVzS+Wb2NbRS3jM/u5HZJPnWpo5q2dR7j5ghHW3GUozM1kYJ94RgxM8vu9vJnYaEzYuWnGMBJio3g0DCc6vratisaWVhZMtOYuAwP7xlOYl0lCbLTf72UJxUSklKQ4rpk6lL99eIhjpxvdDsenVpRUkJYcz/ThnRagMMZvLKGYiLVkdjYNza08+f4Bt0PxmfqmFtZsr2L+hAyioqy5ywSWJRQTscZmJPOp8wbxxLr9Aa135E9v7KjmTGOLTWY0rrCEYiLaktnZVNTWf1REMdStKKkgJSmWmaN6Wx3JmLNnCcVEtMvGpZM9MCkshhA3Nreycmslc3MyiI22/7VN4NlvnYloUVHC4guz+eDACTYeDEx5Cn9Zu/sIJ+ubbTKjcY0lFBPxrp8+lL7xMSH/lLKitIK+8THMPm+Q26GYCGUJxUS85IRYbsgfysuby6mqrXc7nHPS0qq8WlrJZePTAzLfwJjOWEIxBvjihdk0typ/ene/26Gck/f3HuPo6UZr7jKusoRiDDBiYB/mjE/nz+8doL6pxe1wzkp9UwsPvLGb+JgoLhlrSzQY91hCMcaxZPZIjp5u5MWNobMaQs2ZJr7wx/d5a2c1//7pHPrE97iyhDF+YwnFGMeFowcyLiOZR97ZF5BS37116EQd1/9uLRsOnuB/bprK52dlux2SiXCWUIxxiAhfnJ3NlvJa3t97rOcLXLStopbr7l9LRW09j90yg4WTBrsdkjGWUIxp7+opQ0hJiuWRIK5CvHb3EW54YB0Az9w2i1mjB7ockTEellCMaScxLpqbZgzn1S0VHDx2xu1wPuHFjYf54sPryeyfwHO3Xxh2a7mY0OZKQhGRVBFZKSI7na+fqLMtIpeJyIZ2W72IXO0ce1RE9rY7NiXwP4UJV593FqZ6IsiGED/01h6+8eSHTBmWwtLbLmRwSqLbIRnzMW49odwJrFbVMcBq5/XHqOoaVZ2iqlOAy4EzwKvtTvl+23FV3RCQqE1EGJySSGFeJk+9f4Azjc1uh0Nrq/LTl7bw05e3siAvk8e/NIP+SbFuh2XMJ7iVUK4CHnO+fwy4uofzrweWqWrwtUGYsHTL7Gxq65t59oNDrsbR0NzCt/66gYfe3sviWSP4389Ns5nwJmi5lVAyVLUcwPma3sP5nwWe7LDvZyKySUTuFZH4ri4UkVtFpEhEiqqrq3sXtYkY04YPYNLQ/jz6zl5aW90ZQlxb38QXH17PixsPc+eC8fznlblE26JZJoj5LaGIyCoRKelku+os3ycLmAisaLf7LmA8cD6QCvygq+tV9UFVzVfV/LQ0m0VsvCMiLJmdze7q07y160jA719ZW8+Nv1vH+n3H+M2Nk7ntktGIWDIxwc1vCUVV56pqXifb80ClkyjaEkZVN291I/A3VW1q997l6tEAPALM8NfPYSLXpycOJi05PuBViHdVneTa+9dy8NgZHllyPtdOGxrQ+xtzrtxq8noBWOx8vxh4vptzb6JDc1e7ZCR4+l9K/BCjiXBxMVHcPHMEr2+vZnf1qYDcc/2+Y1z3wDoamlv561dncdEYe6o2ocOthHI3ME9EdgLznNeISL6IPNR2kohkA8OANzpc/2cR2QxsBgYBPw1AzCYCfW7mcOKio3hs7T6/32t5SQU3P/QeA/vE8bfbLyRvSH+/39MYX3KlkpyqHgXmdLK/CPhyu9f7gCGdnHe5P+Mzpk1acjyLJg9maXEZ350/jv6J/hmu+8S6ffzwhVKmDEvhj4vPJ7VPnF/uY4w/2Ux5Y3qwZHY2ZxpbeKbooM/fW1W5Z/k2/uP5UuaMz+AvX77AkokJWZZQjOlB3pD+zMhO5dG1+2jx4RDippZWvvvMRu5/fTc3zRjO726eRmKczTExocsSijFeWDI7m7LjdazaWumT9zvV0Mwtj67nuQ8O8Z15Y/n5NXnERNv/jia02W+wMV6YNyGDISmJPhlCXHWyns8+uI61u49yz3WT+OacMTbHxIQFSyjGeCEmOoovzBrBu3uOsbW89pzfZ0/1Ka57YC27q07z0BfyufH8YT6M0hh3WUIxxkufPX84ibHR5/yU8uGB41z/u3WcbmjhyVsv4LLxPVUcMia0WEIxxkv9k2K5dtoQ/r7hMEdPNZzVtau3VnLTH96lb3wMz33tQqYMS/FTlMa4xxKKMWdhyexsGptbefL9A15f89T7B/jK40WMzUjm2a9dSPagPn6M0Bj3WEIx5iycl57MRWMG8cS7+2lqae32XFXlvlU7uPO5zVw0Jo0nv3IBacldFsY2JuRZQjHmLN0yeySVtQ28srm8y3OaW1q567nN3LdqJ9dPH8pDi/PpE+9KYQpjAsYSijFn6ZKxaYwa1IdH3tnX6fEzjc189Ylinlp/kK9fdh6/vH4SsTbHxEQA+y035ixFRQlfnJ3NhoMn+PDA8Y8dO3qqgc/94T3WbK/iJ1fn8b2CcTbHxEQMSyjGnIPrpg0lOSHmY08pB46e4frfrWNreS0P3Dydz18wwr0AjXGBJRRjzkGf+Bg+kz+MVzaXU1FTz+ayGq594B2On2nkL1+ZSUFuptshGhNwllCMOUeLL8ymVZW7ntvEZx5cR3xMNEtvu5DpI1LdDs0YV1hCMeYcDUtNYm5OBmu2VzNiYB+eu/1Czkvv63ZYxrjGlYQiIjeISKmItIpIfjfnFYrIdhHZJSJ3tts/UkTeE5GdIvJXEbEFJIwr7lwwnq9eMoqnv3oBGf0S3A7HGFe59YRSAlwLvNnVCSISDfwfsACYANwkIhOcw78A7lXVMcBx4Ev+DdeYzo1K68tdC3JITvDPSo7GhBJXEoqqblXV7T2cNgPYpap7VLUReAq4SjxjMC8HljrnPQZc7b9ojTHGeCOY+1CGAO3XXC1z9g0ETqhqc4f9xhhjXOS3WhAisgrobOzkv6nq8968RSf7tJv9XcVxK3ArwPDhw724rTHGmHPht4SiqnN7+RZlQPvVh4YCh4EjQIqIxDhPKW37u4rjQeBBgPz8fN8tCG6MMeZjgrnJaz0wxhnRFQd8FnhBVRVYA1zvnLcY8OaJxxhjjB+5NWz4GhEpA2YBL4vICmf/YBF5BcB5+vg6sALYCjytqqXOW/wA+I6I7MLTp/LHQP8MxhhjPk48H/gjQ35+vhYVFbkdhjHGhBQRKVbVLucMtgnmJi9jjDEhJKKeUESkGth/jpcPwjMgIJLYzxwZ7GcOf739eUeoalpPJ0VUQukNESny5pEvnNjPHBnsZw5/gfp5rcnLGGOMT1hCMcYY4xOWULz3oNsBuMB+5shgP3P4C8jPa30oxhhjfMKeUIwxxviEJRRjjDE+YQnFC12tHBmORGSYiKwRka3OqprfcjumQBGRaBH5UERecjuWQBCRFBFZKiLbnH/vWW7H5G8i8m3n97pERJ4UkbBbZlNEHhaRKhEpabcvVURWOqvcrhSRAf64tyWUHvSwcmQ4aga+q6o5wAXAP4f5z9vet/DUjYsU/w0sV9XxwGTC/GcXkSHAN4F8Vc0DovEUnQ03jwKFHfbdCax2Vrld7bz2OUsoPet05UiXY/IbVS1X1Q+c70/i+SMT9guYichQ4NPAQ27HEggi0g+4GKewqqo2quoJd6MKiBggUURigCS6WfoiVKnqm8CxDruvwrO6LfhxlVtLKD3rauXIsCci2cBU4D13IwmI+4A7gFa3AwmQUUA18IjTzPeQiPRxOyh/UtVDwK+AA0A5UKOqr7obVcBkqGo5eD40Aun+uIkllJ6d1QqR4UJE+gLPAv+iqrVux+NPIrIQqFLVYrdjCaAYYBrwgKpOBU7jp2aQYOH0G1wFjAQGA31E5GZ3owovllB61tXKkWFLRGLxJJM/q+pzbscTALOBK0VkH54mzctF5E/uhuR3ZUCZqrY9fS7Fk2DC2Vxgr6pWq2oT8BxwocsxBUqliGQBOF+r/HETSyg963TlSJdj8hsRETzt6ltV9TduxxMIqnqXqg5V1Ww8/76vqWpYf3JV1QrgoIiMc3bNAba4GFIgHAAuEJEk5/d8DmE+EKGdF/Csbgt+XOXWb2vKhwtVbRaRtpUjo4GH260cGY5mA58HNovIBmffv6rqKy7GZPzjG8CfnQ9Ke4AlLsfjV6r6nogsBT7AM5rxQ8KwBIuIPAlcCgxyVsb9EXA38LSIfAlPYr3BL/e20ivGGGN8wZq8jDHG+IQlFGOMMT5hCcUYY4xPWEIxxhjjE5ZQjDHG+IQNGzbGD0RkIJ4ifACZQAueUicAZ1Q1UibUmQhiw4aN8TMR+U/glKr+yu1YjPEna/IyJsBE5JTz9VIReUNEnhaRHSJyt4j8k4i8L7XXav8AAADhSURBVCKbRWS0c16aiDwrIuudbba7P4ExnbOEYoy7JuNZh2UingoFY1V1Bp4y+t9wzvlv4F5VPR+4jggpsW9Cj/WhGOOu9W1lxUVkN9BWTn0zcJnz/Vxggqf8FAD9RCTZWa/GmKBhCcUYdzW0+7613etW/vH/ZxQwS1XrAhmYMWfLmryMCX6vAl9veyEiU1yMxZguWUIxJvh9E8gXkU0isgW4ze2AjOmMDRs2xhjjE/aEYowxxicsoRhjjPEJSyjGGGN8whKKMcYYn7CEYowxxicsoRhjjPEJSyjGGGN84v8D7ye62zZDLyEAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x, y)\n",
"plt.xlabel(\"Time\")\n",
"plt.ylabel(\"Some function of time\")\n",
"plt.title(\"My cool chart\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"x = np.linspace(0, 10, 100)\n",
"y = np.sin(x)\n",
"plt.plot(x, y)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.5.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
section_4/20_scatterplot.ipynb 0 → 100644
{
"cells": [
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\litak\\Anaconda3\\envs\\tensorflow-cpu\\lib\\site-packages\\ipykernel_launcher.py:1: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
" \"\"\"Entry point for launching an IPython kernel.\n"
]
}
],
"source": [
"A = pd.read_csv(\"data_1d.csv\", header=None).as_matrix()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"x = A[:,0]\n",
"y = A[:,1]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(x, y)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"x_line = np.linspace(0, 100, 100)\n",
"y_line = 2*x_line + 1\n",
"plt.plot(x_line, y_line)\n",
"plt.scatter(x, y)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.5.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
