├── README.md
└── eda-on-shark-tank-india-s1 (1).ipynb


/README.md:
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1 | # EDA-on-Shark-Tank-India-S1
2 | The aim of this kernel is to provide the whole season 1 statistics in the form of data visualization to understand about the deals of equity and amount, and other features using Data Visulaization.
3 | 


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/eda-on-shark-tank-india-s1 (1).ipynb:
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   1 | {
   2 |  "cells": [
   3 |   {
   4 |    "cell_type": "markdown",
   5 |    "id": "70d1cdb4",
   6 |    "metadata": {
   7 |     "papermill": {
   8 |      "duration": 0.027614,
   9 |      "end_time": "2022-03-26T06:50:57.697776",
  10 |      "exception": false,
  11 |      "start_time": "2022-03-26T06:50:57.670162",
  12 |      "status": "completed"
  13 |     },
  14 |     "tags": []
  15 |    },
  16 |    "source": [
  17 |     "# **Exploratory Data Analysis on the Shark Tank India Season 1:**\n",
  18 |     "The aim of this kernel is to provide the whole season 1 statistics in the form of data visualization to understand about the deals of equity and amount, and other features..."
  19 |    ]
  20 |   },
  21 |   {
  22 |    "attachments": {
  23 |     "4e2133b3-854c-4bd8-a15b-ab4fb52f9471.webp": {
  24 |      "image/webp": 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NRGCqWhTsSKioeDvhfj222rYaquh7fc3xNGaKdSaZGg5iC2MchcIzptZUoW/na+KgwADL6ia9J11C9s2Lx42xbBjcvKhL3/KR/iuRUZZ2b/Qhmu2JInLl3n9fJexhmJ0af2g6OshVCZLgcnJH/zbzMuQSXceG0+sLOZTKrAK1vu6RoFhqVOdWEeEEBcgNqbo+craLSLDgV8/mKMDdpmISu6ktN8JHzXrTTSHogpDeuERPwAJREkuQvmqnEIOC/8rRl5rFTnkec+8JkH+weg0qX83MNtoSjgnFV/e214BmoMyZGa+1f8+MsQs9FtpVP01O4S++rOH1+85Z1yl+vfRNz8MChqtLO1wDR1CJ38Pg/TKHPGaLVWChXzB0Dc9BVpR8GE/Ljy7DcY24PHhe4d9vn0Hu+efl4TCvhM42z1AAWzek+nt2axkZpMTZLYQcyfDyqXYLLoERHn9bDVhvBoahl34HdtCR1VK/SVO490VQRsNbIUcfmzYKhQpKg96C8YJcqpT+c/QyrwPL/ONtGlVApyatPqT8Ml8QT1Il5Urk+ilp3olfqeh2Wp1FAMq6d73cdHVjNQM4nTByJBXprIDMY/E1nOQ1Xi8S/643w61q2KHOKxzvUN5zekXlURfSVDyJHZ2GJ619og7GxeCX+ynxDhs5Bn1GdhooIjIlLX9zypA1itjIGjXP50x05UfcnoyrtUi3U7uECfsgkuII+VqDjxEmJbjEEatJi0F4KoCsVt+aCU+rjMauH8jY956l5Qx0BYz6VLPoUPJ2auofkCWrQkcJ3WOlIvY/EHZZJLYHRxmqBujWm372DlmBQ+cJcksXiGPJK83qBrgS1V+suSN0YOBuuELsdsY/ZpJZpCMMkO4FNSaMyeGb57fCQF4zAjyrtUq+dgUVZd4iVB3s9Dt6WvzpVN6sVkftVnr3BnJoOM2UvxVdBb/ZWFz3HUq0ryljWi+w0W7A3tDeptD4yxJQwUxytEMXvX+BAZuKGJ/o4lxQt//4QphhNF9yhanT6rZgMYb9W6YhNpVT0+KhaIvwNPwdeoO31MqNnD7ErMdwc1f3D5aU3iOixN1mm+ix5AWLO4NH3h4r6qgYzKVekp+NQ4lMOEN5byB46//RGyavrtkUaby3USTFGJsYJYkznhjG69EKcMPIBdRgzR+He7IuGHj2YPmejRQm9W5guVxQU6NP1PrTWQYyeaDpMYn2BHrZ/vh+sJqJKxSQKMlNj1Wje8E6VONvnGlbDI/9AOHZU+SwoQIBo+BsgurIJBJesHKrHoiLfVxn0wIWqMwQLW8uVd1llfFH2rYjTEgZHLYW/FB9n5EAY6oozx/9iPuoZYAx3tqY6Celpc1sxALlIBJuYjGQkoZL0trr64yIldSLkbVWNef6s/7DxwbdsQKSaPVVw1XhkT1AIN0241+xdTJz1+GqQo3b+cedsYqC2ZcbHP1LIRP2vz1gaQfK/hgdnglv9/aFvxUTO40dgNP8MnAKmCMsrG9FdXqaQkSN/KCjsBv9Uoqpoy6kbGXH0IbXZrzQEBCSTixhEndVp6vSlLzXFtpN9cTBQdUNJqLBUDwlagMy4tgrX21D9cOSiB1KFKduqouZJHIrSYkmAUBRp331LLscKE+gdutDBN9UOJA1Q1d7HUHV/y+VTzKcw9sHldLs6++7g6UjdBmto+Esa865MVSh5wk31gc8Sv0+8LWbxefnUu4z7KlLphaVm6m3/Vv84wTrPZc7+gS3bRQlQQIgrp7tCOYfOu4kJ00IcFTD/99yTHtns4DzDXHW4NYWKRAFecOAEQKET5wfL6hizcx4IxYTQx/youxcIhQtFAEEp9h9HLtNNDphaGEEBmDM9vWDY3SoHZmOexqhdc86ZZVqZ8xwqkWnSEeCSewmpzQwdskZAuAeCfpOT9QzF6fEClg/jIGP50RjnxcjDaAzY/oBEFm6DDjjWmZomekxf53+lXCSQipqASgXCthjte3EapPwF7sUOeNEdrUI1wPCAI4m3/v6+RV/IhJjBT95qeUcOvl46j2VZvSFiOXSX/skJ5hjVRIXja0CeTARSDksi3sJ5FxZdWkXdPPWOvbvJo7wMpRspaBwyn+CvNr2YX7M5ZeYxUY7YHo2ru8IxCVxVxodLclVDhajy4zdnWNlDWyLemuCZLu2bR7oFEwMWQK7oI6HhQTLejnZRvZumeaXSHiQbARjRS0vNTLN9kE4NfhKrcVxc9MTnpEC9jgouk3FQ/RazN3aOHVP9H4DVVayWj+1ihSyWPCVbAyisL//4qlpZxdlyRjEv3Ydpto/TCVqX6wmYqIX7yj21bC282Cff+cdFvqQc5LE1gOAW6u1JdotluiGQcoHwriL49h3+n3/9LIAYZ6135rnmFwAocOf1wtdKtYvc1rDRdo6tR+k8z+olO/KaRfSAHTtOgJr9DS5rmp/X7b8GEJqymMUyNqL0rdV8iiKowkRDN+KWK3TW+4CujtNtvSptn3/E8tsU86EgLPelOoeSwtiieRurc/OJRLDNit96vNZ6aQ+Pgolnabwm6pGblsDdpVx0uQWg5RWEjPCGSQVQY97eqrfuSps9PRw3t30drWJyJVGZNATsQ3bNZxo2MDHUbZOtx/Up/14AVT5/MSUo/5c8effwQbKUyJNJp2VA3n5eVkI6tuBEzml5gWpXxM4cblhb1ORmqGb8tRZmeMokEU4073PrcRZT2ZmAEEEOuO9/OAxNzmKkXqzENKq2YW3/ODJGC+0XJKPF5Y1183cpSJcYZxtPHDMhO3vmZCpspY2LCt/63hHoKPfty5ioaEBODt63uxNRmWmXf3dmqdtRe3s+Gy4o+PqjZi66yXMl1SD+pWUid3j6mgzdGd0K84WW+WRIl7CRZd7qFgBakm078fa6SKrLlz5X+yOiuhOl4fYtO5l1W0kzDolT6QddHYC+RtguiHVlECPWhkNk15z9ljjdQYZmL/4rK5/0j1gfd+hpGh3Gon1hTX+YB5Psdpse3vbelsd9XjDOchuDrLOi4JKXeyiOn5K6ATtAveze55doioNcNR2yO7Zm/SJPlmZPf5kIh9jnaBctu0qotbtzgZZQLFUGLyUO6AcBGhSqRh5nGNDbQg6/JO4DKQylllzFDlLuE6QIHa+UcAoHRvSgYBhJSQanGH6zNpRRzWFNfcwapU48jp6O+NUGwbvjhZONn5rcgWrjoeHoTOmDcrjJAFqDll7ImW+QavzuurvF8wg18ZcKYfNHpl3JOGj5v+48lPumZqXzSd2IEs93iwOvuynqSbTJXAcDdMkPiz2NNHyuzmlf3Tq5Y6lC/2EgUetjOcZCyjC7zMEtKgzF54+8sj8a/Xj6JXNoZg3oFGtQn6Aq9Kq88bG446wlNleQjCkHYIpZQNlYV0o7DX0wJkjkkEXD+8EcGtRDZJiDdPo4SMmoLALcrU2Gs2JMNx4bSe7fsbCfeQkWWaCedaBKRhZxIZXa4lhbRGC4ccqD0ZkFddlQQalCProImHpCtc0MkVD8FaqlDPw4Mq5oXZyypo05zCNxLQ0y86ELQXhMlGKPFmc1OCbqyQsp28LEXKa/9UfUjgEkBp30Yak+LrrJJo+WLFKTURkMrr+0Y7vGwxl7eY587uc2gQkXUQ1vPGICtWTJclnacP/MgmCTtwJY50emnyQUNfKxILvb0GsuNqmWHI7KidYsFVAPCv9BVeWcFYf+5bBuAb6gapW7wC/pL6wCIBN/MW3GDSpZRMXImPlKVjLAeWCX2wfm4ofnvj6Wj2Gi7njJjUgsYKWPezw8G+YIaeew3FPaazYFcIfTn4o72V5doeYrFJuxhYhSSHTIoQc5iqW7proMfb+zX6/OPphXrJ0FrCGS/0/V48FEZmXE9p3R6KDSA+gvOQJDbT51DMiR/L6+py9BuOUv2g6s+sVPcy1MuP7DcvaWHjWHqjiDBGXJOxdLGRnIReKZzX9/IqWhKDgNTLeXxRQ4hnaGprOiZbP2GuEx8k9wlvpstMyTqOhZ4r3gyCtJH9PZ4TnEmKynY0nCpVhhUotVvNDvMv19HMfZ+ZiE6W0kXxIXbFXteeWtr+OBCZLjy0B91oTVH2m7F1A/2d/CYPTZ4zawKUckVQ/QGt8xPS3PH+OWe9BYRmfJje/P4DZDin6sX2LaTZdJxq2Nv58WtuFm+csIgzfDOCgsRlQoAMxEyJTxJhC15RaBNR5fgi/e1brlsX1veIs7YwK/O2T0q6o9RnNmdkf7/P+592zWSqvR3EeZZPiBO0SmzWhVeycQzJQmPhlFY8Xo+8sQuMcYTff98L+9RPIpnS+RFhih1EXX5hYrzO3VuS8f72vtXwESZuG19L+RUktNM92dStilPbu8X08Kg4ZBezBiia51cBwfZFSU/OKHl7aLCK9/dfnD1JNWuqbP2SXQKHD0ctlsUZWhLQaTxKEglYHpMwgy5Aq9PScX5ZGpdVzx2RlSwWGNc1E0CplkPHh60HLzFzQnBmgMB90NH7DcKXVFnSFfpBrKqUMvwttG79K0W5s33My0EC8gUM2YTuYkYZZH3LOGDaeq9LqWq27LrOplrjyzpQZlBH6KgLMs4+U4/2O+yIFNmYALIme6ZZNBAKyicRQpR+hu1OJCe+vsNkzxv2GRrwqRaOjhqf0pplpKzTEGnL5HCvG4c38h8XhE+5cCgpWS2aeI3FoNQc7j7rcC8hMULOED/FssiIEANawmdTiFdYNyT98NgNAqpwItdFNbxGFdgBm37SHh6RUn/aA8vELwPIh6FsGWI3PTIrQPENKVAybKLtFqYaywcMTHvye4r9KCHqocHlLDrJX6v7JZIvuqisr/YnI5pLG/QZQvObb9s8fgQXzXVPprBssUVgDf9nvyuUZQgTCq7MmQUNloAwIFwbeDe3XaUprDHMRfVBfovp344V8nqJ4o1/n8F02PsFrobRTokGgbDOVfmwO0qGIH9D05LDncLZb/Xo3IU7kx3BJ++BFbegOhdVZ8KhCJzr79Rhi6XZngY9EQPTjv4Y5qD0H0nLbaZUHpHPGfVlyqRwoyjJbS6hd4aXltmdZ/KKG1GJmFoFeiMsK6sgr/ujnkzX14uvjb/juvNVuLB3qLfGgEde3UfsnBTx2iYhTYIA/o1xIJtsHgJSVB8s0PC/L0lrik1E8AmZ2jPTICKBKOTlSvryweBKO9Aq5097G6WFnjc1KGTzxBNHwaPZHqvg+b078LsMCfLa2x7QMLGBqXMRUgiOedFqLRWmnqfTOIp5j4nS+NSRNmNMFnKgO1Xd1WE7e9jvoBPF32IrK0he97OAo89y+b2XZkG0507zyRAc6FY7YGDIYevFWI8YX39cWKKCf4bV7xp8kVhCDN87G5dVhqakQZCn4CHgHaEyOF36xer2TDyhrt9G969JLkOZy/08Hu3Myhy1PKguhW/TdfWPd2g0ekK08biUSU27VLvl/cr+gYkvX8lQ+1SGEL+RGd5BCkOWh5wvtKRO6uy97VKQlfRy40oY1tjSMWvysM0wzDNngmjbSWJbLNIef452UWxwamehzHVCIukwcBFolbioKmeN5aF548BtJeE6W19MkMItyntKZw018APWP+V+CdiVNS3ne4dfpmUnAH29yztnyvl49eLYq4tgykXz280uG/pxO1RIzPZY4R3vLojIhDiMNsL5JiuH7PIXcPoHgo65H00WHenKxvXROkF1n7yWixfp78YFzpCqSCYz3CM/m6eKfiKE0hEyhmS+BXaVyybaUbWdaHTqWyBqoS+Ooj/rZ+Rq4j9QGotS+VQmk1QxRnuAm7gjohuGkZepRbbptOmZs6MX7jaNH/dX9evuQrJmC9ZYpfzegM6OwtpOapYv9LfBkfckNu94oA3ML0FKluSeGd4m/C4nN4/6Cr+ykjiPHwH7OCcD46//ly8c6/H3de+IUeeFpNjumULrJqi5ijHlqlUWBaU7iDfh5CwiXIA01nCOGBi0mL/d6p7E/J3YUzNqq9keriHSkAbhYUPPRARBugjQdj5YOzWzpbNBsPLI+z3v+l2Jz8IbBpfGSZsXUqKJnI9OszlymblYqpDYufLLJU6tgra1LJMRVXzIfmkwJsSrq0jdSbTx+zO0nQMbKxwxjFb09BYjDblwbuWmoMgxwfhwSrG9mfsPaCurgPXXKFspOIZEt88WbJhjhudTLB7+cbyKL3HY0dvf1/WC6kVoem8ulAJsujS7ELKQy8Zksm1FdE5JJENIaTG7HHm88iSNSTBjfXqV3T9XPEa8GK9V+CXsn55j4nd5d7QCKPZExlHGgslWgTeGKoAGOoglb4j8ejXJDRUuJyX3XNSeVor/Qk4PMj2FflYwFWO4r48anU2CEcxKYe8WAObTfmOEVlQXRmIL3pgZsqkLcIlsu4m/m258El2/asTOsE9x4JuQrrq0GrddYQUT0XCzZdR2fuGXsISKY8jAna1HGKA+1b174lRB6CCxWR0VbBw5qQ9rxyfBkS09/axZUSXy//epPdiT99jJzl+I23aA2hXGqYIGJXqraEMLWu9QPfI/fDBbOo/bJWJ8K3FCnAZeUo7vr0t0I8nj9bLVIIWlxF4uq9O+kjIFZFZ9mffpLEOAI21iYgoyyBp/nsaP0UBfl29alH5cpp/tsMVDDVL8Rjk8JK8g++ztV6ONxDj5310cZGfUSNh0FLHXeimpsHzyOCzmPA1mRosbvZzv9rdkJ3yaEHdMLzdIHVFYJ8PFiklXeV4nqZxlxaC6FPR/2MvP3gOslpc+/9vbKaSpBTJakAN4a0wy65QitirJB3V2clzChYtnZsJkafpg94+9gMLP2uAST+3Rg66nfJmxBkhhOwWc5Ac0lfwWro5B5HUK5dktNjofvX+guEsRYMGI52uQdj9p7ytj1fIgcF91w7iyPGDc13WBzzU6s08ltTb0ukkefJmi7LMwSRAwTAjKj22Gi10MB+vJV4qyeMdDqtEbWR9508dxQ8mihaC7bJg7oy4vMUi/RAGEOPcOrgMi96a6hssHiD+8uFT0sGWRvedV6L6rIDotWuTj2zVZNyDg7GCydPqkRoA2db9VI0llddny7E+gdaNQ6fu2n0TafZXBUlLIaJp88IWhWR0ORqTYh5ENVWZFVkGQp0lEEfeuOS0vjABma9AbgFKaREXv2ncnA3IKsN/SKewsBEAJCaOkWAAMyDa/8myTOg46QvYQC5N/dGRtVMKVJU+66jQAAAP7+ZxpcFilTqB6U9vy8ZcVjLFx6nM/gdgY2V9xnR2MVckSGPMds3N9m/JTY2J6wTAR2/S159wKQ45E9J+Cvnw5iQfQ+xq/77eFqGTYbWmV5UL13krJyQ+cRpxdNguPg73J2IQZesRe67BiX5yLdWBADJEfwp4uSFV3RTtt7OkCqF6TpvI8/tQxmgofvYbE4kddRoNXTvvVR1Cd9vHOS7rrpGXn6nLCpbzGxMbkfvBa/xqFuog3+pads2J5M7kPoYhX44Wk+20VoOi/zQg9AC2t3g1xmac8gMV2uQuJAv3tuukXesXIgZ7aVZ7fttXMxZ9dCYVwu7dHjTDRVomBQsaPE5IflK0Y8s/rislK35Di8/0bd+WxU+uQRgn0j2spvnMPICCca7nCyQPyKK8tEfhG+mkszfBKDZ1gdvn5jNUSRR3rJH7Dm1+h3xaeHofPG//6lmY3pPZLLHE0CipEALcENkjanV15CCJU8WGcaiQgOMb2HpHqq80o8w8fPo3ECsLij8gSAEMOZY1mIp8+9Fc7P2jYu6hS1bPZU14GFR17hGdNjPm7r1raTXzpiidgffYS6Horc2nsqQBMJyvNFcjXMOSCblbeRfGwSjnlrACOe8JDQWfM4exQJ/N4/mS+YMyAvnA2Vq3HsW8nv5PeQImRpLukPKTw0RtrS5YqfvTiC9tgz7iGFRHeUXQrDnCX1eJDSOv9/76NvKs2aLUJMaSiAqRy/+aAmR9HIQh6ypYBVm727yx9ILFFo79UC17cNHO53yDviO8SxoId5AvVGnsD8t9erZ7WJyr9CCxbgaFjrCTNYNMBi5n6OGm/8mcEFXMVZXvRfHvahy9VBRmrZmBp/4gFkRKFVfQbHxVbWV2W2kgC4mE7W8DWxWDnJ8Vv4cPZnzcNgBWY8cLoC7V/Cm14cd/NHeS4kSZ0PHx0brtunAj8NlDP8kSZ20LgULX3UZVLYnjaWkBeIuJnjihmtbiD7lLZnWOF3fNV6faHexFoGz+TGaICWxStpN6Vy+E3Vww2/CkO6bbPz2QhHem7HZ200jVMwbOxaUA1SORKKMJsuDAQFxq0zfB1aKRZzyfifnKqAXu0AQ1SdwNzisg46oIz8ZZggCwLCJ8NbJ0o/MXRDB2GXsgyUHubw9hZq/Ej6jmA/QxK85zMyI53/IyIZdlWthjUveV8iNxEUpS2cfCgg75qWIMZfo0Lg+Gr45Uu/Slku6hItJR+vZYd3qeUWWRAMPdQjGeT9o6STSf6GCBfHmAp1agjVYRG9AEMeeLInvhoV09UnUYWNoy0kwihARy5ws8a0C8mCiHV+hUKHBt3JoJT8SeaN0yuwd3CLQbxVDWre4D69SvTz9ROrt5xR9BeEDAI03CHcHswQcoLAd8o1KY/kZRc4yBSfSjeP4SyPKbWDvB4sInwyOjVQTtTfReQ/Qgv5Fu1oGs0xHTLlkMI5J32J7S78xcJgpdgbKzp9ApiSq08G476c9UpXj1gG5S4hgG+Cr+YCkmN1KtaIrSb4QJYH/ii60ogpSfcF4yaGIfDiWYYJRUDgXryyVs/MiKR5PQTcHf50NryytcFtIelDFtOGBGEn6S2KqQ30kLNreBsNoVSbgAvqAAw7wmtpX7xK93gVKPeBUL4AQYywRZitFOCuynjgUeQt5YSBuMkauSz9H2CUsbjpA/F9s5DzEpgDvWbi8fRJeeDNwseZb32Lexe29M/JmSU1kA2OFEp/J9EZsYwhC5isew2WCotXjexvkuDu5XbcNCFxFp4j6nx/KQk0muH5UXMkrVmI4+thoZ+ZS6fT0qKEKR7KbOAEdnJK/RfbUVlhvToVyiA/CK3dGl78pcJunRdbrCmORCSSPmv9IVUMYKQJjoyFbdLmFr8n5JxqNekUViwlHEUE9UW92Wa00dEm/2kGYB1QUbLvB40B+Q4ye3oVwad3rdinp3VjikfHHixoXWUGVXzv1tp3oO6wKD4O00PvY0vR6obOrwd4kJVmBrkYDL+3P3lOFSlKHgdW5k/TMBgqXZvtIzIQBkEEzP9OJ1IubtQASu32CQsa7B9ozwComVo9Z7qD6/imQVDRXfUYtNLAMhnFycQhGlIpnK6xlk6C0qwXsIw+bsOYFfjcJnNJAf4k5ZKFKWkKS/Gxsnc1KBpmcK+6OsDItNi2xqAjW7AR0Q3IBPGJ8z1VeP4SxYXG0VthBHeh3s1k3IsbJqBUuh01TECGzFNrZJh2lrqH9RapYCRtgBcMadAY5YlFbPAExXHd6DPsklxXldAsinYVS25cz8Uz4CY+KiOBuL4O9pdoY9VIkcalFhb4Unj371dvAIThI+PYeuFLgH3XYsfmLYGDMfuUxzGvb+pU8OK1WZG265rOR05Xeq8Cqf0meno4wRuX5vV7h8kJ2tJ9aRG31uggj3nXXJ+6qUYsMZHoBfoFjj/fDn+NFu9Mg4PV4aUiFHHut3ysRHlkDXddZoHtC0d0sHXUrmgRW97B1/vNF3XL9P2+5CQcA9VnSvdaiA9PnDyCrqXAh/IqwYOPA4Kstt6SjDHpmf3fE49my8IdU8jMuUhwjXWVubzQShJPLhDgFmxruHnhdyfOqXT8crovlznFi0jO8e3gwEXVWdwibBDjgFbymm6sb67k9hfz+JLwZcjsSrOqtoCf2h8IV01Reer/iRAq7xnGdTLhwQK9BCe9uFbKkmgJCYKyUFsW6BpTKrfQ+Bi+vGYEMT6FSz9lYFtiY0iM4mCKv8rMzL5kaliZ5PyjCByHkeAEitd39HdwJsT+n8X5wgIbhkC7gW+SxW+2a6IFKsYURk62AVW5DWx6lDBl/qH7Ig2rxTrJkBsKHZXq0Vsf1FB9w473H60WPSkhybmQlH902hNNjnHKcGNJvS35hyGRyTCTO5liQQfkzkkTjgdlfj48sX7eChysOHrHl7HKajIu19C1H9g7GwzQnUxpmnYfIw+zAi7zvPFnrV3xdSzyrOfpWx1vgfatlUpS+dAmYIaUfPNveCtkPhKgy6fK/FVTu9PzfDrYz3E84jS5CXUXnNIZ3o3QojMHvtRGSdPiov3O3C2gmHybaYtvC3Zk/xWUwlIwrPh1fUsOWJ2PofzsGjTvtoXPPiOgYj9Q4GkKcZ6+DjRtkp1Ktjmt7FPpXjfAi+56EzughXm+m+RzkEkrMnp+ob0u+YZaeQMShPtc9PL+eX9OXZT2XTv1kYPSof52TkJvIHTXo+d3uh6AacTD0KenWqmCVdNMyu7NZz5nOp3R+A0FNfIVY6Emi+0G7zFy9WH3Pr5gjiinX4z0M0fWpPcEIm6vVCqes3QB799Ehl+dgRTj2Nm49+lFYLLXoj2G6cylIhlCdbBSdRaCQ5Q5D1DbOD60jFrEQ8wmN89JkQaZbd8VF4T7MAypmJg4gKN+YIUfYO3gfIzYuiKSexF7SJNvlf4Lgu+wVAAdBD+lGnLbfOZzEVPJ+C0NDvKd2qa1VRvd4pTOgfY+XuSc78lWp1ygcNqQVGZvF6DSfZ/vdkGsw3lW9/W4oe93TTAti9JGjYB7k/KOtz5tHZ3JJ7emKkmU2ZtdZFfLfLXo0l5brSXVaHQvSMPvzoN7AKrjuBZM29xp8wjcVfLC8qI7+QdoogX5OEwweW1aarwLcXP1CDndPjidanwXbALIiguUyNEAnfGa8quVP2zCvzXHCS9WrfrVc4Gzs44UMTCHlIlDCtleM26POubEekOT3N65qpSzXGzI2zENcfC5sCn5+ZFd4LodnmWm9r/WbmbAoRd8s2xZGap48QgVr64uvmu/5b5LBEI+TR/qVrfAp6qFgtZ00fpVFiiwT1oXgt3ZyEIZBD8MTF+cC+LSzLuWIrw8J/cwCeZa8SfiPx5zs2Skng+LaAlEe0P2fBR2Qlj61WISbfV+sOJWz+NMuyyyMwU6ikpME0NRQHbrKZvzVm78d1D3NY2PCp7YS0cCHoIQXmF8dYdtjOL68AWk9VAuru0uLXWsDlDaY6a+/v9Z4HUwREaGBEarU3Jy5DO7aeRC0tNFyvXc/UHcFR78XSQwb7OGwsz9IGz/GDDNZiOXna8xIO9QH0iRcGYyJfZvY3SDuT0Vcw4QcnlIa7JS6jIEEUgJkwnTgH+N0UR7qXlNy1HrwmOFFAI4DW/3rwjb10IBiXs8bs5gqHXPrmKe/gcFhI3mD2FuqLGuMHMvKHW3BeI5+RA9shF0nMehcKgDmungGXbYNID9hpMLY4DykSeIBTd6YGRyLPETDyOs4cCHgmciQLhHj84C5U5ARS+fX8ZXeUWxTWq5fa5ClRWnYdn9AYjqzNldIchRXvN3Lva+uCFuCYFmssF+RaytVgxyN2Z6iCAlSO+NgbyvN9mPm8trYmPX8hU9nxwN8FgQQniNgTBJ1R7cNKgxgD8K/s/1UDNoylj09hINE5MLuISy796+U1vELc260XFnwPN05VhYtCFYAppOxJiXEV3amjwoynnwygnIJCfRmB6ozIaW069ZNhbbAbGpm0Q+EccDmhoiXe/KknuUj8Di1eOv6kDJReo71Tx2XHth5PLWOwpCCgREqiTzgMcCYrDlaOOHpFqbnHeeg0yTHZfzeKj3KkJTbptf5GfIgFBD8arp6VnUVcsFnkKaMcmoTFrM48cMVN1PquYPfsSqfFAihmAInkk8KlQz5QBQVfudiovudQKFA38PHQ3B9gY9Ji1hwdqPJ4tvoNwrMx+iuVBrzDU6C1xBTCupU4T7zdnRCctkzQYTE2N2t7ndhsFjiHlzP6O46MOCYfSlLEHgeKFY2aSYfPOGXHLMpYRjUgCGFf5I6FZyHprvGisIVK5Gd4rE/FQNC0AGmVDE0ho4+n09NUiMvfcYZF7qMrkLUqY2CzveRu9TIrGWByuakBv1Byg6aS9md46bwYdnTbi5vSI+FbQGcRCI2vTA0sIERKpx8u/TmAyQ7iWri7WvzpCXnRrHAYjX5sZkOoF0tpqsnXGd0DHO9NyhE7pI49zLijJlDR+Vt9bWDXwgY2PMnOR6IzpuD+ST6L70CHhP2aUuQ17Axfm1splVdCOGbam6J9LjNsYlVAAASz2KHM2akarkoNheYHIp3mh6pFpz6QZ4wm6SnEnxMh664WeWaAkZIQEBSDlVTuLd4DiIhEogAXoNWDagEjwZxalKq3rOeYo6ifebg6wC9DffqE+4EFRvqPsE6lXnXgw3f5e+uiWJ4kg4oeAW/Jb+TB9GbhoC6KGy9+mvmbm8ul7Rxkd3m4P6qddZxfljm/fYs7z+SP400SLvrvUR10FrPSl7TyF90zQzR3edkDxYWcb72eCv7Ksg/QO21ffS1xyXfW/2ZYA6neDT86IHptO9+n6JcgNqVbCbYKHRCL5DhS0zi+YUoum7iQ5Yr8GcNRr4lDfcAefiQHCAB4Jw7J0A/TIZn4niB4lyRnfwLFxIh3oiZuHqLrk9zdsXE86G7a99HhQ1Zhg6Tvoqt7ZB87SeweFrbC7noU440hlYKLwmE7ltKYoGVJxNIBGC6kS2Is5kF1X9GtI5ssooydj0RxfICDLm2VOKqGtvQefF3xOt5YFy76/ILEUeOQ09YZIJVNJH/V2cVhggvGLp8/HHxnMUGULIBr3kC62LvgIINypg2bOJXn60NwDiYBr9jmfi1ojngcwAuT1cyOQjbWkKnMzWjIJkgQvnZzMH5hFILN23/ZK23pgELdSQEKPMcxUhLb9pog+OmpHPobXk7N3ddPo6MS1RjqPHOqbsdzZHbhCYGB8FCcolrTBhWMnYt5aShweoeRRNTkpYVIoABe8Ipzr9YL53VggSmJXHlEMAua6liHNUyGwcirTGR6hK0SlUMJfTzFO9OZME26qBc7w5iXkuB1aL3svn2eEsR7233yf9YwSteApOthG8EgK8QwDbuixbxb4XepHgTCLDmCjEc/I2ZDR8KbBNNq+9o5jeUNSBlu9O9T8I7eb7rHpK14If0LCyPqBR+5y4cCmTVggT/tHr4R7goguQ/GPl/oD+BapSvoyhStjoNrR7bWJEAmibA7YBQfLtKW+G13D2FnK7DVkqcH0aL2QPKsNtn+tadT3wUYg+CuOSVnr3kcEZpuQneGPy5UFsG2+bpg1rbAG1t3H4IsNMqv4dQx4z5InNwIf8gJylm9j2N2g5enzKIFvG9miSHV1o75IBM6SmYZka5WytSYFIiOA9n8HolHvXJZd++CHy6Zki9t2IPJjn186Sh8VCbX1Vkh4dcgarCd3Njzc5s4m27gMrse4acr6goF6dMGip2edrDW8tNLRpSLVZ99WpSPrvGAYudNEhGcIOqyNwTvDfAOG7DVcSzzIMrUFTPMMEEu6UcrIgUHnpdHLRXAaQvB8t9V0d/VtZ9x+U3kNP31gVLlArrt6aYmW8AYpospRuAXdxk1NvaKNuXbSnVm5zafvHrn7JmqXPp85F0UL7qJoYWdVP6DmDxkK7NGw6UUgBg+XjCeN1D8Wt2BgdJ2NtZEhOdZjc49iIX5QhF9tTIlNM8BFuD7VQVB9oUewd8xaQzKv/p98KnvgTYyuGmVkuGJ4PAyu8nB8QQ4mnPaR0AJqyG9Xng1y3FmcpnVR4smxqOmqisKqKG4rrBJ2SV+6AeOQKTpxFt1G+psftivPXJZjuupk57H72rbdMJXUoYy+TQ/DwaPH2Az3tqFpRpOGY4B8n2jrdLAFvo8ykATLL2X8eDkyHq3d3CQfNmbAdAUtwmVJUOHLMyIY98s3Mf0cHvr5A0Dxstktv2HqO2GL9b1REb6t/XaLcTsRoXDMbcRJHWJTOZXzc1/XFjN7IaUdlMSTrjiYSfZM1gha+xGYZyEjcM0GaqHFk+8qTCXZceJMY81niVWryUnWrECl5iG9RN/lNOX7CGz7d7LyVrtv660VG135qhExkxziABjBzOMgHsHAF7j9ZxpqmkPmJu+6uMqYTt3JJ0RDxW98WtjCGBizLb/3xM6tPVQNYT3ndtMpdJukw99Cj+j+c1I6dTATl7YvgA2LNRjKf9kFIrJZHAP3tl3IPl9RM0OgQy8Cck+DlkolX/Eg+9T+dLC+Z+y+xtonpmYfjjH2Co9oK3fqZY7nbzo7bT8vzOSgdGQcJBNyDH6CI93BWTrWpbjd8VSiEbshemrGEeaPwagpJ3ya7rozcqXMU/ig5iHIBUaJYKhBaDeycaxWAcIEfkZdWPX9eLiW9F6NE8ipldnjeiJ7ffT6B0ZZ8I5OZZChpFY5GLI+kHFPLFt2453hbdFSTHPid6rl1ant3WdCCj/WdxTzVSEyXAqI1+owy7AYDBfI2d+HAxM64zwKa+wXgosWkRuj+ENFjgUpje14SyUIBl7+SUiWpDQHtlxcY67DdojQDCDQ1wghhdn9FVHgdzlh7Mfkc4IZIPrd/ABU6YgzdqcDqLcOH0UWkfKx5D2b4NrJ2Lneex2KKcNwSWBvoD2FDd7u+ixYaQ6lvVgFk6awUHf5TjKxrXKIQtUtI1I8o3tA2tG7NK1sunwaoB63K6RTb59bdB75Cq/4UIM9+pwHSNZJnaKs09AEN8rGK+agSMgih1RQUMkgNIi3Kn11JE5SMK4rwAU9VoSCqiC2RAp+hT9FWO6kr+zcjUrp8y2tdrLOWf2sJwkhSLwWdCk4bOvZ8MX5nKpbkAcM/nf+xw9L4wnoASHNCGopoggMM3vXwOo7NwcICS84cwKdLfIShSOvbAVm+EjLYSjG726sihSgdwlI4/VXnpfJZbwudPyeiRlw1xFzb7xVee+q4ZNG0DtiOV0K/KhpedWbB0fR/AlbQlZjMgEvRsmxvzKbb8en0iSzSmoHiBdrwpbasM9mgqxO07HnxEROPqpUhlC7l1Hc2vNVj4lxMYhshGTo5BejmOGNoLb7iV2UdeQrgPIaFubwjqeYL4vKn6JDMaASzdXmgPo4g714TYYjEoY9fH2/eS1S6flwG7lj2PL02Gi/MuMo9OACvN32zt2o0NnJ3PGA0/wiE5mMcMlhtkfxBmbKNMukOyNw6ZAltV106EzCaA20K97JQQL3de5S53Ad9VutGj8LcQNtL0A33icm/Sk1vfyMCgNHPiWtmeARl1js1hMQAOLPXOJGbPbje8P9wPpUnObchLfcBlGLMX3MQdSEA3F4VYoba/Y0sYkNaB8ano5CZn8eT/Cyv5tKqdkPbJ06v3dtevl1zVCHQ3IRn7CVkU6nsXGLNE8nCdDfzHIjyf23cnj7PZgl3HY83TMDQ1Hpx64HZnN0AzPkBtLskn1yYgmwECwKXYfRx5m3xOcbjwg8b3ZHONNYCO33thvp4TqHm7trV49FVyAPmRMnpW4+fzRotbgw3XIxfJDtjZLHZiuzk7MZcbkDO8V/MhanttAuxKYvkc50GRNc4Ee8qvvmfQbDnwqx5IpzgHQZkPIS6GMWoaITL70/g3O5Dypeyd3z3q8rauHG63ryUEIKyA4prvO0QoMUiXJCSCrVHdKXZSAyEsftN3fgcz5ug2KWGlvOZKRggH5QjggyBao19aivCumjakSFwiV5LKHwOiIDLj8rj3gFpI94calPkHAAlJnWiyThjs+7nXXmSc2T62H1tD2BJTdfFy+PI2aP+8oyhVqzwTHoPQgbyNuGMgm3nQ8DP3jzgNWnuE0lkDSOZ6ACh3meCShliv/jNWAKxqBXcuQdXENhbYdBJEs2SFTn5B5ti7ZMjltbpIJbK2PNRkGtfrlCmGaxJdCdnT6ch4RYEhuthuIkfwERUAc1YEKGyfCgedrOcXVGiUjH9sA0kIsxIhY5Hye9z7jYpPJZP8dDa0dEbj7AXPHSzmvxoj9yOT6qHiL+Lyd45EssPZQEBQz56VJ7AVuyov8ICrZWjHgLA7Lhv8QWM2pMSEhpzF1aXlHsMDufU1BBIkUtiNPzQ2xnkCHU/XeBXaEQYk/EoXt57YizKR3JPnWB0jINxhlaYfLyxDx9DZ1SnnUtWU4U0cZZ7tPnYKOlaGf6da6qxAlc+a09zE62b0soNxXyyX6uykxUZqATnNGLXLJDZntzMtx7bKwsuMWNf76clTO9I/v1JXqLOaLM2FSKiMYljgsgeK2DfmUysw0PDEihAlbgnt+AU0ddFIzY2XtF6ZAI66TFeYRjudROWtxwT9uMnOLSa+GjuF/+8y3MIybEHjFXSr6uk2WB8vY6zBgGV4SnAVTDZGMxlaaskf+ocNvCSi0kwypk7vLFg8HEEyh6DJeHRuauGwedhAIyGfKyNKPJmquHVVrcwelwr1C+J837k3777QMd9Cre0PRn31hjCNB9iP9laj2837qnM0gWT/PiBYKvYw+QWuxoSeL+S3xmPSAE/Br5WC0U1n+CvAr2k/5FiVdcXxFwbMDxOILFMH7sednL+39EdV4/HQO9R/YT3ZUJlu1MgS2yEZ5yQA5O48sGRNoa7M6t4OP3537ZMe5/tw+R5+snulUJIABXsdlOEIQIZPjGLh1zPN1Az161y6/W/8X2NhY5kjHNz6DWcne3jlWQlsxiMERDKlhNO+K19XSIjqBXfQg3vtQl/3FM+IiVid8GlogYxBp0CTyRluQ4zxp/fpFqDscnDx5WJJIs1ig6sIAbi+uUHDto/k+GehjrG31x+7rrp0EMu3VLrakKPsl1oSKrf06sAgtvbnKGehoAQSWZW5kjzaDpYqozh2yQsmv/PbG3JJKBD8ZoFshkt4EUXb99pRpHR5nIOTWqVxQCg6Psut6e/nCg4AzDk40IqDruCa5oBHwiJHf2uK94lJ+z8wIYsdvrQ3v+Ji6zWFGhW4zjIzRD2u+fw6y1fKj70DlqzSOS0VJl5N+DxAEwPG7PPy6P8SkXItzVli6xcMYbgTtCXRpGFRQkW6WyJpB7w/VlJFEVFoQUCv8hMbsaCnkIlBMUJB1yj4rxO7WCC0GzPDJ5B6bBORN6lbfjlLLClxCc6ML9VCxgIATp65LGsucXIv5zCmP/CpB1OfZFqMMvbIshAKzHj1Yim6l+krz4lQqd+P+pqlKC135J3m3GH6Wg45geDJNQjrO9Sxl4WN6CXZLmlNiVKaokefNidYCUbAfcfCYF7IduYRAOCR28PXE0y5tre+W1mJ7ReGyA49wN0by0Xc3l8+SWmcLO6YDVFb2PmTSnPAa8wg/LViejByIQOZ48UKBQuQqxfP95A/wZgc3GjerUDelwXg5OQ6NvuOab9euf8sdBHm/YOYsm8usHZ6i0S2+tUzJGveVk65oBZd93YpH3+huc2j5K5ei2D8fwsmcmtbajl3CyA54zZIV/j8RSwCkBM94VWVtLkfhrxu3rmhR4rt/Id3mslPvz/1uTGVtR9OWIzo/bvP060jEUQ8I/O/Ma1o8w3z55c0C/BT3oAczPzRvnABn+1gNjbJBtOQy1VIUwnMspR78kxTh+CPIPSMGxp+XlcjBdjGaQvAXe5Py39eO7CorW+IPQEaJ/ptS+OTuaJWM/sebz03VwVCGLBECgpZhuk5macW2dt2i4+UDd4SFRT+gw2NZ+n5gzAoD2FGA+VZX3OUn5mFz478WQD0xfwOm2zIea36GAwj3SqjqQULc+goV1IqAZQeR1pDB1SbiVzy4JtSluafBo41oboevtbQDCiOLdYXawJU3dh76XR4LVFZHrzaRUmpUZNoqb3rSW9nDCCP2u/OPXSCSZaYcSjSljuery+xTgmVm//rChnCVBtLfYQQHQx2qNcXaR9yUwGi/RHyQSid3GLqwghhLnexfDK+lQz6RMGBkAJ0dL/RTPs8OSbuMw7GeZHqUeGfDtR8ailhml4UywybPf7Xnk5wiaJLfowobyKW73lC/IyAyB0apdVZjIJ/uKyURgu2qUwa0yZ+Yvuf1eOvE5IvWyLbeqJrD2d+lb488bgYf5K71y8wvb5cOjP4ksS+BZ050t0ft23fKbJXtIsH45PeZ06sahIiUe/qhmMj3Wc12DWb6lkwOfpKFf+qlJeDVt7klUn82MiMbg/HmKv34VDMxU3pCoXmO6/zJDs42FU7Nws4GTyeldASqgEWHvNbICi36/NPbeGSoKyO85sR5TXoGVcTAraaaT1P+N8O60JIE4Ww5x9cMCxjJxX25UGZstYGh2cWOEee1bKl6zsQYn9ROmvJ7HXPHissvR/80B1CoSZ+D/OxZfzSHht6rfAORdazG5LBNkMyfaGweZD7sP0k6wlT8dQgEUmsXFJcfXl5b1ELZLtR2gWS3OiRsopKxB8qF21ADn1uQEeRdDPeIiII0fxc6f1pExqhOmxxVo+AwUiywAsK9C1TRDsPlzlMuzGFtP4z3ftBfwyOK6JRc87p4g0gQPZCQenNWaJ+XrhP06Ux0F8jJ8hIeJVEo+5iD6XkYhS7ETWAEp3oxoRho3hh+e7ZCQ+z4+yl6Cx9Tm82RSZmi8vE37twTr5Nu4LX9sgr+Zjz1G2vGToKHhUg60vJDmxBUDNjNaqLT7JM/csPJiwhqevROl/OlScNpkwRVjcsEQuMTHM8ObRjLFMrL+LZkqHOewTy1Cvs++6Jc9V/g0/iA1bn2WaryOZpWASeHF8lzeBOi44ro79PAj5gHKS+c694RdpHu1/gyFqmno2FBqu4GK8XDrwsXfmfZ9wKBdchpR/wTUbpLnGf+Ghk9lXCB5Hw4MHBzilBycHbvqgSACb2+JQSNgwIcQ+1FSMAcERMmuPKtinQjYJuCk7RSuOY/wM3EIetf6ZbTQErIb+dVzjlZvFJO9lXwT5OCSZY52+XYQjf4YsvFClooJI/12CPkxHKSjxZ7ABkfVQcSKGP6xDuQRiT+riareMKl6Avr/6t0kY9zbWSRXeH9YkgD0h7iDDMCkzU9/OqhHSDWk4NNAxu4qJOIQSRkkTf9e5kluqfCZbMtbWUXgz3TgobAvCENjgqEANeqkn5sor8JnwUdn6M1kj/Z9qBfHVziOlW3fV6O+kn/Td7xYjEr2qdCIcGZwam9dVeB65AkVLUGrrMHQ0ytA7CQvO8i4j0aYbdY/x1nce6eTGjnHVwXrttDa6sxQS/j4BNjp/K/Nh7xF4WLUG98wLxD6Z2Mtjx87YInYJXdRp65MK2utItVGm0MahdrfWnyM3Hwiix9sa2MrVogK/KiQBMIOkFO7dI3B/L/5JmjRTqYlQXenfEI0JlxWpoQThEX5l+eHQUW2iA73kAS8EpDSC55cNLaqCl5+GLCwmJlCGEfDAiK6evFh2ZIPHMEySpDST1zhgcearScH2e0lpb44LPNAO2EL+H2KozGHKIr+8YJX/p4Mq6lGAfi0B/khfgzYDjG7dvjeBT18OTC8jfKaSA0IPUAv51NfcC7HkIXTImcj3hnxzcGqHn8tH0YWvdCAdFrv56eN6tLeXe7UHmLb9RzlTeJR2Pzs/QyP339FsyolqPK930xW9ZB0TZsmf8OzMmPm5E647kOXRXzeAw01/aieKCFyh7irq2pa2m9W7/6IWOnG1fu7TL8/0JHpkZ6JW4jfu7gn4s3ZIutXL8vhzkUWFCLloHr/g0dsHONR08Sd5Jt85Dq39+e8jWRGORSuNwTx0Qc64DC82Pc/DVEWAJ9T8awLVsU/MqPusHH+sgaCxpzEqlm/xPMyNVESMPAC/sGydjIsM00oa+xJVJq4P/WJgU9ZGz+KC3pagyay7KTwNl3nTxIOjsPdl0jB5LlwACeGCj12cOsN3nvFWLt8pS50zGEdTMUIQ04U5Dzzz05Ji1zeeV2rers+hmekoe+Gz+A8A/q1AHC9RPaL7p5dr2OAaQE3ZPzleHXoM7aCQ5Uh258AULxowNM0a9nhpAE2RJGL5amFbEZQEa3xCjqvJwbcyBlZop9qqvbM1Y79gvqVaEt1VoOgbaTTo0Hh5kcN7u9H8F/dZEA/4kobimJshG++d6CV/YhD0ImFT5B1T+o+lylFHWiiqAds9WavK8Zk/qQhdVdH7Pr5vwGrsMFcryVHcRvUv1RRnwVJ/3qcJdlMuxIHi/ctSIkfukVxGS8xANqCmtXLmFbYiUyxdYnbUXhbq6uQsNx7pVWoWj6HsC0fZKcjZNo88zVz6fP5BSCzugXU0pRHw78KASNVWCXnVwAZ55JCD6OhdnVRDnU3SuPa/MQo6Ut5u3v4HeIrW8DcyLcpXGPSoe0VWpa1iiMolVkvApbSdRSetFXR728673Jn/4tRN/LT1jhx+3WakPXat2WmQftiIiEKLJcCFdtDfww868IkcVzd2iYKZm86R4CeOrs/NEO/mAu+ez/jQq8tJt330ua5VZe2z4Mzpr/hGT/WkuVT8CsBdcMUeo351INk2tPjD2SCHrEuKPs/FWq+p6RHwQPcDkgZTQreGnK3QqSQHZM6eWQ8+CRgli/GueF1nCEwEYrxn+jcM4Juw+S4gs3Shjs0f+LNNhi3+UHfSeJ5KyijmMa5a4QjCBopJ+XeTc+Cdxjio1J/rkcC3xNq3BdYp4unrONJOIvtGFm30TQVID4Etkj2iw6uST5YP4XQEPvvwOZGJMrPoGpV7MbUr2CMXEqv3ErGxBF8vVYQSJJMpw6qbmN2OjSIRrMvuL7AVv374wTnOJUUFZmTuzRg3pi4QYALnFlzNUXosBUxE/MN/yCL5IsZqC4UkwsAy8MsOLfzMvHb9S26MDjvp+GVdqbJ7M7WgerZMOXi7IIRu5T/CzuE0pJ53vnptsNbz3ftfMlUeFHQY5BM+WJaqHu2vguWNzwKsbsNaNxAc3y4zp+QRPB/frYlyEq68vfiJkdE4rGrEnGKs6sauNi6VsivbyjsPYGrhrBfYy2uM4t6X4XMyANrmsWNIp9KFwLgiR8MswI7Vw+5UdX5sWt8fZ4UvVTTSIJfhsby8aUnyxvj1uBk/vadz9e/Nva4Kudq2VYr2ncrGeEwMPcmk/Mp6jtZ85ii0lejQo5mon7TKV23Fxcjy+e77mqYn/moTbUqM0PlthEKwMlkchRUUAFRZLzG4QtDQv0V9Zn05FNJbx0H08kZrrgB/+4Pz1AljXOragVFsXVWlOm7HCbtbLvpeckAwLsl8xHt9PMVUcuwy4riVSJRtF5FvIKlvP/jiG0Q29XzsaRLKm2dgnVfLrzxSnTtYX7KlBSJ8YalbFEd6Vjiy/euQIwLwee86zdkJMguhuSipesU/Xr7BfLgTATPV38nmeoXyVMugSPKexfAuU4rywdAcOXtZ7EXvqTQGiyz6EHyEQifxM/zPshTyr4I7tZ6xTKhe+dTF60b1siDCOBrKJnScJRYxUbLeUwjjn4DbnwczmEBiqOghS6pJiga3YFTeamrSltQrZXY42kJpLQC2DVCbXan0/g7TCRi2Vua8Pjqe1J5tJFNwvqz6nFLyIxzrECMqWLNr5OVoaE79htlCyrcm5QEWOsJcl1GxI2TbhouHRt/ZdZspJU8iheclR/osufpP1FKwc6wPMMBs0/3we/B3UOULaj8J9TPYbUzAja73YSoJRfK6/QGS34sr6TMmaQfYkeE4VlWOgq4cDEgNZUOkPISdUlGglR/uUgNDSPrefEuokdtvNN1/ZyjJlRfY+/urR0Y4StyLMrXgaS3homE7nwBjCoyctd/BJTdtca5qhMNjAIoAnVBq4Isv0zgvkw2FTHz9KDE78+rPhqDBnCbiOeroN3Yca7nWRwPEj5TaGHTUDBo+3YJN7atleTKfme80e3cfYNtL6q9QFoHVrcc0gzf5fuDyAjoJzV5cJSBwrzL7BWECoZTlP1WPWGr52md34Og2V05sflyrekxwvnOzGqTrE/JZlVN7vm42/bakiqZZBQdOspjik4IkML3YurvC4t/yKfvVs9ccQA+ZaS91lf0yo5aByA9/+FfKkSDU0cK3Ix+220hpLScK0flCmEU74Yw2BhZd4LYETXaj0JLtupvYY3p92o5IyNwqsnq2mHLtdYp8/5W6QkW2k74AjRwpldoH91N6FRfcEFBKsPVvnNen4cCjIN3R3Bn2msmpHY2xMxd5+OxC5XtnWLyz7U3OjznPsROTCRj/sTJ0JCkhDbg/43xfpFmcPcERJRTw1bMxo6jqmtv5cvHpT+W8nuL2MtwM3m4KT/pN7+R6T4UML8lh4IwpNE+0fEQScZFpYsaal2LgmCMP5C58lNBzs8xRQ1P7irWQyl5qSu+N1soz86qSNTh3LQyteXG6J6H10/NrtpI+YfDF5RtivskxewK2avJgXuF4MsIThQAP4YKT2XfH3EE7WhlFhYCdFGwL+cMen63jamyyJrFxpXxihcFa0iHpyLz0gC9AfVqHuCA6Z9GPCwi6WuosXDD/d3Z+EQw8OPR1tEDz6kptZebHHTGULaz70vgCR9h3Xs5eVnRtAmXZxRH7eoeNMZcq7wQgMw6xURaG4iH33AH6QwFpLYX9rvaCUbGfHXzajD8THMdZ6P6zbUJHe1qbYypqcIb9+V1R9gyakPgjZ4k0VB6minewhLHybZf09nahoHWGWuOOq/k5KOy7yxbJmihxqb045ramfyHi4zVbL9v/0WdoFRo1fkOgLc7AJVTei+zjAhnTwBc3dTkVKmmXn+NtWWSd8Y6EVJPIGrg8Chswn3wmhG1PJuTejLcSfPVUWVkTk0BhUrQUfMY6Yawm4PTJMrnax+MylTXWMWVs62nAJvzxCdsJgB7qT0nAciBIW4z2MbAsICfBk0woIkXk+4VtIQiMgJmiQh9KStl8+ycp/G0d1Er+C8A3NX9gBbzh4/Zi2EII9hbQNiX85cApMaiJqvsNhhIZqrh7Pl4x35K3zPAvwKaJZEtqpvHGV2JlRg7sCwCslrze9mrn4iBoNo66RqAmM5crnm7bxqhjlqndpfMcmQh4jEpJx2DBfG/soS84hk+1LQvI1Khdt0NhEhVmYB0FXaRIpvgTW+ecka6dLFhi7ADr6kxY6VbBLOOis4K9HKLcSG+2r0KPNhDDX9QEJTyVRKBv1dpEJ0woxLFbow0KlS1i57XdSlILZsKFCFoYmIJv9IQ/Ve/HGA/wClCBz87wqriQ/43ZTzprdtG70l12TEsfXRqUS3tYuUUp7wJ9+zQK5DRkz01xQi1JODQooOcvC69ULbjC05ywF47MhfyJSm5uDfWP9ve+RWdINN8PjcDTQxWKlYDjdFgNfqjc+AxoCjIuAuVX2+GfN6dhR/5adJp2Md84CbdlBiwuJTIqES15hYpwlzapNIRgNvCZ0LFh+E9ZF3oH6ogYDYwEbBdXK+7IQgWTT0/X16IBAXUaND90N60xNMyy9raiWZMVr0doijxuZLtD2ZBnSK+O/FdvcTV6BYd67n8stPDX9NLI9EA6dMhH5aEkKVBA5bD0YiaKrT+PgmUgYM0j1Z7kPNHzPhtg0YAUaMK3cUO1y1+jDvyDn+nlD0g/pP/a3TAiJWidz3gdOQwLEbWa4M3X6LVtKh6aOl5KxApoaGgum0AYeHPa/GWE7OXoA/OPuQmaveqAtv4ZtEhJsD5p/SdGj5whP+K0uHO0/gUKs7QT3D3jG5rLDOxXSo3i6o/i1tmG0WB0zON30qLAEIL4WAlRiNarvEebDxquWoR6dAwkU8dS7IC3YJJCWMAyt2RJuHpufvhIAy913DVzQIcHoed/Vy8d8eW4d/SFCpRk0MeA1RBK+dAOsd87jIcuQA90x6lmTY/pCxQm3IxjPskjxqtAo9t3aUV6FMM7yM8K9R9J5wUYn8Qsxuih13skfKNDO7H6EnUk5otPNOuMyv9hqbsEFtfj3HvHtD4EOHRx7C2nfvcnFL4//VMkFikvqTaXjByVUyzKI6OWva29oslQISwQx0D9eHCbfR1wZ/SKLSRKyC9hrB080FHVEZsyx0df6YKQQyovWORwboKA31SAiMCt+kc1GdoMYFD88Zmn/Jqpmsn5af56XeuaxqeCGESUcj60105BxALv73uv24+QYx71/Q50W0p5sp2FCwWIqhaFnWzAVQQDAJ65MQ9WOkM11QiG4Z+/KRcC8UetpJ/651NC97QbIxxMq43ItsplE4rs8cvU8JaQGCdojdiIs9wl3ev1Jq237Jg5BictR/FeqmlUzHnfjGAfI2tixkxgoi4QVBj20MeJwVQ2dMorpe7kNyGLbJvG0U4RxB+nb6x1oFbnYGFaj3Qg+zT6ilVql18BSxGwsJT5sgW4lZM+8UpHFbTESKki/v07dinwZQDhdjsHVfHxqpa7z2+5tEjXwdJm7TNESwqh3iYAMnXjMvqx64MjijOiOWZFK5fwnMI5sgDessEkI/KZT2NCVNcv8AvK1GLHkCSArSfWsHDHwHO8bNsORXCLx5A9V8oBm1MWoANANPnfm+MSJ3qUEQ+bZ7LzbzCzs3GLSepQACC5keuR4oWCtf3NRYl2K/sgmBVQIpkMK/qhqxfRV2ySmow04Vfr2RHWZ02CPkzR5it355jjnhuaOoanElK9bRRFACVaYQ1MMWUw9LbaJ4vMf4cUBTdaAU3iGPUeWjTPndFpQ3FilP5yx3TRtjHZcfRxoSIem0/s1ljkoHC/Kw/or3Pxqua6FHrhKDVGbcuBUB1kJiXmTxaVVpBGx+v2gF6VWvPVEHA5ziG5WP9nDgEThnpUmPwPoMb8Zz0KvCQwxil525O6q+usk2RrQ2IvvlTJo1TSzJwaj8oLT556gO8Z0uwN/o71AZYyjxa6C7nyyzomv75jqm9RftZXVMPvEq+TXeI/L0CR9jW7he+gTzrJOuxUmEHs3pqKowtCm2F5ajhc/w4L8l5uBIaC1436Dn8Sy4jDBDbt/VAKzfac3ZNRc+zifYYMIdOJ7MargioGlh0q3rR9Qr8Pkg8sgMo97ad0ryoTQZu0947D7OkK5dQvkLkczPFy5Z/xQmbUHSIKcXEEjWDL8qYG/SUBW93Umi6X62aHvrQIDhqq9LflfmoSQyLq0bAOzaY1YwDVXzAyekng6QRXmY3qu8lLDb/VOQZqlV0RC7UW+Lu92qdACLx6C050FSCeVN47kmyYGXh6tVSthevBTEAvDEa9tEAtqExT3R3ya25+qx+oaujNXiZo5YbXinhzojYVtYTKBrJmsj5aV9zPgIdXO3XXiJ7GQl2EfaW5X9HsmBeSDTc7Qkjvf/I2eEGjK387lCDm3qrUAHNhJ3tOJwvk5wHcfIBBJnyHG7fqa8mQxcLp8ztNxrK69eyMW30HeWy+rajo0dTolPZTfD6GNJR0J/fHebBctSc7kwGV8bXZjdnv0yhcn0wYmqDMwtXa+9srdI7SePtRKIdcSevncLnAgJ3mFmEwUbmYsaM0dcUI7KO5Wrlivz6G01Who2OndOVXCDfZpv5HEsWUYMIjTmkV1iEdDfK9YMKCzxnQoelNEWVuVabQGDPFqOwajdTQc+wuIVno4BeUrLEmSMsYHDo7zkSn6TbCpwLLnG+Cp98FP8gw1yVtINLCeUxR4M1V1MELGN3PVheg8vGM9P8blWJZhGRnZ7SE0IIoi+ohS0NlBSuVeX1oL5liMRdGVHHKDj1sCVw6qsuLkrkyzDhI4rWghHSL3EbczOcsI2s6FtsWEkOGW7gqMFGdnfe7pLUR+/ypPQFZWsWPKsLuabwb75by3tYYsxttIgubfH1b3CmWYxXv2mvoArrXX87Ds5O4I6pcMTl1L9n2sPdSu0R+ZSKeVzqXJAOkmKvqMuP7yuaA9cS/Ep1xyeOh/tzTBqmlxkZV+b3FvAXYBDY/I1cvWjd9yKivpXmgWMGnaHzIB0DBa048ap0zGE5i7usGL/5qt/2WkSsxu5X8ASMjda/BDbZPucZgY1uqjUqsfOOSIY3Q2z6JUh4ACYET1VbYtTUgWnTFc0hsD+ZKFb8tK9EPmbJwR16lJizV49qqyOHh/hQwEVwDyv1DKSnG6eCoOPyoPL2ajb2JGcSH/XMKUbn6fdafvjQ1Lj/muAHPydHD7AYj1CfzlzFEI7edr02pik6qVuUQLJ9N8OdRfF3aYwQqONADUjnhJsQgc1LIiMS7vS3AWCk4KgvTRL3lZ5UVDfn8s4CJWIndL1z5rNzmSRlv7dA9nU1fFduN1XWHg+YkTnRZNUI6pD7gYS22KhnhHktvtypp10B7LInc4HSL2CYaBsewYRb6w44MwzCgkxkMNzPbL2od7u37mymSSV0vBubNWA6bW2EBN1wT9GK12IS/c4fmFC4GwT9+mU++zyfAjqQPgeCI+i6U45lbzA/yAgNplR/Zl21hl9zDgl/Htb1SUpCPFTYoPB+j8CZq5i+Vg1VHpfKtQMZz279qM6Bid9OIg07xiMQ+059cQE6BAgfopENAZ+9lbK1L3Ya2Oqdlub287Sm6HAUx857K/bOmtXSajt7G2XfZN0O9WicphWrYjIuj0O1y4BovAEWC9K20/+IEZBZHnA3dt/sLIGZFo9XJzcZgoEcksaY1Cs+rfO6znak8pJXqt/s1aOQzZIX2UEjHTm+GNahEXxIh2R0+KL35HpcOrHQ+qomZJS+W+JJ0aadtWI90Ej+TDzua17VUe3eX6UAcBwxHInBqeNjOlKBVxKBJoQWbq7WZCpvbPrd1FE1yrjwj5c+metUCmYZEaOIKu8miXk+KAE5BR5mCLJ4W/VD9R1SLQofJ/iMpIBJC8YPhkfZUlReETc9oXA8fdN8FR9YO8migqwQq8WVrF48EgzYdh1wtrmrrU+kRE4SCES4Xt02Pjz6dqnYczGMsc2HleGnKFKFNMdgRPo1Oc0WQN7H5KWTb46Woii70aKwmLUtPdv/B3Rz3wJAGkNBPH8lyfz1evpuGY25wPPsgPPqtemftCL3nOQ3l3yorbnNeJLuCsxc8B4ihNlaV8pV9aJ0jM0kMEiC2W1pZn3pNz8/7ndu4nJz80ZaXK7F3fspd2xaHzxVaY4pUVfp+ZZG5s1hapTsKq51WGPgPfLAp3DBtc5otTLTfEbJV9gTzPb5aidKaLt4iY4REUz7MqegClv1gOOaLyqAGtCsYzqsXYjieOUPS6SYHgGVn/OADt+R74mCcy8NuIw6qeXwQ3uDmG0xODgIDH2I0P2n/rVIDvs0XQ8sLEbXXRNIQZyJvlUICc5UmshGueqH4YFd+mRaA87foluRJ34VtBMyyvVNKHwOsLLJM1gXPk5HM6AxHdkTJjeKWDT58bjV3xkZ9OzP+wwiV5I95aILqtXFcEVr/Wbp9bcGROKtz9KK5aBoqWNLonQpitPHxLkbcvWhSz7GFPtZsXG0OtRReraJNsUwRSYroHi0WxjFJ60rCiBQawqD9t7KTGlrYNOLifYr35NMiw7q1qvSsLTvOEVHMqhnFozCAjJwRVE5eF11hDVma8molV1CSM7EuNKBdxc7yGYnD4OcKR78NQb/bgTm7A2ZpT1p5CQnTLmpXRvuJQCNYKjyyXpQTsLQX9Eqhe3RDImb0750O3gOxlwLZlnxOBJwC1F7uXog8hNqfvHqZG0FAwyeI2Ll79R/x0EqE0AGS16C2BBhAqis0xX2ZwNUGMe84txKFaUOWWOAoOcMXTdgdoY71Xv+vixAz5qHhByhFrFfT27nZ3+qYpqwG5uS1awyabnxXDbm/Z1dSnfQld4n8uaXM7CKjg12pbvGVbT8HoKM/gZvWqMYpnj23ubh77qbvy+QpPZ2WgJUN9qnHQ5m++vgBA9SzRYHAhwSHGhrIVQ6UoeKCfqQbnGhkKN7mPaklTMno9Q7N2idxdJHWF8k28C+qvV+FWVHH0I2Iqa7p09hSXnkb486il7nPSHEg74PyRk9MflVBD2Y+X0MearpsYJojoyQgqAz5/kbTa791Sk0b6kNex+ObqJ9RQuFYGNTAeAa3FRL42L2WvQCc9spyc63QLONoTXUm/vYcYYypnbdPSWjmsY5bA22hOg5OQasgPBQecirWLbb3HnkmUJoXug/lc0HfT8TB33t/iwgYfXpDaTINjQPJf34/HqqSJNDTx5M4YLsFAgTzBeIqBpBLeJaHLRqXYWcMRf16oOr+185R91A0ecNDjjf+JLvuL/WpkL+JbzNOwoXL4OhFvsyu8jpeemeal+rwjreesuR5bolsDJwgnOBi6NNa3kM/Zm56CFh7N7Mlx8X7EXrUNuHGnn0HUAvqsMJR9gpkur0SLs1uYHaaYxBfJU61zT7l8HqL2qY86UZJO6rXIPL4K5Ay6+7Y8Aq33lRSdovRRuvv99BhYRNKd1K3lfFsh3pK/C+nPNFkQXC2+jQ64Ne4fT9rBr7kpX3vANb/hXLRxSaplBuDICmxyO7IWkdw+9JlsqvkEwyu98iqTbPoFMxMefB1pgW3usToeFDu/eESKz+cD5edUjF9MPe1svdNF/8RCWxSIV7IadYNKPQ53IQUWScG4H+M3iGbVLaOLEDzWVzzSLjG3unno1U4ZC2w0FgYq0fVmbrqPgzKPKTmGIY4ocRaX5d2vcqlF2xJG7nfDNT2wekO58foha0xu8Gqjp87tWZeF1COi1dMNBSXpR+/Id5JMGOl7DvKV0fqqa3MpoIPOrndxcVjnFFeANBuoYo4ACnDOyDNuspo0o5/pdFFkZ3fn8SqS9XvXqBq/i0sXUitUlg7exHZg/DLAS/aLplJhj5QP5ElLCyQQOo9CtBuuoj2Z9TJberudr38cQGVC/PmjJ+goL0gdxqSqto48y2s9iQsCUtDHYETOtr+g9/ynHdti7kL1g0UETuy/ifDhDK6ecRhr/XjC/tEwogiyXhl/8RtANPHed5GkkgY+V0b0bOQhuHDxIAgnG5vyEqQ7yZiMpbrguQIrdamSvbfWbfn5hfAeasd0E1uL6Yjybza8QyBbSpBoSrFTKwoFPSuS28pymsJJ3Wuycud6P6AA49fPJXU/4jW2pEZjOUcbhFJ5oRLpn5PPDQcSKr0gR5zruRyhf/lRN/4FV7VNISFk2PYEVOSat6bim3J851RCz6xJz65HrTq9V3qhMxCUV+EE0F8xUs3sugUF4dpGxMr/DI9cZHpLHmPa5Km/JrLf016jU54szDW3k605PzpsXasYG1dXMMpG23M/R8EST8daNtHQjWqM1YNKG+IiGRW0OioiMHXvkKzEpl+QII7EynsjiuAH2xXsJS+hbmBljySzgqMZxVc/7QVXpCMhozYV/Xth03okmz/osza1Q1bBQuIWdmxFIZT5mrAGCPcMFdF8OKmHx695oY5+B/JuVs8Vfh7oCnhnBSDVO4YV3hVmEJOLpJC/Cgi1JJ7+9mBJ44rCJ9gxFhHSlXtHfytRTi9gQGrPP+CiqeSkVETqrriFA0/jSPB1QZrLDZV29rGunOjDEmnQEDCgb5Mx47JZKhGNA+nULu8uK+AA9H6j3hGRFXEeioDmLKp5/q94dSj1XqulqzMCXv797OOoDNVwfIBta91zzd1H1bmOiMsulgTAmkk+h0JBn/0A3OlLz1Xwx4S+moo/x6PmVUwwskwEIA4lxCu/jzQrRKma/VMmsWWnz6PJzuX54FYhiaSa/eoN8RKEIY+Qhnv2cnELdWjTShcdzw4kdNGkxeguPh+R48SB7QYUlEVsc21WN1S6yLxXcZZrOpbQlIZYj2jn2RbNpmXzxiv4INDXmnd1uUpBhwGdjQZgv35KNF6bzmoBjNxdtQSo14Def91eDOnuRcS+G0qyAgaSaii1SyTvU03oS7el9oqAcI1yLOo+tC7HR2DteRFCKA3AJWS6HpjiAep0nC9366NtyR/+L6bUEwa4POfdf4RCtfZ/C+7dnFIA0/I6YZNKu5ltmpW4WQ56VQ1daqT83aoinOFK4Ezg0/c0B54kXOfSarpkMlOeOCfzpFk2AtKw83nG/cZQ2CaiKycUU+UbVI0JmQwXFGbDpkOhrkE1XH1NDkWz5APXd8BQjx7QbU76x3gP+mZcNPn2SQGc1Z8IdtddOZ5wuUVnDThIC8K0DEv4Fiel7K6jO0vANSalf04C3yAO19RMQOWGaAsjLOx+Zko1vf9qtKGB1sSd7lmUpfmDS0aBtkUiC2hDPDFuhbFoEyFrjNiGXZKEsN8TbqeyOtyAoqMXR0Cj5Qgt8x2UsdJIWfFitKzQ4OiNaga0X3fxwdIw/UCHcdaraC7QbsLaSInO+6X3LBbBjVFGYxRXS1Rqi+4N04DsG+28ZFNGGBmTMDb+qD0bpYuoFp3oRCuez7ExuGaDlqqmfuPNIPBJiFzNwUf6eYs0MEvpwAwGfd/1HQrOtZXV5hxBRfC6Br5RTk9e26goLbFbuOqlBLNejKp5F7rFEmZ6z9L+5br6HzdQyr1HRuq4pBtGE05vbizyiE2nGxVdh0aiAb4cs7yB9tWJ9luGuE2laKnn7pGvs55hJtfckJKNpe8vdJeI3CNukUtuNfKr2btd7KU/S7mhxXq3UW+C6xKnmuDh0JSYQwfEoRQ+Mo9Or5OzV9TgJ6wEmo7ZNFaIVKFNA9nejxfui1hg/7tPe5sXktktg/QkjdhYVFyrwnQUl5WCus/4HecqzCbT9rG7YuPeS327MUeelTe87I4ZVp+Ys+Lia6wMNh4kASv0QjgfwHNqFzYuEbSzgHHvxPsy0W0dA5Aa57FOpNu+8S/DwT7+Hrn2crmEx1XBNqL2GLhfNpG5V/NJxIMbX7Nyu2qWa5XnS0CIdYdFXxhOl0Fp+PV70uC50n52f3UZ2EfvAmRdpQskfoERdE7sD9jZeSAFMYb/mKNwnbQFRfRMlR7cr9uuZNykHo8JIPy4/ojNSz9JsVJvoEka2HCp8t1RHLRDvRDl1kyczj+Vj1dAZ6v+Gw/JJK87Hwn+Q+y+YQjNC8vKS+BMVUVEcwRdI5+9FrVNCNESTI4gy9fLkcu3gZUBxceRaJWQU9489wlkiBGvm4dPzZEmltcfv6yefNheObE7NcQD1o6Um1MYsHV0iemaXKbtAYJk5TK9/ZkF8k9z5fOHE0qXWWnUmWT4jFYuJ/so3+v+62HWefDNFtU1UqHBc33IsG4USmAxnL5dQ/d3uG0dSYQWNMlYV8b93Twx29cZUOWDdF3zG5NmyqKm+XaN0Xpk6Kiy7byOjBQHIzJ3zi7m3kaofhDt9i09HB1b8BKQC1R7lZ3/brU8u4Afv645ZhTUXtG2YWAX0lda92escL46KFFhnfOzq/G1dGMQIq+ul7G3tNRUMTrsQDgIe1O3Wo7KjW0L/NxEojXthx5hxzB87AHdKBKf1qBy1DywmWjnYMGR932QlaRV1aw3ohWJVOIboKiDnd90AAAEEQgAAsoZ1oC9JxrHWDD4HsIKathZ+BN7fB4skcQJyhQnb+BSroDZ4WLkjxpCe/8+PNaX/p4hsWw4JhWmDhJLFKqYkbthu6i03+w9L6V5uUFyI+NrvmpSTyHFINAV+GZHRZhEUpkApjY4h9ftHJMkHonk0AJjXC3WEg8pFUoHFAQSI2/oXL5QptdlmHhx80a4tRPu35ruNrL7qLTPJ6pMYuarI965CS+Nzskyq/sbYy7E0osX2TkUJRXXsiUoVP7p/XFIFJQVVakE7Qzhqt2Rk71oLWdD6D0JaLSZDPFUuixLFwiRXtXzjLLrtWxcU1LoGXU3HqH5SJLEzjxR5nGvgt0mYVBUrYMKFhuOcWSITfVR1OuDTKRSSWmqLCsWAync4AUUM2x2g97NcethGFK0zmXUpHlutqVzjPgicZ/JkXMtQD7rPbBKwUapNbKwn0Lbb6SZm1cAo1+M9mXXBWJHMtHT0/PtMnbxR0XiY9A2IeEoeFEVrMOMH4KgLO8WDohJAY5ISK19Z3jy4U+46TNnAqJwMlbjK1bRDMbgTA0+x6ZqrxxpP0F9H5YRIhH3zJCn1IXU5LHxKQLErdyZPmfTDKXHANpgSzIxhzoW/k1fX8P3Jdf4wcVHX3UspK2nN1nvG47be8uhh7/EFDw0PMcY3LIj7xSCVBRwfdMHZAou0DD18MRVgtBFR/Bu6ouXgObIcGhLqEkGQnYdRXgekmRoXhpYOqcgdEi3ToLvmf/diQjFkp+UprDUDqnZdm57/efddlcb6/w7PtHC2fYdvGH5iiap44DJC6vDlTdod5jOFViVG1puN+qL9aXqRepbXTFw3nmIyoqaR+PjRuX1nEERLhijUFmNr6Fc8mTVS+z/+wXeyh+clhKdHYYG218KkGiwsZLUe9/DmUQN9RyuwbDOQVVuMwmQDOToLw4vjjgv47vvs+wegYVzo3/tjyZsz0BmzPCcjFi52RKhfjjOoelbcMx4kDykdrE0Ul+qB7QM8OUzuH8pLzCGEZBGXWF1fg/Y1F3L26IuuGiBNPd7w7oKwhD9AQa5DESUunlIeBWwUiOAQZuTXCW+05zavSEwGTdbF6cbyydnZdDDI5+usCnmpoqVtOc7/RhDTFonD55QBi/NrWfFCKgzEPj/FY7o8s5v47OcH2dXzWpNcpRY5iWnjbSKeFaScbJSbKXxVbXs9AG7DQLJ+/g8oZMB1yMJbsNP2dKjBHFzuoceCPLHzV7ptIK3N/ybL40leVAVtdzklx6D0HjIWE4pSzxil37qDZWoV2o24K682jeEKsd/5VoXLj2SBfYaQCAYr8icsc+ErW6FvudlnN2Izo98rMWkINwIk1B4HOQcHmHP+uTCy7TjN4gHNwPITfJaBrd+fVEqudEINzlXDFFVMH/DZPxB0cnmQ2FufQwKzSuHEl54Ly35OgJkSeU/4PSzyM8LZqIwlE4H+9Ie4L361kehPxrkuUacLXaYj/1gLzFGlvbRmTJKCXlAogahSgFYX1QtRhDk516ZuNJneXHB/qpMHlM0E8UtE1i+jrS7ipTgBHTN0mNXSGtH0XoKjrS3k9qlmUvrr220Eag6Zmwr/p2sbeKkR2NqIHY4Cr4kEIUTCSu3cRuu8haN8gTEie4jyNa0h3BhEEewGq4wpBDulObtC3zdD/DoHUEyjhPm9/3S4Z9zcJn2ET6UidTbXttxwkPbb5ok3AAc7DR8WrLiqP4HHG9ITSNAD282SMV+r5PK9cVIPCbPxN6lMkR4rjbd9m4288EiTIZLcN75UBvSq12wRBL+3WKI2QvIDp++3QpWaqzI3so3w57jzT5yY/Gyy3pWBbDiaKOCE3M3JqFCZCFJgPIGhJxPn7ravPjToy1ncImNLnVcGBGg7U07mLUIjl0MWIoXHoWVJu1rzsa/KihsIOZnc9CNYS9KCQ/EVo4RJVdgL47DHjoJkTg28c1aT2G7828FnxIXnV2NM8zOIy6vyrytbD6y9KKv50dFYpCJ2bOL8L9zcCJUURAo3P60ufqOz6PkOla/0SZ/06tUKs/ctDiP7dRFgCcg2qPPf9UyWp9iaoEcdq2jYW0B4E4KGs+SPVU2Cl54D0jLFKCBaf1DyHpUeX3OOP1h0FJnBIXx0ZiVotd/+H6vwFb6/7s6zH9uUpYm+CV64nbbuHSUh2O3tGH92Uwmtp86h283gyeCe0VouNeyUfnwAREW5C+ss7EoYL6YiiA8m0YIQE8/1W7B+f1AuolkvviWazOpOtsPD1+0UihCsp/qClCIuOMF8wenDHi0+AxBwoJYnuHYCHB001kC/e0O5sHhMBUBi+UDXS+TvHcA0loIH1H3A0lWerirAf6Gf2MqdHbA8J2QOvcjLeRtvj6L4tZlIDXY9ceK8z+SJ4xRDQmR5dvJxLna5+7LX+qqy9Uehw76yFbYdd1Q+nhR93TcAVi8Z7l0HJ1h3C3F0j/mfYG3o4X7uMDHuOJGf+aHtThLO3M61J7GavoNJrzpc3Jq7KY4mk9wL4XbZ9ysKpTpv0y+1QWgGblblIslea4viCnQv2RUM3X++58TCUgpXnyT84smbLAcqUNvgM27I5O5bIKdLGXAX7hjYYuRYIzlMp05LOiLPn0sEpPvfKz82D5WZb7amPdRNAbiF3+Q8v7jtOZ3zmrEoz2tAXY6XSQgOtzse9ZTkBSrkU8XFFf+J2O1FdUlIYhK6BJld7SXjasO0ULpaHSXs4JaTmWHRlDI6gjVPg9Uadhafj5qlFOjrNik+Ht+yKp+hvITz4LVKUyRuH/iUeXuHj82ZIZsNuE8iuAlQ1nVdNm1p9htX4yH4cc5AHw9JP8sNGWn2mxKK4Nx2JVYTUv+pol29cMAKVMAKyhzOu02SRdKfEuChpcAxACsxS72Rc4w+KOLGylUrsL+n83wJ3NIw2ru0y1n42BHPk0078p7DVSHUZ3XhccmftKUOvuDoQ+cgf0hB67rStw5Hy+UVk3HgK/n7XHid1RbNCR2O2T+jBe2McWoQ2rsizqzG88lsBsOfqsKyIjMb3lTs/yNNiPkvtOFZaMNeQoklD6lS0ddVmpjzV7JEDUAots27tqS2vJGRK+UEzNz1c40pfTHDdvgexbM06gDOPQUX4muv0BWacllkqfkPthAEHqIhLYzv0z0yPTffkZH52yWiRjsMx6l1/SuzNqieGy0sxb9BXz4+6wphjla62kPjyb/JTnQoqrrJe5WA7SV7WIqBlnQ/lWnQyvFRT2MiJLupGBE1XGiddc+ALtw99tbMz2VkmAB1JAiys+NeTnmJuahwbVzPwWr/H0R1J2fsZmqWSApS3kY9HVZzFmvhcKB8vbU7pMKXnHGrj0gWM1//rNC9tpnJHK314rHCgxQn3Cxg9d+o3GmM/kk2u0iwrGC+jSKuzyjBtTblMlkjdqKADi5L3r24JadBHcEjIsEJiIyXpq76/+74yaPkSfmkLj4gXuxQ5o8ZY3xa85d+3XRNkLAve/Ix6gLgdeT/cfvJZ3nkvWVK9v8wozPzIieD2pisI4ESvL3kT6Ich9iDdV4ehBtba+uEQeXiD9RIgmKk1b80iO2YJVpOsqv3UZ2ChLKY2AN5fDDIGFApNZ+5i3//B5R/iUjbIr5yX8ywuFU/CKIRc4Kvr4X772yq4/7GKcg6H+vzx7eNDKf78Ip6rjV/7Q+OB3V/vxIP6ttmcwChwIZ3RKYga7AJX+GzhJwZTDAqSOvbOXdldm2rBMG3Y675EhEbytUcM/bLBrIMXWn7dLMBxG2yJAeuQMDtJrKhXc/fPjX1wQ8Bp0Z6sag/N0rOBf+y5wuP7cOMGLiyFK5NpZJpj0+1jnFCb+4yD4534fHSUk0pc9tuRxQUfzqje+JSwWM2/TKZV+ML2R3OlJq6SwszsDwRljf667u7YqmM17VSXrqzJhuCW2EzRNIWiO/uBDxOnBBlF/SAjCEOPgNOjnxfcW0+DgRj2+SfhIjy9BZzKSK/aPOxN4awDakvd6usa05irF8NaSpgBS38Y9V0fbKV3AoiQIEYCq33L1ZzRRSk8B4QM1fBf7fnGaXmQnymzm3i2gxiK8RLnXdD1E6R0Muu9fjdBI7uF20xeiHoH87+gX2lyOPGvjZKTuJ7a/fNTj6lu7lmsvpj8/bGzp9ir+9XXKBW6/TS41UgyNhMyp3h/aUCnJE0hydCuKbZOVfkHl9DokpmPmJA4pik2IMGKu/KrRYFESJJ34OJcPSmygL4AAJlFNcdyDa7ibOu6ksW/gOKeDw9KbPVT7iPUxa3imIhkwgFJPp5p13lF4p6jz5X7FzKUmUe1vfxHnwMtSlGbA+x9Q5lJdp9OsvXnSZWct8mP/