From 127b9a5fb04b87062af47a0cff3f402eb09b6986 Mon Sep 17 00:00:00 2001 From: Rishabh Agrawal Date: Wed, 8 Jun 2022 04:40:49 +0530 Subject: [PATCH 1/5] 200789_Rishabh_Assignment 1 --- w1/Getting started with Anaconda.ipynb | 100 ++ w1/Jupyter Notebook Working.ipynb | 95 ++ w1/Matplotlib Tutorial.ipynb | 357 +++++ w1/Numpy Tutorial.ipynb | 480 ++++++ w1/Pandas Tutorial.ipynb | 1900 ++++++++++++++++++++++++ w1/data.csv | 170 +++ w1/dirtydata.csv | 33 + 7 files changed, 3135 insertions(+) create mode 100644 w1/Getting started with Anaconda.ipynb create mode 100644 w1/Jupyter Notebook Working.ipynb create mode 100644 w1/Matplotlib Tutorial.ipynb create mode 100644 w1/Numpy Tutorial.ipynb create mode 100644 w1/Pandas Tutorial.ipynb create mode 100644 w1/data.csv create mode 100644 w1/dirtydata.csv diff --git a/w1/Getting started with Anaconda.ipynb b/w1/Getting started with Anaconda.ipynb new file mode 100644 index 0000000..70d7d69 --- /dev/null +++ b/w1/Getting started with Anaconda.ipynb @@ -0,0 +1,100 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "3b74e3e5", + "metadata": {}, + "source": [ + "Anaconda is a distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. The distribution includes data-science packages suitable for Windows, Linux, and macOS." + ] + }, + { + "cell_type": "markdown", + "id": "8483cd59", + "metadata": {}, + "source": [ + "

Anaconda installation in Windows

" + ] + }, + { + "cell_type": "markdown", + "id": "1bea4602", + "metadata": {}, + "source": [ + "1. Visit https://www.anaconda.com/products/distribution.\n", + "2. Download the Installer.\n", + "3. Once the download is complete, run the installer." + ] + }, + { + "attachments": { + "image-2.png": { + "image/png": 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" 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" + } + }, + "cell_type": "markdown", + "id": "88856733", + "metadata": {}, + "source": [ + "4. The following window appears.
\n", + "![image.png](attachment:image.png)
\n", + "5. Click on Next and then click on I agree.
\n", + "6. In the following window choose the Just Me option.
\n", + "![image-2.png](attachment:image-2.png)
\n", + "7. Click on Next.\n", + "8. Choose the directory where you want the distribution to install.\n", + "9. Click on Next.\n", + "10. At the Advanced Installation Options screen, I recommend that you do not check Add Anaconda to my PATH environment variable\n", + "11. Click on Next and run the installer.\n", + "12. Finish the installation.\n", + "13. Launch Anaconda Navigator.\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "58d65c35", + "metadata": {}, + "source": [ + "