section_4/21_histogram.ipynb 0 → 100644
{
"cells": [
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\litak\\Anaconda3\\envs\\tensorflow-cpu\\lib\\site-packages\\ipykernel_launcher.py:1: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
" \"\"\"Entry point for launching an IPython kernel.\n"
]
}
],
"source": [
"A = pd.read_csv(\"data_1d.csv\", header=None).as_matrix()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"x = A[:,0]\n",
"y = A[:,1]"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(x)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"R = np.random.random(10000)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(R)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(R, bins=20)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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/V7TwMTO3AG9e1aJWyQkb/MexnEdJtOLaJN/t/kt7Uv6XdRn8PAxWwB1J9nTfmte8M6rqUYDu/fQJ17Miet3OudKS/AvwkgGbPlBVXx6224C2k/LWpeOdH+CTwEeY/7N/BPgo8M7Vq+45o5nPw7N0YVUdTHI6sDvJA90VsBrwnA7+qnr9CLst51ESJ4Xlnp8knwL+eYXLea5q5vPwbFTVwe79UJKdzE+JGfzwWJIzq+rRJGcChyZd0Eo4Gad6bgU2d78E5uXAucC3J1zTqus+tEe9hfkfhrdoOY8WaUqSU5OcdnQZuIR2Px+LLXzMzFXAsJmFE9pz+or/eJK8Bfg4MAXclmRvVb2xe2zEF4HvAUeAa6rq55OsdUL+MskG5qc1DgDvmmw5kzHs0SITLmvSzgB2dr8aYw3wuaq6fbIlrb4kO4CLgLVJ5oDrgOuBLya5GvgvVufJA6vOb+5KUmNOxqkeSdJxGPyS1BiDX5IaY/BLUmMMfklqjMEvSY0x+CWpMQa/JDXm/wDibBpzWE9MsQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"y_actual = 2*x + 1\n",
"residuals = y - y_actual\n",
"plt.hist(residuals)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.5.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
section_4/22_plotting_images.ipynb 0 → 100644
{
"cells": [
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv(\"train.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(42000, 785)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.shape"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\litak\\Anaconda3\\envs\\tensorflow-cpu\\lib\\site-packages\\ipykernel_launcher.py:1: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
" \"\"\"Entry point for launching an IPython kernel.\n"
]
}
],
"source": [
"M = df.as_matrix()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(784,)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"im = M[0,1:]\n",
"im.shape"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(28, 28)"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"im = im.reshape(28, 28)\n",
"im.shape"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(im)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"M[0,0]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(im, cmap='gray')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(255 - im, cmap='gray')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.5.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
section_4/data_1d.csv 0 → 100644
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