bGSMC2kbDJO/E93pB8aflHm5bxdZhuFagHJIE7e3ffl5sIQ/24221W07d8emUs/BIldFhX7hZBKgugEv/Nplux/y3TkZYYoKjXCwPrSOOxjFVN1Lh0mJ15Bawoy16PGkMQcKaezo2yoDdomEwjD3QC6CnE5tG67xC7uNmOPu72sviY5Ape7eHqVJpelTFlHgyUeeN1PsjaoJVazZ5CoPNZINTHMyXQFkw1weziIreoltTORZ3DUG9CQpGWsNffUcRMu7mV9rGx/ZkrkXFxP/JrmLDf7UEXfad7Z5zDpXUQcIunYXXUJtXL0IjlJmYWkbi7lzvOpLTUVVP5lDkI0HL16KL71fBF8huRrySaWX7+Fu2Q6Csf9FU/pqcxvTYMT0nNGKv+XMrZyi7l0L+mTuquNubvfCeITLatrk0jabB4rShxhVvkwz4vdA3AE6tHG7ZtDtCEerAuZi/JpjkFIbXCC9Ip5Yxk5VP4u8i8r81zfjqQncjD1CFI6NmGY4ruvoAAI4DsafRpGKL7nGdw+1dZPQgbYovTrsi9qjuptJNXeaQdrdNqMlHoPM90XyWQ1OzZ2HvjC2hQf1RDh8J/zjUAASkGlmHla5fs7KHZbWM7T2yqYm2lXyRCplf/mk01p+tEaDBZmUmKBUbClvznAs5uZ4AO+2otcoY51Zdl9PJnRYLJ0qJmRHFATKM9oCPa9rH7BJ+3xIK4eZJdr9lKQc5JL3JlQmtIdR9XGhYBPxuXcZ2A7sBJSpcAjffRg/J+NhCOvADpG28M+L3nAXoCZgt9RUWKkt3fuDzLM368+JJe2yFFBSPsZ0TPCR/sOFrA21wXU6ilwhoRBNOsAhH5GLr7oX0giY17PDOfb63+rC0AhAte6MXbx5Zo1bFxpFYKSpjCGXLRTFhQRXpE5/NFil4lonocwprJv8l29csG254hAXiYQ2/qlxZdsaHxZ/1dUMzuuAXQ4+am2v3bXhQflz7Kq19a2pIdqPK+Oaso/mjFHFFNmAm/fxLdt/qdEgeUB6C4+uxw69NehYqTbTft9mx9ijNHKpLtuR873piiq/XSQ4nNY3QCh/iPKW6U0gbOmlI5V4CMO0HkHLd7qz4I+wqaSMqpARwa+wOiT0pn6RDFyw6zsDVQa5bRQ2eQnFxzhIk4YAwL7+LlP0BwPGKLjQLoXRVVBQeXbhnrJWdxhFzwvlLhy2dip4MNYgGdx0YR0kEEnIA7mSHg5R5IEV26Tjf++xprkB9BT9KkE2A8QF7Mt41spjjDBR/N1LDPWwtKYjNsDj/1QSArr6EtN6fccNTEHbhLkI8H+GJMlYaTJkkGUBS14YYXQSAAWWq7MgNYG2fI+VF2jq4If6R0/ANlNSC2QSV9EMAVoNQqXjbqtzG29dUiQj4MIbi2fagU6ncxa06vxF855KO+1Qcc7UfEOvwHi189xKHVZ10t1TJCEK9OD6vCjiC+colXSBzs7C8Qc1CchJxvWsciZCXbeDt4l8KlqgfdJR0vLSd9F7Y51ZT5PXSklmVnAqE0TdSD1CBBVpQUPoj5E88TQATRTLzgdfgKDNUC0QVMJZUyq8gdRUF1/3RTeuMeFW1HHlFQM0aNWFKFsDpMYfK2WhGJYzAHdWupPJwa+EMmJdPcJrRZAphF6IQ1dV2i1ASKCIiAD38uTuTL93zqxNTaLOdvmMZISgIfq02dhJKzSgLChQOQ0xv13BTeKJbwikVUwkwswxGu7ButcRLrEe+92X00FDoZCrvWXOGY4X0i78c0tjkm0ZSj9oKTuZUFCR/yvia6/HJ8KLrtjEqUfdNsIeom1AazvwSjY5olR4YDG/0Cr0RBhEdPqylmKpqIzBqWh5VxJFS5YYZtTX41SYdKee6gnkN1ucmiRny2rLSYyhMtwLybWjr7WMXB06BjtmDRZUrT4kedFWxSC5zmOOPpdy5+C8CeUu7g6WZHBXdfk4m8IMPgsuYNdPEJU8ClAD4lf2hJtHPtoy6OzcQTQn6qccAs+Uc/FOD7/fMvKxk0jaCs2CCK3O1zSPbdWxdHF/KMIU2uwQ8zdZviwTpXPKvzH5cNRPldcRuwLfcQ+bV3p6ak+c9MEuVDGHWYLXWtMY2c1HEemS6S5vw8v424WgraPrNCW8rRJhWiWHa4VJ/Ja/pFWGDORBLUap66SfuX6UlaLu76ddkThQzHvLgpFuYo7doN6sD/BVuHmVLOImhBlonOBwCXG8cYNcn6J+ThS5l2cTizmDyqfeCEOAXad2oZsmPWDaxevb8zVHfO2TdSs2qUKe5Q6j3hSLJqzUlRAHz4fBIdnn3hTrP+vDR68muqOwonOjw7gkC6CsZyPzNom/IfdkMv9OxlauhjvU35pmreew92Xy0xphg2KsWi3B5lncEkKXt9/dmJzpjTDTF42U8IPVCXRpLXvBSPCehT11WOY8Hh7Qhs4glzSfMNXAII4xCjzlmho8Ryu1dla/dPagu4TJ4SdciEmATQZMRCkzhC6R1y3jVZJYRe4UVHlqXJTGLtL3fAYbbAyKWhrcgdK3te326197Kniplltwkk3i397ncHSNjAWX26yy3hNDdOsxnMc3e6muE8AzZBl2bbsN2OkOrJ9IvT/Lm4a+gpdi1Xg+nbQO2yFDr69nV1g9lzXPfLXwnPszaHzpZZ3CLNASwhz/ygIpPe9NSJVvfNBuFfoDdA4vw3+prShS5bHZ+Ka9Ev9sdhGxUQGWB8Lcg4HkT3JHFzcIKrCNXhBQy/Z0Uwz1xKbopEHgzUitVhm7BfGLN7y8p9/mnJhpQH33z++9+0rTj8oF/VJIw5/w8fkW6fWFKRkXWRtFnD1k557FQy25c+1jtAv//bwjsyakJNjlXDfHIPkhYpkxGOSqW37p5kUS6MWu/+V/fW8v0u3DOuwXD0kvsqQpxMZ4oy/b0pt2PbP6lxdm2ioQoWGdvbtk8Af8PgutMF/Hi5CsqEhYSzkf+gfe+I9ihxaJ/DFj5OeWxoeuZRsN5AdPxc9nTxWibBEkLWbqzY/119a81Unt1HGdNvL8zGmSWG4Nz2v7BKZ1DX1yTx4ppsAS7cdVk3cqCoeqa4yDplpAFVEugA2YsEErD6uOu6E9NmX9b0oXBeYdJ4yGfILyK4lNoissk/fbxIg8SiPl/huczqcyo82FK0K2lHBTg+EN2oat+4kI/6Jien+2NDy4VRVitY++YjUoN+Ty1mZXbA7aHbBKCWiBMxBeRsu77+shR63EKKe0j5OM6dNPElgaupKKVoUHk7Rn2ECYmC0AnWkWW7oqYIn8z0pPQeWBK9DKofYTY/r4MgftMlQrtI31uZnlkYeAu8lN8j0aHEu+4rqvU+ZwxyGYgxXg/jGdMwtnUlOBXpYbq5Os5vvltuUVKmOwbAfVFhYrxyrBKxl02rVCJq3OW249bu9FbqpPiAl3FGkyXIi69z7LPjj2HdFznBag0Lgn5WdR4K1afGrTLLAIIe0qt9OpilDJz45ygGRfzxjkQp5IZTijwRdnjcZ0u5SZh84OP2Ksk7JJo3Nzx/+7vB3Oorp6QFQzPD6CTBPaYBbXif1mrFbrgd1zypq7BmqxswbcYf9ULO/nlvPwXpxkQx1sTh9znhWdGkast5DQqiEAvGyJa7IgQESU19g1j/nImenj8sbGEHhJPMPgqMDPiOTDwYiJisGTbMMMxKSZW9RSm3ZB7oP0ku5VwYJuRdX/jzYPHjnmfMOEDpIU7IINqGqjOknKMvcftQ5KWG+p60r4EOwE89euOjkqoLSNE7Gm0TnsBg/NeHxQ6CamAfoxJl3UVFmgEDK7OlppxuTtlY7Pn5r8EZmSbunDjPwXDCw9fQBi4cII1Ky09NWhWqD4camHFPNPqlnqSh19hFYGv56x+lt47a+6iMqQbylr6V4u50LRZvjlrK8mlZMbqpUySDDK2/MUoOitJ10iiKMuQ34TXi2wYDYcdJwL3jSdc3zt9zPjxXCTv8aGSq3xLtR/8NrYihvYXeBnevLhIcmc27S9JsPqj4zOtIwD0SuYjWowc85cpc+5aGTprdVWxy2KCyp9tYfqW1IQUMSA54SRuNH6BGiny5DWLj+8+gcSWQd5c3RkYvJzuo+c3lnFNcgECPfFHgL9cNvQiyAunK7kYWA5xds3qfpNtwzOjFAdqEAS0qyQBPo3dJ8UQ8Di1t42KpCvz2+uRC5JYy8XujZPgEoYoykVfK2TqdJUk93lbOz+C13nZZgCHDTJV7oLGm8+sEpzhZm9aVC/tUpbWYZbiLol6nY4Uq2hARu24Iq/wsSQ4uswXMDw6xL2P5OP6o2f/1ZYpIyDKsr5KFLes0RVNZ2FJSeP0c6G6mDJGfaKXrlC2Cm3JkBq3G+TwbWhdRB3v3+xiYGwxxitfcO/JLSGqSEDx2wetgCZj5EtCPPcRcaJRcezjO+a02KmFFi56Oqp4sM/RsV6LDOFnpw1pRjswZlSRd/AW7aF/7br3H3V72Csj6tPyU7bGKw9+FrPPYyH7YkF6h5Wkzkl7SUsoYWangeLH3a1f/JuX3fRL9sYp6E6+7a46yiTc1eJ2kFDRPVDRsXD/bKad60QLwE9bxQvs6r4b1EOzfk7W8nV+JpOV0ZSuIuYT0m7nhNGGnDj8OQXubYvTZ0QV4Kt84bHLDOU97DDYuf+no6pZqoKZNcB9WUX2CheyZJqHoWchwiQRHl4QV+jubfFCOMD70w65JjXdavne2CfwiMrWpaqUWGlKbS0ZdQdQ71li+lqXhPV4ZtNN22McMCH7A7FCdO7iTiu2u61ujtjFGD6f/AIm4JbXhi9KHRWh9K+sTc16p6hV9Ya/WoAi1vd0VnU4CLHnzLGYNJrPGg8aHyvF60Aq9aRjh6Tcyr2Jwt3DFtNTxrXhewhPyl9G1G2QKvTgjo8OqM2Z1d7oS66bS0BqMjOeIbUNzdejHpNPJpw3NNGZokaPVFhkjBpgGqK2a1SyYARBBpC2iwVvleEGoNdYxa/elXuM16AZZueyAEC1PpSkjX+AHXAw+ZsSjwnMXv+DWU1ocTtWx3Qwf2Cheyp32Q5P5r6rd9dyo7yvS6pQrwL7YXH3skAvWf8qLtJYd/MSINoqsq4EV+STKcR3VMCEjGtFSe7DT3JJ3/CLsb7M527DPQ/bpRBFsoZ3p7DuIWga0TqaNDZu4lXK9JIIqg8kY5C1eYF6tw/xJNDMSXDaUWmYcxKSCVzGHzbVfsjJluLUzEO24po/Sxmx6DoGPBHR6yIWjnsE8cgD0jhvz/NfEQH0gaav7dzthrakHRlUdO7G2ZB+rPQYlfj8WdiY9s99jzJG+9cF7SlGsraqybyiy4cZqkh2BHTHy8PXklqsIcranlu4/MyTDp9l+WV5qiBDmnewbSacBbYlVGwQOUFyNAMF5gJmPtmOankju2JI3QD3w4qcxkP/i++W0uBeDIhqbzfQY1BfeWg96gPkO6Tl4zQYNAcH4Mko1IgvFR+3XUxOReCOWSWh4B4kfnlCMYBO4Hz03xrRXARqrwrZhBIBiMMWndB4ATJnsD1ZyRbVnG8canePQdIJ+Ami8jPJlXZNcoSB19V0kyA6qFvsDiaSp9ueWhvR5EGpum/62n8LAn/dvLBjMX5SQUk/vY/3ae8zBCkplNAgALvpsTGF+/u/vce7GXz7eU1mnps/8LbPSKk2SBmSMIX+L+H3RhYEVfD53FT/VaRaNctVXu3deH5B0U6BpJkVA328NUchPuZKSMSS1ioZo9KI0+Rk+03Ma6O0ILKYtde+X4lNuefc+aW4D3ft9vqh8MPNZ80tJbj5Sl9O405JV/vY8bZUps1pPOCXfzMmsUW027KiMwVf2Lzy/W5DUCay9AEGN/81f2l74mK6khgtE4y/GbsgXcbotif/KDMt6Lb7beR0+JVv8d+xRibcPBrb2tOIAKJbE8RF2oYhxA+XN8OI0uR/E2aNlUZXz6cfzCfT250MuRSQ7Opeoo1pzs77G/vz/lV/+e1ojUoJKfvtgccUvP7JfgClV0NFUinFeJzUy3jW2natI7kDaeQvqtspGhK+uA46T7g11rmW0vJHYEUPp6PnSdN6z9qU1ulXXQ/C7+au021MNLFb7y7WUz6K00CDhcvV6WlPhOd8WQJOB6z+eitOt4LpcH2sQl6NwWtLJP0Q7lizCO0cb8j3h/YbNsEjv/mreyEwPK//NBLfW/HAiUbSSv65FxldAuz3lLKok2TdO2z5VVaHZP/IffLQ9B4ztK+nM35A+pDmh1A5gCO3OufNiI/9KNL9ICRG9gj/3S3Ck5185c+15kkSex4RWzOQwXLcwH75URKWEz15ioBVRQT/mMYfGLkdInwqnmTovU/nP5V+sl5qfDr6bSUMWSsHOfUtwh2c3Hu8Eykf0ZA4KRD4S6vAyUBrYwJuwITW2jDXx+1vnFqV84gPlvBuSc8g3E6YeuN6ugeHIqrjBH+Sq37uis04hlPL7F6ToSBpp5Hb7syKz0/o0Hv1R/jw603weFifD5U3fe28ek0WaXqQ8mMsEZP+6kkX0hOAS5L47ZAS91Tl6vccb/RCkkQwv+qoTSvaKoJv0aveEGNi7DsfuZP/0LUO/MT/O1SjapnfBS+19Djdh2g2ilSkYB8s4prA9N4E7jaCpaJFBcyvJKlT9vjnuc04aUNOn8S3w8+UWLirF8ju1S0TJvgVG98CHPo0Il+6OddQOMl8cTvf9lKG+lAQyUFn+bmQTTZRveHEzVggeSo5my6NK7r4bIRUYTa/Yflhdpbe7jlKAatT8NPlZ4XZor4/4ulJxfdab+nPCesfDDjUYL6sv+M2XUj2WUvZ3MyrfgzUUfkTrMVV8gimU9DGyqjpp/8x6KfkMbESVPH5OEVde4NgOaX+06Li53HwPs/hyvv4FafMPVMeZZ2yiU01fRzrAoOIGCW5YRHEO4AQBa6dK1Tqe8574KmX9xE18x5+MlWqQnknrRG3aRhZophq6uncuHB4jMNmtI9MCY/HRIGRvGTo8ATOOuhWW67jRQ5DVpKqd4DpGN13UCkxaR7eaqqWmMmIjOjz5ANX0m2iOQ+4C4eZOyUtMwLxw4iQbCm5BHjr7UaLZGIbF8MKbGi2tngoMsWC73tXkezw8IlWDHrksl1djfSV5GaMT2T5m/MwaAKu5ChY3M/yLSZr4eQE3vYqt38hDxtA2cloUOo20UJqo81y7w/Sw4uxsvkbXBa+ki9Aj9Zf8hmOD0dXY3gIsw7stzoz4oXWBEiBtp5Qf76Uzw7OUD1dSuF9ssVZHrnMfJfG2dHKYnVo5h4QSjK6MTMjChqhLhR/+1XIqOnrRgXbcKcmRvabwFAPocLePdrKz2YjvKscEjs+05irhgw+x/eAb/SaM4w1K/hCGRgIInWhzk7T6NEp+Bd9lHTRWUBwvafmTfDmhzN2sNjADe41u+T3OZDbP1F+EQycTp5RloYNECuFH6op+UPP7jgtzoF6DshEUUfmLb0v7IczRtUPe/YVOvj9bxL0cbj7WRyx5YC0tUwg/wjkyYiSqtPCRKon1LyEoDV56lGJMEgCFHO4sI8gJZ/P6qmOFsnAER8zBLLQtIn6lWu1oZIC1XjNn9oQgVN10D7qsireufwlmAYx680KZV324Js63guddg/KQcoJt7zV68Oen0TIfPAB0NQeeKCN1e+TS44uawUZXUhVzJJtxrNciotssmEuoy4xMOD8Kfj6yntUtv1J8KchuNL46mpRuKMUr1tIggmZ+/49Omcw48h/4H+JUdG00+1k4buNZkfOjlR3lLI71f4s69eU6sohE8LB6+mWSfH5BzekMbftlZnNKm3PM+Ck9G8ced/Um/B1PvN4x7BULhhExrQCPHz8W9CeWyuBfdVkUj3YEioaCV24FCPe8eOlaXS5SIgCDBHVD7eIQhKXcvK/fbJ8pYV0ztJyFiRogibF0w2NKoY9VtWJNIf+ExulidGkH7lfmZFPCGpLtZRD49fF3hrOeHM8+Fr60ATOgOut1jT5lfTbIYuDs2xg2sjnwESs+E5Sf3afTZYrbPXdy6qKwCe+aCSQtMWVleDCLz+5gMUQP9/nSTOvo4V6JeMz+17RQ822ccNK00VpXuKXRTXR2lMzzYJ9Fs72tw9aO3ghX8G+gEu+JNffma4lwVeHMBzqZc4LT4MYMgrfCUZXdI2VQO9WV/RDxyg93szoKINBhwmFdx0mzvx41dfll/kTvrPt0KQGZXBEX2StDKhEJzgxEHqW7nwy3rAdztaWhiCPpgTfyO06i3DhHXS0CG/IB17g3c9eGD/THGRJcwAyrau+XGnTliYjyVaw+aJzS3qVtgCw9HVqb7HoJCRaWwu+JgWBG+/OfdlaPJvW/F/8I5MeZdNgZmJdZ8DvufMZ3tbaz/S5CrwZuO+wsuxfZUM2MjyRyKVDrAtCncjEXtThY0zypIQ0jLf9+o8OkmiAI4SaNs+uCz8K2kYYTxfM3KBAoz/GqdkNsRjPri+MyksS5edlZHorV+v0K8BNkXV2Nvt8Sgsmm/cog7yFy0xpgsZV7gIqpZ/WerW5+SPQx4XvWtpHbmHM4351db7xgnwhui2eJS3qNsD60Ot4/Rvc0GrPR2uObuYrXUFnz1o4HuxkxIXy0XhiTG08X/gGZjGIhmOf3BP2cCSqrM7RFNLXRoocfXVFBF3fQkHCUpKi++SWbDoOVYli9xtBbcNOFKWr7gfA9tX1t1lGw0/ijaznE+imKB5Z9dRQV8BdQIal1tPo+SW3GETOL3FOvRrEZO14a/uq21NwHhFNWV+beRENA94GbAWI15PHuHAFckZnt9A64JnLldCY0t2Ef+0NKRGWBiKkZa0Rp3dNwvR1/lqy5ERKElJ9x1PYoYEo1pZv4M+IypXWzSLrFcYvE4r1lr+jed/ycujcBfUTlu8ULayxcyT5w53UW8Ywhk78zO60EyFJJpFxBKWH5s2Nk5dL0HmaupV9icteNecyTAsgvBmNtLkfXsAxS5J8arekjLKkqaMg+IXWPyILuAa7xktLvRrbMOijea6HCcUoUKXxAuK+LRSOdH6sET1nt/2oFubkGj1Wtw+bDnxHwuhX2fyxXm+JKtDXsUSfYhOMXBdp+HN9S/m5vgRH9iuK9dfdAXIEfj2psL5fDvrrAPDL1UfD6pw/mosB72ms+efhu6ityFwrOBmaJ4kx5jNwfxTL5+Nse3lpGFlzkTocBq3lHb4mp//tD2Jqo6CLuyYYJgyu7DendGrg/4iyPEDK6Jeurp5Ke0GXRS5dx8mS0BSBZyT8bpydxf2O0RfpvBr4RHHKc