Installing Dependencies


\n", + "1. Open Anaconda Navigator.
\n", + "2. Launch CMD.exe prompt.
\n", + "3. To install Matplotlib, in the cmd window type conda install matplotlib
\n", + "4. Do the same for Numpy and Pandas." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8ba770fa", + "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": "3.9.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/w1/Jupyter Notebook Working.ipynb b/w1/Jupyter Notebook Working.ipynb new file mode 100644 index 0000000..c3ad860 --- /dev/null +++ b/w1/Jupyter Notebook Working.ipynb @@ -0,0 +1,95 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "944347d0", + "metadata": {}, + "source": [ + "The Jupyter Notebook App is a server-client application that allows editing and running notebook documents via a web browser. It can be executed on a local desktop requiring no internet access or can be installed on a remote server and accessed through the internet.\n", + "\n" + ] + }, + { + "attachments": { + "image-2.png": { + "image/png": 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C9bL9f/3Xf8W//du/ISUlPJzWPh1F6ROTkJ6Zi/zDPqSPT8eQ4+XIXzAZQ4dk24LDKcicKUNR+LHi1Sg3M3yrFCskwjYjE+n9EtFbrSv9JmOoCd9N6rE8752on2vHK7HsziEYKtvechR9xsoyyWjYko/czKEYEi1IWrcBufdOwrLdRnoT91UhsY/3IS36jM9DwSM6/I3seY0b/qTmT7ORlpSG7AX5KG1INvapn8rDZ3MxedgQjPulfJVg6tIbyer1VLPHcfJoIw+SVVNh0cHRIUMxWdZ3uI+xvoENwfVN+lWl+7AfqED+tJEYOW2lejRUvS8VPd4rwcoHxyFpzGKUO/PNzOtBGbOxcn0NEnVep6oyKzbeM2Q6iiOCzA2o/NUkDLluEmY/XYyaRCP9qShH8dOzMS5pEKardcVXh/JF2Zj0m3L47liKksI5SLHlgbsUpN4vf4tRsduRAw0VKJWhTMZnIHWAqlujMiA1s1TVy/AArxUkB7JH247VJuWFoWJVDjIeLAWGGOVUgd5I6mK+6LSvEDkT56LEn4pZLxdgxR3J5gux1b66GONSxqk8r0bvYWo7o5NR85ZxTIx8MPKmnTXrp2PksMnIfbYc9fo4GwpsW4nZY4Yg+9kqcykPzEB589zkNQ7ZlteboloBfNsUkUZ9o9ULcBPYC5ZHxhckjb2xsf+FyRem/DwxvgBtO+lpR3Q9uwD1uS3Rx/D53AS4Y9Y3OabP6wbSRERE1CRfnTyD3Z8ew1+q/Kg/dcYMWqvJjLHJX4lb6eC2OU/H3/Rj4696YC6nXpPHMt+84aVQpy56UgsaPbz1dEZNp4Gzx1QirOFP2osjeOnBW/HTl8M70LZNO7HT7ZfjraBdBL87Xe5TUxISul9qzmkmnbsioWdfdOo3EAndLjFntg1W8EGCxNJTOikpCaNGjcK3vvUtDB06VAeeJSg8ZswYjBgxQveefvfdd3XgWMYjl57fErQeOHAgOnfurHuPS69qOxnKROZLALxPnz4YMGCADnJLwFx6a99000245pprdDBc1idpkHk333wzvvGNb+j3SOMj25agtfTc7tevnw7Iy3ISTJftS3pHjx6t1yXDsUgPdXtPdwl+yySBfunJft111+G2227Dt7/9bQwbNgxXXnmluWR7tgy586qQ/tsqHN1dhs2vbEbVJ7XY8PNUddVViOx7lwXHUk4em4UM9de/qtTlorwBpS+vgB8+zJ+Sjt5IwSy1roJ/T9Ovpv17gV735p9YQcg6lMzLwNw/qXfcvxpVR2tRVapef6UMe49WoeAnqfD/aS4yFpZGBn9fLUThNauxt9pKbxnmjDBf8yQR6QsKMEfi3+uzMft3HsPfe/Ix+86Vat+TkbMmlF+b363F0W1LkeHzo/TfM5Gz3gxY+TKwVL2+bKrxNOdXsn+bsfQOM1B/uARzdXDUhyzJ/9oqY33le3H03QLMGu1HycMZyH3VLfxdjPyNyZhfUovad0P5tvp+te63cpE5zx4kVWWz0MzrsfOxodaW16f3okjltezb5HsXo9K2qYZXc5HxcAn8vnTbdjajbHcAe4tnIRU1yL8nG4u3u4fnDQ0oX5SBtAXlatt5KPYU+BaJGDlmln5UsN0x8MmOchSoPykTR6qSUAaPRIaU//oyVIRFhqtR+aL8nYX0UdaXLk3LC0vxc9XIKa023qPKqXZ5hvtNNPepYyc1G4V+VVfWeQ98i5ULclH/wAbUqvSUWfVha57Kb6DmN7nIt39IS528J1+VRGpYGRnHcDIKFyxWNaWtkZvOZntKl+4Nf00RJn8iJ4nm9EkBKuRXFB06IKTahHUBFN3r/Us9CZjOMn9pQ+2ZcXyMLJ+vj3m6uPnuXYmCd9P4JRIREdEFduDoCXxQ+wXOWsFsHbS2JjPoLY+tIUyCge/QPCsYrp5AvSG4nKV7ly7o0TUBOHvcCHjrwLcZAD970uz5fcxcmprPTjx16zQ9jGpb0C6C39JLG126mU+amXwFJIFv3Zu87bCC39ZjCXRLQFl6dFskSC1BaHlNhjiRoUgkwC09qCWYfMkll+ihRySgLT3CZWxyaQgsMpa3NRzK4MGD0b9/f3Tr1rh8loZGgvMS+JYe7IMGDdI9zruoBsYi65R1S1Bb0ixDnEjQ3WLtpwT6JX3f+c53dM/vK664Qq9H9qUj8D1SgPwfDgkF8br4kPGLAqyeqB6/NRcFVvB18CRkT1F//SuwYYsjMthQhtJn/WplOUhPtfXujmZHPnKfVsuPmI/iVTkYYo8g9h6CrCXLkDdCbeqJZSjYY84P8iHv4RwkW0UZredtLD3Tkbd+vh4Ko+RHs5EfsQ2nBpSuydXjR6csLMCKB2z5pfS+dQ6K9HAqfhSqvHO/+WK4yudysVJlQcpjxeH5r/S+KQtLf5Wn0ufHsl8VuPZOz3yyAHkTbcExlW85q4ygvv/plSiy9mlPAZY9IQH5TCxbm4cMezytSzIyl1tlrdKz0Yoe16DgV8vU1l22oyTfvQIFv5WvQsqRuyqyN7KhAeW/nITMBeXA6DwUvzwfqZ4C34beKWkqxWpftlSE7X9leZFKlw+TU60vUlKQlinpW4nSbbZ6uaMMRbIDU9Iw0srcJuWFzZS5mD3WVlJudW9fMaaPl8C3D1mFm7F6ivfAtzZiKVb+IgM+27p7f3sO8h6RR5Wo2C3pF6E6mfFbRxnZj+H26q3FSFuQiYJPHDcGHZCFovI8YAEDQtTx+F+YhWwUIGe0OYMucupz5OE85D7JoauIiIgupC9OnMahLxtsAW1z2BIrgC3xKx0ANyYdDDd7detJ3hf2XuO5pVuXzuh/WRd87TI17+yXwLnTajoTmgKngDMyDIp6LRAa1pc6no4RVeyArOC3BH579uype01LMNhJemRLz2gJXkugWALLMi63kECz9AqX90mAuqamRvfStgLg1jjbEpyW3twSJG8sCXjLeiXwLoF5WYc1Lrj07rYmGQ5FXpc0SY9ze89vi/RQv+yyy3D99dfrfe5YUjA3Kx2R4epkTLpfQo/Asq1WKNeHjHtz1F8/8l8tgz383VBeinx1ZeabOQnpHmLfNdtKdIA4Zepk94BoYioy7pFgXglKK52XfOkYMtB8eB4Sv52LlY/p8DemPyi9Z2OpROkvJR3pmHVvqkt+qfWNz8Zc6YEc7eaLYWpQsVHnALIzo6xvdIYx7vXGUkRkAeZg1t32yK2pZzom/1AehPKtprxEB0jxyCxk2oOIQcmYPMPoZS3lqkO++8pRslEeRNmOkjxlFvS7ni1FWUScuB41z+Ug899L4R+dh7JXGxf41gYMQZrkp9z0Mrh+VQ5rJd+ykWrr7Z8yOlv/LXgr9LWDNd63DGli7UGT8sLGlzIkuC5XdeVYfO9k5O/xIauwDAX3NjLwrfjuSddfyoRLRB9zaJ8GdS5kqEa5fOGETGRPdNuO2pcfyvHazDwMQ2KNX25NoeE7ZGiCJGSvVw8XyBjw0YZ28KPwyVxg4dzwwLdldDrKygOY7wwQ6qEToqfLGhohuIzrWOiOZeIMPxE2VrvOm8kofCs8j9yC9M48Cl/GMeyJNaxLtP2T+dcYven1vQXMXvF6yAQP47070xL+Hist5eZY9W7LxOLIT5ce+7Hzwni/W/6E1iXLqHx/wcqfWMNnmO+1bS8yTY5lFhU6tmeIne6m8KP0xWJk3p1ua2e87r8sEyevHfXHrQxj1QX9WrT32Lal651tHa75EpYWVV4ef4AVP8/j5IGVd1GXMV73Ut/D0qJeL3TJn7h5EdGeurQ3qr3LW5+N/POuX0REROTVVw2n9fjeVvA6+DcsoC3Bbnls/TVfC5tCy1k6d0rAiG/48E8DzuGyLuqk9VyD0dv73Fkz8G1Np4CzX6jphPnODuKzl/DTW2/V9+HT0/Kd5gsmx+tPvSzPf4qXPjNfFzueCr1fTfahVo68/FPc+uBLsEf2QvOMXt/Pq3nPT3fZditg8LuNk+C39OqWoHE0EryW4UZkWbkRp3UjSgmGyzjhMkmQXIYckZtwSsBaJhliRG64aY3xLYHnxpKe37Je2ab0Il+3bh3mzp0bMf37v/87iouLdW9zGSfdujGnneyHDKUi6ZaLk44lHSk3mg8dfMkjjQe7aoIXc73HZECHvyXgGcyqBpRtXKyWScHcO7z8ULsBNbuNH5nUrpmLcd8d5zrNLdSLoFBtP9xQJMWMQHqViNR5KzFfgqgbpyP7V6HAaYT9NTAG30jHUHMM70jJGKJ3vxI1n7j0GrZrUOt7VR7UIv9h9/0f9925engPlQORN328eySSo3zJkDzE+NLCyjf/PmMohMyUoa5BdtH7mmQj4FpebXwJ4K8xhqWYMhJDo74pCck6AO1yU8pV2UibagYB9tXiaORh5UGoR3fZe8Yc7KlAiXyxMCMdI23pShyVrgPxMiSPUYoNqKqUPUhBxqhQYLhJeWGTNjDJfOSmDHPGpyFXByj8qPHHqQNRRNtG0kBjCKGg/dWo0Bms6oJrIN/Yl2Y5VCwSqLlGhmQIndDVFmYiNzUUbJSAUNq7Bag1X5dhSpBl3Sg3FfMDtSiQX5AsLFOvRxvaoQY164E8GYvdVSpSI3rG5iLtyeTgdssWSiDYHkiSoJgqH71dc5lh2UiyB5t0ICoNFYW1wWVqCyuQFiUArvdV9063B+KLkZ1qG6qlPE8HpENBLyO4lrYgD2XmNiKXcRNj/0bP1/ksR36elM1jRr757i1CYF1WzDoQUV6BMh1oS3IEDYuz0lDzsLmMbEstM8vDmOS5qUuRbMuL8B77Tc0LNyrfs9RRqNfj+LVAkGwvCdnDQnVA74tKU+gLGucyqr6+m218YRPUnOm22V+KovWZmDymaUdtzLyWYHNqha6rwf1CeDnHqwup49U61xehNOyLhXKULggdqxLsTVLlENyOOUxR2Pj1Oi25Rl3Vy0xGUVau+WI0Zp472hZZtz3P49e3eOVviFffnXklbUm2eXNrS9y8cGlPyxaq4zwi0J6KdDneo91vhYiIiJqdjPn9xYlTYcFu6MfhAfAE9bdbl07o27M7rr6iJ67pq6Z+vXBN/174up4u09O1V16OZF9v3DCgL755QxIm3dIHw3yH0PX0LiPgLYFvK+ht7wF+Vl1Tys0wOwoJWmcsQvLq7di+XaY1uG/tNFsQeieeUq9jwabg61i4CG+arwodyJ5eg8dKzHWUPKaWmeBxrPHheEi2qR7dJ2l4cLgxuxUx+H0ByAF7PiSoHSsYLD2mJbgty1gn9hYJJMtwIzJet4ztLeOCS/BZhh2Rnt8SVJee1hJgl2UbS7YlgW8JgkvP7q9//et62BPnJON+y/AsMva39Ea/6qqrzDWEyH5KALzjBb5FH/SIFgV00y8dmTPUX38+SsvNiGZdKYqfUH9HZCPd1hs3ujr4zWCp/71SlL4aZXov/PKvRfRMRe5vjOFPyh+ehWVxe2zH0ht9zLhl7fE40d7DfjOw6kf1Fpd9N6fqaFmgDoke5sNm0S8JOkS8oyGsR39sSUi6Tv5WIuI7I78f/tHzMX+GTz1eiZwlLmO3e2D16C7ZZoS0/dtK9NhcmWNGho+13Xsk0vSQPKWo0MO9VKL8OfXHN9noPd4YTcoLofZZhjp5bL4eG7/84VwPw+m0MF8yHCHz8+LfWoTiKeFDMvjGTEYmilGjA2KqXr+r/gyzBd1lmBLVHkf00o5lfw0qzIfeZaLgyVCgN/UBCQbnotQMfPlfWKqe5aHMDAyL1MfK1JxcLDWDUdb+rbSNta0DyC5BeglsGYHvyEBrZuHK0Dx1HOhAtTVswVv5yF4v77Ot07mMq9j71zRm4PJhe4DcCLTh3dCXntrCslAZqjKdq5YpfrE0RnoN4XmRo7/4CAbxmpwX7jILcyLKKYwZXC54wLbUgHRMVmkq3mN+1aXTZK8n6ph+UvLappnTbdH1L8aXWfHEymt/jRxR9nWr/VqnzsuC++mhLkgPZJXCoq22PXyrVB9X6bpulCM/qzg8HaqurCxULURWvvFFjVqT8auO8Poky8RklZ3tGHBrW2LWNy/lb4lV3/cXYqkc+/bjUbcldh7yQrVzaomw8k59TJWJyxdWyYNV/jiPSSIiImox9afP4Fj9KSOOde6cjivpHty28bw7JQC9enRF8pU9kXp9X0y6JQl3ffNqfF+mbw3A90d/HXeraXKqTNfinm8n44Hxg/HoD4ZiwpBD8HX/B3BaXUQFe3q7TGe+6FDB752vPw9MXYOHgtfow/HQ6vuAtaWQ8PeRl/PxfNpjWHBnX+Nl6/WgI3jjtTdx24IFuMu6Bd+Vd2HBgtvw5mtvhPX2bi8Y/G4Bxk8qjUkOVgk2O1kHsj1QHU285WSsbGs4EwmCO3uJS3BbbmYpN8KsqqrSva6ll7YEvyVgLTeVTExMbFLQWd4j25O/0mtb1jVhwoSYU2pqqg6Su2lKGtqHevOvV72RPmW+ujALDX1St7UEK9Xf9JmZRo/ZuBLRu5/xKGtdqIdl1MkWrGoJeviThbKNcsydEbrBZ+PV4Wit8Si5X5yhenr2hhEnVxfvtS777JgiAofqczBeyfm6NOJbjcO1RjB+vC/ioju6WtTulr/p8JnlGSRDnWzMQ97CfMxSK/Q/kR3lxp2xWT26Kyvlor8OFVul53Y6MkY5U+lD6vh09bfUGO5lTxVKJUpwf6rHOmnTpLwQPmStLUPBQrXfT0p98jKcTguz9qWZ2HsSB3/Obw63YfAh/e7MOEOatJRYQUNjOAksTHcER43gnhH4MpexB+6jqHhSenQWI6/crYdxZM9do8dsjS6LyCCkwb1XrV3Tg6LRSU98q30JDReR5ujBKjIHN34IHzEyOXpuNj0v3MXalqaDpWaZBYebSArr1V3+ai4wJdn4AsxiBkgtzZ1uS80eVf+c226EWPtvfEmVizS1z+69073UBfN4CX7pYQWyzeNKB8Ij67+x7QrzCzL3X3UEf2kWhdcvBmLWAQ/lb4lV393TYn5RYPGSF+aXCdnXOHrGu9D5Y7YhRERE1PIkICmTXIvroHdwPG/rGv0cknr3QObogcid/A3MGncaU0Z8hLuHfYi7h3+IzOF7MfnmvcgcUWNOH+LOf6rCP1+zFVfj/6JbQylw+oAR4Lb39NZBb+kFbg6Bck5d9cvwJx3CEXW+C9w28GrzuWlEOu6Tc8TPgAP73gTUeZgV+tauSsZt5kO1BGrKgOSvhy2Bvuq86rayGvVq+8PgdwuRgLD0yJbhRSToLAFsOzmQT5w4oV+PRd4ny506dSpiHRYJZssQJvK69OCWYUzspNe3BL8lTTLMiYz/vXv3bj3udt++fXWvbGfA3GIPRkuanaS3tgS9rR7bMua3jB8ea5Ke6LLd1lWJld8dh7TrYo1ZqvKuZxMCm67KURWld6pxga8uuhzjHCempiNHzfD/sgRlDXUo2yih7wxkjfV6yd4bSdcZIcnSiCFNWkMiUn+2DHly0f/WXMz6ZVlkYHlAMkbqTCiNml9yUV+to30pSOofp3yCQ4aURg4Z4sWLVWbwwcka7gNIH2yE13WPMaW4sipqT+a6mmoj6K/e00f+qv3V71pfgapobzqs9lf3lB+CJGfwOyMdqRL/75eB3OUSLPVj2bw8lB83XvbM6tH9XBmqjlej7Gn1eEQGRroMPZM8KkMHuguld1xlqe4hPmvMyLDhTZqUF56lYZJ5DKTMWGnUp43TMfe5FqrjwTppBZUi1X1Scx5f5rgIBowSzOCvOvGTIQHMl4UOkMtwA2agTZZ1Gy83Jtk382Gz0kF5M03m5Az0egnyFq9Xy0mP0rBhVRrhPAKczU2GbzDyIg25U4xhHKQH8wVzQfPCGDpD7698aaOHwDGH4WmsNlSGnujAr9E7WY8Lr8s8/DzDS10IC/DrntTOQLYRzDXWY072L8ii/arD+syJ5bzzvBnL35M4eaG/cDC2X5yVFFwm+tA50dt6IiIial49unZGz+6djeFOAtaQJ0bQW/2DS7p1wfdSrkL6DV/g6m6v4zK8jUsTduESfBA2XRrYpaYqPV0SqEbiuQ/R+exnSDirLozPnVSTGei2enpb435bgfCErmpq/EgI7cpnzfAF/8GasKFR2hMGv1vIJZdconthW4Fp6Z1tkYNZgtmffPIJ6uvrgyfidlagWQLacgNJGVdbguBOsh4JYu/du1cvK4FuCUbbSWBbgt8DBw7U6fnHP/6BXbt26cdWYFwC9W4kXRLglnVLD3ZnAFzeJzfjlBtUSjrkBpqyT26B8ralNxJRivI9ZZEXOQ1VqNA9lHwqf2w9i9VF4xD9wP3CqGabNQ6ym1IUb3Framqw4Tm5RPMhZ7Sx9qDEdEyaKVG3ApRvLUOpBCSnZGNS1LGwI6WMzdaBSv8qdRHtGhA1LlIHpY7D7PWNCps1Tc9UzPlVnu69Vv7vs5C71ZgdkoLUB2SfS7HyhXLXwGnDqwVYKsFgT0NtpCA9S+cAVhRHGRJEBxoHIe27s1EcUa75KHLrSX1YlacM94FMTErVkVH4RmXoYTjwxEqX9YgaFP0uXz8KDicyIBUZE+XBMqx80T3/a17MV6lQpqRhZIyO7r4peVgmwYUdi1Ueu+dddKEe3ZXry/TNKn2ZabruRBiRZtwg9L0KFG2TAeMzkZYSnrAm5UVTJKZgzhPGcDrF83JR2JQvOOKy6mQxCja6HcN+lDwnX0w1n/Jns/WwINY4txG/SLCMnq9f15MEwl3GkI4tGckSXI46xq0ZxGrUOhUd7DLTZZ9svy6JGP7AhfT4LlpnDJmS5iEN1heJQVF7cLZE7+4Y9PANsj9mPsQZH7xFXMi8CA5XElnujdZWyrBRjN7dRr2X+ivBWfMLHK91wTb0idED2hryxGLL37DJ7HEd7YstPQRIHOfb87k5y9+TOHmh+YzhZ/R8IxBuv4dCuLZct4iIiDqWHt06o1ePLsZn9Dmz97cEwNXUuRNww9V9cPOAkxjQ8xN0PfchcOYzc3xuGaZEblKpHp/93JjOqOn0EePv2WPq9ZNA4LQR3I43db4M6NTTTFV71xfJg4E39zn6Z+vAtbr+uxK4euBtgLoeCxu+JCywfTWS09RV+8fhA5wc+VidJaYlq1fd6R7lbRSD3y3kyiuv1L2gJXAtg8NLkNoiwWEJEst8GYdbOIPfdtI7vLy8HNXV1bpRsNuzZw/eeust3bv8iiuuQHJysmuvarnp5Q033KCHR/nLX/6ie4BLGqUXdqxtSwBfxgKXQLkMk+LsfS7Bbwmqyxje8tr777+Pv/71r3o7bZu6MBxvBEVzf5aLkv1mqLDBj5KFuVgmj32zkX6rnmtKxlDdc6kYK1aVwn6bPf/GXGT/SEKG0ZX8KBu5G20BzjNqW/+ejekb1eMpyzB7bGQv5tQ75iJFpbFoQZ6+KWPOvRkxgybF1Y5L1hFqm/erd/iXITtrsTFEheVMHcp/lYM561Wjtm8IMsZemHBM4ug5WKaHP5Gxm415IYlIn5anA6eVC7Ix+9nqsHyu274Mk6cuU+/0IWu5+7izFbvD8yDl3lxkSRY8kY3JvyyFX322BR0ux7KZc1SJqov9wRlIj7jg9WPZ1Bzkv2dLRV0llk3LwUqV9tRf5CLTes/gbMx5RPKwGHOmqjoVltc1KH7QLOvReci928rrZGT/bI4u0+KHHfVDqXlxtlmvUpE3LzNm2cu6sn6x2hgHe4HK4+2NC38nD0tX669E0W+L9Jc42aNdQ99KClLvV38kKC83Ex2fgVRnvjUpL5pGhtNZKtvyF2LOgmJVYs0tVCddj2FVT+UYaj7GeN6Zd0t5hBgBsBhGz9c3xWzceLXqOHo4D1iw1D0IpINYkUMnROdT9Uj9iUiDEUQ3hhyItkw0qciR/YpIo2NMZEUPZ2EODWEM7xD5RaXrcBstTQccncFLY+znC6ExeVFRY89T1S42oW7rLyGmTA5vT83eyxb7EDVBjmVaqgz1L1OiBHibY//DpWK+/tWGuR+e64I19IlqZ51DCene29b4/zZyg8vgMEjuX2xFfEHkEC3PG8NL+XsRPoyLxZFXnvLCSbV7+ku1yPcZab/A7QMREdFFrGdiF/S+pJsR8LYFvuVxl04JGHZtX/Tv8Sm6BA4ifFiSgPpfJkcPbpmcvbrty4QtJ5N0Uu0EdOlvBMA7iOHfkfG9p+Gp4L3WduKp6TIOeDrk1pN978zBfWWLsDB480rz9aC++Pbtt+HNhQvx0mfmrM9ewsKFb+K227+th0vp+3V1xqTW8Zy1DfV6/lrzseYeQG8t7SL4HTi6H4Hjh81nzezsGZz7dA8CDY0dJyA2ucmjjGstQel33nkHhYWF2LhxIzZt2oT169dj3bp16N+/v+4hLpxBbYsEpmVcbuklXlJSgv/8z/9EWVkZ/v73v+OPf/yjnnbu3KnX873vfS9qL24JiEuQ+rLLLsNnn32mg9kSEJfxwGOxgvhfffWV7jH+pz/9Se+DbPPzzz/X6ZOe5bfddhv+6Z/+Sc+T/fz973+PV155RadTgvxvvPEGXnrpJT1JgLwtSHkgD7OkF7W6SJp0TQ+9Lwk9kjDpl3K5lIq8F+eELjY1HzLnmb2WfzkOfa5Lwzg9dEoCkjLy0efJpXrcZHfpyLofWJyRhKRh4/T7hl5jbmv0fGxeFaX314h0ZI8AKt8qhx85yBjj3kdWLlj1+xdlYmi6Wr9arxH6VGlepS61x/rg/1MuxiUlGa/r7fdB2sMl8PvS1b4uRYZzSI0WYxv+xM3gHKx4eZbK5xrkTxsazOdxw5LQZ9RclPh9SP9FMfKnhOdYcKiNqapM1PLTrWEwBmQi/8U8pPvky4ZxSLpmqLG+9KFI6p+GuX/ywzdWXQYvyYjsgXz3fOSNL8X0YX107/hx303DoD4jjffcX4CCR1Jsw30kIn1BCZbeofJ6i6pTwbxW7+k6CJN/o8pa7VvRC/ORYvueI3F8HkqezIDPXxpWP6ReDcpcqS7ek5GzrgDzb40zxItQ6zfGwS5H7k9WNm4ojhGpkNtelqu6BlWT00dF214iRo7RI4SjUn3QpUwc6RIoaFpeNI3a1jxzzPPnZiHvT/avS5qJ1Ml1OWo/yyOP4UU1mPSAOZCAh3Gs4zOCw6Eb1yn7CzErywh9G8E5tx7Z5o3fHEHzuPQNBKVnqqMXpPwiIlXGGbbdkM4DfUM6Rw90/wuzIDc3nGve4FLfRFItM8s+/q4OVrn3xPTduxIFU1QaHw4f1qU4a1ZoefV+fWNM6yZ7+iZ8th63Qi8Dx80GLwAdoAvd8FOUL0pTc5Tz7WXrhae8MIKl9ptrBtPYSDqAqso3PzishKqvD5vDUFhfeug02Xv0h5YJDonTQmXoHlRtnv03xugPD7oav+Qwg8GNqAvGFwS5yF3v+ALKvKFjeM9l1Tap4zV0M1Kf+cVWWmh4D1s7EpWV52HHmjE2ebzxsi2eyt8LtZ9zpW2ypSWYV1Zb6yUvXNoW68a84V9CmF+gNUs7TkRERF5cfkk39L8sUY/1fc4+1ve5c+icACT1uRSJXaQXtz1eJ0FvGRZFgthnzckKatsfq8kZ8NaBcJms52o9nS4Hul4JdG5fPb/fXDgBt956a/j04EtGb+4RD2F7yWOomW69Ng3PT12D7Q9K6FsMx0PqdQTXMU2dNz5mG/NbAuS/xvbVyViUYa4jY5FaZhN+bd0kU21j04Lb8Ly1DXXqmaOeh1gBdLUNK12tqH0Ev48dxtmPd+LsJzt1sFrNMV44H6rCB77w48wHr+Pc5x8DZ7z3kgwekGbAWgdN1WR37bXXYsSIERg0aBC++OIL3Tv7tddeQ2lpqb7ppASrx4wZg379+ukhUZxjf1vrkyFHJGAtvbbl8bZt2/DnP/9ZB5hlXTLciQSnb7/9dnzrW9/Sj91ID27ZlqRLtiVDo8hwJRLcjuVrX/ua7h3u8/n00CsSxJb9kIC+BLotssx3vvMdjBw5UgfWJZ2ynKRTgvYSMH/99df1cCtWb/dW1y8DK7ZVoWhhDtJvMi91fEOQ/kAeit4twfzRkVG5xFvno7RmA5Y+kI4hx8tR+moV6obMworSSmz4WZp5c0U3vTFpYQmqCudgJKrU+0pxVG1/1vLNqN2qLsCiBp5TkDlThqNQZmRGX270HJRIT+jBflRvKUXpliqY94TUQ43Mf6UaFcV5yBnbB0fldb39dOQsLEJV9WbXfW1RMvzJb4wvEtwk37ECZbWbsfoRVTaJNTq9pYf7IGPGUlU21dj881Rb0Nngu3cpNjySgSG+GpSr5fPVRbZ1VCfKFwzvVhhl3e+osb4tR9FnbA7yiqtQXTofqW6fdV2GImdNJTYvyYHvsORbuQ4O6PeszUKyc1iwnimY83I1qoqXYtaUZDTovDbeM2eNKuvq1cgcaC4blIiUn21A9btFWKrKOLnBKJ9ylTs5j6zG5tq9WK3W5VVwHGwZV/1XjQh/J45E+gzzcZwhVnqnpMEI9/owOTVKD/Em5UUT2cY8X/mjXJS0wHelyVNWo0KVUd4DqejxnuxLFTBqDgpUvVpxb+P7CYbGA7ZPRtAs9TH5Wb5tLO9rijD5E2McYWO4EJ++iW3Bu/axtdOQu7AMRWaAWS9jBr+iBZUtqY+pz7PykQgbN/eabIyUoRkaPWSBDPmg0mob9zspayTKAuoYM5ewxkUeaRt/NyG1AgWfuN3YUpj74giY5xVORpGV5oj3Sx7JWMq2fNTLxBhGxgsdkDPLzxxjXQc8Y423Lvtbnhc23nAayoye+ufZy9YbL3khy5hfXJjLLB1c27Rxyc1fIYTqeBKK7jbXFQzwyvbsdViWKVP1Xr9oaqkylBtrOn850Dz7L2Px1xZWhNKrprQFeSizhjdpTF3QQ5+IyCCtsR3Yjtk0VBTW2o5/RZWDDIcULAdpRwqNNUZn5vmwUD64rjsWT+XvjbRN9rRIXjnLJG5e6HwIb9+SsqDqka1N0oxe5d5/6UJERETn66o+l2Kw73IjMKljbBIADwXBu3XprF4zg