8iwQmznKbsqJc60RL7SoOBh7sk2gYoMZKACcabD5XX4a1b/0GMnrxPJiF176/Pk3exbK5YJypWSOu1ILc3IKUgryXx4unMU44r6Yz/8FDOTFjmyeq83Nd1PlhMa8WNZK4cceSlWRLZb/ZD5Q8hs+Pb5fUDy+ISZ5FvcTMXf1msu+kpsl4PComBWwqg//5kJ1OO25f/m4kxr5vtnrK5B/PL9S2M2u9ZMImPdDOb1O39x2IeytaZq0UayNROorJbInXs8yZtJ4D0zHhZ8z7VWYLw5VC9rVVGLpHKrxNOKKP70FLCry4L554NGAR0GpIVHbGqKVuN66Dqx8N6KSxQznWK5DBEX0qPqUuYW7MfAHO2EC68gWjUliRSaB8mEYtcpbEY0EZ4wTz9hAsIDOxxYWpd9p0VzOO2s8JydbPMgWuPRLCNmTdf0Oxm73HtgxE/Iz0JovDuka6sOE3UOWwffnVaEE41przAlEYOAn6ZU+hokvYToM0l8+mIOVsaKlVefYt+4fEgOicGa2YZ/YQZxrLvWwTB0QxFEb7WZ1TvmQ5qmuGP4nMML+TIH2Zo1rgv/g4RjsVlvwrojDV91LKRkCUzxM9cAP99kI/r1/tgWyF3X4MEk7Zuf49I91HvcnlWu04vtipjH5bAyV7fIb/+JFrkmxOdSFt/U1BYjCtnGsitTu+Qg3U2q7eKbvAY24Htuhzzri3c8bgftcbz5VnTw2yDcYyLryUeMmhqIDRNX+McFqOB0txarYtAPkww/hhAn5Qi7fDe4kg6ytL6Zor2mACb5Y5GspGz1BsLCFIW/M8DHG9kN681uAjnbR1JqWiTlRnDNuF+fdIHG05Bv47wvJfwDGr+fGZIQoBHtzZbHLEscalrhIrfCKNnk5JhD6jA4PNjo/IeYOUb1orjqbCjtBE/4OTl8yes5aFfhevxl8XRUVryObEKjIwjYectRLA7/F7zjTDjMDydHLJR69uH5TmsB94ac2wUwvOzHyR24X2Nm5rcVBRCNN2f8I3cQt9spnYQBtWQRMFW0lowTmkqswhgR8jeUzfcnEIeP+tUC7qB6Ht1EHtQptb+5ZGbuHnQTiuv6XOuvFR8v01xqeJi08iNlxqKMEmdaKq4h9F31UlGQtIco1G8891FmFZmzOLrIPA/fdlTPDE1oZUUD+gPSBhx2YGhT/te7UypK5pc8jI5p5/g3edjgpAVE6C62sKMs3wTRHtxNIAw4v2234VgAewlLeeFb8pkla7ad1ELnVb3qK+vE4rf4QawElsGOKxZ3EDKaQyJgwZZiFtWJb4TyRX6A3swOwzUdqxVVyz0ChGnMf6UswAkO2FpLeuaqs7i2PrajAbg6XqKGmCBKXZDQnRKoAkKDVpFMH139jTbh+GcIGD+g0pjMd512w/wdeG5rIL7h/p/6bJQUa+OiOypvY0dt6LcdvNfz/3fFzkN3nL5Ny/7m327C4JRKgsmETA4xCbtV53ZNl73jz37TgetTkEj4D+Gxykl9B6Z+70ACf36bMRebHHKnBKjTabXVWHp2e0HOwROeQzHozj5inBwZQnIIocUWj38DFVgqaCOTA/7ndwSuPJI4Qgs8SUaEBr+lrEMJCFX46ctmPPssmIvcbA27B5MallYhPnkxd5bkgfvvzOyU4P82Qj4bKT9s3gcCvzRvRPt7DJ0aV/dNs36gfkMFKb9I7jcq3C44OXiJdC+5DF9MQjNQcaq9SvrbjwFC+C3ve7jY4HfKApc3NAla3RCssdFEn9vP77Wve9LqqOnG5Qm5FF8u553Qpm3deYvd9d5fhzOdfiSpQOXygrdEEZLP3fJjN6sjrw0vlwGedhn8tzB9htqK6v8pKho0RYYPcRvFvsXOlMe8Jg2+Pzaj5ecNzm6P8S8GUgH9ZxeGrd3bALmsYI7DKBHu5JWfBup/82jsNtiBNLnspC/h5Sb35/Aru/5aPVZ24Yqjq3UIZQmzqsDc6SYMGhrTCt6rOILmEb05Rap1+rVuUE6/Dg0DmLJttFylJwpxFkquHyZPdwS2Kbr0RUeF+wbH40PlNjpq6WpJu+16JfDe2p2+3lrQRNEDXPuTgFxBY/DhUO26OK2ccwjIEas4BByntya/kDlX12HmccltnM45r3yzIw0sZdv1r1d68UH9pa0aqyX2YPbs2vsdrKJtqwpKeeeMuph29hixstXlBWbyig4qr61Ds163Q4/c+xTc8jYsd+tFPmK3SCJagO7lFo/ozh4FBbsZT/hXHBhxEmUmxpeSsK7qsAkQ3EKqdfEh2Dx6ZfzR8a/B/ZWjj0VOYH/2gg/lxOQg+6oFDFKfC7y44UjANQ/7bTQCYNV79PCluCEsaoFbMPPUvN6lsYh4UEO6bWj7JQyiB+UdYOue88TrFehFxvCqAMFG1pVMxFWgBNjPBhjktYdzvRHwk+5Yv2+mHgWwiJQnU/YjWL/lSPrkrDKlpvS407VjvxknQTFezpnLdrhCkFjm8EOky/5E1XcNdVrnqHAzXz/Qwiw77Dc/ljWR/khmslRiHc2UknQMyczLHYLq6qezpgSTVb69LxPswmtXEAwglRxo9ciwSRq/Q8PeW3e00iUdgttu2Y5Z/NBRRIs6uGOUICHX48zc+kXg313yrCjdI834V1LwR1MKQ2Krep4wnI6YhN4d7ToZe/JyJCjmk48WsDj1qnyy5aWURSbRSw55qv3zBQr4LOQGTxjtMq0XLNMVEs5d8hiLdmjYm7AgoHs2HXMXsdnyQSEBsYvmi+hjCwc0vF5ykKySfY+GhifwAyo2kvtEVIUlrwl5EOUe3EBfHLcL03/Awy5ggbWs55FX7Ad/iOzFQsvMQHyEpF2GKDiaPQfhLMhQhPhIDcpEXoNL8a4rc8xTzrHA5oMMLCk5yqw6MaAIVoKjob212+EnawpG8ZfxVuSmGU/9k0p7l9iShd9lC2uf1Touw0BHwWG/bAQUcpDEHTyTRziOToez3Zmqcb8McYy/dBJp7n4yo3qyrJN23Wvu9MXXgmIro6shIGUDJvKW+tfjrr2VTpP2z4MiZUlkD7sakN9qPX7pn6M6cNcnymeseRdOP8HRfKp1+XNd/n2ySPHLkEmvGKIbFZpCcS+O2yJzztPCZf4IsX+Tz/3KYDYgQZUDx3p83+US8zBwW0/wRcSUNdgy+1t+L6TF1jxITqN2h8Lfndg5ZX074dd++9Mj3UQX6JVEvmlzzGrz07npCB/4dQDpxjlNXXVmp33PO4NgdbYZmiGURWeBs53CM9v/6E99tkh7fQkDto36BtHY4IQHvM7F1x5UaNfa2MNa+sr+KuUwx8zl98vFCFy5lTqNXL/++tEytFHALJjdol+rIw0PiE5gOCQl28cH/3w/si+E84vb3YclrvgJzXYfV45cASfBCtT0nnhu8LCT7iO2HY82ZhZAbIFOyHG7mJ98HWukHk7xg4LfYWr2r+BQ0w/CAjF2WFipJvdh4RSG7bE72n3CN2tVyhXR+i1lpT85JMZSdHe/3V7PpdbXckOF3TxaUfdCjHdLhzPm5Hu+aoC4WOeBSSbYwz0EXV9bvGsNYc+5WeGWS8ONu6r5SVv74KIABmD30844XHeToTjIUcaQvZAx+EQ6U2vjyOfdFa4mPHOqJaVDkf6TXzsbd68DO5mWf29pBfzviYjbZOE18GvsdqLKJIXb5WsAcBBD2HpW+eJS//ulM/+IXYv8nocuBuOVeduuyr5f1ygZp2E9cjl5y1qM5u2I0fJQYWB5GH8OxP6AGZVFLgbX+8/+r/8IvHUqrVmOidrbJxqsTLad6XWbEvCF1KQEyVi2cWMHl8vpAGmk9SEcqGX/h73dru719/XyjWnZYb6nC8lXcFsZ3BmsRR/qfW0G5WSkrmuxitnuuD+8cao9RUx+9EYkU8Z1yRe2wSRuzQduk/WmR+Ejrs0fh6eFk3cbOj2uqh/fEUbpNeFHYTOU0EJIwFfNzMf3g+AVbg0Z+oVUDN/cSqqUp2Uarw1jZ9duYt3Yj9t5L/GfT+QKPKwbEMBZZtBoKP+L/nq5QY5Ox6wsfJqPIu6OPzDeD4l6uXLxHYodQ7IS4h7cFKTAPHY7GU1BfDjkyzAJt13GCM0W9jpYzILYo6Nwqoee3ZsZZHOvDIf/5XjE3HEIUvB6yqzgO2I5oIlsJE13u3syRzwTYQzQdrtjfAT8yN9K8I8JZ2Qpn10ifUCRsmzY9qb5BKZuEKoex/S1cgQGaRm9NqWQhTFzuDdmqu7qQdYeiAcONs+1RnGX2m/7d7LjYSRgnRxKDyylcJzK5jNMXtnotrATAEN1L39oKcmdlRoE/hwmVT4FR9+AQKMzxOqmy15LxFTyjnVB4jz0ExdkteKdd0FZOS+hGlvKhbRoevJDsI1bf1UUYBbuZcL7iBWYUwASUzo2En59MTAEfthd61HRlxvDFs5vDY2ZRz5YmpxME5mQShp3dxMFGxOZ/U4VYCyg5ZwjYECeuIVLqyb669VytIrFUvcTGzgBRRUl26eL7yePI+1V9px3yJPmDCqNOocqIyHf59mHyGzkgofYzYLqQq4yt2hFcKkXTrogH++5S/7CGldw3XNXr1jan2ivzKj3V3/DhAOynM4X+sJ3m5ndKHbzLkqKGt30S0u+pZUCIi2GwItg1LgkKA4zya8LFKKBWSPGYzcjWexr/ZCEJ0FMYHn3ilRQTVAT3t44jmxEhGCzOa4p3QZ3OkTFSgOggpYHYhPjl07nCgsM1lNqXv5mXi1CpVfnIdkBQ3ENHUOtjvXB8cd+EH0lDxS/6JA8IhdkiSb1RoP4adznGAMnamHWwdqDs6zM3HzKWAcZozcy6tAG2RAYVCKy/uhTXaWDLuoYeF1iklyTzZJP8KwfVbGWIQM3aQE++Z5/EuD9FXauk1yWwpauY+KAtUd6pw8vmhSAFijn8CmrJui8/k3Z+NrDo1WDEFRI9F1QCU5K2G0hcWgwTS4gAu7//PdRB94M/RgoiQpBbM9BRkGXgru7HEM1ClETZgiF7dnrlw5Q0wh2uLWf6uf+3Bvj7C+LyQTBhLm/ZsoLJkFzGhMVCb98GoYaWURv9VZa6AvhORR20PTpsyi8T5pJMhZlmZhm/6beyOgd1VRyjlYrfA7TBgV4J9y5iQECzwEsNEQU+bXo/Fh5Z5GPfqG0MFT72PAufgA9ndTlj733aRsFZU98Qd06TJSGGpPIf+Q0XGl/QYYooDJ2TgxwRkP1Mgy6SeFDDwjG7Kdl90mSVRCllMc5Ie2mUtdPJz8y+ZMKXnIRzgXYaCo5fo0ypfWPRcjZzhmUZa16aSTzXsF5AAqQF5TQ3Q0DefDO36T8/bmOjYhT/AD3BO5ep5ypEV/s9xnG81I7mytHiMdV/6+9dYUeh9nQhi+31rmrwHhtcD/A9JBvJV1BHNSUqJbfG2LxPyRH/SxNd8e/eJQ+mFHddoJKYWQpnoxxYyDJnQa2plJbZVNhcn5kgUr7BCJJwsmtPQsfaejaRXYrJQ6Y3BgD5OENsN+wcIe5e9fleVk9zMhfiu0l3GY5v05OYKV1M7Qq+hM1tefH15ACuRBkfXLiMuhh/4ElDmQ6gl+6tyZXvIpqTCB7jVLNKGVV/wIT1H6WnrrlocMW+BqjWQFMLvjKn2FzBVNkuZWjK2PhpApSBtiXMIlB8Grj6JSzgIKF//eJ+jlt6ZebF+/nhCBGiR1r0Ilo2vdtDSL3r2Ep28i+kNCVumMNvbCbbG0bxdW2V5tZjAcKbEKXAIWow1BZ1rTr+R0QcOYkA1goTrpD+iXELRwauGq7KZxT+fc+l0jH7A21sbrkO2/qFfkD33z8dP5UOSuxdFTruJAcQyxYNf/CqIcGL+LDj1vZNT76LvHUedXLt7mSLd71QzBGbY+aLjyaerxmqk9/uV8vi/Liei8zggcoTIcK6UITxwdPL8ldUahfZeZ03aT9wcTgDNYsZayJ8GsQ3w07S4KDF4S39+4tmVsY0hE207QMGWpdhV6mQ0kA6iEYOHZ6Yv9nExWbgufTmB+qDJYdzr+Oa+aPRva0jUNER4UeYCYKZAEwxwcCx//ifSfrCF2J0ytdweBYQLUZxTB6p8CwLZNDrzAwJZsTKQvuCqJ9zQOaENeKrNhHPPfZ44XW8UCwHyaCS0mPOr9D6vRmYPhWoiiuHNIltGQE5GMS8e8OGMGktXZQ44ROnwlOic81ca4N0dyGJy8NHv6kDpVbndxGclmwYHCV6W8mZUuCUop7MJZJVLquk27EA1DvmveXrmJ9p0ph5i0yleMe1bdS2GDj5ZC0fbq+GpOUdl2PSpDmBab1AS/WURQMaHvUWwNSWryi44iOfR+gWTK3DIqjYw9+ChrtFd+97hNC1ZEKYF/MI3Jo6rdN/QO3OWsGhqPRQW7zXq/kvTxCvNNBZvkP4imXexhOiVMZbU+QKGpLjnYyLLLhzJPszwU5nsKK+2OnB0KEI85ZvWLprpanjAd3M1z3xBUu6C5jQ0cUGIi1xPFN7JcglmUO1sj3tWZXBShE1Ib8W1zVnLt5OmPFmJpDBvHobqquYdHYv2WgFhl0AoEaEmjp8/hrcT1DRp4BL8Xlvfi8W/z04+1oycRYy5cdlzocztcfEWYOive3Q4/EzPVfovz85xgGBgI/hc8WKhN3M//wo4iCQ13HnsGhb7dGUwDhPRMMrrbOS22XwMrqGx/DQm6L+i5ojoeZ9905+2/rrP8bDj7SCuAyy8GKPGMMy36FPFwT2Sf0ZuPRALuuBhNVZ9x5TyIeyIzeiDEssWsvnIDXZuutg00z8LXC+19DvNqvMfyHBWupqH1aJHPvS8UQ03copL4/XZNL4zm/HwGMbzqSafjKyykds9itPYY85CkBmSOwY3pZ9KaCbDdpWZUfNeTMKcpxjqG93H0AYi1+dTMs1WHU4DHvTHljUWB9SaR/xzXJPFtf7JehIztablntAbD2h/Kgcv7G04Dyu0J2nf1kFJUlIdR25ZYxHePDx1MFSIg2cXhqesQxHbjm2GJSv6XhhEEK3YaqI9N7s6yqXiuF28hmsP8f5pOR9ARx6MUZfKCrLeT8h5TTi+nBRx0diYS6x9AZQbJXWXn28GqplR70wwYDRHSVRvO/1WSy+Cnm2rAQNpCsw2nJAMPCixbl+BPbuD2L6MkhuMcPcogT2BuIAQVPeaYCS6cMgLG+QjDK3HI4t6/BfRFMdTtKYMUbVDuQExfO/97+lq0oc/GsjBrR502l7PNnFLRj0MB7sQwgHtSh+z3fUnoa53wEjxPOT6g55a84D6goX4Gy4T+XSa0+0Sx9p3f9q4bTHY3TIBaTPmMQDgwmiSJuPOjhdoVtg9U8Yg0u4VhCA3nCg2L5bWTJ61X/Y9Qnbi+JwKNJuxSuAEopPs2ozl59FaiLZCvggxTH30U0kTezV5UA20i9LlK2mOE6gIZNfnf5zmiliwFx9481V+fRMF/odNwbbLMWubOMHTg4sMDTG239dlv1iUbC31QSUe8LoAF9NCUxQtae+mdXovhvY3xa3ufT56/Skobp0lbTSs2jgXSNNojZwTgQLpqguoDY7KvFkBsI+fhdGUlwzzgjAqX93g63qTpTItXgkeWJnyh3wjc+ig+OHC1GBMYcpX7QfmY1Wd8Ufiu3jQAhCk90CMMqUkAnckmTMiHBQlPc7qXO/WYQ3lf6hkHo8NM28BgoVGtzzp3vokL4ly0fwF5E8rRVH2ZmfrqQIcIE43J7LfqLrCJmahaVRbOMuIJIoZ40remKAIobJ/FdGMqsQXoWsbSu1UcRvfLIVT+g1yiKSI+VzAFt0fV3xwfgkOXdmC9z/4iKpUjdrxCrQRrCrThdrM/1YdgXW5LkaIbnFn7D0XWWRN8r1m6L5PeruJYLDgt6WgMYQs0e3inc2QwOKo43kxl/X1BPeQwF9POS/v2IiM1oh1/s5z2FuyldYPraR0spkVTymyEmgHBupw5QT1QjoCKUXJw5sDTDjZiUe4UiFAAAA=="
  25 |     }
  26 |    },
  27 |    "cell_type": "markdown",
  28 |    "id": "c0ed7a1e",
  29 |    "metadata": {
  30 |     "papermill": {
  31 |      "duration": 0.025707,
  32 |      "end_time": "2022-03-26T06:50:57.749564",
  33 |      "exception": false,
  34 |      "start_time": "2022-03-26T06:50:57.723857",
  35 |      "status": "completed"
  36 |     },
  37 |     "tags": []
  38 |    },
  39 |    "source": [
  40 |     "![1.webp](attachment:4e2133b3-854c-4bd8-a15b-ab4fb52f9471.webp)"
  41 |    ]
  42 |   },
  43 |   {
  44 |    "cell_type": "code",
  45 |    "execution_count": 1,
  46 |    "id": "c6f046fe",
  47 |    "metadata": {
  48 |     "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
  49 |     "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
  50 |     "execution": {
  51 |      "iopub.execute_input": "2022-03-26T06:50:57.807009Z",
  52 |      "iopub.status.busy": "2022-03-26T06:50:57.805158Z",
  53 |      "iopub.status.idle": "2022-03-26T06:50:59.371187Z",
  54 |      "shell.execute_reply": "2022-03-26T06:50:59.371747Z",
  55 |      "shell.execute_reply.started": "2022-03-26T06:30:57.944652Z"
  56 |     },
  57 |     "papermill": {
  58 |      "duration": 1.596809,
  59 |      "end_time": "2022-03-26T06:50:59.372048",
  60 |      "exception": false,