9ZW0DsYvDYD3REBbnPSy5nLBOfZHsv7Ezqr69aR6rr/CrX+6CMitC19cdfy7bqTacS0/C7dK1u78i782v5aMPBtcrz+kD7fTNbDogRJEN22TDDwbdIBcut1te3h8tyWhuDr9nS1kgRVoZohktyyztW+j7N7yhA4fgSdB30LCX2/joRe/ZDQrYfag0bG71VlD3x1FIGjB3D2YDXOHfwHutw0AZ0GDEPCJd5GnpVgtfRofvzxx/Xzhx9+GKNHj9YBZjsZ61t6SEthHzt2TB+8iYmJeogQCYzLjSZffvllPZyI9Jr+7ne/a74TOHDggB4+pKioSAesMzMz9dApO3bs0GNrSwBbhiORHt3Se3vUqFE6uB1t7G5RU1ODP/zhDzowLdufOHEiUlKiDW0QIu+TfXj33Xd1GuTCYdiwYUhNTdXDrFhkTPKPPvpILys91a0besrykla5Eaf0Pr/lllt0sNwi+/q3v/0NH374oe4tf8cddwR7xLd/0mNKeirJmJTRAjux1fxuHAb9qArzS2uQ5zI0ChG1Lgl+yo0pfb+oQO3P47epdJ6kV7oZnD+vICi1McbnJS5Auepj9sXJqG2N8dfpPMivXoxguudgvFfSQ/zJZNYJIiKiC+jsuQB2H6zDujd3Y2vVftSfPGUEvs+dQ68eXTE385sYdeVf0LvL+8C5Bhg9viWgLVO0x27znK+r5xL47pYE+H4K9PinC97z++2339axsdZw5OWfYsLCZKzZ/pAeBkXNwUsPTsCiwfbe4a2vOfOoXQS/Vc3EmXc24Mzf/gvnjh1Cl3/6LjpfPwad+n5dVdYeqs52BTqpiiuB8IQEY9JvC30zFJBveM6cRqDhS5zb+3ecrS7Fuc8/QadrR6Lb9+Ygocflxns8kDG7ZQzuX//61zrYPG/ePB18dgs8yzjY0hO6trZWH8SXX3657p0tQ4UICaTLfAkQ29/vDH5Pnz5dB8tl29IDW/7KTSZlXV4CxRKElt7a+fn5+v3Z2dn49re/7To+uBsJeksPdum1LYFs6Tku+yLpdpL9kfTJeOfyV3qsW2mV/Xa+R5aXfJK/sqxMHcf5Br8rsSxlJOb681BW6+ylREQtz4/iaelYuT8Jmb/YjFlh9wEQDSidl4xxT/gx6+WjWHGHty9R6Tww+N3uGV8YSe/b0OeiMc/xK4EWYwRRax5mHWqzJBidmqtvDhosIz0v1q9Emor1gYiIqLUcqz+FXQeOonTnx/j4sy/xxVcNOH3mLC7t3gXTJ9yMm3q/iss6VQPn6hEZzJZwZhcjcC2P9Xw1wVrGWs4+X/1J6A50+xpwyc1A7wnmeN8XNg7VmsFvsXP5rZhmH6M7bFiUtuEiDH6r+nn8CM7u2oJTr/4GgVMndNC7U7+B6Jw0FJ2+NhgJVwxAQs9+SOjRS1XcrrpiB06pg+Orozj3RS0Chz8yepAf+AcCJ+rUMp3RedA30e27D6FTH3UGLcFzj2TMbBnCo6CgQN9k8sEHH8TNN6uDJgrJYglyCwnsSvDXLWhsFy34bQ8Uyzqs9cUjN8aUYVJkKBLpXf1v//Zven1eA82yPWvbIl6Q2p5O0Zi0diznE/yuQ/XvZiH9R4UY+du92PDDxg+tQETnr/JXIzHy4Uo9znvZb7OQHPwBRgNqXpiNcVn5qPHNx+aaPKTzxxktj8HvDqF8kQwJYj7R8i5Q4Nuk61EN5l7IbVKjWL+qCWn6r+hi0dvZM7cJwzwRERFRczhz9hxqPv0Ce/11OPxlPU6ePoPuXTojbejVSOr0RySefQ84ewLBQLYOYsvUCeh0GdB9kJonMT0zAA4JdkssSv2VQHenS9TfLua8BPX8UvWea4AeN6m3SWfSCx+nau3gd3twUQa/pff2ubqDOPv+X3G6rEA/TpCAdY/LVF3uaQyB0kVV6s6qQltDocj4PmdOIXC6ATj5FQINxxCo/xKd1Hs6D/kXdEm5C50HqoyU93is7CdPntTDhsjNHGX8ahnY/Qc/+IEe27s5HTx4EH/5y18igt9NIcOJSCBdeqtL+rOysvDNb35TB+6ppTUh+G0GdoKXe6PzUPaqujhvX/dfIOo4jqvjeLw6jvUN3JKROj4Z6hMHte+WolqGDdY3jd2ACz52PhERERERUUdW93ugvjI8+K3/qkkC2p37Aj2kM6rE9azgtxn4lnBn92vV60OBrtHv0NYaGPyOrznz6ML26z8fnTqj0+U+dBl6O7qm3Ycug1OR0O1SBOr8OPfpbn0zzLM123B2TznO7n7TmD58C2c/qsC5g1U4d+QjHfyWXuJdRt5lBL6vGa4OFBl+JH7gW4LGkvFyA0cJJMuY1jL0R1sNIkuv6y+//BJvvvmmvtmkjMMtvc9lbHLppd6rVy9zSWpzBgxBmr4Bpw9D7s3D5hcY+CZqVXLT2K212LxmDnLGJqJGbpiqpla9aSwREREREVFHJ8Fs+40q7Y8lIH7qE6BuI3D0JTW9aEyfFwFH/qCm9cCXZcDpz8yV0cWqXfT8liSePn3auNmiet6jSwLOfWgEuXVg+9hnCJz4QlXoBqO3t02C9AZP7ImES69AQp+r0WXwaHS54V/0MClG4Ds+2b4Ekn/3u99h9+7dOh0yVvaQIUNw991367GsvQ4f4pWMEb5161Z9Q0wZpuRf//VfccMNN5ivxidjfMvwLP/xH/+BvXv36httDh8+HBMmTNC91GXcbiIiIiIiIiIiojbp83zgxHZbz29rsvUAt6ZOvYBu1xi9vY+/DZw+CFz6LaDvZPV3pLnCtoE9v+O76Hp+S7BZArkyfEfNvn04dvIMEm4ci27f/Sm6TfgZugyfhE4DhiGh99XGuN89++qp02X90enKwehy/Rh0+/a/ovtdC9A1bSoS+id7DnwLa5zqzz//XN+w8cYbb0RGRgbuvfde3fu7uQPfQrYjAfbBgwfjmmuu0cHrxpA0yTqOHz+ub0wpN7e88847cf311zPwTUREREREREREbVxn6FFMrN7eUaezQFcf0Os24PLbgZ63qrdebgyNIuN+00WtXfT8fu+99/Dhng918Llzl85I8iUhZWQK+vW9Ajh7RtXzk+rv6eC43tIDPIBO+uaXMh44uiaq+t7VGBO8ETe2tJMhQw4dOqQDx926dUP37t3135a6gaMMWyJBf5kkkN2jRw907ty4tMt7q6qqdIBehmaRdTDwTUREREREREREbV7di8DxrcCpA0aAWyZ9w0sZDsX2WOZfegvQeyKQeCPwRamaXlHzRgB9/wfQrZnvmH2e2PM7vouu5/eRw0d04FuCuQ31DfpmkPUn6hGQQVC6dENCYi9jWJPeV6HTld9Ap6QharoBnfpei4TLrkTCJZerin5JkwPfQgLP/fv3172xL7vsMh38bqnAt5CAt/T2lm317Nmz0YFvIT2/r7vuOlx11VV6HQx8ExERERERERFRu9A9GcbNKhMQ7OEtQW/nOOAyr2Ev8OXrwPG3jCmhszEEStcrjXXRRatdBL8TOiXoyaIfy//O4LMEt6V3d7ceSFATOsvPGxzLnAcJQLdkwLu5SVovvfRSHQRvT+kmIiIiIiIiIqKLXOJQoOe31d8hCN78MuIGmGfVguq1M0eAY28Cnz0LnD0K9P5/1HvTgATvwx5Tx9Qugt9f+9rX9FAnMna1DOFx7bXX6qAuERERERERERERdUAJ3YwAeJ8pQP8fAZePBy5NAbpda4zpLWOCyzJd+gLdBxvB7isyga/NBi4bA3TtLyvRq6KLV7sY8/v06dOora3Fp59+qofu+MY3vqGD300ZCoSIiIiIiIiIiIjaCenlffY4cPqg+lsHnPlS/T0GnDuhXuyk/pfRHy4DuvY1hjmRm1/KzS7baOCbY37H15x51C6C30RERERERERERETt3Ycffoi6ujrzGbnp3bu37vzcHBj8JiIiIiIiIiIiIqIOp12M+U1ERERERERERERE1BgMfhMRERERERERERFRh8PgNxERERERERERERF1OAx+ExEREREREREREVGHw+A3EREREREREREREXU4DH4TERERERERERERUYfD4DcRERERERERERERdTgMfhMRERERERERERFRh8PgNxERERERERERERF1OAx+ExEREREREREREVGHk1BbWxswHxMRERERERERERERdQgJAcV83Kr8fj/69OljPiMiIiIiIiIiIiIiMhw9ehQ+n8985g2HPSEiIiIiIiIiIiKiDofBbyIiIiIiIiIiIiLqcBj8JiIiIiIiIiIiIqIOh8FvIiIiIiIiIiIiIupweMNLIiIiIiIiIiKiZnbkyBHU19ebzy5OPXr0QN++fc1nROenKTe8ZPCbiIiIiIiIiIiome3fvx/Jycnms4tTTU0NBgwYYD4jOj9NCX5z2BMiIiIiIiIiIiIi6nAY/CYiIiIiIiIiIiJSpk6daj6ijoDBbyIiIiIiIiIiIiLqcBj8JiIiIiIiIiIiIqIOh8FvIiIiIiIiIiIiIupwGPwmIiIiIiIiIiIiopZz9jQO7XkHf/3TWqx9bi3+8Go59nx62nyx5SQEFPNxq/L7/ejTp4/5rHlU/X4qHt9sPolwOx5dOxVDcQivLZyDstRlWDC+P/DeWkxdAvO19szYr7V7zKcubp+n9vUm84nT4dew8OG1GGgt45IvVb9fiIOTFuD2fuaMNsXaf6uc3Rl1RJa5FdunPg7EypMOSucBHsXaf20jNV7q3oarsKCtpCce81ixH2oxj61oHMfYoVcXYk55GpYtuB2qZWqbdJr3YeqTke1AsP0d11bqVhXWtulj3Gyzro3ML10XntuDwfebn1M2Op8/mqrqyc14x/5Z5ir6Ns5beztuowjlp8tx5/xc9KSt1zsiIiIiakn79+9HcnKy+SzcqVOn8Mc//hE7d+4050QaM2YMJkyYYD5rXpK2K6+8Et26dTPnNM5nn32GoqIiTJ48Wa8nmpqaGgwYMMB81j7IDS/Xrl1rPnMTO+bW2JiAXPNtTFpgvsdYd+xru5bm3L/YsTUvvtj5Apau2IiPGswZNl2TJ+LBn9yLmz3EF48ePQqfz2c+86bj9/werC5iVYWVShs+WYXWH7cvWNuKFaqFSeDJdf8beSF+kxz4tor+3toYXyy0BapcM29Xf1/DH149ZMxyOqxe08G5W9V+DcXUxuYJtQDVwK4KDyS3ZRIom/pwGdKetB1bT07FviVq/u+rzKUuPvLBLe2DBGvbzJcqbV5/XHWt+vPRQXUU2B3CO+XGEbGn/B3Ha1XYLvmcerN6d2t+lrWv45aIiIiIqC2QoPM999yDvLw8PeXk5Ogg8c9//vPgvJYKfL/99tsoKyszn1GTucXc5t2O15ZMxdr3zGXiOfwann6ubV1NVf1+DtYiFE99dNxreHzqWnUF2jQH/7wQDy+VwHdXXHJ9Ku68fwbm/GwGpt6RisG9uuJ0zUYs+5+P4YUPTpjvaF4c9oQ6rptuhYS/IwNGhkOVZdiDwZg6icE5agL9BZCqP85ez/1uxwL1YYfNj3v/sOtAYvVSptiG3qLqzZ4yvHPYnKEdwsE9qp7Nm4rBztcOH8Q+9WdgEvOZiIiIiIioTbhpKh4dB7z2djvtEGd2FJUOpdaV5tB/fRS34zVsb0KM48R7a/HLwj043fVaTPz5b/BM7gz8YHwqbk5Jxe1TZmDB8t/g0Yxr0fX0R9j4f36P7S0Q/2bwW3qsLZyKhdF6Bwv5qfPUqfpnD3rqiD06Hfu4ttKcb5HhDcxveSS4NXXJa+rRHqx9OE7etaqhmHj/YJdgkjB7Uw5OM39WIT9Nd3wzF6vcdX4sxGv29brM0z2D21l90eW78DVUyd/g/jv21TxuQq+7fKsZ57jR2/n9a6H1/H6jKgPzZzWbH1fzmv6tYstT+1+sjoFxP3Af9uemW/FoxM+cjDoWzA+Vx231yGmquIHvRtcJ9brV9ui/ofdGfrHQAfJXf2G3Bwf95nPx3nZ1ijEQV910lfo3/DXjC7zbcWvwp3HO9thxnP7+HXO+nXMZM/8dZaPbMmuZsPZA8t3tuPXQRnQQ0fMmkvWZEPaeDtgWEBEREVHz2bRpE/7yl7/gmWeeQW5urh5GRObJZOecJ727ZXlrkufW/BdffFEPt7J8+XI9fImQ9botb5Hlli5dGnz9ww8/NF8hV/pXvcZ1akTczIoflam/5jCq0ls8/DrMcU3ldt3gvMZ2LOMtvuMgHfrWOuIZZserxjuIvxa+hi9wCf75pz/HvUMuMefbdL4EQ//fn2POuMuB0+VY/cfm7wXP4Hc8UpFURYT8fF9391+GqR+pC/yOdLEasY+PAs9F/wl7//EL9M84IL2mn2zbQ8b0T0lTqdyDskpHaR1+B2VqB+3fZIWJV+4uQaqqt40vBELzDuHgRyqXrmqHvTL3rMXjB38Q2vfBe7B2lVXnpQGeY4wbrF9Xk/5Zj60B9XrcbF6rx7HSy/zrREzV21Lz9U+Hzm88qZYlvXFV/bklWgqHYmhE4PtxvGb7SdSj167FnDYd4G8k9eEdN/Dd6Dph5e9reLz4KttPruTEwJ53HSV/++MqVf/tPQQO1apTDHNoplsdvQcOSSXUr7kxj1P7T9XUs/Ax6ZzHspSJcxkjYGvcG8FYz9p5A/UXn0YwW4aMch63HtqIDiJ23kSx+XHjPgv6PSrvVLnM6UjnFERERETU7LZv347MzEw9FEq0McTtJJC9bdu24BAqDz74IP7+97/rAPYtt9yCu+++G8OHD9fzZbxuCXRL4NxaXv7K+60A+FdffYXi4mKMHTs2+Po777yj55OTEQvCtVepKzzjOs45IoGOH0lnzDR1NfDkVMjllIwTbh82dM9zj+NgpnmdIcvsWYun7UF0CaA7r7Hdri1ixne8qdqwFnsGT8XExg4VvOeveGm/+jvgLkwc7hL4DroEQ7//A31te2JzWbNfxzP4HYdVwDOCwZz+uH2mUek2todebLonnu1boOAUCgpF7uNQTNXB7Q6g3+34gUtDE95jMlL8cncGqWTs3cEYrObtqzW3pAPsg5GW0g6D3ypvHg02uub46cEe9EbgNyyor8eEDw3/4f24UeXjFiht6xr5reehV/+A18LyNPSzoahj0rcnlepDV/8aJHp9P786MRhTZ9p+cjVJvc/2k6uOk7/9cXOqakSC434bv1CxjrX+0ujYXov55dp7G7FWhkux55vOExu9jONYlzIxn2mHzZ+8zbN9GWX9jK842glT/DaiTVN1co7b56Y6sQz7XqBJeSNc8ry9nFMQERERUav4+te/jt69e5vP4vv888/NRwYJcM+YMcP1xpRy403pxS3ji1966aV6nvyV5xIAlwD3rl27cMUVV2DYsGFhr1OkQ68+rTsUWZ3lhkYMb2m/d1MM4x4N9b6OiG0dMn+N/qit81n0a+zo8Z3YdM9xdS0k9/SK2nk0hi8+2g0ZxaT/t27GVcas6C4fipvlPlin9+FgM3ea6vjBb9eLWK+9z6JUyH43I80e5GzLbD0hwyfrYt0MoDj30XdVeACkHTMaGvvBX4WNcjOBqD0mvZS7I0glwdDBafiBmmc1RjrAHhxWpZ0ZLN9QRmN+c/ncnCi/gGjEcRNzOx2FOcRORH0z8/FgZA62L3uw9rnXMPh+9cEs3yA/7Nbb+nzrxEBcFfU46lj52z9poCTabFfCv0DTv2SxTlLifLmme4xHtD/Gl3YWo7eBI7/NMrFE+6LQaFetQLxTvDaijRsc5UbZZo8MS9PyRnHW1fZ0TkFEREREreLyyy/XN8j06sYbb9R/f/nLX7oOYWJ3+vRpHSzPz88PDmkikzy3HD58OCINEgC3guUXLZcOp3Oegx4lIRi4NkcOCI5IoIe2jN9RMvYoAi4djoR5bRE23vh5xF30yA/6euhRYEnjhz0+dc74e/klXY0HcXT1tlijdfzgt+tFbON6n+kL+LDKbI5v2iEYB0yEfjK+bAdx00T9k/zgwW82NPFudBmv3O2BKAmCIPVmDNXzjKCHDEkQEezrIIb+61os0+Op275ccowR3KGPm6YcHy4fivLtaUdgDHUy1Ow1/Boed9QFS4vWiY6Sv/rEyOzV7j8Y/gWaPpExT5rktRhfCughUSL0x1XyTXqjyZ29w/PW6OkfnZc2omNofN4QEREREbU0CUr/+Mc/1kOUyBAnMsZ3tCC49Ow+fvw4cnJy9PL2SdZx0Qe4Y3HtcOqMORr3o7M6SgaHPGlEXDKagUkXKuJk7sNzG106u0XX+3IjfR956pT2BQ59Kn8vxaXd9Yxmw2FPPJDATmRlbttjXXsX3hMwqMmD2bdFZi/tzdv1Qeq1oYlb7joAaozxLYEm3ejoeRK4Mnq6XriG6MILfQNoBrk2Px72LeDFcNyEfZsaRsY8dgT7ov0KwzZUR/tk+8a63+2Y4VIXLC1aJzpM/hp1S3oB67ZKjxNnMYLX0ps9NBa4Oz1ESgTjlz6Nd3toTOuwKfa4/PHaiI6haXkTLsqX0EREREREHsnQJV988YX5LJyM8W0FwWV4E1nWToLbPXv2jBgqxa5fv356/fb3StCcY357E+o8GeVX0U0U7dejsXuNXzhdb5C7VwGnX/8rtsv4JzGcfq8Mfz2mHgwYimt7GfOaC4PfMRlBiMifzRt3a415Q6t2wwymOMbENnoVdhz9x//A7E1pNDSxxyryWu7GT/tfe3utWqf103czcFVsjEEcbUzxjkaCXDLOrZFnF8dxo8fJ2qzK2W0IJT2Wsqpneowv4xgLjdVsMQLkHS0YGKwLzz1ty5uWrBMdLX+NL+v2lG/E9o+sOhSih9T4aDs22sYCd2MMn+Icxy08yOo6PId5M2CLXg8ix1yz7hruNXfD24iOocl5Y34RG6S/bI7/s0ciIiIiIosEo9999119A0tx4MAB7Ny5Uz8W0sP7mWeeCQanrXG9v/GNb+ihS2T8bgl2y5AnEvweNWoUtmzZElyfkBtgrlu3Tr9XhlGR5WWbQtYrr5NH1q94N2xvpnP/KNfY5vXceXXElBtpugwXrX9d3NghVC5Pw+23dQVOl+P369/BibPmfKcTVXhh9Ws4ga64eVJa/PHBG4nB75jMweIdvdWqfv84XhvchLuctlH65nF77HeNrcLaDvezbTNQvUSVXdygtPdy18Gjza+p+VYDYAau9qhGIUavzPbNCFiGBRWtG7+Zwd6L4bgxbmwnY1w7PhRUXiyU42dc6OYU+kaDMvyDrSe4cROMdnrDzziMGyvax/9u2TrR0fLX6BWg2pU9g3GVz5xpkfsxmK/FPGHSwz2F38Vb57f5WNPL2IepOYTXVhk3dQwG1oP13DaWu6rjTz+3J8aXiPHaiA6iSXkjXPJ83A/ax81AiYiIiKhNkN7ccvPJ5cuX6+FMPvjgA4wZM8Z81Xg9OTk5OOb3woUL9ZjdMl9YN76U12tqavT8sWPHBtcnk/T0/v73v6+D5RIgv//++/UNMOU1ed/NN9/MIVE8M2NFm19rpnvDWR3y7NfY5rXF+V5ju1xLSkC8aTe97Ipb75+D268Avti8DD9Z+ALe+fS0+Zpy9jQOvbcRy/9dXat+rpa+/l5Mve1y88Xmw+B3PP1ux4InpwK2sWof/2gqli1o/F1OW4U6EMLGIrVP1sV3xD4+Dtw/FYONV91ZB8PDtvW0cTrIr/4Ovn9i/KC013I3bwxq/8mK0RuwgwV5wgzF1LWPYqB9/OaH16o6syzsTsRNO25CDbj3G9O2HhnXeO28gcZxYMuLgfPU/LDhNow8u912PM55biAebdTQCO2J2l99c0AZD9kMDLZoW9rB8tcaU97tpCh4Q8pYNwEV6lhaoI5JhMbcVrmj738QYi7zkZVvc1CWKjcuNV82ST1/dJxtbGuzjgeP94jj1kMb0UHEzxsX6mRUl4Z+zxysvfbRDjD8ERERERGdLwlWu42xPWHCBD05yTxrbG5rGfty9tetZSyyDWtMcNmusIZHsaZ77rkn4gaX1ntkSk1NxYwZM4KBdIpNd3JSfyOGPFHXyj/QnTXV9UEjfl0rnXHkpvyha2zz2uK8r7EjryWnLtkXfhPPxrhEXR/+fAZu7dcVp2s2YtkjOZj6o59gziM/Qc4DOZiz5AVs/xy4/JYZePznLRNrTQgo5uNW5ff70adPH/MZERERXXjSa/txIF4Al5qk6vfN+aUPEREREbV1+/fvDwaXL1bSs3zAgAHms/ZBAr5yL59mJcOJ6CCy84aYF4mzh1C16Q9Yu2E7Dh6zen93xSUDhuL2KVPxA49DwRw9ehQ+n/Mn0rGx5zcREdFFSI9N7fiFxaFXL677FRAREREREV0IVW/L8KgX8XCHnftjaMYMPL4yH2vzn8EzK59B/rP5eOYXczwHvpuKwW8iIqKLkHETSnP4KvPnbB17OB4iIiIiIqILy+h0ZP4ClMMdGrpegkt6XYKunc3nLYzDnhARERERERERETUzDnvCYU+oeXHYEyIiIiIiIiIiIiIihcFvIiIiIiIiIiIiIupwGPwmIiIiIiIiIiIiUjjkScfCMb+JiIiIiIiIiIia2ZEjR1BfX28+uzj16NEDffv2NZ8RnZ+mjPnN4DcRERERERERERERtWm84SURERERERERERERkcLgNxERERERERERERF1OAx+ExEREREREREREVGHw+A3EREREREREREREXU4bSb43bVr14v+DrhEREREREREREREFE7ixhI/bqyEgGI+blUnT57E8ePHcfr0aXMOEREREREREREREV3sJPDds2dPdO/e3ZzjTZsJfhMRERERERERERERNReO+U1EREREREREREREHQ6D30RERERERERERETU4TD4TUREREREREREREQdDoPfRERERERERERERNThMPhNRERERERERERERB1OQkAxH7eq+vp6fPzxxzh+/Lg5p3X07NkTX//619GjRw9zTqS2kNZ46Tx58iRqa2tx6tQpHDt2zJxLbrp27YrTp0+bz1pfr1690K1bNyQlJaF79+7m3HBtsXwlrZKu1tZe84/avrbUVsSq523l85TaJi/nOXZttT41dj+IiIiIiOji1GaC3++//z6uuOIK9O/f35zTOg4dOoTPP/8cN9xwgzknUltIa7x07tu3T18Qfu1rXzPntA1vv/02brnlFvNZ29AW0/Tpp5/qgMPAgQPNOeHaYvm2pXxsj/nXlrSlsmRaootWz+Uz6tJLL9VTQkKCOZcIkFO+r776Sk+xznPs2sr5mZOX8zUiIiIiIqI2M+yJ9ChqCxdWkoZ4vZvaQlrjpVN6tDKw135J2UkZRsPyjY35RxeDaPVcPhsuv/xy/QXPJZdcwolTcJI6IXUj3nmOXVs453Hj5XyNiIiIiIiIY353UBzKof2LVYYs3/iYf3QxiFaXZSgUGRZFhmrhxMmapF5EGw6KiIiIiIioI2Lwm4iIqIPp1KmTnmTYE06c7JPUCyIiIiIioosFr4CIiIg6GAlyErlh3SAiIiIioosJg99ERERERERERERE1OEw+E3txrEP/oxVC2Yge2p2aHrkebwf/b6Gze9gKZbMsm0/xjSv8H1cyKQRERERERERERFRSEJAMR+3qrfffhu33HKL+Sy2U/tKse7Pu/Cl+dxdP9z8vYm4bWAv87l38dLSmLRGOPE+Xlq7GQfUw8sGT8Q9tyejm/FKo8VKx3mlsQU1NV3Htj+FaT9+HjW3P4Sn777BnHsEb67MBR7ejodGmLOaoDFpOvLyTzFh4ZvA0PuQN+s29DXn251693n89Bm1DO7Dmu0PYbgxu9HaW/med5rOHsG2F/8L2w4DV992P+4a1vhj167Z8u/YTvy5rDtuu/0G9OpszuvgvOfPKbz/8mpsPmg+9eiy4f8D96W5HT2RzqtenT2Fg+9vw7bt7+DAictw9dDhGD58OJJ7m683UmPScuyDnTj2jeG4yqXOHNyxDd2HjULfZqhPbmmSeSNGjEDnzhdJhaVGOXv2LHbs2OG5Lp/XMdjC2nLaiIiIiIiobWiXPb93vTwP6z44DhzcjjWr15jTFuw7Ybx+8G9r8OftW7Bq6jQsKTtizGwjjvxlFRaZaX7q0Zewy5zf6iRIVLUN2/62EzVH2lZ/ZR34fngnhk+4AbhqOEZ9a1RwamoQi5Rj27AqKw1jH12HGvPYaU3HtvwKMx43jo1Fs57DTnN+q6uvwcb52Zhwfy6e/1vztSc7l9+KW2+NMj34EtpWyxXNLmxcaLXB3qentsvXfy3pFGpeXoTssWm4c+pPsWi5bPcpLHp4GqbcnobsxS/h/WNqqao1mHb7qhapa6d25eMHj7yEg2fNGTaHX5+BH6/chmMurxERERERERFR82m3w54k/0sOZmba+9TehvsenomZP56Je1LU63fmoaDgPhx49MdtKwB+xvzblpzYiVX3/wvunDoDM2ZNw5QJaRg763m8Hy8geuIYTrVw8MYKfE985hnM/FY/c67DyVM4VncsfGrpYG7V88idJfkVORm9vtu4Y9vw1AMzsOYDlXevLUF2busHwE+p+hR0ou0NGHPqgz/jqVkT1LGxBm/us6X1fKQ9hk3bt2N72LQG95UtwoTlbSb8386cws7l2Ziy8CWjDbukL24YeoMxXSm/szmF919chOwHsvHAj1dhZ13L1bVTry+KGgCvWTsD0xgAp45IteURn8mNmTheGBERERERNaOOPeb3NXfh11YA/G/NFKzqgI6VrcOaDyZiyRYj+LZl7WNI//QpZM9ahxq3wMyx9/HnZ57C89t3ofSZRXj+3Za5Uj21Q4Y6eROj8vIw5aqTOFzvvp3nZ6VhQtaP8eMHzWnmDzDhey3TmzOWXgPNAJtM1/dFN7yJl15r5HgQF4IZ+H5+n/lcOfV62wiAtwfH/rYKP/3BBKP3cJ05s1kNx0Or7wPW5uOlz8xZ5NnBlx/Bj9fWqEfdMHz609i0ZRMK1hYYU0mZat/mIV1+MbLv/fhf8DUDBsDponKsFIu+dyemWZ/HjZ3k8zvrecgRTERERERE1Bw6VPD7pFsAQQLgK8fijcXr8b45i9yEenH3GnoXHvvVPAx/9ylsrDLmaWeP4f2Sp7DkD19i1A8fwn239sPJE32RfFVTRy2P5X08v0AugGuw7uE7Mfb2sch+YhuSe9vGgf7kDZTuSEbyQGDUj5eHAlxPzcSoVug5fFeuuX0rDTiAjQt/ikVtKQDuEvi2MADeGGbvYVUvZ6zehiPNHby8Khm34U3UBKvOTjx16614aof5VDuClx68FbcGe4hbyxh/g0OoXEw9yE9tw/NL31SlAwx/pABrfhw5rnZ3HMfhC9w8tKkA+M583HNPLjYdMp9H+Ayb5t+De+ZvUo+a7r3Vah2r3zOfeXBoE3Jjpovs1q9fj6+++sp8Fklek2UuuPpjOHxCnUNYn4WNneSzc99hdUZCRERERETUPNp38LtzN9vNIp/HjG8ZwZ5pa7uhXy9bQPZrVyP54Jc4aT69cGrwfFZaKAilJn2zxKDnMc322q23pmHRlgt/yddr7P2YObAUudMXYd2Og/pnx0cOqr84hSOHjfQc+dsaLHqyFBjzEOY9MAq99r2EJSvfx6iHZ+I2b/eta6ST+PLgbXisJHxIiPVTk42XP3kJP81+Hlc//gzmfceY1fbco395cLitBMBjBL4tFywALkPtyLHxnZ/ipU/Mea5OYecz2Ui7dSzmlbTBXvTqKNn2zAxMmDANS15+v/kCmAdr8CZuQ/JV5vNGeH56PpKt40b3IJ/mCJp3XMdefwnrpO5eNRP/8wdmW2F37E38HxnqpBW+4GlrPcC3PpUPt9D0ZxuXYyuuN59RWyRBbZn+9//+364BcJknr1nLtQ7jyzlpe+T+Bj99+Qiw4ynzfgbyBZ1q+z8zXpNl5GbSF9UXdUREREREdMG07+D3sJn4y5Yt2PKaY9ryFzw21tZDuNUcw+EPGtPF8BQOt8Zgl51vwLS16/FYyi48Nd3oZT1h1vP4MiMP36udh+xHn8fea+7DY4/chRtUth7c9BRW7RmFeY98D1c5elVeEPbAd1pfdDdnt0XdzaF3Wj0A7iHwbbkQAfCda3+sxxvHiTexKDtaANwYu3na6vfVo2MoXfB/8Oe2ehfIup1Yt7C5boq5Ux2HzwNTc3DXleasRrhtwYLQ+0bcj8fSgOdfvziCSjV7So0H/zIMN7i1Tb1uw//c4Pi8eP0h2O8e0ZKsAHiNy70fLmwAPBljvl2Dv0VUi89Q+Ya8Zj6lNikjIwPXXnst9u3bFxEAtwLf8posI8u2jr6YuHgLZg4Dhv94C/K+11efs21ZPFG9MhwzX8vDRDVr+HRjGSIiIiIiopbS7oc96darF3r1dkz2Xt/kzSXJuGt+AcpeNwNCW8pQeOdBrFlzA2ZO64Zt7x8Dzh7Bm8uX4I3BM/HQhCZ0SW0Op7ZhSfYivIkv8c4zDyJ7ajYWvQz0uqQtlvlLWKTSlz1/HQ52q8FLj/4Uz39ovnRB1eD5sMB3N9w2/2nMSzOfiqm/xhqrV72iA+BLS1vsp+c3jr4Hwa2ZAfDn9ti/+DmGUgl867GbDd2+k47hMlZzG6Zvijk/N05vdhu5sWXYrz9kmobnp67B9gebFpJN/nqL/BSjfThl1qEu0b8Si/jMuMR84QI59frzeL7MfOJQ84f1eLNFxpGPdPWtY1DzX46hTXb+CfnJ30KK+TRID0lyD+6xT7YhTWSIk9yNm5Bvvpbv8l2LHgZFvZa70dyiY535243ZdtZ7jCk0JMpnG3Mdw7IYQ7UE1y308C7Su/09na78ncZfa31hy7Yzl156Kf7X//pfEQFwZ+BblpFlW8cRvLH8x3jggWw8/34v4C31mVKwC71OvaE+F5/Hrt6n8MbjM7CuthcO/GEGHnxmm/k+IiIiIiKi5tW+g98navDntauw6pno00tVrdCTOmg47i98Gk+vDE15WTeYr4l0PGR77emVa/A/b2/FwNXZY6h5txQv/edz2Fi2DZu3HMCoxfdgeLcbMarPO1jz5Ebghp7Yt/MAWi1X39+GPw68D3lP5OGhWQ/pad7iAvysTfT0t7lyIv7n6iWYF0zj03jo9hps+0drdF2+DP2+bn05IIHvP+DXdw9y9JjvheEPFoQFwLv37NViveq7jXgIa565LywA/nyhPfjxEp4PC3zPQ0HeXa3zSwOvLrkBdy0owJZNT+Oua8x58aQ9hk3BYX026V7awH1Y08TA98Wu19fM9vXTtjpmcDLuevzX7kM1qfozbXkepIPsBdE/BWOwFZW2Mbbf+/smTPjmTeYzy3vIn5WP5Nx1WLfOnHInAK8sDAtyf/DsVgxYabye46i+EsRe+MoELFCv5U2UnyUY68QDK8x1LgCezccHxuKKEcxeWJODFeY2VzwA9R4jAH7lrWNw/W5b2g9VYutulYYDoYC27Au++y1Ye7Mp72/4lrkuSf8Hzy5v1+OLuwXA207gW/TCjXcan3+3qfaw++Dv4aHbVIvf60bcNes2dSTI69MwStX3frdOw0P//1/j6Umhzx8iIiIiIqLm0r6D3x+8hNw/vI/j5tMIB7dj0epStOZICX2vH4VR37JNg/uZr4irMNz+2reG46oL3AvRcqrqecyYMBZTZv0fPPf6m8hf/FMs+Rvw5ev5eLp4HZ763UGM/el9uG3CTMy79X089cRLrXNjxLOncKp3si3PZLoh4qZ2ra8brhphT+MoDG+lzvLy8/Pv5T2Lh8aOwj2LJfAdLSHddAC84MF0jPrBEhT8dJRtTP3m1+tWRwA8CiPwfQ+SW+nYiK8XRv34abz8WgEeu/MG9GpyXeyLu5avwX1yLwA9Li41VvKwcapVVTY9j40ehvi5sIzA92O3XxX5pZIOfD+LmSMu5C9YrkTKt4Gt262A8Xv42ysToD6GHG5CzjpHQHv4tzDBfBh03Rik9Dcf24QC3znBQPRnG/8Tm67LwYM6EC7UNiSgbtHB7OuR89AElUrDlRMfRM51HxjplcC99Vj5bPtW4IEcTHjlb2ovhOwLwgL51z9wR3D7Rvo/wP5a83k75QyAt53Ad0i/G0ah35FteOeTk8DhXdhWeQAncRi7/vYODqhziMPvb8PhvqNw8zVteQAzIiIiIiJqz9r9sCcYmI6cH8/ETLcpU12tn7nwt7lsd+pKsfDHT+Hwdx5DwZYybCoswKYX85C+7yVg/GOY93AeCh4fhZ2/XoQ1Mp7xNd9T80bh/dVP4c9eh3doklM4WXdM34AzOH3Zmj3527FLbsB9TzyNeXGHq+mGG6YuwdOPpl+QXtbxAuBtO/Ct8urueVhTsgVPTx+Fq5olbjkcD8lNKssWYaHcIM6h5mP7vAOoiTJ8xkVr6F3I0b3nd2LJ3Kei3NjyFGr+66fIXr7zAv6CJRT4jtAqgW+D9KDGG5XG8CE7/4ZNtp7SkYze2MawIQuxyZwblHx1MFAd9MpCLHxF/b1uQNhrnx34IHL5pAGh22zW7scHKs+uDgumS7D+erN3t/2xsb7kq1Mw4LpNxjjmh9SxgfBAfvLVEanrEOwB8LYV+D6GXS+vwTbVZB3evgZPrXwq6vSmOo84uefPeOrN0K99iIiIiIiImkv7D37TeTtS9hL+fOI+zJtv3NBSnKrZhV0Yjqusn+D3ugF3PfIYpiXvxZqFS/DSh73wvQdn4oa/LcGad1sihHQ1bsz4Ei/l/Rg/ftA2Ld9ovk4dRbQAeFsOfPcadg8eK9yEgvn3YHhzx9RkSJipwJsLF+IlI7anXI3kNDXvtTeCPcJ3Lp+G583HZOmLux59DLdJndn3PKbdOQNrNr2Pg+aXZwer/ow1syZgyhNv4v2105C7KfILhubXNgPfmm3oE/chT4Q1VvZs5CcvCA5TEtHz25X0+FbL7s7H8mYYY1sHzU1XXq1aDN3T2+qxbgTEaw58pnuCfxAzkN+xWAHwthP4PqWOt24YNWsJJvY9hn4TluCZ5c9Ene665hgwfAaeuTNZve9k6w2rRkREREREHRKD3xdY3xtvDgb5ul3fD21hpOpefa9GN7yJLa/V4OC+nfjz6hmY8OPn0X3qQ/i+c+ziK0dh2oJ5+PaJUqx68ims//gG3No8XV4d+uJ7CwtQsNYx5d5lvt46uvVuG2XW0TgD4G028N17FGau3IQtz87DXde3XE0Y/qAMf/ImFmU8BWNYZXNIFNsNMvMHbtJBcnK46i488cxDGCU3R63bhlXzs3Hn7WMxVk13Ts3Fqr/JaODdMHzWGjzW4vdYaMOBb80a+mRTlCFPFOkRroPY67BuuhlO1j2rPdAB6JtwxwPXh42xfeXV1wM1B2w3rFR0b2+T7gVegwNhY3J/hgNqo9dbPbj10CUq3atDPdaNnux/wp/e+CC03EVCgt5tIvDd90aMuv6P+Kl5zDV6ylqCXXcOj/gylIiIiIiIqKnaZfC7V+9kvLlwAm6d/rweHsAKBkVM1usZi/DmJa0ZYLC5fhrWmze4KyuMP97xhdDt1hw8MbUXNs6fgjt/MA25/3kSExesR8GDw6OO+dx3xF2Y+fA8zHv4LgxvxXt0Xmi9vvMYtgRvUOi8UWF70gtXDbSCt90w6hr7WPStQwLgzzwzD9MezGt7ge9LQjeznPat5qnwwx9UdWf5XXBf23A8pOvWQ+qRxZpnTL++s6+xjuDNMY3XHxphPtUkaG5fpvl1a4M987sNvQ9Pl7yMpx/8HoZLEDyoF5LH3oe8wk1Y88Dw8xif3Yt+0QPf3dpC4NsgPag/eDY/zpAn9kC0cbPKUB/s+KzxuvOf2qQD3ldO/H8dvcHVOvNsA6mYY3pby4vPNi5H/u7rMeZWK6h9E771XWDTK5tCge7+VyN59yZsCluOLqjON+C+wrJgO9WUacuCdH7JTEREREREzSYhoJiPW9Xbb7+NW265xXwW36m6Y2jUaN6X9EIvj3GGeGlpbFpbSqx0NCmNZ0/h2Amgl9eMaoLzzrsP1uDO6f+FXgNjBGvPHEbN/rvwzOszbYHD6M6/PI+hdP5YLHr/hpg3LD118H1c9fAm/DrDW/C02cvXhT6OOndvljJvrjQ1l2bLP7nJ6tlu6Nb6ccoLplH5c+IYjjVynILuvXqhm8fAc7PUq1MqjSdUPe99foXYuHqjpmj7GOu1RnJLk8wbMWIEOnd22cjOfNyTB9sNKGVYk4VAbuimlp9tzMXsN8ZgxWLjhpP6+bOhcPeE3BUY8F/mMCjTbzJuagnjsSVi3qFNyJWg+XetecZ2rZD3hAdyUPPsVoxZmYcJ5ljfxs0yjcfA9cixvabpfakJm6/fU5MTTLvb/rnPu3icPXsWO3bs8FyXm+UYbCFtOW1ERERERNQ2tNvgd0uKl5a2ktZY6WirF4TNkS5PX3x064VeHnukNkte6eCa+TiG5gr6tcXybWtpam/515a0pfxhWmJzS5PMixr8poseg99ERERERHQx4Zjf1O50690LveJNF3ooBgm2u6XDMXkNfBMREREREREREdH5YfCbiIiIiIiIiIiIiDocBr+JiIiIiIiIiIiIqMNh8JuIiIiIiIiIiIiIOhwGvzuoXr16mY+ovYpVhizf+Jh/dDFwq8s9e/bEkSNHzGdE4aRuSB0hIiIiIiK6GCQEFPNxq3r//fdxxRVXoH///uac1nHo0CF8/vnnuOGGG8w5kdpCWuOlc9++fejRowe+9rWvmXPahrfffhu33HKL+axtaItp+vTTT1FfX4+BAweac8K1xfJtS/nYHvOvLWlLZcm0RBetnsu8jz/+GMePHzfnEIVI4PvrX/+6bgO9aCvnZ05ezteIiIiIiIjaTPC7rVyse7kobAtpjZfOkydPora2FqdOncKxY8fMueSma9euOH36tPms9UlPzm7duiEpKQndu3c354Zri+UraZV0tbb2mn/U9rWltsJLPSdqDm31y5TGBvGJiIiIiOji1GaC30REREREREREREREzYVjfhMRERERERERERFRh8PgNxERERERERERERF1OAx+ExEREREREREREVGHw+A3EREREREREREREXU4DH4TERERERERERERUYeT8OGHHwbMx0REREREREREREREHUJCTU0Ng99ERERERERERERE1KEkfPTRRwx+ExEREREREREREVGHkvDxxx8z+E1EREREREREREREHUrC/v37GfwmIiIiIiIiIiIiog4l4cCBAwx+ExEREREREREREVGHklBbW8vgNxERERERERERERF1KAl+v5/BbyIiIiIiIiIiIiLqUBI+/fTTNhv8DgQYlyciIiIiIiIiIiK62CQkJJiPmi7hs88+azMRZga7iYiIiIiIiIiIiMipKcHwhEOHDrVaxJnBbiIiIiIiIiIiIiJqLC/B8FYJfrdE0JuBdCIiIiIiIiIiIqK2qzmGMnGKtc6Ew4cPX9CosZcgNQPZREREREREREREROSph3eUZTqZf1ucBLS9BrUlsfEmIiIiIiIiIiIiImq/3OK+zsmLaLHnhCNHjrR4N+tYQe9or3kNlBMRERERERERERFRxxMt+B0rKG5/rcWD340JbnudR0REREREREREREQdk1tw2+s8Yc1v0eC318C3/bnX9xARERERERERERFRxxEvmC2cy8R6T8Lnn3/eIlFlt2C116C3l/cSERERERERERERUcfhFsiOFvh2Luv63gsV/I723D4/2mPhfE5EREREREREREREHUesgLbb41jLixYJfrsFqt0C29H+imiPnWK9RkRERERERERERERtizNIbecW5BbW42h/hf2xaPbgt1sw2i2Qbf/rNs9ifyycz4mIiIiIiIiIiIio/YoIWrsEtO1/3eZZwh63dPDbLZBt/xvtsf2vsD92ivUaEREREREREREREbUN9uC0k1sQ2/432mP7XxGc15zBb7cgtDOQbf/rfGx/7vZX2B8TERERERERERERUfvmGrh2+WtN9ufWY9e/LRn8dgatreduj93mWY8t9scWt3lERERERERERERE1DZZwWk7+zx7ENv52G2e87HQzy9E8Nv+15qcz93mW4/d/nrRmGWJiIiIiIiIiIiIqHnYA9Hx2APYzr/Ox/bJOd96bv1tseC387H13HrsnK6++mr9OhERERERERERERGR04EDB8KC3fZJ2B+LTubf8yYBbDf2+fZgt3MiIiIiIiIiIiIiIorGLa5sTRb742YLfsdi3yARERERERERERERUXNzxqFbJPjtFux2Rt+dExERERERERERERFRNLHiyvbHlhbt+e3coDNBwm0eEREREREREREREZGd1/iy9bxZgt/OlXvhligiIiIiIiIiIiIioli8xpZbfMxvt0TY53lNKBERERERERERERFdvJyxZLe4sn3eBbnhpV28xBERERERERERERERReM1xnxBgt+SAGuyeE0gEREREREREREREVGs+LI12V3wnt9OzgQREREREREREREREblpTDy5VYLfVgKdf4mIiIiIiIiIiIiI3DQ2rtzqPb+JiIiIiIiIiIiIiJpbiwW/2ZubiIiIiIiIiIiIiFqDxKfZ85uIiIiIiIiIiIiIOpwLHvx29ghnD3EiIiIiIiIiIiIi8qIx8eVW6/nNoDcRERERERERERERNYWX+HKzB78Z1CYiIiIiIiIiIiKi1sYxv4mIiIiIiIiIiIiow2Hwm4iIiIiIiIiIiIg6HAa/iYiIiIiIiIiIiKjDYfCbiIiIiIiIiIiIiDqcNhH85k0yiYiIiIiIiIiIiCiWxsaR2fObiIiIiIiIiIiIiDocBr+JiIiIiIiIiIiIqMNh8JuIiIiIiIiIiIiIOhwGv4mIiIiIiIiIiIiow2Hwm4iIiIiIiIiIiIg6HAa/iYiIiIiIiIiIiKjDYfCbiIiIiIiIiIiIiDocBr+JiIiIiIiIiIiIqMNh8JuIiIiIiIiIiIiIOhwGv4mIiIiIiIiIiIiow2Hwm4iIiIiIiIiIiIg6HAa/iYiIiIiIiIiIiKjDYfCbiIiIiIiIiIiIiDocBr+JiIiIiIiIiIiIqMNh8JuIiIiIiIiIiIiIOhwGv4mIiIiIiIiIiIiow2Hwm4iIiIiIiIiIiIg6HAa/iYiIiIiIiIiIiKjDYfCbyKF8UQISEuJPk1euwmTz8eK3zDdfEOVYbKXhBb85r/X5X5iMhHsK0dIpspdPZL43R94Y62h0me4vbKX6YGmmevHW4mD+XojyjM3cp0Xl5nO6cPwovMee9+bzFqsTdah+YS5WbjeftiG6bUtYrGqjftai+eDfsgyLXwyt2dj2ZBTuN2dcAM40WG1Cs7VrddUofHglKs2n5yO8bCKfdyxGexhs313KpS3Un5bnbJvauOY+fi64prbNLf2Z4aa5t+k45i5m/lIsW1R8AcqyNerNhdP0Nrlj58t5c2tnL1idPV+81ompmcuxY58nUjwMfhPReZOAdFJWsfnswsl9splPAnUAOw255tOLUfmrtr1fX4TSDhU0oTZrfwlys5ah7oz5/KJUjvz0uahoMJ+2ipZPg39jLrJ/VYdW3c0OqS3UH+pw2DaTUv67cZj7LhsXaj9YZzsGliM1Jwa/iaj9Wp+NWeyR04zKUbrAfKgVo2hra+ZvKuYHAgg8lmo+p9bjQ9Y6VRbrstSji9mFzQffvUUIBIqQNcCcQWQZPV/VjQDmjzafu2D9aQM8lBMRWXiuQURELYPBbyKH1MfUSZcE3PRUi4Ip5gsLy2zzAyi6q7f5giF8uBS3n7SZP1kLLtOMP4ONOuRGaCgM6+dUwXTKT+fsQ1yoKfTTztD7In/uaX/tv/XjNCtguj4bSfKa7adbzmFknOuzp6dc/xTJfbloirPyVYo8sOWRNYX9XFy2fU02rP7ruamyjL0cG1d+4fsd5edVcdIUxlFWXn82GUpH/OX9Lyw1e73nIW+hfuCav8ZPxmSdar+c++D42Z63+haNy08BD5dj2bRxGJok60jC0PTpWLYlfl1p2FWMxcH3qem6NEyeV4jq4+YC0XjanvGz8EnDkvS6k4ZNwuzflKu5IdbP7EreWoZJ1xnbz33m/2CkWn7uq5E9GsoXqXWlLAsNDSE/+5uWhkGS9oRBSJu2GMW77O8z8mryc+Uo/tFQdRyqtN6Tj2rzVVfHq1G8aDrSJD3qvYNSp2Pxi9VReuS6/+S27r1CzL1TtqdeSxqKSTNXovyw+aLQZa7q3q5qFM6bZOajpH9ZaDlZxjz2jOMu1s8RG1D94mJMTze3qdM9GXNfsKfbzAs1T5eL3j9jm6X2xDvSpvNWlcv0J0rhj9rL0T0fjPoVq3zqUP6b2ZicOkinOViX3jBrie1XJ8VZUo+M49X1J9J18crNTKM6bureWIbp5jalXobnk0OUNATV16BkUbZ7GZriHWfSHhi/EspFmrzuaC/CqGNv5czJwf2U+jXOZZvx1L0Xq2wqsSxFpcmRjspfjVTLJmFx2FAPxrLjflejn+m8teqhmbaw+hVN3GNZqHoebFNUXclaiUpnW2W2p/ozw2P9sdqhct2umWmQ49alLax7YyVmZ1h1J1vXVd2eO+p+BA/l1rh0hOrwoIy5KNlXb74Sg3Vsv1GM6ZKHat2Tn1WtoTXfXq+FY7639Hk8zuzlFHyuthWrTbTovDTbJrX97CdkW1H2IcjR/pmfS9JOBNsbyxk/SlW7FPWzS9IarW2W9z7h7fOjVuVPtlWX75yLwvcc6VD8W1R9i/VZIuK2fS6Oq/xIV9tOzUVpzLbDwzEn4uWZJebna6juhHPOd/ssk7SZdaWuEiut+nmdS/set4y81GFjGX2eb57jW+dujW4DdyzzcM5jpimsnYnz+RmLh/YoXB1KZjq3r+b+abZ+f/b6sLnGsvNKg3ka95zI4ldtS5axnJXfHvZGi308xTgXjFN3jX10tC11JZgt+zI1fNgJY9m5KJUdV3W9cF4oj61zMuf+eD5fdLbbjRa9zroz6lesYzr+NYSXYymeo7HPWUUj2t0Icc49pEwj80rquJSF+hwI1ov41zzaebeBscrRYxrsn+HSRv6pBh7OILS4n0mN+Sx30eTrUjo/n3/+eeB8pyNHjgSnw4cP6+nQoUN6+uyzzwKffvppwO/3B2prawMHDhwI7N+/P/Dxxx8HPvroo0BNTU3gww8/DBC1TbWBgikIqEMlgIVl5jzTJwWBTJkfdcoLhN5RFshzXQaBzMJacxmvQusKvteWlrxyY5bBtl0z/WULzefRJnO52sJM4/mUApULNuV55rKZgYJPouyXXoct71xfN7inR9ZtLuDgunxwfS55owT3xW1y7m/YZKXDQ/nFrQ/h++QlTZZYZRbaz8h9t78vvF64cdT1qHUqTtplstUZr/XNnblP1jL16vkIBHx3zAmsLt4c2FxaFFjxQKpajy8wv7TeWMbN7tWBDLWe5Cl5gYIS432rf5YR8Kl5vhkbAkfNxSJ42l5toOiB5AB86YGc5UVqmc2BouU5gXSfet/9BYG91lI6z3wB3+CMQJ5a14bCgkDZob2B1ePV/j2yORCeerVd9f6UJyv0s/ptS/X6gukvKQjkTVHbRKoqG+udRl75fL5A6k9WBzbIPr5cZb7m4phafrTadjDdat9+mK7yxBfIWielZ9aHYPmYz21lW1ucE0hWy6f/cEWgSO335uIVgZyxPrXOrEBBjbmQbi9SAqmjk4PLWfmDiauN/DlUFdi8bn4gXaU/Z5Xkc1XUMtn72wy1vuRA5sICtY+yzdWBOXeobap0zHrZepeRFymjU1V+ZwaWStlJ2vT+ZgWKrOMwmDafytulwbSlSj7eXxTaT112VnsemQ/1aj36PWNzAiusbZn5YGyrPrD5EXkeqiMbCpca6VFluLRSFqkNVJSq96n1pD8my1QEalXRGtu2tR3BcssIzC/cYCs3BFJVWRm1wUyj2v9Utf95slywzsQ4VqKkwWrzfb5QGW5YMye8DIWH4+xotcrjx9LV+lReSflVRynpY5sDc+QYsvK0dEOgYIlRNhi9NGAcGc6yiXweLJs75htpssrGduyULVTPR4TWGcw/9b703wb3LhCoXBpIUfVFykvWm6LyMuNnq0N1X5fL/MDmKNkrvB3LgUDFk0Y7k67Wv0H2fWFmYMj9WbpNDrb5Zrno9tlj/TGeq3qhjkfjGDLWnSx59PNQO2Tlm5VO45iV96l9dJ4T2DWq3OKn4+jLs3T9sR+f6WOzAlnSbsb67NB5o9pbleZZa1T9V+3Ehmprvsv5hWO+t/R5PM7s5RR8HqdNFNaxbq3brLupanuu+xAUav+SnW0SMgKrd5uLqS0V3G8cC0a7ZNtH67MrWttcXxFYKuuz0mZ7b0Q7pD6TfKrtmyPloPJnvm6vVX3fZpWySklhltGGPWC2L4V5gczB8l7bZ0lj2r5gHTX3cXBOoMhaTxSejjkveSYa/flqcc6PLMsNhfMDGVJXpswKzJL6ucRcv/PcpDFlFLMO1wdqt21W6VfLjZ+vy6fik/omtoFeznmcZejh8zMaj+2Rk3H8zwpssH086c8JeZ897Uc3BGapeda5h5dzImPdckzY6trPjc/J1F9UOPLFzsyXuMeTUWcizwU91F3zvD90LqWocpa0AXNs5Xo0sGGGmqc/1606lBNYatUzc38y1oQ+P72fL7q0216EtbPuddadlS+RbX2wPDxdQ3g5lqIxykyXrXpv1HNWT8e0O2/nHup6RvLCp+r+IWOO8RlsP7/2ds3TPG1gtHL0mIZD6vhU8yS/gnk6Nj2Qdb+cg9pjNJE8fSZ5/Sx309TrUoogcWSJJ0tcWeLLEmeWeLPEnSX+LHFoiUdbsWkGv4liMhth+VByNtBhwU5bI2p+AIc+hOWkKXI54wTI8V5PzA9JNbkFXsMDlaFlrfSHBSNt+xSab15UBdcZfpEVXM52Aew2L7R/tvcH8yY0z56e0AVGdPZtlUVsI3be2Pc3lD5bnkXJx1AaY5RfWH2w7bN9vpU/jUmTrT7Z8yeUJvd9d11XLBH7Hr3u29ftXuahbdrLN2Z9c2Xuk/U+nRdq+bCL2KrAivHJgdQl4Wm0q1iVHhgyWpVT2JmhuqD6uZzwxjj+PGyvvnS+OlnJCKxwnqDrE5vQCa+VN7NKwk9P966RYK79okJR2/Uh3QxSqIvFiepk6BHnyZB5QRg8wTLzavwKlcL4jO3aAyFC1pkcGDJltVqH88TUfG6Vd/3mwHx1gpexyrk1M71WgMisvymPhZ+YG/kReZzErqsVKu+HRJ7km2kJpdXMC/tJqrAuhB1pCztZVupfmaNP0MPLzqonjnww9zfiRFe2NXhIIHONyh91Aj5HghTO9s08+Q3NN9JtX86ZTxVLUoznYXVS1cpV9vK0jl3ncmr9YfnkJjINwXxyBCyMOhTahtfjLDw/3R19eY6+gHS2DcFtmvOd6wp/ri4URxhlFVY2p9UxbCszKW/7Oo2AhvGliHFxb9j7W3XBZAbJdft1t2O91SsC6YNTA0uj1mGPx/KhIh3EdtbzvWtl32xlY5ZL6JiJX3+M52qZtWEpV/tjLyMj3yKOC7U9HTSytflOjSu3JqZj6/xAiqQjVj028ybd2T7p+ZHpc873lj6Px5mznMzn8dpEfaxHtGFq3Tro57IPQUY9wIj5gbJj5ixhtrFW/ThanKPWkxKYvzXsgA0cLQlv/9zaZl2evjlhwUFhtJ3Odsj5OWO2mVY9Muu7Mz/kOLS3141q+/S695oBEkceuvF4zHnNs8Z/vlqc893LUrdFki57/VSfg3PUPN8vjJBu48ooTh1WdJtnO/ab1gZaeRPrnMdehornz89IXtujCGrd6ao8Q3XeaIv0F0+2L0qNz46cQJEECj2eE1ltS4b9i1XF+GI/1nFtlVWc48mqM45zQW91V61rvEqrrdwrnlTHnQR01XuDXzSYdS2nWFUus32Yv9V8TasPbPiJLzDkAbN+NPJ8MaLd9sLZzirOOuvGOIf3Bea8Ep4vUh7Jo+cHNqvjztu5jfdjKZJZZup4le0FWees5nu9HdNuzHyOex2hfFIUyJJtyvmeGTy2n/t5veZpvjYwshy9piHaZ+h8OS8MlpsLj59JXj/L3TT5upQiNDb4zWFPiJpBZmEO1EWhYXQ61IeYVlEjP88JjaNsX85371xzuVyUxhg+o+Xkocw2lnLqY2VmesxxngekY7Ie8sU+7rNtX+5Wp4bGQxd+lL5oDiCycG5ovNHROeYwMm5jSedh7r3R1+gmOZiHxch+2P2n2P6tRfonu8799d27MjikTe6rzp9d2TW+/DILV4b2eUAWVhaqU0Oxvgbyg/nGpCl4A8opBVhpy5+I8rKRn71bNyBVFwaexhq1pyldL68uRe42071gaZSfWGei4MnQuIyx8zROffOinzrdUcuveDIf5fusn+oNwaxX9qLskdC6nVJmbEZV+XykJpoztEQMHZam/h5FfbTfC3rYXuWWxfDfOASJtaUo3WKbPmlAkqqRi98IDlyiZCJtWFgikDwmU21jGUq2hhJR/uoK+CdmIX2werKvHCUbgbT+qj2xr39LGeoShwIbS1BuL5sxI1UK4/GrdJeoOpWNSbKNoESkL9mLqnU58dexvRSL/UMwJLHWliaZatCg6r7/l+WhIVuUjO+mqrWH+JJHqn+LURP1p/tuUlTeV+l6FF6UQzF0jPp7rD7sp5++mbORNdB8InqqNm2mD/5ny23Dwfgwe2YWks1nInH8ZMz2+ZH/loef2/orUarKJ/P+SWHrkG0t3V2FogdUTvbLwNLyvShytm+Dh0JqYN1xrz/CVNsqVLn6yCxk2vdLGTIlBzkoQaHK/6C7JyM1bLlkVd/Un3drXNvKeHLuTA/L9+QhknpVhubKmnycueh9x1KU7Y4cq9rYZp23de0oRcEOYM4PM8PLpssQZP9QXdpsLETpHpXCUemYpfajrNL8weyuShSpo3LuvMnAi5VmXfGr47IUvsw0VQtVrRmQoV5bgWWqLtVYP1G9cRY27y7DnGjtrcdjuaGyDPlIR8694fU8ecoszDEfn59MTB4TliNIHiz5WmEcj2a+Zd8fnm+Jo7Mw+27zSRSNK7c46dhTgRK3dHw7B7PGm0/iSE+J3xpGFyd9liYeZ7HbRPNYvz8n/FjvmYqsmebncjx3TEJqT/OxGJAMvYU90kbUoezVfGD8LOR8O+yARe+J2Zg7Qn12bSyL8lP6GpT/SX1+jElSybTX41KU1anjXbVDJdtse/5ADiaHfc4kI/1etQ/rN6BMLVZXXqrr+6ypjna9d4Y6r0tRnyUlKGtoZNun2pvSRdmY/GwKVpcXhH8OuPB2zHnNs2b4fHVylGWPnjLsoqN+JqryVcen/4yUWiPLqAl1uEltoBL3nMfpPD4/m/w5MngkMlR5FpWbZzH7q1G2IxOz1WdCyo4yVJvHf+VbBaqc05HWTz1p1DmRqrN3O9qW8dmqRIuxoTxWq6HEOZ6Cws4FvdZdVYcmqmOuuMxMqx/VKg8yZ87F5BGVKKs2N7CjHAUqtemjVD1U58lDVNHkL1mMkl3WjawTkbG8FlVrzHOrRp4vnl+73TjVb+XD75uNyePD8yX5hxuwt1xdD6njrlHnNudx3pXycLbeXpCcs/5Q5c+qUpU/jTym7RpzHTEgE8uWZwFP5GLSPTlY6ZuP4gWhcz9v1zwt0AbaeEtDDSpeVX9dPkNzZqabT9x5+0wy5ylNub5pzvNlahwGv4mawchkx0mZ3X7VAJsPjbE4zbGdzPE5hREkv8CmqA9k86FBPTcDl8bFUSj4WfxiqfGh/VapmeZ4geoa1Kw3Hy5Is+1zErLN+cY2bCLS40Uq5quTE2293PzSsU6lZo8ZhI9Yvw/Jw8yHsU5KmlB+zvpgfBAK46LZe5r8qHnXfD4sORhkNjjLy12w7GIqR74ZLJdgvh6LV01WAF2tJUqAeiSSwy4qYuRp3PrmweBs5C3PhP8305GW3MMYH23mShTviL+HoqFOncirOlzywkrkzpyE9Idl/1Q6o43NFnd7qnx2qT+7ZNzLcRgXNs1WJ0/K7trY+T94ErJVPix71Qo0lKN0lR8Z6oJK55e/RuW+yqN5kxzrH4fJi0rVK2XB4KN3tah+Vf2JqFPe+T+RkGA1ZDx0Z7pm/06WqEKtLV09upgPmkUD6vzVKFcn14W/ycXsO9MxR9qVfX51iReSNjiyRdHBK39F8OJVLeWow0LVTXWx4q+sjn/sqItiKYWYnwGWMyrd+yrVSXox8p+Yi+mp2boNKfV7LcAGNOxQF4bXJYefkIt+Sbq+hK1L5XkP82Fz8FqGjT7OYjleh5od6qLmxXwsm6eOw/t1jnlbV0ODumBMx5DkiNxC7ySdW8Z6eo9EmjoGV26t0Mdgzbtq/ow0dQGehkx/Kar2qJl1FShTdSx7tIS+VQ2ZkocVU/zGeLu9ZCzLyZj9m2JUxipKj8dy3WFpD1Mi62ViHySNMB+fr1hlefyoyrdMjLzOmW/quDB2Pz6v5RYrHYf96h1u5afywS1I1hK81PkmHmexj6cGHFXHeqZqoyNK4TrrfCKOruZfV6otkrIYkYwkY4ZNEpKuU38c7WmI+tx7Uf1ZPxeTHPV43D2LdXtYtq9WL6klJyH8DjnWPlTr+t5wXJZ1qe9K0gA5TqXtaGTbt342shfIF/BlKI0WELLxdsx5zbPz/3yNEK0sw+qQqoXB540soybU4Sa1gSLeOU805/P52ejPkRSkZfpQuVGds6tnDdUVKB6RhiF3p+kOERXVkvJKlBX7kT4+VZdz486JVB2SgLndQOPLqer9tnJxE+d4cuf9eE9R5ejbUYIK+dxrqELFepUXwzKRdof67Kqs0mVWWV4E//gMpMrxkpiOnN/OwdBtuZg0pA966DHVF+svo6z2o7HnixeOOk4koD/GeX3iztO5TRM/D0TygMjSSR6irsP9tahV227UMW3XyOsI35RlWDZFHZdb+mD+k7m2L968XvO0QBsY5DUN6j+VBrfPjD6+2KF3b59JxnNxPtc3zXq+TJ4w+E3UhoXdLNCcdyH5xkxWl8DK+iKU7pfeGXLCqCxMD/V0b23B3uTqgz3LOBkmZUqmWXbypUCc2hP8UiM6zzcWbVGJSPlJEfbW16KieDXmjOmB6hdnY3JKEtIWlZsXUi72lWBuehJ69EnC0NTpyHu2GP6eGci5P/a3/563N6UAtbab4YZNazPjnPz5kHFvDvBcqdGTQJXFCn8GMh09DvPKXdatp1rMv9VcKIJx46PQFzYyyQ3L1IaapUHJRMEnbmmSqQDq2rHZ1fxpLsYl9UAfdYGV9qM85P/Jj8TxOcj22BPUkIhELyeriRFhlkhnvGRlAyp/MxmDuqp0J49E9oMrUbitAb4fSY/FDqTJx5mL45VYec8gJPTqg0Ep2Zj9m0KUHfchZ2pL5JgPqeNVGp+T3md+VG4tRWbqEPQeOARpI0pRWulHw7ZSrMQspI8y60TPFMxatxf1n1SgaM0cpPeoRtGDkzEyKQ2L34raEmlNO5ZFb/Tubz5sQQ3n0+XogpSbOn7tveM6oobwX7G0SY6bwNun2p97+ZakD3q3VDn60tVxVovNjwCFD+ahpMmBhKYcc831+doMzruMYmhyG+jtnCfkPD4/z6M9ShmdDbxq9Iit3l4A3CG/+lGfCTOAgu3V5i9TUpAxyp7u8z8n6qN79TdFMx1PI1KRjVKjF/F70sM7Q30OAkNGzdKfkdWoQcXGSqRMHBkMGCffsRSbPzmKqtICLL17COq35iI7fRCGTC3UXx4YLvz5ohcNXhra5jy3aRL1mWedjp7HMe353ON4FSq2yoNq5Lv9AijuNc8FaAPP47or0cu5fUtr9Tp18WLwm6ilmT81FTIEhVtDHfFzPlPyYKPntRV81jwEKj0xh+AICfXWzrR6TA7IwtyF8qAY2c8uDg7/kTc+Xug71Ks36ge1bQiM8+ND1pPyAzx3oTx07q8/Rq9qmyaUn7MnuL/G6jtu9JT2nqZYvdNdyssiJwXrisyyix+4Dn6pEZPb8DyOn3/HylMv9c2rRB9S7s7B0jWbUaVOuDc/loLyBQUode2mVofihZOw7Gg2NnxSr8prL8pe2YzVS2YhU3q7eBF1e73hk5/Tra9AlZcT6Ch6j1EnPP58lJY3GD//tf9UsJ8PcipUqsq/+SRjyP3qj8svHvzrszEoVZV1nLuN9+4nZWb1gLpADhdj8Z3LcPT+DaitV8fe7jJsfmU1lv4k0/UnlDX+yF4wNXvK1MWdOg6DlbMGtRGBEVU31Yl/SoqHXisDhyBL/Yn89Y4fxVMHIW1BKRp2rETOg8VIWVWBo6fVBcq7m7F53Qrk3Zsa0YMrNnUBpC5CS3fXRF6MHK7Vx1fmwLgpbiHNcJzZVD6dg9nrU7Ci8qhaV626qN6MolV5yB7diBxTFzgp6iK+uiayjtbV6twK1oPkURlIkV7eO6pQ9pz0dJP6PQQp44HCd6uMn7fPyECaY/OJA1KQ+cBSrC6tQu2hzZg/ohy5a0uDPd7CeDyWjWOrMvInsw01Rm+qFpbYP0nlmzq2dzvzzda+R9Es5WbR+eVWfqqu7zAfNknkMe//pMp81EaYPY6LVV2JKIXg+cT5SFT1TP3ZofLCmGFTi9rd6s+N0do/dWYiXzZurdJtTly1RyOOh5rdsg9DdO/XxJ7S29Glviu1+2ULQ9R5UyPbvjE5yBmt6s+DK1X7rNrfJaodNl9y4+2Y85pnjfh8jcgbtS866HS+GllG56FRbaAp5jmP03l8fp5Pe2QNh1VRXYmKLX7MGiVnGb0xJCUd/m3VKN9WgtIR2UhX9VI07pyoFkedGbTP+JXpEF8f43k0cY4nd4043hNHIn2G2pNK9blXafwKSu/5kBSky6/m3ihHyaspyB7rCLR2UXkzNgtzVhWhbHc99q7JhP+5pShWbXWrnC964lPlqfZ6q/P6RNm+GIOGTUb+ruY9t4nF9Zy1ulidsyahj7oOafIx3ajriAaULszGMsxB0bo5wBPZyH3VKjev1zwt2QZ6TYORX26fGbX7ZFiU6Lx9JhnPm+bC1SmKxOA3UYtLRbpbEPKtxTB6Yk6OMp6yarqDw2UUI/sas+em+tAwyHh/5sm+LUCb+2Sol3j5otDQHJFyde9VS2hZ23qV1PHmsCILcs3XrTGhY1EftG7jRe8vxGSzB+ri5hznPBikjxTsve7YX/8Ls4JDsMQO5je+/IqzZoXt8yxr+BCzx3xj0hTMf0cP7mjlJazx2EPjaudiadTe36Exzd2/qLDWodYSMY53+FjrsfPUW32LpeaF6Ui7bjqK7YELdcKdlBTrYqEa1c+qP3dMRoa6gA46U42SF+XnftHF314i0ibOV3m9DCvXO04q90ldH4RJzxojBsfULx2ZM/zI37IMG1b5kXNvhi4/bXA6siaqE7hVqu6FBaTVReOCkUgaFitQnYr5EeU5X831IWVshqpTBdggP20NqkHp+kLUXDMUQ+P0IEpUF6/zVSKX/a7YcSJeg8J7EjDoznyV881sT7X+SWPGnSp/7B03dpWg2CUoWLm2KDzP/MUoUPmbkpWO0GVbJQqKw3814H+xACv8Lhd3bnzqglCVT/FzG8LzYV8pCp6rQdKQoairlvEzVT2fmILeth7ndVtKUGA+9kZtK0ul6YmVKN5nzjJVr89XeaPaqhS5yGwNTT/OIvlRvU1dnNyt1jXCHqSoQ+mrjcixEenIHuFSR1WaCn6natJoVQ+ssSBHpGGyrxSlywtVmaj5N8rMRAwdlQX8aRnyiv3IHDPSDLaoOv6jNAyaVhx+0dYvCUmxeol6PJZ10EWlZeXa8HpZ82J+I+tLE5n5VvCcI9/2bECB2b67a6ZyswxOQ6Y613CWX8Nbhchv6pcA+guRSlTX2EvOaPfaFvNYfy7fcazXYIMql/PXG2njc4BXVyL/jfDQQN3GAizd4cOs1Gg/DZcxhtXnh8t7G97IxcikobZgifJ0Pkrs+3C8HIWr1D48kK6/TOqdmo4cRNZ31Kn28clK+H4iwbcmtn0DMpG3JBP+J+Yiz5FWO2/HnNc88/L5agYjy6UfbUjDG0Uoinaq1iiNLKNGa2IbaIl1zuPgb/Ln53m2R+ZwWAUvrFTLq8+EIcY6klPU+bU6R8hTx6F1DwjRuHMiVS5/Cit5lD+3Qp1R5yA91Z5WF3GOJ3eNOd57Y+QYdYXyXCFWbi3V42/r1Q4eiXSfOof6RQGKfZN1b3DtrWUYNywNy8K+kExEki80hEernC96NGR0Dnz+FSgKOx5UebxchJrDIzH0xuY8t4kt4pxVXUes+J36NNDnrOdxTDfiOqLh1VxkPwHM+m0uMqfkIn+GKrep1uter3lasg30moZkpN2hrkOdnxlyvKyJXW7ePpPOx4WrU+Ti888/D5zvdOTIkeB0+PBhPVl31JS7a8pdNuVum3LXTbn7ptyFU+7GKXfllLtzyl06idom6+7NLnckNu9wLa/Z7y4dvGuzmoJ3IbctGzHFvAO0bfsx3xdjOWsyl9d3TXZ73Zoi0hPaH/fX1dbNu5eHL+N4n31y3jHeMS+W6MuHb89+B/iI9Nkm+3KRaTbv1uyl/GIto6fwOz97T5Ntn12mUN1zqXdKaDvud4+2pyO8HoeEtm/sQ6y068mtfKNNLvUpxNynYB6bdyEfmxNYWrghsLl0Q6BgSU5And4EUn9REX5X7qCjgQ0z5O7ZyYHMJUXqPZsDGwrzAlk3+QLJg5PV/Bh35Pa0vb2Bgvtl/b5A+s9WBzao9RetmRPIHKzSLXfyNu/cbuRZ9G0dfXmWkR/ICRQdMmea6svz9DYxODOwtHhzYHNJQWDpD9P1HeqzCq17tDvyKp5javnRanlfRmC+3reiwNIpkh+pgbxtsmfOO66bz21lu7cwS6VB8mdOYHWJSlfx6sAcax3lZmm43IFfc84/uiEwSz1PmSF5WOW4I73JvPN8MB+kPBZmBYb4klVZ2tMWOhak7FbIssVLI8rESoMuux+uCBRJ2S3JDCSrealqv636ZJSddfxE5oNVPr475gcKdD6EtlUhK6lcarxu5ZPK6xUzMgLJkm7Zn2AeVwSWyl3oJ+aptFQEatV7I+qNS7mt0HXBnubINBqizbeLTIO3MvR+nBl1PSUw67cq/dWuJR2oeDJVLRM6pjYXrwjMmpgc8Kl1yb5aaQkvm8jnkWWzIpAzVtJpq6NafWDzI2q/1bK4vyiUP6rsUmQeMgKrd5vzlNp1Uvel3iw11ivH5AOSZuv4ceftWLaOrch6KekLtu8R5RK//kTUJ5Nzfn3pfL295Cl5ev82qDYt3ecL+KS+xqg/jSs3D+kw8ys8HUY+xGzrIvLGovLIfvyo/M9TbVbq/VmB9Ebnk8fjzJmWaGlzzj+2OTBf2hFVV/J0WlX7ququT5WDW9pCon0WOOdbn12pgZzlcsxKe2rUM9/9BepVk1vbbLVDwePd+GyUsgm918yH0amBVGsfrOPPlxUoqNELadZnSeoDRn2XtkO3ofblmtz2mWVutcdReDrmvOZZ3M9Xox2073PRcpV/g7MCWZL+YBm5l6V7/TT33Vq2MWUUrw4rFU+mqHVlBPJUu1XxSX2T20BL9HMex7Y9f35G8toeRbP3t+lGGn2q7pjzrONB1ju/NHw/vZwTGWWnjonRqlwWFqh0WfU4/DMgkpkvcY8n9zrjue6K3atVe2jsY942c57+jJd5avmfbw6eHwXqK4x6ptI0Z42s1zgHztD1LPRZ2vTzRXN/Iuqog8t7nXXWXWS+rP6ZWR7rZItez228H0uRjH1MUWWbbJ6zBttA+zmrp2PanadzD/WZM8dRbta1re8Rq8y9XfM0XxvoVo6NTIPjM9Rod0LniW48fSZ5/SyPcB7XpRRB4sgST5a4ssSXJc4s8WaJO0v8WeLQEo+2YtMMfhPFZH5oSUPpPJFoTPBbs63L9fVovL7PuZw0nqG0WOkPCx47ArbR0mMPYLo35rbtyGT7kI8IfjryMSw95rxYYi1vnFQar0fsi0tw2m1f7OsIXyZOOTjqQ/h+R/mQ9ZgmzfwwDU3OD8do9S7afGHfpxgnArZtyzpCeSTvcZR9rPL1WN9CzHXb11mzIZD3QHpgiFz0qNd8N2UE5hRGCZZajlUFCh7JMN/jCwyRYHbJ3sBRHdiKvIAJ42l7RwNly2cFMtSJi963wamBzEcKAlW2hdwvVm3q1UmnvHfGBtd9qa8uUulQJ8ayjLUPpS7l7GynYlH5UrQwR11Imeu8Y06goNrKC7NuBNdnPnccd0e3qovJO4bok0Q5kUudotbxrm0PPJ8c1gcqlksgW9aTFSiKUjXqqwsCc6zt+YYE0h9YGtiw+6hxcuybH9isk2/lxQa1TnP/1LIZjjIJpqGkIrDCzFu38jXKzjo+3PMhrHysbVkn4MrRrUsDOepiN1Q/VgfK1DmRvpicuDp40bL3ZXXRaJaHXHS61puj9nJDIHm0UZ9Dtdg9jdHnh3OmwXMZej3Ojqn8vtcsQ/tFVhh1TMkXTcF9lAvrMnUeaQQeMtYYORZeNpHPxdF37ceOqqNSZ2oij3krGJP+W/slZFlgvrxvfKiMLHtL8gI5Y626bx4/9rofRfxj2VBbGqozuoy3Fum0BNtNl3KJV39c65PiNt9eZ303ZantV3ioP40pN4/peDd0zBvH54bACklHrLYuWp0Vh8p0kE7nvzoWc5aUBY7WyGdTY/PJ43HmTIvX40nY06ralSyV1oq17mkLifZZ4DL/dG1gs+2zS+fvmgrHZ1CUtjns80Pem67ycnOg9rT5upUPanu6XuptqPp+b546/sxFbGpLbZ8lug1dHahwfBHc1LavfpsR+El9MhjCdBX3mBOe8kyJ+fkq6gNVhbZ8MV/X50zBMnIvS/f6GcrvIK9lFK8OC3UuNGei2R78wsjHpraBWtRznshte/38jOStPYrK+vIzGPgTewMFd8v65pjnG+HinRMZZac+oyQ/g+1aljoPiZMWK1/iHk8xzgW91l3ri1THPu7VbQ8Cc15x7PjRisDqGZnBfDbaVXs9MzTtfNHcn4g66uD2Xpc66y78HN449m3p8nRu04hjKYKxj5nq3DN4zqryJ2OGagOdhRP3mI4u9rmHansekyCzalcc7fPe32ao+SmB+Vutco9/zaM1SxuouJajxzSoz4xg2Znn5htWmceguUg0cT+TGvNZ7uSpTpEXjQ1+J0jwWhXQeVHbNR+FHtv/2qdz585F/JVp0KBBenkiallyE800GeZCjwudFfWnhnbB9yAPEgpQFxF0EfO/MBlJeiiX+PWhKfWN6PzIjT7TkCvD+MS6t4AMXZSaq28CND/uUE5EF7saFGYOQvZN6rhayLOA1lLz3GQMmjpEffbm8VyMiIiILlp79+5Fp06d9CTD0Tr/2ifBMb+JKLb9hVgaHBPaGLOaiIiIOqC6Esy+Lg2zX3QMvLmvHEUvAplDks0Z1HLqUDJzENJmFgfvqWGoQfmfioEpQ8FSICIiIvKOwW8icmfdnPKabBi3V8pEwQMMfRMREXVYvdOQMb4GK2dmY/pvilG6pRQlLyzG5PHqXGB0Hubewd/vtLzeSJuYgZqnZyH7RytRrMqgdGMhFt8zDtnrU5H3cCZ/RUVERETUCAx+E5EneeVFyBpgPiEiIqIOqDcylldi88PJqPntLIxLH4dJCzagz9QiVG2cj9Se5mLUonrfsQKVpXORvGclZqkyGJeRiw09c1D0bgnmj040lyIiIiIiLzjmNxERERERERERERG1eRzzm4iIiIiIiIiIiIguegx+ExEREREREREREVGHw+A3EREREREREREREXU4DH4TERERERERERERUYfD4DcRERERERERERERdTgMfhMRERERERERERFRh8PgNxERERERERERERF1OAx+E4Xxo/CeBCQsKjefX2jns/1yLE5IwOQX/Obz5mKm6Z5C9SgGfymWLSqOvUyH5TGPzDJqvfrV/PwvTEZCwmQU7jdneNXW68tFXZ8vHk2uv169tVitPwGL3zKfN6e6ahQ+vBKV5lPPdJps++x8fl5a+zO04/NvWYbFL7Jlal0tdb51MfCSd3WofmEuVm43n3o+x2pLzu98z3mct/hnVZPT6yyrtqatp4+IiC4UBr+JqFmU/24c5r7bYD4jiq2t1xfWZ2rr/Btzkf2rOrCWXkzKkZ8+FxUsdOrI9pcgN2sZ6s6Yzy867eg4b+tlddHXJSIisjD4TUR03nzIWhdAYF2WehRLKuYH1HKPpZrP2z/fvUUIBIqQNcCcQUQho+er4yOA+aPN50RERG1Oxzs/JSIismPwm8gD/5aVmH3nUCTJTwKThmLSzJUoP2y+GFSH8t/MxqRhSZCfuScNm4TZvylXc0MadhVj8bRxGJqk1iPrui4Nk+cVovq4uYBnDfpnfMa2kjA0ayUqXddh/NwvVpqsdU1OHRSepvCFwh0vx+J0tc7UXJQeNn6OmrZAzV+frfMo+HPWM36UxskT46eci1V+lmNZlpHHstzcF6od6XSyfl5fgvInJmGQet8gSY+ZD3XvFWJuvDI7Xo3iRdlGecgy80pQs68Qk20/LQ2mz3gaFD7f+ZNc82e9z5Wj+EeSBlVG9+Sj2pwf/FmpNdzArmoUzptk1otBSJu2LDKtKn9WzjT2U9Ka/YTKxzfiDVcQGoKg7o1lmG6WsZW/YZ2KPJSVm/Cf4nrZXoz6osQtNyvP3ijGdEmrWmbys9Xh9WhaWjCfJrkdXzKkibWMzu/FKN5l5Ubs9EXQ5TIZadfJuoxtjnMrP13XpgeXG5Q6HYtfDC8Do32Ili6Dl3qt8z49tIykpzRsF5pwzJvitoVRyiequPmi0vri4tD+6GUmO+qvebypefb2Tta17A0POyX8HtqfmPUmCp0ftmFPPB/zscuofJFKZ1axepSLNHk9+FN143Mo+D5pe9IbkQ8WaQ+eiF1fhf04H5QxFyX76s1X4vNcl7y0jxG81BsXMetv/M9Tt8+zhOtC7V/Ni/bP7cj9iJkn++WzKU2VOFCcJetQ6bTafo/lFUEdf4XzQu2XlUfO2tKkdvl/z8NItfzcVyNTUb5ILZOyLDRkT9xjK9pnahQe2mXvnxnGsRgqt2jnWy468ueDp/awCXkndemabOjWLVXWHX7+dXR7PmZnGGmLPJeJXU88tznOcyq3+bpsvZyT1aNm42Jkm+1G3M+lWMe5qKtEvm27jT/HiaYJ56exyipumxStrBrzeR6nTY5Tl4iI6CLz+eefB853OnLkSHA6fPiwng4dOqSnzz77LPDpp58G/H5/oLa2NnDgwIHA/v37Ax9//HHgo48+CtTU1AQ+/PDDAFHbUBsomIIAFpaZzwOBvYVZAR8QSH1gRaCodHNgQ2FeIHOwWsaXFSioMRcK7A0U3O8LAMmBzIUFgQ2lGwIFCzMDyfK+X1QE6mWR3asDGep58pS8QEHJ5sDm0qLA6p9l6HX7ZmwIHNXridy+m4onU9W2fIH0n60ObmvI/VmBTLWuzMJac6naQNEDySqd6YGc5UVqe5sDRctzAuk+tb37C1SKzaUKM9W6UgM5SyTdsn/zAxlqGUxcbS5jpmlKgXokzH0dnBMo0vtfH6jdtjmw4odqmfHzdR5VfCJ7bOWJWrfefihP3LafOtq2Pz838iWYd67MdPl8geQ78tR21fvWlul8rC3OUdtR6/uhUWabi1cEcsaqtDjKbPXdMi89MGfNhsDmkoLA/Dt8Ad/EjEA6MgMFnxhLGenLCzhLJHy+M4/KAnmynyptqT+RfVJl/XJVcH6wfMvz1DpS1L4nB9NqlVEo/5Vj6n2j1bzBmYG8QpVWc39SR0s9CKU1kpkutVyq9V61n3lTVL1Q+TO/1Mpdb2XlxsgHKw1ethetvqh3eyk3nWeqnHypgVlSbsUqf6utdEg9ijwGfT/fHKxH9duW6vwNHofB9KUG8spjpy/Csc2BOXI8jc0JrCiWY1ptc0lOIFXKePTSQIW5WLD8gsdikVp/uqrjvkDWOqPG1Kv9kvcF12Xb9yKrLnrIH1lPilomQx1LwWX0tucHNpu7YeVV9GPenae2MEr5uPKQL3t/m6HWZ5Wp7M/qwBx1nMo2Zr1stJrWcZWi6l2yM/+QEVi921zMhZEXkt7Y7U/8ehOFzg+oZezP4x/z8croaLV632Ppahm1v5Iv1ZIX9YHNj0h9CLX5GwqXGuWv1rW0Uq/aTIOt3XA+r68ILJW8s45h27GUqtoua2+PvjxL51PylKWh/RibFcgar7YX5zPMe13y0D668FZvXOhtutXfxn2ehtohVacfkHY6JTDrJ1mqfs4JrFb1x+2Yi5sn9bWBilJVr9Uy6Y9JGioCtVIYHssrktVe5wSWWu8z637GmlDuNr1dVp+xUhceCbW/BnW8qn1PedJoIb0dW8YxHvmZ6sJju+z1M8Pb+ZaLDvz54LU9bFLeHaoKbF43X52HIZCzSvKtSp3Xhc73fMF6XhRYGnZuIaLXE+9tjss5lXO+p3MyIy36HNUqtxLVDkmZxPpcinKchz6rQu1a0ZKmnONEY6a3MeenrmWleGqTopWVMT/+57mHNjla+oiIqEOQOLLEkyWuLPFliTNLvFnizhJ/lji0xKOt2DSD30RhzBNs6+TvUJE+AU15zHEBeXSDcVFjnnDWl87XFypzXgk/sZQL8OTR6qLimLoIWJUeGDI6L1AWtkh9YPPP5YTOEUSNFTgw0+S8qN27Vk6MQxcURpoyAiucgScdhLcuFsztqf2zqy+ZFfDdlGNeEJjL6MDuXvNk03axYCpbaC1jOKouxOTEef7W8Dw5WjJH55V1sWKc0Lvsjw5exApcmenCrMAGlb9B9ZsD81XZZKxyXhirC/GJoTKTwE1k+vaa6wxd5Bjpa1rwG+NXBMJT4XZxEVm/jHWH0lCxJCUyz62LL7cLtSArj9QyYeWl3isXMGY6vJaVm/C0etuecNYXr+Vm5Vm6YzmrHmWuDQVtRNlC+/FlrusR68smixk0tF3cR6TPxdGX5+ggvzP/966Ruhuabzx31mXZZnJgyJTVqo4Y6YoI6EnwZPCQQOYata8e80en+27HFxbVKwLpg1MDS3UA1iyjmMe8C49tYbTycRM/XyoCK8YPiQzgmXkRqk/mcTVifqDM3hZ8UhA3QGXVm4zfhtcbo/2xytB7vYlg5kd48DveMe+tjIz32NqmQ6osJJDn3F/zi9fgfJ0GW711PNfl4psT2OCIEtS/Iu2BVV4VgaUjVJ44vhyr3zo/kKK25eUzzGtditc+RvJab1yY23TWX2+fp6H6FNYOqe3OkTxx1M+9v5UvL7ICRVIsXvPErOv2MvZWXi7M42P+VvO5Vh/Y8BNfYMgDZrmeZ7tsHONzgoFVTS3rQ7qZLq/HlnmMR3ymRvLaLruWlRL2meHxfMtNx/188Fhm55F3Vt0MtptWupz5ZB3TwfRGqSeNanNc2hbHfG/nZGZa1LEp1wBBVnvsqHfhIo9zq76Gf1apPNfXEKpt0c+9Hk9uzPRa7aN5TMdtfyPKyqzTcdukKGVlzY/zee61TXZLHxERdQyNDX5z2BOiGOrKS5GPdMyamopEc57WOwPZD6fA/8sSlDUA1W/lw++bjcnjw5ZC8g83YG95HtJ7AikzNqOqfD5SwxZJxNBhaervUdTH+0WiqaGyTKcp597wNCVPmQV1gR1UuWUx/DcOQWJtKUq32KZPGpAEPxa/IT847g3fYB/wuzws3liNOjMNiRNXoPbd1cgaaDw3HEXpomxMfjYFq8sLHK851aHs1Xxg/CzkfDs8T3pPzMbcEWr7G8tsP3/MxOwHHPujlstECUorYww5IaakYaTK36DtpVjsH4IhibXh+72lBg0DoMqsHJVqyxVbVwIj1P6EpS8ZmT+05+J5GjMSQ8yHsWR8N3zffckj1b/FqNE/da1EaaEqq/tzkGnP856pyJqpTum9uHsyUsPKKxnJY9Sfd2tUTWhsWXkQc3tReCq3kPQUt5zNxOQxyeZjQ/JgOb4qjLzcV46SjUBafzUnbBtlqEscCmwsQXnYz5Vj633HUpTtjhzvPHmIbLPOPKb96lgsUfU0G5MGy3NLItKX7EXVuhwM8asyVunKvH+SyimbnulYursKRQ+offWYP74B6rL6xRVY9mw5aqyfQt84C5t3l2GOHne6Mcd8iNe20OJePnYe8gUpmPVKFcoec2xTldVQqU/H6sPr5R2TkGpvCwYkQx9Je2qM51HlIOduR70ZL+1PMTaUqxrbzPVGxD7mm1ZG6JeBpeV7UXSveq/d4KHQNfK4lyFJalD+J1UuY5JU02Pf11KU1anPK9Uml2xTebKnAiU7gOz7M8PqbOK3czBrvPkkisbWpdh55aaR9caFs/56+zy1ONqhxB7oI38d9TN5SKr6twENZxqfJyEey8tNPx+GqKqSv2QxSnZZN05NRMbyWlStyTLK9Tzb5eQxmcjAMpRsDSW+/NUV8E/MQroc9409tjx8pnprly2xPzO8nm+56bCfDx7L7HzyLqq7s416Y7GO6V2OcwtHPWn68eWmkedkP5ysrwGCzPa4eF/Us6EYMpE9PqzFNa8hqlvkHEc0vv1tZJsU7ZiO83neuDaZiIiIY34TxdRwvFb9m4Jkx8WLSFInYnKS5z/sR021OpFTF1Dhl1DuGur8qH6rFCUvrETuzElIf1hGo5P1GK/HU3dYTvxc0pTYB0kjzMfqxK9ml/qzS8Z2HIdxYdNsdRGg7K5VS6kLrB/lY86QCuRmDEWfHkl6fNjFL5Sixjm03vrZyF4go+WVoTTaxXRQg0qn+jMiWZ2EOiUh6Tr1R534hzYxMnJ/zBPdQnVR0xj+T2R0x2osm+bc73GY/TtZogq1/jr496mH16m0yCybxOtGqsuLC6tHF/OBqwYc3aEueYYlh1+0KckqrZ6o9fcwH0ZqbFl5EHN77ryVm/yNI1Ze+mvUJZu6eJo3KWIbkxeVqlfKUNOU69HjdajZoS66XszHsnnTkXa/jNZZah7Ttah+Vf1R5ecISYbsr1ZLq6MgOeoSnvMneUoeVkzxY6WM99lLxsmcjNm/KUboO6RGHPM23tpC47k3HvIlSNVRfzXKt5Sg8De5mH3n/9fe/YY2de5xAP85NqjghQoOTsELS68vTNlglXuhKeyFkb0w4mApCrYo7GYTXDdht/ri0rIXEveiS32xtQ52WwdKMlCSwSQdbCS+cLSCl1QQmoGj6cVBArpV2KDCxp77e86f5OTkJHnyz9Xs+4GQeDxNnvM8v+dvT/P4aeIaH3bG5XPmc8M49neZLy0vGO1P9ge+7g7ETe0631wZFf3G+bW+QukbCVr48Ay96RvTvz82XVBJJPcdX/DTtTN0yHGtB46e1+N0aZ3zhPu9NPnJ63G2StwPlS3iVWo0lmrnVS2KcVOXan9q45ZmZ3w+W2olm69fiuXlpsdPoU8naOD2FB3y7qTt+vc/n6fYjVwxf1pul/ccorEjRDPfWL9AXab0xQIFjviN8VKn2mSpZrtsUyO+1MZbdXRb/6BYZm3JOycuq0bHFlJ7+68Gx2RN90tV1GoPn3hf5aaFNsmuZr410SYDAMCfHha/AdrgscodI+uLdMbfR9t38mTC9yaFP0tQYUeAQsf95gmt6qXe582XliNRysvd290el4PGZOuFAEXSedrIpig6PULezTRNjR6gfu8YxeQCsUXzU3g5T6mzRLHTYVpUnii0RnvWOb1QEaTofZdr1h9RCtZabWt4oN9hj+vfpdg9Wii3BoSX3d5fPvI0+XfzJBW/rNDc0X7a9ped1D84Ru98HKOlXzQKnQiZJ0hcevVmYL/VP8WgkD87Bmn86hpt3s9Q/NIE+bdnKX56hPb1DdP5W2Ykqdb5jlLIF5a7foYO9G2nnX0DNHwyTAvXC9TzaojG6txd3C47d/Sar9oYNyqaKqPHtPLxCPU/x/nl2Udjp+codvsxaSdDZI9IJeeWXK7TeOT/PWie5KaHeux36/1BOhI3Kv3pH6XJ8vIcjlDq/gatpqMUed1LmzenaMzfT94TMSr92rmVdlmjwDGOvitp487aW2maLQQo6Ljbuq11S6ldbpXLeMupy/uH5stMIe+2sqdgTPZE+6pqmu5DGrCV22QAANhysPgNUEPPDnkv7Irrn/flf5BTQy9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+ } + }, + "cell_type": "markdown", + "id": "459c4858", + "metadata": {}, + "source": [ + "