  61 |      "start_time": "2022-03-26T06:50:57.775239",
  62 |      "status": "completed"
  63 |     },
  64 |     "tags": []
  65 |    },
  66 |    "outputs": [
  67 |     {
  68 |      "name": "stdout",
  69 |      "output_type": "stream",
  70 |      "text": [
  71 |       "/kaggle/input/shark-tank-india-dataset/Shark Tank India Dataset.csv\n"
  72 |      ]
  73 |     }
  74 |    ],
  75 |    "source": [
  76 |     "import numpy as np \n",
  77 |     "import pandas as pd \n",
  78 |     "import matplotlib.pyplot as plt\n",
  79 |     "import plotly.express as px\n",
  80 |     "\n",
  81 |     "\n",
  82 |     "import os\n",
  83 |     "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
  84 |     "    for filename in filenames:\n",
  85 |     "        print(os.path.join(dirname, filename))\n"
  86 |    ]
  87 |   },
  88 |   {
  89 |    "cell_type": "code",
  90 |    "execution_count": 2,
  91 |    "id": "daad32eb",
  92 |    "metadata": {
  93 |     "execution": {
  94 |      "iopub.execute_input": "2022-03-26T06:50:59.428272Z",
  95 |      "iopub.status.busy": "2022-03-26T06:50:59.427278Z",
  96 |      "iopub.status.idle": "2022-03-26T06:50:59.477125Z",
  97 |      "shell.execute_reply": "2022-03-26T06:50:59.476529Z",
  98 |      "shell.execute_reply.started": "2022-03-26T06:30:59.479819Z"
  99 |     },
 100 |     "papermill": {
 101 |      "duration": 0.079025,
 102 |      "end_time": "2022-03-26T06:50:59.477272",
 103 |      "exception": false,
 104 |      "start_time": "2022-03-26T06:50:59.398247",
 105 |      "status": "completed"
 106 |     },
 107 |     "tags": []
 108 |    },
 109 |    "outputs": [
 110 |     {
 111 |      "data": {
 112 |       "text/html": [
 113 |        "<div>\n",
 114 |        "<style scoped>\n",
 115 |        "    .dataframe tbody tr th:only-of-type {\n",
 116 |        "        vertical-align: middle;\n",
 117 |        "    }\n",
 118 |        "\n",
 119 |        "    .dataframe tbody tr th {\n",
 120 |        "        vertical-align: top;\n",
 121 |        "    }\n",
 122 |        "\n",
 123 |        "    .dataframe thead th {\n",
 124 |        "        text-align: right;\n",
 125 |        "    }\n",
 126 |        "</style>\n",
 127 |        "<table border=\"1\" class=\"dataframe\">\n",
 128 |        "  <thead>\n",
 129 |        "    <tr style=\"text-align: right;\">\n",
 130 |        "      <th></th>\n",
 131 |        "      <th>episode_number</th>\n",
 132 |        "      <th>pitch_number</th>\n",
 133 |        "      <th>brand_name</th>\n",
 134 |        "      <th>idea</th>\n",
 135 |        "      <th>deal</th>\n",
 136 |        "      <th>pitcher_ask_amount</th>\n",
 137 |        "      <th>ask_equity</th>\n",
 138 |        "      <th>ask_valuation</th>\n",
 139 |        "      <th>deal_amount</th>\n",
 140 |        "      <th>deal_equity</th>\n",
 141 |        "      <th>...</th>\n",
 142 |        "      <th>ashneer_deal</th>\n",
 143 |        "      <th>anupam_deal</th>\n",
 144 |        "      <th>aman_deal</th>\n",
 145 |        "      <th>namita_deal</th>\n",
 146 |        "      <th>vineeta_deal</th>\n",
 147 |        "      <th>peyush_deal</th>\n",
 148 |        "      <th>ghazal_deal</th>\n",
 149 |        "      <th>total_sharks_invested</th>\n",
 150 |        "      <th>amount_per_shark</th>\n",
 151 |        "      <th>equity_per_shark</th>\n",
 152 |        "    </tr>\n",
 153 |        "  </thead>\n",
 154 |        "  <tbody>\n",
 155 |        "    <tr>\n",
 156 |        "      <th>0</th>\n",
 157 |        "      <td>1</td>\n",
 158 |        "      <td>1</td>\n",
 159 |        "      <td>BluePine Industries</td>\n",
 160 |        "      <td>Frozen Momos</td>\n",
 161 |        "      <td>1</td>\n",
 162 |        "      <td>50.0</td>\n",
 163 |        "      <td>5.0</td>\n",
 164 |        "      <td>1000.00</td>\n",
 165 |        "      <td>75.0</td>\n",
 166 |        "      <td>16.00</td>\n",
 167 |        "      <td>...</td>\n",
 168 |        "      <td>1</td>\n",
 169 |        "      <td>0</td>\n",
 170 |        "      <td>1</td>\n",
 171 |        "      <td>0</td>\n",
 172 |        "      <td>1</td>\n",
 173 |        "      <td>0</td>\n",
 174 |        "      <td>0</td>\n",
 175 |        "      <td>3</td>\n",
 176 |        "      <td>25.0</td>\n",
 177 |        "      <td>5.333333</td>\n",
 178 |        "    </tr>\n",
 179 |        "    <tr>\n",
 180 |        "      <th>1</th>\n",
 181 |        "      <td>1</td>\n",
 182 |        "      <td>2</td>\n",
 183 |        "      <td>Booz scooters</td>\n",
 184 |        "      <td>Renting e-bike for mobility in private spaces</td>\n",
 185 |        "      <td>1</td>\n",
 186 |        "      <td>40.0</td>\n",
 187 |        "      <td>15.0</td>\n",
 188 |        "      <td>266.67</td>\n",
 189 |        "      <td>40.0</td>\n",
 190 |        "      <td>50.00</td>\n",
 191 |        "      <td>...</td>\n",
 192 |        "      <td>1</td>\n",
 193 |        "      <td>0</td>\n",
 194 |        "      <td>0</td>\n",
 195 |        "      <td>0</td>\n",
 196 |        "      <td>1</td>\n",
 197 |        "      <td>0</td>\n",
 198 |        "      <td>0</td>\n",
 199 |        "      <td>2</td>\n",
 200 |        "      <td>20.0</td>\n",
 201 |        "      <td>25.000000</td>\n",
 202 |        "    </tr>\n",
 203 |        "    <tr>\n",
 204 |        "      <th>2</th>\n",
 205 |        "      <td>1</td>\n",
 206 |        "      <td>3</td>\n",
 207 |        "      <td>Heart up my Sleeves</td>\n",
 208 |        "      <td>Detachable Sleeves</td>\n",
 209 |        "      <td>1</td>\n",
 210 |        "      <td>25.0</td>\n",
 211 |        "      <td>10.0</td>\n",
 212 |        "      <td>250.00</td>\n",
 213 |        "      <td>25.0</td>\n",
 214 |        "      <td>30.00</td>\n",
 215 |        "      <td>...</td>\n",
 216 |        "      <td>0</td>\n",
 217 |        "      <td>1</td>\n",
 218 |        "      <td>0</td>\n",
 219 |        "      <td>0</td>\n",
 220 |        "      <td>1</td>\n",
 221 |        "      <td>0</td>\n",
 222 |        "      <td>0</td>\n",
 223 |        "      <td>2</td>\n",
 224 |        "      <td>12.5</td>\n",
 225 |        "      <td>15.000000</td>\n",
 226 |        "    </tr>\n",
 227 |        "    <tr>\n",
 228 |        "      <th>3</th>\n",
 229 |        "      <td>2</td>\n",
 230 |        "      <td>4</td>\n",
 231 |        "      <td>Tagz Foods</td>\n",
 232 |        "      <td>Healthy Potato Chips</td>\n",
 233 |        "      <td>1</td>\n",
 234 |        "      <td>70.0</td>\n",
 235 |        "      <td>1.0</td>\n",
 236 |        "      <td>7000.00</td>\n",
 237 |        "      <td>70.0</td>\n",
 238 |        "      <td>2.75</td>\n",
 239 |        "      <td>...</td>\n",
 240 |        "      <td>1</td>\n",
 241 |        "      <td>0</td>\n",
 242 |        "      <td>0</td>\n",
 243 |        "      <td>0</td>\n",
 244 |        "      <td>0</td>\n",
 245 |        "      <td>0</td>\n",
 246 |        "      <td>0</td>\n",
 247 |        "      <td>1</td>\n",
 248 |        "      <td>70.0</td>\n",
 249 |        "      <td>2.750000</td>\n",
 250 |        "    </tr>\n",
 251 |        "    <tr>\n",
 252 |        "      <th>4</th>\n",
 253 |        "      <td>2</td>\n",
 254 |        "      <td>5</td>\n",
 255 |        "      <td>Head and Heart</td>\n",
 256 |        "      <td>Brain Development Course</td>\n",
 257 |        "      <td>0</td>\n",
 258 |        "      <td>50.0</td>\n",
 259 |        "      <td>5.0</td>\n",
 260 |        "      <td>1000.00</td>\n",
 261 |        "      <td>0.0</td>\n",
 262 |        "      <td>0.00</td>\n",
 263 |        "      <td>...</td>\n",
 264 |        "      <td>0</td>\n",
 265 |        "      <td>0</td>\n",
 266 |        "      <td>0</td>\n",
 267 |        "      <td>0</td>\n",
 268 |        "      <td>0</td>\n",
 269 |        "      <td>0</td>\n",
 270 |        "      <td>0</td>\n",
 271 |        "      <td>0</td>\n",
 272 |        "      <td>0.0</td>\n",
 273 |        "      <td>0.000000</td>\n",
 274 |        "    </tr>\n",
 275 |        "  </tbody>\n",
 276 |        "</table>\n",
 277 |        "<p>5 rows × 28 columns</p>\n",
 278 |        "</div>"
 279 |       ],
 280 |       "text/plain": [
 281 |        "   episode_number  pitch_number           brand_name  \\\n",
 282 |        "0               1             1  BluePine Industries   \n",
 283 |        "1               1             2        Booz scooters   \n",
 284 |        "2               1             3  Heart up my Sleeves   \n",
 285 |        "3               2             4           Tagz Foods   \n",
 286 |        "4               2             5       Head and Heart   \n",
 287 |        "\n",
 288 |        "                                            idea  deal  pitcher_ask_amount  \\\n",
 289 |        "0                                   Frozen Momos     1                50.0   \n",
 290 |        "1  Renting e-bike for mobility in private spaces     1                40.0   \n",
 291 |        "2                             Detachable Sleeves     1                25.0   \n",
 292 |        "3                           Healthy Potato Chips     1                70.0   \n",
 293 |        "4                       Brain Development Course     0                50.0   \n",