Components of the User-Interface:


\n", + "\n", + "

Notebook Dashboard


\n", + "It is the first window that launches in the browser upon opening the Jupyter Notebook through Anaconda Navigator.\n", + "Given below is the snapshot of the same.

\n", + "\n", + "![image.png](attachment:image.png)\n", + "\n", + "This is where the various notebooks are shown.


\n", + "\n", + "

Notebook Editor


\n", + "Once we click on a notebook, a notebook editor is opened.\n", + "\n", + "![image-2.png](attachment:image-2.png)\n", + "
\n", + "\n", + "The Notebook Editor is made up of various cells. When a cell is in Edit mode, the Cell Mode Indicator will change to reflect the cell’s state. This state is indicated by a small pencil icon on the top right of the interface. When the cell is in Command mode, there is no icon in that location.
\n", + "\n", + "The Notebook Editor also various provides controls in the ribbon, to add/delete cells, etc. One of them inlcude the option to choose the type of content to be added to the cell, vis-a-vis, Markdown, Code, RawNBConvert, Heading.
\n", + "\n", + "\n", + "\n", + "\n", + "


\n", + "\n", + "\n", + "

Kernel

\n", + "\n", + "A notebook kernel is a computational engine that executes the code contained in a Notebook document. The ipython kernel, referenced here, executes python code. Kernels for many other languages exist (official kernels).\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1f6d9791", + "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": "3.9.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/w1/Matplotlib Tutorial.ipynb b/w1/Matplotlib Tutorial.ipynb new file mode 100644 index 0000000..b4150e0 --- /dev/null +++ b/w1/Matplotlib Tutorial.ipynb @@ -0,0 +1,357 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "38faad38", + "metadata": {}, + "source": [ + "# Matplotlib" + ] + }, + { + "cell_type": "markdown", + "id": "3ab57580", + "metadata": {}, + "source": [ + "It is the plotting library in python that serves as a visualization entity " + ] + }, + { + "cell_type": "markdown", + "id": "e5701363", + "metadata": {}, + "source": [ + "The first step is to import Matplotlib library to the current jupyter notebook. Most of its utilities lie under the pyplot submodule." + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "85363626", + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt #Shorthand notation is given to facilitate easier further usage" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "7f4e0cbe", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "\n", + "xpoints=np.array([0,6])\n", + "ypoints=np.array([0,250])\n", + "\n", + "plt.plot(xpoints,ypoints) #plots a line\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "50b74847", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plotting multiple points\n", + "xpoints=np.array([1,5,7,8])\n", + "ypoints=np.array([2,4,5,6])\n", + "plt.plot(xpoints,ypoints)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "cfc51c0c", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Markers\n", + "ypoints=np.array([1,2,5,4,7,6])\n", + "plt.plot(ypoints,marker=\"o\",ms=10,mec=\"magenta\",mfc=\"red\") #ms defines marker size, mec defines marker edge color, mfc defines marker face color\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "bd2afe0a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#linestyle\n", + "ypoints=np.array([1,2,5,4,7,6])\n", + "plt.plot(ypoints,marker=\"*\",ms=10,linestyle=\"dotted\",color=\"red\",lw=3) #color defines line color, lw defines linewidth\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "37a100d9", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = np.array([80, 85, 90, 95, 100, 105, 110, 115, 120, 125])\n", + "y = np.array([240, 250, 260, 270, 280, 290, 300, 310, 320, 330])\n", + "\n", + "plt.plot(x, y)\n", + "\n", + "plt.xlabel(\"Average Pulse\") #create lables for the axes of the plot\n", + "plt.ylabel(\"Calorie Burnage\")\n", + "plt.title(\"Data\") #give title to the plot\n", + "plt.grid() #add grid to the plot\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "2adf1fd3", + "metadata": {}, + "source": [ + "## Subplot function" + ] + }, + { + "cell_type": "markdown", + "id": "0ce5203b", + "metadata": {}, + "source": [ + "It is used to draw multiple plots in one figure." + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "99388d02", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plot 1:\n", + "x = np.array([0, 1, 2, 3])\n", + "y = np.array([3, 8, 1, 10])\n", + "\n", + "plt.subplot(1, 2, 1) \n", + "#plt.subplot takes three arguments, first: the number of rows, second: the number of columns, third: the position of the plot\n", + "plt.plot(x,y)\n", + "plt.title(\"plot1\")\n", + "\n", + "#plot 2:\n", + "x = np.array([0, 1, 2, 3])\n", + "y = np.array([10, 20, 30, 40])\n", + "\n", + "plt.subplot(1, 2, 2)\n", + "plt.plot(x,y)\n", + "plt.title(\"plot2\")\n", + " \n", + "plt.suptitle(\"Plots\") #add title for the whole figure\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "4643c622", + "metadata": {}, + "source": [ + "## Working with CSV files" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "id": "5e7ba9da", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "df = pd.read_csv(\"Data.csv\")\n", + "df.plot()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "id": "7c4d7d1e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.plot(kind = 'scatter', x = 'Duration', y = 'Calories')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "21925362", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df[\"Duration\"].plot(kind=\"hist\") #plotting a histogram which gives us the frequency of each interval" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e3510645", + "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": "3.9.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/w1/Numpy Tutorial.ipynb b/w1/Numpy Tutorial.ipynb new file mode 100644 index 0000000..fda6488 --- /dev/null +++ b/w1/Numpy Tutorial.ipynb @@ -0,0 +1,480 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "e986db8c", + "metadata": {}, + "source": [ + "

Numpy


\n", + "NumPy (Numerical Python) is an open source Python library. It contains multidimensional array and matrix data structures. It provides ndarray, a homogeneous n-dimensional array object, with methods to efficiently operate on it. NumPy can be used to perform a wide variety of mathematical operations on arrays" + ] + }, + { + "cell_type": "markdown", + "id": "81721f02", + "metadata": {}, + "source": [ + "The first step is to import the Numpy library to the current jupyter notebook." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "bcd76cf5", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np #Shorthand notation given to facilitate easier further usage." + ] + }, + { + "cell_type": "markdown", + "id": "8f043d03", + "metadata": {}, + "source": [ + "

Array

" + ] + }, + { + "cell_type": "markdown", + "id": "99c2f9a2", + "metadata": {}, + "source": [ + "A numpy array is a data structure which is similar to python lists, and it has a grid of elements that can be accesed in various ways.
\n", + "An array object in NumPy is called ndarray." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "613fe783", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "[1 2 3 4]\n", + "[[ 1 2 3 4]\n", + " [ 5 6 7 8]\n", + " [ 9 10 11 12]]\n", + "1\n", + "[0 1 2 3]\n", + "[ 0. 5. 10.]\n", + "[1 2 3 4]\n", + "2\n", + "8\n", + "[1 2 3]\n", + "[2]\n", + "[3 4]\n", + "[2 3]\n" + ] + } + ], + "source": [ + "a=np.array([1,2,3,4]) #Initialising a 1D array.\n", + "print(type(a)) #returns type numpy.ndarray\n", + "b= np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12]]) #Initialising a multi-dimensioanl array(3 dimensional in this case.)\n", + "print(a) #To print the whole array.\n", + "print(b)\n", + "print(a[0]) #using indexing to print an element of the array.\n", + "\n", + "c=np.arange(4) #used to create an arrayof range of elements.\n", + "print(c)\n", + "\n", + "d=np.linspace(0,10,num=3) #creats an array with values that are spaced linearly in a specified interval.\n", + "print(d)\n", + "\n", + "#To print a single element of a multidimensional array, multidimensional indexing is required.\n", + "print(b[0]) #prints the 0th element of the 3-D array which in itself is a 1-D array.\n", + "print(b[0][1]) #prints the second element of the first 1-D array.\n", + "\n", + "#negative indexing using numpy\n", + "print(b[1][-1]) #prints the last element from ther second dimension.\n", + "\n", + "#Slicing of arrays created using numpy \n", + "print(a[:3]) #prints an array containing first 3 elements of the array.\n", + "print(a[1:2]) #prints the second element in the array.\n", + "print(a[2:]) #prints the element from the index 2 to the last element.\n", + "print(a[-3:-1]) #Slices the array from index 3 from the end to index 1 from the end.\n", + "#Similarly 2d arrays can be sliced.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "4c8c64c8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[2 3 4 5 6 7 8]\n", + "[1 2 3 4 5 4 8 7 3 2 6]\n" + ] + } + ], + "source": [ + "#sorting a numpy array\n", + "e = np.array([5,4,8,7,3,2,6]) #sorts the array in ascending order.\n", + "print(np.sort(e))\n", + "\n", + "#concatenate two arrays\n", + "f=np.concatenate((a,e))\n", + "print(f)" + ] + }, + { + "cell_type": "markdown", + "id": "3cff1578", + "metadata": {}, + "source": [ + "### Shape and size of an array" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "d91daa31", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(3, 4)\n", + "2\n", + "12\n", + "[[ 1 2]\n", + " [ 3 4]\n", + " [ 5 6]\n", + " [ 7 8]\n", + " [ 9 10]\n", + " [11 12]]\n", + "[[ 1 2 3 4 5 6]\n", + " [ 7 8 9 10 11 12]]\n" + ] + } + ], + "source": [ + "print(np.shape(b)) #returns the shape of the aray\n", + "print(np.ndim(b)) #returns the dimension of the array\n", + "print(np.size(b)) #returns the number of elements in the array.\n", + "\n", + "#reshaping the array\n", + "\n", + "g = b.reshape(6,2) #an array can be reshaoped as long as the new array has the same number of elements.\n", + "print(g)\n", + "\n", + "#This can also be done by using np.reshape, some few more parameters can also be specified.\n", + "h= np.reshape(b, newshape=(2,6))\n", + "print(h)" + ] + }, + { + "cell_type": "markdown", + "id": "bd52f32a", + "metadata": {}, + "source": [ + "### Adding axis to an array" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "32848044", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4,)\n", + "[[1 2 3 4]]\n", + "(1, 4)\n", + "(4, 1)\n" + ] + } + ], + "source": [ + "#Converting 1D array to 2D array\n", + "print(a.shape)\n", + "\n", + "#np.newaxis\n", + "a2=a[np.newaxis, :] #1D array converted to a row vector. Similarly it can be turned into a column vector.\n", + "print(a2)\n", + "\n", + "#np.expand_dims\n", + "a3=np.expand_dims(a,axis=0)\n", + "print(a3.shape)\n", + "\n", + "a4=np.expand_dims(a,axis =1)\n", + "print(a4.shape)\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "e1911376", + "metadata": {}, + "source": [ + "### Creating an array from existing data\n" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "55cea3c1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[5 4]\n", + " [6 2]\n", + " [1 2]\n", + " [3 4]]\n", + "[[5 4 1 2]\n", + " [6 2 3 4]]\n", + "[[ 5 2 3 4]\n", + " [ 5 6 7 8]\n", + " [ 9 10 11 12]]\n", + "[5 2 3 4]\n", + "[5 2 3 4]\n", + "[[ 5 2 3 4]\n", + " [ 5 6 7 8]\n", + " [ 9 10 11 12]]\n", + "[[ 5 2 3 4]\n", + " [ 5 6 7 8]\n", + " [ 9 10 11 12]]\n", + "[5 6 7 8]\n", + "[5 6 9 8]\n", + "[[ 5 2 3 4]\n", + " [ 5 6 7 8]\n", + " [ 9 10 11 12]]\n" + ] + } + ], + "source": [ + "#stacking of arrays\n", + "b1=([5,4],[6,2])\n", + "b2=([1,2],[3,4])\n", + "print(np.vstack((b1,b2))) #vertical stacking of the two arrays\n", + "\n", + "print(np.hstack((b1,b2))) #horizontal stacking of the arrays\n", + "\n", + "\n", + "#view method - any changes made to the original array will affect the original array\n", + "print(b)\n", + "\n", + "b_new=b[0,:]\n", + "print(b_new)\n", + "b_new[0]=5\n", + "print(b_new)\n", + "print(b) #original array is modified\n", + "\n", + "\n", + "#copy method- any changes made in the copied array will not modify the original array\n", + "b_copy=b.copy()\n", + "print(b_copy)\n", + "b_copy_new=b_copy[1,:]\n", + "print(b_copy_new)\n", + "b_copy_new[2]=9\n", + "print(b_copy_new)\n", + "print(b) #remains the same.\n" + ] + }, + { + "cell_type": "markdown", + "id": "99d65e77", + "metadata": {}, + "source": [ + "### Basic Array Operations" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "01bf7df7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[2 3]\n" + ] + } + ], + "source": [ + "#Addition\n", + "arr=np.array([1,2])\n", + "arr_1=np.ones(2,dtype=int)\n", + "print(arr+arr_1)\n", + "\n", + "#Similarly Subtraction, Divison and Multiplication can be carried out\n" + ] + }, + { + "cell_type": "markdown", + "id": "ffad24d0", + "metadata": {}, + "source": [ + "### Broadcasting" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "58c85c57", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[4 8]\n" + ] + } + ], + "source": [ + "print(arr*4) #operation carried out between an array and single number" + ] + }, + { + "cell_type": "markdown", + "id": "80e6a18e", + "metadata": {}, + "source": [ + "### Creating matrices" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "id": "c4c43139", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 5 2 3 4]\n", + " [ 5 6 7 8]\n", + " [ 9 10 11 12]]\n" + ] + } + ], + "source": [ + "print(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "id": "6d385934", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2\n", + "[[ 5 6 7 8]\n", + " [ 9 10 11 12]]\n", + "[5 5]\n" + ] + } + ], + "source": [ + "print(b[0,1])\n", + "print(b[1:3])\n", + "print(b[0:2,0])" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "id": "7cd964e2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "12\n", + "2\n", + "82\n", + "[225 120 231 384]\n" + ] + } + ], + "source": [ + "print(b.max())\n", + "print(b.min())\n", + "print(b.sum())\n", + "print(b.prod(axis=0))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "40f33e6d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 5 2 3 4]\n", + " [ 5 6 7 8]\n", + " [ 9 10 11 12]]\n", + "[ 2 3 4 5 6 7 8 9 10 11 12]\n", + "(array([1, 2, 3, 4]), array([0, 1, 2, 3], dtype=int64))\n" + ] + } + ], + "source": [ + "print(b)\n", + "print(np.unique(b)) #prints unique elements in a numpy array\n", + "print(np.unique(a,return_index=True))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d6c01d67", + "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": "3.9.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/w1/Pandas Tutorial.ipynb b/w1/Pandas Tutorial.ipynb new file mode 100644 index 0000000..1cce34d --- /dev/null +++ b/w1/Pandas Tutorial.ipynb @@ -0,0 +1,1900 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "2c93fd9c", + "metadata": {}, + "source": [ + "# Pandas" + ] + }, + { + "cell_type": "markdown", + "id": "49f2d993", + "metadata": {}, + "source": [ + "Pandas is a library that is used for working with datasets. It allows us to analyse big data and make conclusions based on statistical theories." + ] + }, + { + "cell_type": "markdown", + "id": "fd209017", + "metadata": {}, + "source": [ + "The first step is to import the Pandas library to the current jupyter notebook." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "ba1b7793", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd #Shorthand notation given to facilitate easier futher usage." + ] + }, + { + "cell_type": "markdown", + "id": "edd9cb1f", + "metadata": {}, + "source": [ + "Pandas Series : It is a 1 dimensional array holding data of any type." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a184c740", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 2\n", + "1 3\n", + "2 4\n", + "dtype: int64\n", + "2\n" + ] + } + ], + "source": [ + "a=[2,3,4]\n", + "col=pd.Series(a)\n", + "print(col)\n", + "\n", + "print(col[0]) #returns the value at the index 0" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "6e2c6b0c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "12PM 80\n", + "1PM 90\n", + "2PM 85\n", + "dtype: int64\n" + ] + } + ], + "source": [ + "#From a dictionary\n", + "Heartbeat = {\"12PM\":80, \"1PM\":90, \"2PM\":85}\n", + "heartrate_series=pd.Series(Heartbeat)\n", + "print(heartrate_series)" + ] + }, + { + "cell_type": "markdown", + "id": "fdb8a968", + "metadata": {}, + "source": [ + "Pandas Dataframe : It is a multidemsional data structure, like a mutlti dimensional array, or a table with rows and columns." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "2593f089", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " calories heartrate\n", + "0 450 80\n", + "1 250 90\n", + "2 500 85\n" + ] + } + ], + "source": [ + "data={\n", + " \"calories\":[450,250,500],\n", + " \"heartrate\":[80,90,85]\n", + "}\n", + "\n", + "df = pd.DataFrame(data) #laoding data into a DataFrame object.\n", + "print(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a9d1f47e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "calories 450\n", + "heartrate 80\n", + "Name: 0, dtype: int64\n", + " calories heartrate\n", + "0 450 80\n", + "1 250 90\n" + ] + } + ], + "source": [ + "#Locating Rows using loc attribute\n", + "print(df.loc[0])\n", + "print(df.loc[0:1])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "30a10288", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " calories heartrate\n", + "Day1 450 80\n", + "Day2 250 90\n", + "Day3 500 85\n" + ] + } + ], + "source": [ + "#Naming indexes\n", + "df2=pd.DataFrame(data,index=[\"Day1\",\"Day2\",\"Day3\"])\n", + "print(df2)\n" + ] + }, + { + "cell_type": "markdown", + "id": "66704750", + "metadata": {}, + "source": [ + "## Working with CSV files using Pandas" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "f4e5e8a3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Pulse Maxpulse Calories\n", + "0 60 110 130 409.1\n", + "1 60 117 145 479.0\n", + "2 60 103 135 340.0\n", + "3 45 109 175 282.4\n", + "4 45 117 148 406.0\n", + "5 60 102 127 300.0\n", + "6 60 110 136 374.0\n", + "7 45 104 134 253.3\n", + "8 30 109 133 195.1\n", + "9 60 98 124 269.0\n", + "10 60 103 147 329.3\n", + "11 60 100 120 250.7\n", + "12 60 106 128 345.3\n", + "13 60 104 132 379.3\n", + "14 60 98 123 275.0\n", + "15 60 98 120 215.2\n", + "16 60 100 120 300.0\n", + "17 45 90 112 NaN\n", + "18 60 103 123 323.0\n", + "19 45 97 125 243.0\n", + "20 60 108 131 364.2\n", + "21 45 100 119 282.0\n", + "22 60 130 101 300.0\n", + "23 45 105 132 246.0\n", + "24 60 102 126 334.5\n", + "25 60 100 120 250.0\n", + "26 60 92 118 241.0\n", + "27 60 103 132 NaN\n", + "28 60 100 132 280.0\n", + "29 60 102 129 380.3\n", + "30 60 92 115 243.0\n", + "31 45 90 112 180.1\n", + "32 60 101 124 299.0\n", + "33 60 93 113 223.0\n", + "34 60 107 136 361.0\n", + "35 60 114 140 415.0\n", + "36 60 102 127 300.0\n", + "37 60 100 120 300.0\n", + "38 60 100 120 300.0\n", + "39 45 104 129 266.0\n", + "40 45 90 112 180.1\n", + "41 60 98 126 286.0\n", + "42 60 100 122 329.4\n", + "43 60 111 138 400.0\n", + "44 60 111 131 397.0\n", + "45 60 99 119 273.0\n", + "46 60 109 153 387.6\n", + "47 45 111 136 300.0\n", + "48 45 108 129 298.0\n", + "49 60 111 139 397.6\n", + "50 60 107 136 380.2\n", + "51 80 123 146 643.1\n", + "52 60 106 130 263.0\n", + "53 60 118 151 486.0\n", + "54 30 136 175 238.0\n", + "55 60 121 146 450.7\n", + "56 60 118 121 413.0\n", + "57 45 115 144 305.0\n", + "58 20 153 172 226.4\n", + "59 45 123 152 321.0\n", + "60 210 108 160 1376.0\n", + "61 160 110 137 1034.4\n", + "62 160 109 135 853.0\n", + "63 45 118 141 341.0\n", + "64 20 110 130 131.4\n", + "65 180 90 130 800.4\n", + "66 150 105 135 873.4\n", + "67 150 107 130 816.0\n", + "68 20 106 136 110.4\n", + "69 300 108 143 1500.2\n", + "70 150 97 129 1115.0\n", + "71 60 109 153 387.6\n", + "72 90 100 127 700.0\n", + "73 150 97 127 953.2\n", + "74 45 114 146 304.0\n", + "75 90 98 125 563.2\n", + "76 45 105 134 251.0\n", + "77 45 110 141 300.0\n", + "78 120 100 130 500.4\n", + "79 270 100 131 1729.0\n", + "80 30 159 182 319.2\n", + "81 45 149 169 344.0\n", + "82 30 103 139 151.1\n", + "83 120 100 130 500.0\n", + "84 45 100 120 225.3\n", + "85 30 151 170 300.0\n", + "86 45 102 136 234.0\n", + "87 120 100 157 1000.1\n", + "88 45 129 103 242.0\n", + "89 20 83 107 50.3\n", + "90 180 101 127 600.1\n", + "91 45 107 137 NaN\n", + "92 30 90 107 105.3\n", + "93 15 80 100 50.5\n", + "94 20 150 171 127.4\n", + "95 20 151 168 229.4\n", + "96 30 95 128 128.2\n", + "97 25 152 168 244.2\n", + "98 30 109 131 188.2\n", + "99 90 93 124 604.1\n", + "100 20 95 112 77.7\n", + "101 90 90 110 500.0\n", + "102 90 90 100 500.0\n", + "103 90 90 100 500.4\n", + "104 30 92 108 92.7\n", + "105 30 93 128 124.0\n", + "106 180 90 120 800.3\n", + "107 30 90 120 86.2\n", + "108 90 90 120 500.3\n", + "109 210 137 184 1860.4\n", + "110 60 102 124 325.2\n", + "111 45 107 124 275.0\n", + "112 15 124 139 124.2\n", + "113 45 100 120 225.3\n", + "114 60 108 131 367.6\n", + "115 60 108 151 351.7\n", + "116 60 116 141 443.0\n", + "117 60 97 122 277.4\n", + "118 60 105 125 NaN\n", + "119 60 103 124 332.7\n", + "120 30 112 137 193.9\n", + "121 45 100 120 100.7\n", + "122 60 119 169 336.7\n", + "123 60 107 127 344.9\n", + "124 60 111 151 368.5\n", + "125 60 98 122 271.0\n", + "126 60 97 124 275.3\n", + "127 60 109 127 382.0\n", + "128 90 99 125 466.4\n", + "129 60 114 151 384.0\n", + "130 60 104 134 342.5\n", + "131 60 107 138 357.5\n", + "132 60 103 133 335.0\n", + "133 60 106 132 327.5\n", + "134 60 103 136 339.0\n", + "135 20 136 156 189.0\n", + "136 45 117 143 317.7\n", + "137 45 115 137 318.0\n", + "138 45 113 138 308.0\n", + "139 20 141 162 222.4\n", + "140 60 108 135 390.0\n", + "141 60 97 127 NaN\n", + "142 45 100 120 250.4\n", + "143 45 122 149 335.4\n", + "144 60 136 170 470.2\n", + "145 45 106 126 270.8\n", + "146 60 107 136 400.0\n", + "147 60 112 146 361.9\n", + "148 30 103 127 185.0\n", + "149 60 110 150 409.4\n", + "150 60 106 134 343.0\n", + "151 60 109 129 353.2\n", + "152 60 109 138 374.0\n", + "153 30 150 167 275.8\n", + "154 60 105 128 328.0\n", + "155 60 111 151 368.5\n", + "156 60 97 131 270.4\n", + "157 60 100 120 270.4\n", + "158 60 114 150 382.8\n", + "159 30 80 120 240.9\n", + "160 30 85 120 250.4\n", + "161 45 90 130 260.4\n", + "162 45 95 130 270.0\n", + "163 45 100 140 280.9\n", + "164 60 105 140 290.8\n", + "165 60 110 145 300.0\n", + "166 60 115 145 310.2\n", + "167 75 120 150 320.4\n", + "168 75 125 150 330.4\n" + ] + } + ], + "source": [ + "df=pd.read_csv('data.csv') #reading the csv file\n", + "print(df.to_string()) #used to print the whole DataFrame" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "419e2c3d", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Duration Pulse Maxpulse Calories\n", + "0 60 110 130 409.1\n", + "1 60 117 145 479.0\n", + "2 60 103 135 340.0\n", + "3 45 109 175 282.4\n", + "4 45 117 148 406.0" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head() #prints the first 5 rows of a dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "0352a257", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 169 entries, 0 to 168\n", + "Data columns (total 4 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Duration 169 non-null int64 \n", + " 1 Pulse 169 non-null int64 \n", + " 2 Maxpulse 169 non-null int64 \n", + " 3 Calories 164 non-null float64\n", + "dtypes: float64(1), int64(3)\n", + "memory usage: 5.4 KB\n" + ] + } + ], + "source": [ + "df.info() #gives the information about the data simplifying it's analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "83047224", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Date Pulse Maxpulse Calories\n", + "0 60 '2020/12/01' 110 130 409.1\n", + "1 60 '2020/12/02' 117 145 479.0\n", + "2 60 '2020/12/03' 103 135 340.0\n", + "3 45 '2020/12/04' 109 175 282.4\n", + "4 45 '2020/12/05' 117 148 406.0\n", + "5 60 '2020/12/06' 102 127 300.0\n", + "6 60 '2020/12/07' 110 136 374.0\n", + "7 450 '2020/12/08' 104 134 253.3\n", + "8 30 '2020/12/09' 109 133 195.1\n", + "9 60 '2020/12/10' 98 124 269.0\n", + "10 60 '2020/12/11' 103 147 329.3\n", + "11 60 '2020/12/12' 100 120 250.7\n", + "12 60 '2020/12/12' 100 120 250.7\n", + "13 60 '2020/12/13' 106 128 345.3\n", + "14 60 '2020/12/14' 104 132 379.3\n", + "15 60 '2020/12/15' 98 123 275.0\n", + "16 60 '2020/12/16' 98 120 215.2\n", + "17 60 '2020/12/17' 100 120 300.0\n", + "18 45 '2020/12/18' 90 112 NaN\n", + "19 60 '2020/12/19' 103 123 323.0\n", + "20 45 '2020/12/20' 97 125 243.0\n", + "21 60 '2020/12/21' 108 131 364.2\n", + "22 45 NaN 100 119 282.0\n", + "23 60 '2020/12/23' 130 101 300.0\n", + "24 45 '2020/12/24' 105 132 246.0\n", + "25 60 '2020/12/25' 102 126 334.5\n", + "26 60 20201226 100 120 250.0\n", + "27 60 '2020/12/27' 92 118 241.0\n", + "28 60 '2020/12/28' 103 132 NaN\n", + "29 60 '2020/12/29' 100 132 280.0\n", + "30 60 '2020/12/30' 102 129 380.3\n", + "31 60 '2020/12/31' 92 115 243.0\n" + ] + } + ], + "source": [ + "df=pd.read_csv(\"dirtydata.csv\")\n", + "print(df.to_string())" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "584bd89e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Date Pulse Maxpulse Calories\n", + "0 60 '2020/12/01' 110 130 409.1\n", + "1 60 '2020/12/02' 117 145 479.0\n", + "2 60 '2020/12/03' 103 135 340.0\n", + "3 45 '2020/12/04' 109 175 282.4\n", + "4 45 '2020/12/05' 117 148 406.0\n", + "5 60 '2020/12/06' 102 127 300.0\n", + "6 60 '2020/12/07' 110 136 374.0\n", + "7 450 '2020/12/08' 104 134 253.3\n", + "8 30 '2020/12/09' 109 133 195.1\n", + "9 60 '2020/12/10' 98 124 269.0\n", + "10 60 '2020/12/11' 103 147 329.3\n", + "11 60 '2020/12/12' 100 120 250.7\n", + "12 60 '2020/12/12' 100 120 250.7\n", + "13 60 '2020/12/13' 106 128 345.3\n", + "14 60 '2020/12/14' 104 132 379.3\n", + "15 60 '2020/12/15' 98 123 275.0\n", + "16 60 '2020/12/16' 98 120 215.2\n", + "17 60 '2020/12/17' 100 120 300.0\n", + "19 60 '2020/12/19' 103 123 323.0\n", + "20 45 '2020/12/20' 97 125 243.0\n", + "21 60 '2020/12/21' 108 131 364.2\n", + "23 60 '2020/12/23' 130 101 300.0\n", + "24 45 '2020/12/24' 105 132 246.0\n", + "25 60 '2020/12/25' 102 126 334.5\n", + "26 60 20201226 100 120 250.0\n", + "27 60 '2020/12/27' 92 118 241.0\n", + "29 60 '2020/12/29' 100 132 280.0\n", + "30 60 '2020/12/30' 102 129 380.3\n", + "31 60 '2020/12/31' 92 115 243.0\n" + ] + } + ], + "source": [ + "new_df=df.dropna() #drops the rows with null values and creates a new DataFrame\n", + "print(new_df.to_string())" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "f825b16a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Date Pulse Maxpulse Calories\n", + "0 60 '2020/12/01' 110 130 409.1\n", + "1 60 '2020/12/02' 117 145 479.0\n", + "2 60 '2020/12/03' 103 135 340.0\n", + "3 45 '2020/12/04' 109 175 282.4\n", + "4 45 '2020/12/05' 117 148 406.0\n", + "5 60 '2020/12/06' 102 127 300.0\n", + "6 60 '2020/12/07' 110 136 374.0\n", + "7 450 '2020/12/08' 104 134 253.3\n", + "8 30 '2020/12/09' 109 133 195.1\n", + "9 60 '2020/12/10' 98 124 269.0\n", + "10 60 '2020/12/11' 103 147 329.3\n", + "11 60 '2020/12/12' 100 120 250.7\n", + "12 60 '2020/12/12' 100 120 250.7\n", + "13 60 '2020/12/13' 106 128 345.3\n", + "14 60 '2020/12/14' 104 132 379.3\n", + "15 60 '2020/12/15' 98 123 275.0\n", + "16 60 '2020/12/16' 98 120 215.2\n", + "17 60 '2020/12/17' 100 120 300.0\n", + "19 60 '2020/12/19' 103 123 323.0\n", + "20 45 '2020/12/20' 97 125 243.0\n", + "21 60 '2020/12/21' 108 131 364.2\n", + "23 60 '2020/12/23' 130 101 300.0\n", + "24 45 '2020/12/24' 105 132 246.0\n", + "25 60 '2020/12/25' 102 126 334.5\n", + "26 60 20201226 100 120 250.0\n", + "27 60 '2020/12/27' 92 118 241.0\n", + "29 60 '2020/12/29' 100 132 280.0\n", + "30 60 '2020/12/30' 102 129 380.3\n", + "31 60 '2020/12/31' 92 115 243.0\n" + ] + } + ], + "source": [ + "df.dropna(inplace=True) #makes changes to the original DataFrame\n", + "print(df.to_string())" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "add5c7a2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Pulse Maxpulse Calories\n", + "0 60 110 130 409.1\n", + "1 60 117 145 479.0\n", + "2 60 103 135 340.0\n", + "3 45 109 175 282.4\n", + "4 45 117 148 406.0\n", + "5 60 102 127 300.0\n", + "6 60 110 136 374.0\n", + "7 45 104 134 253.3\n", + "8 30 109 133 195.1\n", + "9 60 98 124 269.0\n", + "10 60 103 147 329.3\n", + "11 60 100 120 250.7\n", + "12 60 106 128 345.3\n", + "13 60 104 132 379.3\n", + "14 60 98 123 275.0\n", + "15 60 98 120 215.2\n", + "16 60 100 120 300.0\n", + "17 45 90 112 NaN\n", + "18 60 103 123 323.0\n", + "19 45 97 125 243.0\n", + "20 60 108 131 364.2\n", + "21 45 100 119 282.0\n", + "22 60 130 101 300.0\n", + "23 45 105 132 246.0\n", + "24 60 102 126 334.5\n", + "25 60 100 120 250.0\n", + "26 60 92 118 241.0\n", + "27 60 103 132 NaN\n", + "28 60 100 132 280.0\n", + "29 60 102 129 380.3\n", + "30 60 92 115 243.0\n", + "31 45 90 112 180.1\n", + "32 60 101 124 299.0\n", + "33 60 93 113 223.0\n", + "34 60 107 136 361.0\n", + "35 60 114 140 415.0\n", + "36 60 102 127 300.0\n", + "37 60 100 120 300.0\n", + "38 60 100 120 300.0\n", + "39 45 104 129 266.0\n", + "40 45 90 112 180.1\n", + "41 60 98 126 286.0\n", + "42 60 100 122 329.4\n", + "43 60 111 138 400.0\n", + "44 60 111 131 397.0\n", + "45 60 99 119 273.0\n", + "46 60 109 153 387.6\n", + "47 45 111 136 300.0\n", + "48 45 108 129 298.0\n", + "49 60 111 139 397.6\n", + "50 60 107 136 380.2\n", + "51 80 123 146 643.1\n", + "52 60 106 130 263.0\n", + "53 60 118 151 486.0\n", + "54 30 136 175 238.0\n", + "55 60 121 146 450.7\n", + "56 60 118 121 413.0\n", + "57 45 115 144 305.0\n", + "58 20 153 172 226.4\n", + "59 45 123 152 321.0\n", + "60 210 108 160 1376.0\n", + "61 160 110 137 1034.4\n", + "62 160 109 135 853.0\n", + "63 45 118 141 341.0\n", + "64 20 110 130 131.4\n", + "65 180 90 130 800.4\n", + "66 150 105 135 873.4\n", + "67 150 107 130 816.0\n", + "68 20 106 136 110.4\n", + "69 300 108 143 1500.2\n", + "70 150 97 129 1115.0\n", + "71 60 109 153 387.6\n", + "72 90 100 127 700.0\n", + "73 150 97 127 953.2\n", + "74 45 114 146 304.0\n", + "75 90 98 125 563.2\n", + "76 45 105 134 251.0\n", + "77 45 110 141 300.0\n", + "78 120 100 130 500.4\n", + "79 270 100 131 1729.0\n", + "80 30 159 182 319.2\n", + "81 45 149 169 344.0\n", + "82 30 103 139 151.1\n", + "83 120 100 130 500.0\n", + "84 45 100 120 225.3\n", + "85 30 151 170 300.0\n", + "86 45 102 136 234.0\n", + "87 120 100 157 1000.1\n", + "88 45 129 103 242.0\n", + "89 20 83 107 50.3\n", + "90 180 101 127 600.1\n", + "91 45 107 137 NaN\n", + "92 30 90 107 105.3\n", + "93 15 80 100 50.5\n", + "94 20 150 171 127.4\n", + "95 20 151 168 229.4\n", + "96 30 95 128 128.2\n", + "97 25 152 168 244.2\n", + "98 30 109 131 188.2\n", + "99 90 93 124 604.1\n", + "100 20 95 112 77.7\n", + "101 90 90 110 500.0\n", + "102 90 90 100 500.0\n", + "103 90 90 100 500.4\n", + "104 30 92 108 92.7\n", + "105 30 93 128 124.0\n", + "106 180 90 120 800.3\n", + "107 30 90 120 86.2\n", + "108 90 90 120 500.3\n", + "109 210 137 184 1860.4\n", + "110 60 102 124 325.2\n", + "111 45 107 124 275.0\n", + "112 15 124 139 124.2\n", + "113 45 100 120 225.3\n", + "114 60 108 131 367.6\n", + "115 60 108 151 351.7\n", + "116 60 116 141 443.0\n", + "117 60 97 122 277.4\n", + "118 60 105 125 NaN\n", + "119 60 103 124 332.7\n", + "120 30 112 137 193.9\n", + "121 45 100 120 100.7\n", + "122 60 119 169 336.7\n", + "123 60 107 127 344.9\n", + "124 60 111 151 368.5\n", + "125 60 98 122 271.0\n", + "126 60 97 124 275.3\n", + "127 60 109 127 382.0\n", + "128 90 99 125 466.4\n", + "129 60 114 151 384.0\n", + "130 60 104 134 342.5\n", + "131 60 107 138 357.5\n", + "132 60 103 133 335.0\n", + "133 60 106 132 327.5\n", + "134 60 103 136 339.0\n", + "135 20 136 156 189.0\n", + "136 45 117 143 317.7\n", + "137 45 115 137 318.0\n", + "138 45 113 138 308.0\n", + "139 20 141 162 222.4\n", + "140 60 108 135 390.0\n", + "141 60 97 127 NaN\n", + "142 45 100 120 250.4\n", + "143 45 122 149 335.4\n", + "144 60 136 170 470.2\n", + "145 45 106 126 270.8\n", + "146 60 107 136 400.0\n", + "147 60 112 146 361.9\n", + "148 30 103 127 185.0\n", + "149 60 110 150 409.4\n", + "150 60 106 134 343.0\n", + "151 60 109 129 353.2\n", + "152 60 109 138 374.0\n", + "153 30 150 167 275.8\n", + "154 60 105 128 328.0\n", + "155 60 111 151 368.5\n", + "156 60 97 131 270.4\n", + "157 60 100 120 270.4\n", + "158 60 114 150 382.8\n", + "159 30 80 120 240.9\n", + "160 30 85 120 250.4\n", + "161 45 90 130 260.4\n", + "162 45 95 130 270.0\n", + "163 45 100 140 280.9\n", + "164 60 105 140 290.8\n", + "165 60 110 145 300.0\n", + "166 60 115 145 310.2\n", + "167 75 120 150 320.4\n", + "168 75 125 150 330.4\n" + ] + } + ], + "source": [ + "df=pd.read_csv(\"data.csv\")\n", + "print(df.to_string())" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "a6ed4942", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Pulse Maxpulse Calories\n", + "0 60 110 130 409.1\n", + "1 60 117 145 479.0\n", + "2 60 103 135 340.0\n", + "3 45 109 175 282.4\n", + "4 45 117 148 406.0\n", + "5 60 102 127 300.0\n", + "6 60 110 136 374.0\n", + "7 45 104 134 253.3\n", + "8 30 109 133 195.1\n", + "9 60 98 124 269.0\n", + "10 60 103 147 329.3\n", + "11 60 100 120 250.7\n", + "12 60 106 128 345.3\n", + "13 60 104 132 379.3\n", + "14 60 98 123 275.0\n", + "15 60 98 120 215.2\n", + "16 60 100 120 300.0\n", + "17 45 90 112 120.0\n", + "18 60 103 123 323.0\n", + "19 45 97 125 243.0\n", + "20 60 108 131 364.2\n", + "21 45 100 119 282.0\n", + "22 60 130 101 300.0\n", + "23 45 105 132 246.0\n", + "24 60 102 126 334.5\n", + "25 60 100 120 250.0\n", + "26 60 92 118 241.0\n", + "27 60 103 132 120.0\n", + "28 60 100 132 280.0\n", + "29 60 102 129 380.3\n", + "30 60 92 115 243.0\n", + "31 45 90 112 180.1\n", + "32 60 101 124 299.0\n", + "33 60 93 113 223.0\n", + "34 60 107 136 361.0\n", + "35 60 114 140 415.0\n", + "36 60 102 127 300.0\n", + "37 60 100 120 300.0\n", + "38 60 100 120 300.0\n", + "39 45 104 129 266.0\n", + "40 45 90 112 180.1\n", + "41 60 98 126 286.0\n", + "42 60 100 122 329.4\n", + "43 60 111 138 400.0\n", + "44 60 111 131 397.0\n", + "45 60 99 119 273.0\n", + "46 60 109 153 387.6\n", + "47 45 111 136 300.0\n", + "48 45 108 129 298.0\n", + "49 60 111 139 397.6\n", + "50 60 107 136 380.2\n", + "51 80 123 146 643.1\n", + "52 60 106 130 263.0\n", + "53 60 118 151 486.0\n", + "54 30 136 175 238.0\n", + "55 60 121 146 450.7\n", + "56 60 118 121 413.0\n", + "57 45 115 144 305.0\n", + "58 20 153 172 226.4\n", + "59 45 123 152 321.0\n", + "60 210 108 160 1376.0\n", + "61 160 110 137 1034.4\n", + "62 160 109 135 853.0\n", + "63 45 118 141 341.0\n", + "64 20 110 130 131.4\n", + "65 180 90 130 800.4\n", + "66 150 105 135 873.4\n", + "67 150 107 130 816.0\n", + "68 20 106 136 110.4\n", + "69 300 108 143 1500.2\n", + "70 150 97 129 1115.0\n", + "71 60 109 153 387.6\n", + "72 90 100 127 700.0\n", + "73 150 97 127 953.2\n", + "74 45 114 146 304.0\n", + "75 90 98 125 563.2\n", + "76 45 105 134 251.0\n", + "77 45 110 141 300.0\n", + "78 120 100 130 500.4\n", + "79 270 100 131 1729.0\n", + "80 30 159 182 319.2\n", + "81 45 149 169 344.0\n", + "82 30 103 139 151.1\n", + "83 120 100 130 500.0\n", + "84 45 100 120 225.3\n", + "85 30 151 170 300.0\n", + "86 45 102 136 234.0\n", + "87 120 100 157 1000.1\n", + "88 45 129 103 242.0\n", + "89 20 83 107 50.3\n", + "90 180 101 127 600.1\n", + "91 45 107 137 120.0\n", + "92 30 90 107 105.3\n", + "93 15 80 100 50.5\n", + "94 20 150 171 127.4\n", + "95 20 151 168 229.4\n", + "96 30 95 128 128.2\n", + "97 25 152 168 244.2\n", + "98 30 109 131 188.2\n", + "99 90 93 124 604.1\n", + "100 20 95 112 77.7\n", + "101 90 90 110 500.0\n", + "102 90 90 100 500.0\n", + "103 90 90 100 500.4\n", + "104 30 92 108 92.7\n", + "105 30 93 128 124.0\n", + "106 180 90 120 800.3\n", + "107 30 90 120 86.2\n", + "108 90 90 120 500.3\n", + "109 210 137 184 1860.4\n", + "110 60 102 124 325.2\n", + "111 45 107 124 275.0\n", + "112 15 124 139 124.2\n", + "113 45 100 120 225.3\n", + "114 60 108 131 367.6\n", + "115 60 108 151 351.7\n", + "116 60 116 141 443.0\n", + "117 60 97 122 277.4\n", + "118 60 105 125 120.0\n", + "119 60 103 124 332.7\n", + "120 30 112 137 193.9\n", + "121 45 100 120 100.7\n", + "122 60 119 169 336.7\n", + "123 60 107 127 344.9\n", + "124 60 111 151 368.5\n", + "125 60 98 122 271.0\n", + "126 60 97 124 275.3\n", + "127 60 109 127 382.0\n", + "128 90 99 125 466.4\n", + "129 60 114 151 384.0\n", + "130 60 104 134 342.5\n", + "131 60 107 138 357.5\n", + "132 60 103 133 335.0\n", + "133 60 106 132 327.5\n", + "134 60 103 136 339.0\n", + "135 20 136 156 189.0\n", + "136 45 117 143 317.7\n", + "137 45 115 137 318.0\n", + "138 45 113 138 308.0\n", + "139 20 141 162 222.4\n", + "140 60 108 135 390.0\n", + "141 60 97 127 120.0\n", + "142 45 100 120 250.4\n", + "143 45 122 149 335.4\n", + "144 60 136 170 470.2\n", + "145 45 106 126 270.8\n", + "146 60 107 136 400.0\n", + "147 60 112 146 361.9\n", + "148 30 103 127 185.0\n", + "149 60 110 150 409.4\n", + "150 60 106 134 343.0\n", + "151 60 109 129 353.2\n", + "152 60 109 138 374.0\n", + "153 30 150 167 275.8\n", + "154 60 105 128 328.0\n", + "155 60 111 151 368.5\n", + "156 60 97 131 270.4\n", + "157 60 100 120 270.4\n", + "158 60 114 150 382.8\n", + "159 30 80 120 240.9\n", + "160 30 85 120 250.4\n", + "161 45 90 130 260.4\n", + "162 45 95 130 270.0\n", + "163 45 100 140 280.9\n", + "164 60 105 140 290.8\n", + "165 60 110 145 300.0\n", + "166 60 115 145 310.2\n", + "167 75 120 150 320.4\n", + "168 75 125 150 330.4\n" + ] + } + ], + "source": [ + "df.fillna(120,inplace=True) #replaces the null value instead of deleting the entire row\n", + "print(df.to_string())" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "fb3646bb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Pulse Maxpulse Calories\n", + "0 60 110 130 409.100000\n", + "1 60 117 145 479.000000\n", + "2 60 103 135 340.000000\n", + "3 45 109 175 282.400000\n", + "4 45 117 148 406.000000\n", + "5 60 102 127 300.000000\n", + "6 60 110 136 374.000000\n", + "7 45 104 134 253.300000\n", + "8 30 109 133 195.100000\n", + "9 60 98 124 269.000000\n", + "10 60 103 147 329.300000\n", + "11 60 100 120 250.700000\n", + "12 60 106 128 345.300000\n", + "13 60 104 132 379.300000\n", + "14 60 98 123 275.000000\n", + "15 60 98 120 215.200000\n", + "16 60 100 120 300.000000\n", + "17 45 90 112 375.790244\n", + "18 60 103 123 323.000000\n", + "19 45 97 125 243.000000\n", + "20 60 108 131 364.200000\n", + "21 45 100 119 282.000000\n", + "22 60 130 101 300.000000\n", + "23 45 105 132 246.000000\n", + "24 60 102 126 334.500000\n", + "25 60 100 120 250.000000\n", + "26 60 92 118 241.000000\n", + "27 60 103 132 375.790244\n", + "28 60 100 132 280.000000\n", + "29 60 102 129 380.300000\n", + "30 60 92 115 243.000000\n", + "31 45 90 112 180.100000\n", + "32 60 101 124 299.000000\n", + "33 60 93 113 223.000000\n", + "34 60 107 136 361.000000\n", + "35 60 114 140 415.000000\n", + "36 60 102 127 300.000000\n", + "37 60 100 120 300.000000\n", + "38 60 100 120 300.000000\n", + "39 45 104 129 266.000000\n", + "40 45 90 112 180.100000\n", + "41 60 98 126 286.000000\n", + "42 60 100 122 329.400000\n", + "43 60 111 138 400.000000\n", + "44 60 111 131 397.000000\n", + "45 60 99 119 273.000000\n", + "46 60 109 153 387.600000\n", + "47 45 111 136 300.000000\n", + "48 45 108 129 298.000000\n", + "49 60 111 139 397.600000\n", + "50 60 107 136 380.200000\n", + "51 80 123 146 643.100000\n", + "52 60 106 130 263.000000\n", + "53 60 118 151 486.000000\n", + "54 30 136 175 238.000000\n", + "55 60 121 146 450.700000\n", + "56 60 118 121 413.000000\n", + "57 45 115 144 305.000000\n", + "58 20 153 172 226.400000\n", + "59 45 123 152 321.000000\n", + "60 210 108 160 1376.000000\n", + "61 160 110 137 1034.400000\n", + "62 160 109 135 853.000000\n", + "63 45 118 141 341.000000\n", + "64 20 110 130 131.400000\n", + "65 180 90 130 800.400000\n", + "66 150 105 135 873.400000\n", + "67 150 107 130 816.000000\n", + "68 20 106 136 110.400000\n", + "69 300 108 143 1500.200000\n", + "70 150 97 129 1115.000000\n", + "71 60 109 153 387.600000\n", + "72 90 100 127 700.000000\n", + "73 150 97 127 953.200000\n", + "74 45 114 146 304.000000\n", + "75 90 98 125 563.200000\n", + "76 45 105 134 251.000000\n", + "77 45 110 141 300.000000\n", + "78 120 100 130 500.400000\n", + "79 270 100 131 1729.000000\n", + "80 30 159 182 319.200000\n", + "81 45 149 169 344.000000\n", + "82 30 103 139 151.100000\n", + "83 120 100 130 500.000000\n", + "84 45 100 120 225.300000\n", + "85 30 151 170 300.000000\n", + "86 45 102 136 234.000000\n", + "87 120 100 157 1000.100000\n", + "88 45 129 103 242.000000\n", + "89 20 83 107 50.300000\n", + "90 180 101 127 600.100000\n", + "91 45 107 137 375.790244\n", + "92 30 90 107 105.300000\n", + "93 15 80 100 50.500000\n", + "94 20 150 171 127.400000\n", + "95 20 151 168 229.400000\n", + "96 30 95 128 128.200000\n", + "97 25 152 168 244.200000\n", + "98 30 109 131 188.200000\n", + "99 90 93 124 604.100000\n", + "100 20 95 112 77.700000\n", + "101 90 90 110 500.000000\n", + "102 90 90 100 500.000000\n", + "103 90 90 100 500.400000\n", + "104 30 92 108 92.700000\n", + "105 30 93 128 124.000000\n", + "106 180 90 120 800.300000\n", + "107 30 90 120 86.200000\n", + "108 90 90 120 500.300000\n", + "109 210 137 184 1860.400000\n", + "110 60 102 124 325.200000\n", + "111 45 107 124 275.000000\n", + "112 15 124 139 124.200000\n", + "113 45 100 120 225.300000\n", + "114 60 108 131 367.600000\n", + "115 60 108 151 351.700000\n", + "116 60 116 141 443.000000\n", + "117 60 97 122 277.400000\n", + "118 60 105 125 375.790244\n", + "119 60 103 124 332.700000\n", + "120 30 112 137 193.900000\n", + "121 45 100 120 100.700000\n", + "122 60 119 169 336.700000\n", + "123 60 107 127 344.900000\n", + "124 60 111 151 368.500000\n", + "125 60 98 122 271.000000\n", + "126 60 97 124 275.300000\n", + "127 60 109 127 382.000000\n", + "128 90 99 125 466.400000\n", + "129 60 114 151 384.000000\n", + "130 60 104 134 342.500000\n", + "131 60 107 138 357.500000\n", + "132 60 103 133 335.000000\n", + "133 60 106 132 327.500000\n", + "134 60 103 136 339.000000\n", + "135 20 136 156 189.000000\n", + "136 45 117 143 317.700000\n", + "137 45 115 137 318.000000\n", + "138 45 113 138 308.000000\n", + "139 20 141 162 222.400000\n", + "140 60 108 135 390.000000\n", + "141 60 97 127 375.790244\n", + "142 45 100 120 250.400000\n", + "143 45 122 149 335.400000\n", + "144 60 136 170 470.200000\n", + "145 45 106 126 270.800000\n", + "146 60 107 136 400.000000\n", + "147 60 112 146 361.900000\n", + "148 30 103 127 185.000000\n", + "149 60 110 150 409.400000\n", + "150 60 106 134 343.000000\n", + "151 60 109 129 353.200000\n", + "152 60 109 138 374.000000\n", + "153 30 150 167 275.800000\n", + "154 60 105 128 328.000000\n", + "155 60 111 151 368.500000\n", + "156 60 97 131 270.400000\n", + "157 60 100 120 270.400000\n", + "158 60 114 150 382.800000\n", + "159 30 80 120 240.900000\n", + "160 30 85 120 250.400000\n", + "161 45 90 130 260.400000\n", + "162 45 95 130 270.000000\n", + "163 45 100 140 280.900000\n", + "164 60 105 140 290.800000\n", + "165 60 110 145 300.000000\n", + "166 60 115 145 310.200000\n", + "167 75 120 150 320.400000\n", + "168 75 125 150 330.400000\n" + ] + } + ], + "source": [ + "df=pd.read_csv(\"data.csv\")\n", + "x=df[\"Calories\"].mean() \n", + "df[\"Calories\"].fillna(x,inplace=True) #replaces the null values with the mean of the rest of the column values\n", + "print(df.to_string())\n", + "#same can be done with median and mode" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "b714b361", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Date Pulse Maxpulse Calories\n", + "0 60 '2020/12/01' 110 130 409.1\n", + "1 60 '2020/12/02' 117 145 479.0\n", + "2 60 '2020/12/03' 103 135 340.0\n", + "3 45 '2020/12/04' 109 175 282.4\n", + "4 45 '2020/12/05' 117 148 406.0\n", + "5 60 '2020/12/06' 102 127 300.0\n", + "6 60 '2020/12/07' 110 136 374.0\n", + "7 450 '2020/12/08' 104 134 253.3\n", + "8 30 '2020/12/09' 109 133 195.1\n", + "9 60 '2020/12/10' 98 124 269.0\n", + "10 60 '2020/12/11' 103 147 329.3\n", + "11 60 '2020/12/12' 100 120 250.7\n", + "12 60 '2020/12/12' 100 120 250.7\n", + "13 60 '2020/12/13' 106 128 345.3\n", + "14 60 '2020/12/14' 104 132 379.3\n", + "15 60 '2020/12/15' 98 123 275.0\n", + "16 60 '2020/12/16' 98 120 215.2\n", + "17 60 '2020/12/17' 100 120 300.0\n", + "18 45 '2020/12/18' 90 112 NaN\n", + "19 60 '2020/12/19' 103 123 323.0\n", + "20 45 '2020/12/20' 97 125 243.0\n", + "21 60 '2020/12/21' 108 131 364.2\n", + "22 45 NaN 100 119 282.0\n", + "23 60 '2020/12/23' 130 101 300.0\n", + "24 45 '2020/12/24' 105 132 246.0\n", + "25 60 '2020/12/25' 102 126 334.5\n", + "26 60 20201226 100 120 250.0\n", + "27 60 '2020/12/27' 92 118 241.0\n", + "28 60 '2020/12/28' 103 132 NaN\n", + "29 60 '2020/12/29' 100 132 280.0\n", + "30 60 '2020/12/30' 102 129 380.3\n", + "31 60 '2020/12/31' 92 115 243.0\n" + ] + } + ], + "source": [ + "df=pd.read_csv(\"dirtydata.csv\")\n", + "print(df.to_string())" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "8a67787a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Date Pulse Maxpulse Calories\n", + "0 60 2020-12-01 110 130 409.1\n", + "1 60 2020-12-02 117 145 479.0\n", + "2 60 2020-12-03 103 135 340.0\n", + "3 45 2020-12-04 109 175 282.4\n", + "4 45 2020-12-05 117 148 406.0\n", + "5 60 2020-12-06 102 127 300.0\n", + "6 60 2020-12-07 110 136 374.0\n", + "7 450 2020-12-08 104 134 253.3\n", + "8 30 2020-12-09 109 133 195.1\n", + "9 60 2020-12-10 98 124 269.0\n", + "10 60 2020-12-11 103 147 329.3\n", + "11 60 2020-12-12 100 120 250.7\n", + "12 60 2020-12-12 100 120 250.7\n", + "13 60 2020-12-13 106 128 345.3\n", + "14 60 2020-12-14 104 132 379.3\n", + "15 60 2020-12-15 98 123 275.0\n", + "16 60 2020-12-16 98 120 215.2\n", + "17 60 2020-12-17 100 120 300.0\n", + "18 45 2020-12-18 90 112 NaN\n", + "19 60 2020-12-19 103 123 323.0\n", + "20 45 2020-12-20 97 125 243.0\n", + "21 60 2020-12-21 108 131 364.2\n", + "22 45 NaT 100 119 282.0\n", + "23 60 2020-12-23 130 101 300.0\n", + "24 45 2020-12-24 105 132 246.0\n", + "25 60 2020-12-25 102 126 334.5\n", + "26 60 2020-12-26 100 120 250.0\n", + "27 60 2020-12-27 92 118 241.0\n", + "28 60 2020-12-28 103 132 NaN\n", + "29 60 2020-12-29 100 132 280.0\n", + "30 60 2020-12-30 102 129 380.3\n", + "31 60 2020-12-31 92 115 243.0\n" + ] + } + ], + "source": [ + "#the dates in the rows 22 and 26 are in the wrong format\n", + "df[\"Date\"] = pd.to_datetime(df[\"Date\"])\n", + "print(df.to_string())" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "06761e1b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Date Pulse Maxpulse Calories\n", + "0 60 2020-12-01 110 130 409.1\n", + "1 60 2020-12-02 117 145 479.0\n", + "2 60 2020-12-03 103 135 340.0\n", + "3 45 2020-12-04 109 175 282.4\n", + "4 45 2020-12-05 117 148 406.0\n", + "5 60 2020-12-06 102 127 300.0\n", + "6 60 2020-12-07 110 136 374.0\n", + "7 450 2020-12-08 104 134 253.3\n", + "8 30 2020-12-09 109 133 195.1\n", + "9 60 2020-12-10 98 124 269.0\n", + "10 60 2020-12-11 103 147 329.3\n", + "11 60 2020-12-12 100 120 250.7\n", + "12 60 2020-12-12 100 120 250.7\n", + "13 60 2020-12-13 106 128 345.3\n", + "14 60 2020-12-14 104 132 379.3\n", + "15 60 2020-12-15 98 123 275.0\n", + "16 60 2020-12-16 98 120 215.2\n", + "17 60 2020-12-17 100 120 300.0\n", + "18 45 2020-12-18 90 112 NaN\n", + "19 60 2020-12-19 103 123 323.0\n", + "20 45 2020-12-20 97 125 243.0\n", + "21 60 2020-12-21 108 131 364.2\n", + "23 60 2020-12-23 130 101 300.0\n", + "24 45 2020-12-24 105 132 246.0\n", + "25 60 2020-12-25 102 126 334.5\n", + "26 60 2020-12-26 100 120 250.0\n", + "27 60 2020-12-27 92 118 241.0\n", + "28 60 2020-12-28 103 132 NaN\n", + "29 60 2020-12-29 100 132 280.0\n", + "30 60 2020-12-30 102 129 380.3\n", + "31 60 2020-12-31 92 115 243.0\n" + ] + } + ], + "source": [ + "#the format gets changed but there is NaT generated, to delele the row\n", + "df.dropna(subset=[\"Date\"],inplace=True)\n", + "print(df.to_string())" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "f4a08313", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Date Pulse Maxpulse Calories\n", + "0 60 2020-12-01 110 130 409.1\n", + "1 60 2020-12-02 117 145 479.0\n", + "2 60 2020-12-03 103 135 340.0\n", + "3 45 2020-12-04 109 175 282.4\n", + "4 45 2020-12-05 117 148 406.0\n", + "5 60 2020-12-06 102 127 300.0\n", + "6 60 2020-12-07 110 136 374.0\n", + "7 45 2020-12-08 104 134 253.3\n", + "8 30 2020-12-09 109 133 195.1\n", + "9 60 2020-12-10 98 124 269.0\n", + "10 60 2020-12-11 103 147 329.3\n", + "11 60 2020-12-12 100 120 250.7\n", + "12 60 2020-12-12 100 120 250.7\n", + "13 60 2020-12-13 106 128 345.3\n", + "14 60 2020-12-14 104 132 379.3\n", + "15 60 2020-12-15 98 123 275.0\n", + "16 60 2020-12-16 98 120 215.2\n", + "17 60 2020-12-17 100 120 300.0\n", + "18 45 2020-12-18 90 112 NaN\n", + "19 60 2020-12-19 103 123 323.0\n", + "20 45 2020-12-20 97 125 243.0\n", + "21 60 2020-12-21 108 131 364.2\n", + "23 60 2020-12-23 130 101 300.0\n", + "24 45 2020-12-24 105 132 246.0\n", + "25 60 2020-12-25 102 126 334.5\n", + "26 60 2020-12-26 100 120 250.0\n", + "27 60 2020-12-27 92 118 241.0\n", + "28 60 2020-12-28 103 132 NaN\n", + "29 60 2020-12-29 100 132 280.0\n", + "30 60 2020-12-30 102 129 380.3\n", + "31 60 2020-12-31 92 115 243.0\n" + ] + } + ], + "source": [ + "#replacing wrong values\n", + "df.loc[7,\"Duration\"]=45\n", + "print(df.to_string())" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "39d62c79", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Pulse Maxpulse Calories\n", + "0 60 110 130 409.1\n", + "1 60 117 145 479.0\n", + "2 60 103 135 340.0\n", + "3 45 109 175 282.4\n", + "4 45 117 148 406.0\n", + "5 60 102 127 300.0\n", + "6 60 110 136 374.0\n", + "7 45 104 134 253.3\n", + "8 30 109 133 195.1\n", + "9 60 98 124 269.0\n", + "10 60 103 147 329.3\n", + "11 60 100 120 250.7\n", + "12 60 106 128 345.3\n", + "13 60 104 132 379.3\n", + "14 60 98 123 275.0\n", + "15 60 98 120 215.2\n", + "16 60 100 120 300.0\n", + "17 45 90 112 NaN\n", + "18 60 103 123 323.0\n", + "19 45 97 125 243.0\n", + "20 60 108 131 364.2\n", + "21 45 100 119 282.0\n", + "22 60 130 101 300.0\n", + "23 45 105 132 246.0\n", + "24 60 102 126 334.5\n", + "25 60 100 120 250.0\n", + "26 60 92 118 241.0\n", + "27 60 103 132 NaN\n", + "28 60 100 132 280.0\n", + "29 60 102 129 380.3\n", + "30 60 92 115 243.0\n", + "31 45 90 112 180.1\n", + "32 60 101 124 299.0\n", + "33 60 93 113 223.0\n", + "34 60 107 136 361.0\n", + "35 60 114 140 415.0\n", + "36 60 102 127 300.0\n", + "37 60 100 120 300.0\n", + "38 60 100 120 300.0\n", + "39 45 104 129 266.0\n", + "40 45 90 112 180.1\n", + "41 60 98 126 286.0\n", + "42 60 100 122 329.4\n", + "43 60 111 138 400.0\n", + "44 60 111 131 397.0\n", + "45 60 99 119 273.0\n", + "46 60 109 153 387.6\n", + "47 45 111 136 300.0\n", + "48 45 108 129 298.0\n", + "49 60 111 139 397.6\n", + "50 60 107 136 380.2\n", + "51 80 123 146 643.1\n", + "52 60 106 130 263.0\n", + "53 60 118 151 486.0\n", + "54 30 136 175 238.0\n", + "55 60 121 146 450.7\n", + "56 60 118 121 413.0\n", + "57 45 115 144 305.0\n", + "58 20 153 172 226.4\n", + "59 45 123 152 321.0\n", + "60 120 108 160 1376.0\n", + "61 120 110 137 1034.4\n", + "62 120 109 135 853.0\n", + "63 45 118 141 341.0\n", + "64 20 110 130 131.4\n", + "65 120 90 130 800.4\n", + "66 120 105 135 873.4\n", + "67 120 107 130 816.0\n", + "68 20 106 136 110.4\n", + "69 120 108 143 1500.2\n", + "70 120 97 129 1115.0\n", + "71 60 109 153 387.6\n", + "72 90 100 127 700.0\n", + "73 120 97 127 953.2\n", + "74 45 114 146 304.0\n", + "75 90 98 125 563.2\n", + "76 45 105 134 251.0\n", + "77 45 110 141 300.0\n", + "78 120 100 130 500.4\n", + "79 120 100 131 1729.0\n", + "80 30 159 182 319.2\n", + "81 45 149 169 344.0\n", + "82 30 103 139 151.1\n", + "83 120 100 130 500.0\n", + "84 45 100 120 225.3\n", + "85 30 151 170 300.0\n", + "86 45 102 136 234.0\n", + "87 120 100 157 1000.1\n", + "88 45 129 103 242.0\n", + "89 20 83 107 50.3\n", + "90 120 101 127 600.1\n", + "91 45 107 137 NaN\n", + "92 30 90 107 105.3\n", + "93 15 80 100 50.5\n", + "94 20 150 171 127.4\n", + "95 20 151 168 229.4\n", + "96 30 95 128 128.2\n", + "97 25 152 168 244.2\n", + "98 30 109 131 188.2\n", + "99 90 93 124 604.1\n", + "100 20 95 112 77.7\n", + "101 90 90 110 500.0\n", + "102 90 90 100 500.0\n", + "103 90 90 100 500.4\n", + "104 30 92 108 92.7\n", + "105 30 93 128 124.0\n", + "106 120 90 120 800.3\n", + "107 30 90 120 86.2\n", + "108 90 90 120 500.3\n", + "109 120 137 184 1860.4\n", + "110 60 102 124 325.2\n", + "111 45 107 124 275.0\n", + "112 15 124 139 124.2\n", + "113 45 100 120 225.3\n", + "114 60 108 131 367.6\n", + "115 60 108 151 351.7\n", + "116 60 116 141 443.0\n", + "117 60 97 122 277.4\n", + "118 60 105 125 NaN\n", + "119 60 103 124 332.7\n", + "120 30 112 137 193.9\n", + "121 45 100 120 100.7\n", + "122 60 119 169 336.7\n", + "123 60 107 127 344.9\n", + "124 60 111 151 368.5\n", + "125 60 98 122 271.0\n", + "126 60 97 124 275.3\n", + "127 60 109 127 382.0\n", + "128 90 99 125 466.4\n", + "129 60 114 151 384.0\n", + "130 60 104 134 342.5\n", + "131 60 107 138 357.5\n", + "132 60 103 133 335.0\n", + "133 60 106 132 327.5\n", + "134 60 103 136 339.0\n", + "135 20 136 156 189.0\n", + "136 45 117 143 317.7\n", + "137 45 115 137 318.0\n", + "138 45 113 138 308.0\n", + "139 20 141 162 222.4\n", + "140 60 108 135 390.0\n", + "141 60 97 127 NaN\n", + "142 45 100 120 250.4\n", + "143 45 122 149 335.4\n", + "144 60 136 170 470.2\n", + "145 45 106 126 270.8\n", + "146 60 107 136 400.0\n", + "147 60 112 146 361.9\n", + "148 30 103 127 185.0\n", + "149 60 110 150 409.4\n", + "150 60 106 134 343.0\n", + "151 60 109 129 353.2\n", + "152 60 109 138 374.0\n", + "153 30 150 167 275.8\n", + "154 60 105 128 328.0\n", + "155 60 111 151 368.5\n", + "156 60 97 131 270.4\n", + "157 60 100 120 270.4\n", + "158 60 114 150 382.8\n", + "159 30 80 120 240.9\n", + "160 30 85 120 250.4\n", + "161 45 90 130 260.4\n", + "162 45 95 130 270.0\n", + "163 45 100 140 280.9\n", + "164 60 105 140 290.8\n", + "165 60 110 145 300.0\n", + "166 60 115 145 310.2\n", + "167 75 120 150 320.4\n", + "168 75 125 150 330.4\n" + ] + } + ], + "source": [ + "df=pd.read_csv(\"data.csv\")\n", + "for x in df.index:\n", + " if df.loc[x,\"Duration\"]>120:\n", + " df.loc[x,\"Duration\"]=120 #replacing the values as per a condition\n", + "print(df.to_string()) " + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "45dd8530", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Duration Pulse Maxpulse Calories\n", + "0 60 110 130 409.1\n", + "1 60 117 145 479.0\n", + "2 60 103 135 340.0\n", + "3 45 109 175 282.4\n", + "4 45 117 148 406.0\n", + "5 60 102 127 300.0\n", + "6 60 110 136 374.0\n", + "7 45 104 134 253.3\n", + "8 30 109 133 195.1\n", + "9 60 98 124 269.0\n", + "10 60 103 147 329.3\n", + "11 60 100 120 250.7\n", + "12 60 106 128 345.3\n", + "13 60 104 132 379.3\n", + "14 60 98 123 275.0\n", + "15 60 98 120 215.2\n", + "16 60 100 120 300.0\n", + "17 45 90 112 NaN\n", + "18 60 103 123 323.0\n", + "19 45 97 125 243.0\n", + "20 60 108 131 364.2\n", + "21 45 100 119 282.0\n", + "22 60 130 101 300.0\n", + "23 45 105 132 246.0\n", + "24 60 102 126 334.5\n", + "25 60 100 120 250.0\n", + "26 60 92 118 241.0\n", + "27 60 103 132 NaN\n", + "28 60 100 132 280.0\n", + "29 60 102 129 380.3\n", + "30 60 92 115 243.0\n", + "31 45 90 112 180.1\n", + "32 60 101 124 299.0\n", + "33 60 93 113 223.0\n", + "34 60 107 136 361.0\n", + "35 60 114 140 415.0\n", + "36 60 102 127 300.0\n", + "37 60 100 120 300.0\n", + "38 60 100 120 300.0\n", + "39 45 104 129 266.0\n", + "40 45 90 112 180.1\n", + "41 60 98 126 286.0\n", + "42 60 100 122 329.4\n", + "43 60 111 138 400.0\n", + "44 60 111 131 397.0\n", + "45 60 99 119 273.0\n", + "46 60 109 153 387.6\n", + "47 45 111 136 300.0\n", + "48 45 108 129 298.0\n", + "49 60 111 139 397.6\n", + "50 60 107 136 380.2\n", + "51 80 123 146 643.1\n", + "52 60 106 130 263.0\n", + "53 60 118 151 486.0\n", + "54 30 136 175 238.0\n", + "55 60 121 146 450.7\n", + "56 60 118 121 413.0\n", + "57 45 115 144 305.0\n", + "58 20 153 172 226.4\n", + "59 45 123 152 321.0\n", + "63 45 118 141 341.0\n", + "64 20 110 130 131.4\n", + "68 20 106 136 110.4\n", + "71 60 109 153 387.6\n", + "72 90 100 127 700.0\n", + "74 45 114 146 304.0\n", + "75 90 98 125 563.2\n", + "76 45 105 134 251.0\n", + "77 45 110 141 300.0\n", + "78 120 100 130 500.4\n", + "80 30 159 182 319.2\n", + "81 45 149 169 344.0\n", + "82 30 103 139 151.1\n", + "83 120 100 130 500.0\n", + "84 45 100 120 225.3\n", + "85 30 151 170 300.0\n", + "86 45 102 136 234.0\n", + "87 120 100 157 1000.1\n", + "88 45 129 103 242.0\n", + "89 20 83 107 50.3\n", + "91 45 107 137 NaN\n", + "92 30 90 107 105.3\n", + "93 15 80 100 50.5\n", + "94 20 150 171 127.4\n", + "95 20 151 168 229.4\n", + "96 30 95 128 128.2\n", + "97 25 152 168 244.2\n", + "98 30 109 131 188.2\n", + "99 90 93 124 604.1\n", + "100 20 95 112 77.7\n", + "101 90 90 110 500.0\n", + "102 90 90 100 500.0\n", + "103 90 90 100 500.4\n", + "104 30 92 108 92.7\n", + "105 30 93 128 124.0\n", + "107 30 90 120 86.2\n", + "108 90 90 120 500.3\n", + "110 60 102 124 325.2\n", + "111 45 107 124 275.0\n", + "112 15 124 139 124.2\n", + "113 45 100 120 225.3\n", + "114 60 108 131 367.6\n", + "115 60 108 151 351.7\n", + "116 60 116 141 443.0\n", + "117 60 97 122 277.4\n", + "118 60 105 125 NaN\n", + "119 60 103 124 332.7\n", + "120 30 112 137 193.9\n", + "121 45 100 120 100.7\n", + "122 60 119 169 336.7\n", + "123 60 107 127 344.9\n", + "124 60 111 151 368.5\n", + "125 60 98 122 271.0\n", + "126 60 97 124 275.3\n", + "127 60 109 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DurationPulseMaxpulseCalories
Duration1.000000-0.1554080.0094030.922717
Pulse-0.1554081.0000000.7865350.025121
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" + ], + "text/plain": [ + " Duration Pulse Maxpulse Calories\n", + "Duration 1.000000 -0.155408 0.009403 0.922717\n", + "Pulse -0.155408 1.000000 0.786535 0.025121\n", + "Maxpulse 0.009403 0.786535 1.000000 0.203813\n", + "Calories 0.922717 0.025121 0.203813 1.000000" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#correlation in pandas\n", + "df=pd.read_csv(\"Data.csv\")\n", + "df.corr()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0598331e", + "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": "3.9.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/w1/data.csv b/w1/data.csv new file mode 100644 index 0000000..75e9a2e --- /dev/null +++ b/w1/data.csv @@ -0,0 +1,170 @@ +Duration,Pulse,Maxpulse,Calories +60,110,130,409.1 +60,117,145,479.0 +60,103,135,340.0 +45,109,175,282.4 +45,117,148,406.0 +60,102,127,300.0 +60,110,136,374.0 +45,104,134,253.3 +30,109,133,195.1 +60,98,124,269.0 +60,103,147,329.3 +60,100,120,250.7 +60,106,128,345.3 +60,104,132,379.3 +60,98,123,275.0 +60,98,120,215.2 +60,100,120,300.0 +45,90,112, +60,103,123,323.0 +45,97,125,243.0 +60,108,131,364.2 +45,100,119,282.0 +60,130,101,300.0 +45,105,132,246.0 +60,102,126,334.5 +60,100,120,250.0 +60,92,118,241.0 +60,103,132, +60,100,132,280.0 +60,102,129,380.3 +60,92,115,243.0 +45,90,112,180.1 +60,101,124,299.0 +60,93,113,223.0 +60,107,136,361.0 +60,114,140,415.0 +60,102,127,300.0 +60,100,120,300.0 +60,100,120,300.0 +45,104,129,266.0 +45,90,112,180.1 +60,98,126,286.0 +60,100,122,329.4 +60,111,138,400.0 +60,111,131,397.0 +60,99,119,273.0 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+60,100,120,270.4 +60,114,150,382.8 +30,80,120,240.9 +30,85,120,250.4 +45,90,130,260.4 +45,95,130,270.0 +45,100,140,280.9 +60,105,140,290.8 +60,110,145,300.0 +60,115,145,310.2 +75,120,150,320.4 +75,125,150,330.4 \ No newline at end of file diff --git a/w1/dirtydata.csv b/w1/dirtydata.csv new file mode 100644 index 0000000..36e149a --- /dev/null +++ b/w1/dirtydata.csv @@ -0,0 +1,33 @@ +Duration,Date,Pulse,Maxpulse,Calories +60,'2020/12/01',110,130,409.1 +60,'2020/12/02',117,145,479.0 +60,'2020/12/03',103,135,340.0 +45,'2020/12/04',109,175,282.4 +45,'2020/12/05',117,148,406.0 +60,'2020/12/06',102,127,300.0 +60,'2020/12/07',110,136,374.0 +450,'2020/12/08',104,134,253.3 +30,'2020/12/09',109,133,195.1 +60,'2020/12/10',98,124,269.0 +60,'2020/12/11',103,147,329.3 +60,'2020/12/12',100,120,250.7 +60,'2020/12/12',100,120,250.7 +60,'2020/12/13',106,128,345.3 +60,'2020/12/14',104,132,379.3 +60,'2020/12/15',98,123,275.0 +60,'2020/12/16',98,120,215.2 +60,'2020/12/17',100,120,300.0 +45,'2020/12/18',90,112, +60,'2020/12/19',103,123,323.0 +45,'2020/12/20',97,125,243.0 +60,'2020/12/21',108,131,364.2 +45,,100,119,282.0 +60,'2020/12/23',130,101,300.0 +45,'2020/12/24',105,132,246.0 +60,'2020/12/25',102,126,334.5 +60,20201226,100,120,250.0 +60,'2020/12/27',92,118,241.0 +60,'2020/12/28',103,132, +60,'2020/12/29',100,132,280.0 +60,'2020/12/30',102,129,380.3 +60,'2020/12/31',92,115,243.0 \ No newline at end of file From f2ea6dec2e59e8680a18c6a98082df6e19d35c30 Mon Sep 17 00:00:00 2001 From: Rishabh Agrawal Date: Sat, 11 Jun 2022 16:35:55 +0530 Subject: [PATCH 2/5] README added --- w1/Getting started with Anaconda.ipynb | 100 ------------------------- w1/README.md | 75 +++++++++++++++++++ 2 files changed, 75 insertions(+), 100 deletions(-) delete mode 100644 w1/Getting started with Anaconda.ipynb create mode 100644 w1/README.md diff --git a/w1/Getting started with Anaconda.ipynb b/w1/Getting started with Anaconda.ipynb deleted file mode 100644 index 70d7d69..0000000 --- a/w1/Getting started with Anaconda.ipynb +++ /dev/null @@ -1,100 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "3b74e3e5", - "metadata": {}, - "source": [ - "Anaconda is a distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. The distribution includes data-science packages suitable for Windows, Linux, and macOS." - ] - }, - { - "cell_type": "markdown", - "id": "8483cd59", - "metadata": {}, - "source": [ - "

Anaconda installation in Windows

" - ] - }, - { - "cell_type": "markdown", - "id": "1bea4602", - "metadata": {}, - "source": [ - "1. Visit https://www.anaconda.com/products/distribution.\n", - "2. Download the Installer.\n", - "3. Once the download is complete, run the installer." - ] - }, - { - "attachments": { - "image-2.png": { - "image/png": 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" - } - }, - "cell_type": "markdown", - "id": "88856733", - "metadata": {}, - "source": [ - "4. The following window appears.
\n", - "![image.png](attachment:image.png)
\n", - "5. Click on Next and then click on I agree.
\n", - "6. In the following window choose the Just Me option.
\n", - "![image-2.png](attachment:image-2.png)
\n", - "7. Click on Next.\n", - "8. Choose the directory where you want the distribution to install.\n", - "9. Click on Next.\n", - "10. At the Advanced Installation Options screen, I recommend that you do not check Add Anaconda to my PATH environment variable\n", - "11. Click on Next and run the installer.\n", - "12. Finish the installation.\n", - "13. Launch Anaconda Navigator.\n", - "\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "58d65c35", - "metadata": {}, - "source": [ - "

Installing Dependencies


\n", - "1. Open Anaconda Navigator.
\n", - "2. Launch CMD.exe prompt.
\n", - "3. To install Matplotlib, in the cmd window type conda install matplotlib
\n", - "4. Do the same for Numpy and Pandas." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8ba770fa", - "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": "3.9.12" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/w1/README.md b/w1/README.md new file mode 100644 index 0000000..72d081b --- /dev/null +++ b/w1/README.md @@ -0,0 +1,75 @@ +--- +jupyter: + 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: 3.9.12 + nbformat: 4 + nbformat_minor: 5 +--- + +::: {.cell .markdown} +Anaconda is a distribution of the Python and R programming languages for +scientific computing, that aims to simplify package management and +deployment. The distribution includes data-science packages suitable for +Windows, Linux, and macOS. +::: + +::: {.cell .markdown} +```{=html} +

Anaconda installation in Windows

+``` +::: + +::: {.cell .markdown} +1. Visit . +2. Download the Installer. +3. Once the download is complete, run the installer. +::: + +::: {.cell .markdown} +1. The following window appears.`
`{=html} + ![image.png](vertopal_b92a56b7279a4017b3a1930e63d55b1e/image.png)`
`{=html} +2. Click on ``{=html}Next``{=html} and then click on + ``{=html}I agree.``{=html}`
`{=html} +3. In the following window choose the ``{=html}Just Me``{=html} + option.`
`{=html} + ![image-2.png](vertopal_b92a56b7279a4017b3a1930e63d55b1e/image-2.png)`
`{=html} +4. Click on ``{=html}Next``{=html}. +5. Choose the directory where you want the distribution to install. +6. Click on ``{=html}Next``{=html}. +7. At the Advanced Installation Options screen, I recommend that you do + not check ``{=html}Add Anaconda to my PATH environment + variable``{=html} +8. Click on ``{=html}Next``{=html} and run the installer. +9. Finish the installation. +10. Launch Anaconda Navigator. +::: + +::: {.cell .markdown} +```{=html} +

Installing Dependencies

+``` +`
`{=html} + +1. Open Anaconda Navigator.`
`{=html} +2. Launch CMD.exe prompt.`
`{=html} +3. To install Matplotlib, in the cmd window type ``{=html}conda + install matplotlib``{=html}`
`{=html} +4. Do the same for Numpy and Pandas. +::: + +::: {.cell .code} +``` {.python} +``` +::: From 4f922482769200dd49e516d2850823a80b00a320 Mon Sep 17 00:00:00 2001 From: Rishabh Agrawal Date: Sat, 11 Jun 2022 16:56:46 +0530 Subject: [PATCH 3/5] README added --- w1/README.md | 75 ------------------------------------------------ w1/README.md.txt | 25 ++++++++++++++++ 2 files changed, 25 insertions(+), 75 deletions(-) delete mode 100644 w1/README.md create mode 100644 w1/README.md.txt diff --git a/w1/README.md b/w1/README.md deleted file mode 100644 index 72d081b..0000000 --- a/w1/README.md +++ /dev/null @@ -1,75 +0,0 @@ ---- -jupyter: - 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: 3.9.12 - nbformat: 4 - nbformat_minor: 5 ---- - -::: {.cell .markdown} -Anaconda is a distribution of the Python and R programming languages for -scientific computing, that aims to simplify package management and -deployment. The distribution includes data-science packages suitable for -Windows, Linux, and macOS. -::: - -::: {.cell .markdown} -```{=html} -

Anaconda installation in Windows

-``` -::: - -::: {.cell .markdown} -1. Visit . -2. Download the Installer. -3. Once the download is complete, run the installer. -::: - -::: {.cell .markdown} -1. The following window appears.`
`{=html} - ![image.png](vertopal_b92a56b7279a4017b3a1930e63d55b1e/image.png)`
`{=html} -2. Click on ``{=html}Next``{=html} and then click on - ``{=html}I agree.``{=html}`
`{=html} -3. In the following window choose the ``{=html}Just Me``{=html} - option.`
`{=html} - ![image-2.png](vertopal_b92a56b7279a4017b3a1930e63d55b1e/image-2.png)`
`{=html} -4. Click on ``{=html}Next``{=html}. -5. Choose the directory where you want the distribution to install. -6. Click on ``{=html}Next``{=html}. -7. At the Advanced Installation Options screen, I recommend that you do - not check ``{=html}Add Anaconda to my PATH environment - variable``{=html} -8. Click on ``{=html}Next``{=html} and run the installer. -9. Finish the installation. -10. Launch Anaconda Navigator. -::: - -::: {.cell .markdown} -```{=html} -

Installing Dependencies

-``` -`
`{=html} - -1. Open Anaconda Navigator.`
`{=html} -2. Launch CMD.exe prompt.`
`{=html} -3. To install Matplotlib, in the cmd window type ``{=html}conda - install matplotlib``{=html}`
`{=html} -4. Do the same for Numpy and Pandas. -::: - -::: {.cell .code} -``` {.python} -``` -::: diff --git a/w1/README.md.txt b/w1/README.md.txt new file mode 100644 index 0000000..4098392 --- /dev/null +++ b/w1/README.md.txt @@ -0,0 +1,25 @@ +Anaconda is a distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. The distribution includes data-science packages suitable for Windows, Linux, and macOS. + +Anaconda installation in Windows: +1. Visit https://www.anaconda.com/products/distribution. +2. Download the Installer. +3. Once the download is complete, run the installer. +4. The following window appears: + +5. Click on Next and then click on I agree. +6. In the following window choose the Just Me option. +7. Click on Next. +8. Choose the directory where you want the distribution to install. +9. Click on Next. +10. At the Advanced Installation Options screen, I recommend that you do not check Add Anaconda to my PATH environment variable. +11. Click on Next and run the installer. +12. Finish the installation. +13. Launch Anaconda Navigator. + + +Installing Dependencies: +1. Open Anaconda Navigator. +2. Launch CMD.exe prompt. +3. To install Matplotlib, in the cmd window type conda install matplotlib. +4. Do the same for Numpy and Pandas. + From 25c3359f69147e03d6fab9b69c90bfef30f3ddd7 Mon Sep 17 00:00:00 2001 From: Rishabh Agrawal Date: Sat, 11 Jun 2022 17:08:49 +0530 Subject: [PATCH 4/5] README added --- w1/{README.md.txt => README.md} | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) rename w1/{README.md.txt => README.md} (90%) diff --git a/w1/README.md.txt b/w1/README.md similarity index 90% rename from w1/README.md.txt rename to w1/README.md index 4098392..287b771 100644 --- a/w1/README.md.txt +++ b/w1/README.md @@ -4,14 +4,12 @@ Anaconda installation in Windows: 1. Visit https://www.anaconda.com/products/distribution. 2. Download the Installer. 3. Once the download is complete, run the installer. -4. The following window appears: - 5. Click on Next and then click on I agree. 6. In the following window choose the Just Me option. 7. Click on Next. 8. Choose the directory where you want the distribution to install. 9. Click on Next. -10. At the Advanced Installation Options screen, I recommend that you do not check Add Anaconda to my PATH environment variable. +10. At the Advanced Installation Options screen, I recommend that you do not check Add Anaconda to my PATH environment variable. 11. Click on Next and run the installer. 12. Finish the installation. 13. Launch Anaconda Navigator. @@ -22,4 +20,3 @@ Installing Dependencies: 2. Launch CMD.exe prompt. 3. To install Matplotlib, in the cmd window type conda install matplotlib. 4. Do the same for Numpy and Pandas. - From 605036e187fc60d0e43e8ba07c05b1bc8f968b88 Mon Sep 17 00:00:00 2001 From: Rishabh Agrawal <77164634+arishabh30@users.noreply.github.com> Date: Sat, 11 Jun 2022 17:10:05 +0530 Subject: [PATCH 5/5] Update README.md --- w1/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/w1/README.md b/w1/README.md index 287b771..6b700ef 100644 --- a/w1/README.md +++ b/w1/README.md @@ -1,6 +1,6 @@ Anaconda is a distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. The distribution includes data-science packages suitable for Windows, Linux, and macOS. -Anaconda installation in Windows: +**Anaconda installation in Windows:** 1. Visit https://www.anaconda.com/products/distribution. 2. Download the Installer. 3. Once the download is complete, run the installer. @@ -15,7 +15,7 @@ Anaconda installation in Windows: 13. Launch Anaconda Navigator. -Installing Dependencies: +**Installing Dependencies:** 1. Open Anaconda Navigator. 2. Launch CMD.exe prompt. 3. To install Matplotlib, in the cmd window type conda install matplotlib.