 294 |        "\n",
 295 |        "   ask_equity  ask_valuation  deal_amount  deal_equity  ...  ashneer_deal  \\\n",
 296 |        "0         5.0        1000.00         75.0        16.00  ...             1   \n",
 297 |        "1        15.0         266.67         40.0        50.00  ...             1   \n",
 298 |        "2        10.0         250.00         25.0        30.00  ...             0   \n",
 299 |        "3         1.0        7000.00         70.0         2.75  ...             1   \n",
 300 |        "4         5.0        1000.00          0.0         0.00  ...             0   \n",
 301 |        "\n",
 302 |        "   anupam_deal  aman_deal  namita_deal  vineeta_deal  peyush_deal  \\\n",
 303 |        "0            0          1            0             1            0   \n",
 304 |        "1            0          0            0             1            0   \n",
 305 |        "2            1          0            0             1            0   \n",
 306 |        "3            0          0            0             0            0   \n",
 307 |        "4            0          0            0             0            0   \n",
 308 |        "\n",
 309 |        "   ghazal_deal  total_sharks_invested  amount_per_shark  equity_per_shark  \n",
 310 |        "0            0                      3              25.0          5.333333  \n",
 311 |        "1            0                      2              20.0         25.000000  \n",
 312 |        "2            0                      2              12.5         15.000000  \n",
 313 |        "3            0                      1              70.0          2.750000  \n",
 314 |        "4            0                      0               0.0          0.000000  \n",
 315 |        "\n",
 316 |        "[5 rows x 28 columns]"
 317 |       ]
 318 |      },
 319 |      "execution_count": 2,
 320 |      "metadata": {},
 321 |      "output_type": "execute_result"
 322 |     }
 323 |    ],
 324 |    "source": [
 325 |     "df=pd.read_csv('../input/shark-tank-india-dataset/Shark Tank India Dataset.csv')\n",
 326 |     "df.head()"
 327 |    ]
 328 |   },
 329 |   {
 330 |    "cell_type": "code",
 331 |    "execution_count": 3,
 332 |    "id": "76cd8fef",
 333 |    "metadata": {
 334 |     "execution": {
 335 |      "iopub.execute_input": "2022-03-26T06:50:59.537207Z",
 336 |      "iopub.status.busy": "2022-03-26T06:50:59.536527Z",
 337 |      "iopub.status.idle": "2022-03-26T06:50:59.539137Z",
 338 |      "shell.execute_reply": "2022-03-26T06:50:59.539628Z",
 339 |      "shell.execute_reply.started": "2022-03-26T06:30:59.533367Z"
 340 |     },
 341 |     "papermill": {
 342 |      "duration": 0.035518,
 343 |      "end_time": "2022-03-26T06:50:59.539807",
 344 |      "exception": false,
 345 |      "start_time": "2022-03-26T06:50:59.504289",
 346 |      "status": "completed"
 347 |     },
 348 |     "tags": []
 349 |    },
 350 |    "outputs": [
 351 |     {
 352 |      "data": {
 353 |       "text/plain": [
 354 |        "(117, 28)"
 355 |       ]
 356 |      },
 357 |      "execution_count": 3,
 358 |      "metadata": {},
 359 |      "output_type": "execute_result"
 360 |     }
 361 |    ],
 362 |    "source": [
 363 |     "df.shape"
 364 |    ]
 365 |   },
 366 |   {
 367 |    "cell_type": "code",
 368 |    "execution_count": 4,
 369 |    "id": "ec2b7cad",
 370 |    "metadata": {
 371 |     "execution": {
 372 |      "iopub.execute_input": "2022-03-26T06:50:59.597450Z",
 373 |      "iopub.status.busy": "2022-03-26T06:50:59.596717Z",
 374 |      "iopub.status.idle": "2022-03-26T06:50:59.619456Z",
 375 |      "shell.execute_reply": "2022-03-26T06:50:59.620003Z",
 376 |      "shell.execute_reply.started": "2022-03-26T06:30:59.541730Z"
 377 |     },
 378 |     "papermill": {
 379 |      "duration": 0.053413,
 380 |      "end_time": "2022-03-26T06:50:59.620185",
 381 |      "exception": false,
 382 |      "start_time": "2022-03-26T06:50:59.566772",
 383 |      "status": "completed"
 384 |     },
 385 |     "tags": []
 386 |    },
 387 |    "outputs": [
 388 |     {
 389 |      "data": {
 390 |       "text/html": [
 391 |        "<div>\n",
 392 |        "<style scoped>\n",
 393 |        "    .dataframe tbody tr th:only-of-type {\n",
 394 |        "        vertical-align: middle;\n",
 395 |        "    }\n",
 396 |        "\n",
 397 |        "    .dataframe tbody tr th {\n",
 398 |        "        vertical-align: top;\n",
 399 |        "    }\n",
 400 |        "\n",
 401 |        "    .dataframe thead th {\n",
 402 |        "        text-align: right;\n",
 403 |        "    }\n",
 404 |        "</style>\n",
 405 |        "<table border=\"1\" class=\"dataframe\">\n",
 406 |        "  <thead>\n",
 407 |        "    <tr style=\"text-align: right;\">\n",
 408 |        "      <th></th>\n",
 409 |        "      <th>episode_number</th>\n",
 410 |        "      <th>pitch_number</th>\n",
 411 |        "      <th>brand_name</th>\n",
 412 |        "      <th>idea</th>\n",
 413 |        "      <th>deal</th>\n",
 414 |        "      <th>pitcher_ask_amount</th>\n",
 415 |        "      <th>ask_equity</th>\n",
 416 |        "      <th>ask_valuation</th>\n",
 417 |        "      <th>deal_amount</th>\n",
 418 |        "      <th>deal_equity</th>\n",
 419 |        "      <th>...</th>\n",
 420 |        "      <th>ashneer_deal</th>\n",
 421 |        "      <th>anupam_deal</th>\n",
 422 |        "      <th>aman_deal</th>\n",
 423 |        "      <th>namita_deal</th>\n",
 424 |        "      <th>vineeta_deal</th>\n",
 425 |        "      <th>peyush_deal</th>\n",
 426 |        "      <th>ghazal_deal</th>\n",
 427 |        "      <th>total_sharks_invested</th>\n",
 428 |        "      <th>amount_per_shark</th>\n",
 429 |        "      <th>equity_per_shark</th>\n",
 430 |        "    </tr>\n",
 431 |        "  </thead>\n",
 432 |        "  <tbody>\n",
 433 |        "    <tr>\n",
 434 |        "      <th>112</th>\n",
 435 |        "      <td>34</td>\n",
 436 |        "      <td>113</td>\n",
 437 |        "      <td>Green Protein</td>\n",
 438 |        "      <td>Plant-Based Protein</td>\n",
 439 |        "      <td>0</td>\n",
 440 |        "      <td>60.0</td>\n",
 441 |        "      <td>2.0</td>\n",
 442 |        "      <td>3000.0</td>\n",
 443 |        "      <td>0.0</td>\n",
 444 |        "      <td>0.0</td>\n",
 445 |        "      <td>...</td>\n",
 446 |        "      <td>0</td>\n",
 447 |        "      <td>0</td>\n",
 448 |        "      <td>0</td>\n",
 449 |        "      <td>0</td>\n",
 450 |        "      <td>0</td>\n",
 451 |        "      <td>0</td>\n",
 452 |        "      <td>0</td>\n",
 453 |        "      <td>0</td>\n",
 454 |        "      <td>0.0</td>\n",
 455 |        "      <td>0.0</td>\n",
 456 |        "    </tr>\n",
 457 |        "    <tr>\n",
 458 |        "      <th>113</th>\n",
 459 |        "      <td>34</td>\n",
 460 |        "      <td>114</td>\n",
 461 |        "      <td>On2Cook</td>\n",
 462 |        "      <td>Fastest Cooking Device</td>\n",
 463 |        "      <td>0</td>\n",
 464 |        "      <td>100.0</td>\n",
 465 |        "      <td>1.0</td>\n",
 466 |        "      <td>10000.0</td>\n",
 467 |        "      <td>0.0</td>\n",
 468 |        "      <td>0.0</td>\n",
 469 |        "      <td>...</td>\n",
 470 |        "      <td>0</td>\n",
 471 |        "      <td>0</td>\n",
 472 |        "      <td>0</td>\n",
 473 |        "      <td>0</td>\n",
 474 |        "      <td>0</td>\n",
 475 |        "      <td>0</td>\n",
 476 |        "      <td>0</td>\n",
 477 |        "      <td>0</td>\n",
 478 |        "      <td>0.0</td>\n",
 479 |        "      <td>0.0</td>\n",
 480 |        "    </tr>\n",
 481 |        "    <tr>\n",
 482 |        "      <th>114</th>\n",
 483 |        "      <td>35</td>\n",
 484 |        "      <td>115</td>\n",
 485 |        "      <td>Jain Shikanji</td>\n",
 486 |        "      <td>Lemonade</td>\n",
 487 |        "      <td>1</td>\n",
 488 |        "      <td>40.0</td>\n",
 489 |        "      <td>8.0</td>\n",
 490 |        "      <td>500.0</td>\n",
 491 |        "      <td>40.0</td>\n",
 492 |        "      <td>30.0</td>\n",
 493 |        "      <td>...</td>\n",
 494 |        "      <td>1</td>\n",
 495 |        "      <td>1</td>\n",
 496 |        "      <td>1</td>\n",
 497 |        "      <td>0</td>\n",
 498 |        "      <td>1</td>\n",
 499 |        "      <td>0</td>\n",
 500 |        "      <td>0</td>\n",
 501 |        "      <td>4</td>\n",
 502 |        "      <td>10.0</td>\n",
 503 |        "      <td>7.5</td>\n",
 504 |        "    </tr>\n",
 505 |        "    <tr>\n",
 506 |        "      <th>115</th>\n",
 507 |        "      <td>35</td>\n",
 508 |        "      <td>116</td>\n",
 509 |        "      <td>Woloo</td>\n",
 510 |        "      <td>Washroom Finder</td>\n",
 511 |        "      <td>0</td>\n",
 512 |        "      <td>50.0</td>\n",
 513 |        "      <td>4.0</td>\n",
 514 |        "      <td>1250.0</td>\n",
 515 |        "      <td>0.0</td>\n",
 516 |        "      <td>0.0</td>\n",
 517 |        "      <td>...</td>\n",
 518 |        "      <td>0</td>\n",
 519 |        "      <td>0</td>\n",
 520 |        "      <td>0</td>\n",
 521 |        "      <td>0</td>\n",
 522 |        "      <td>0</td>\n",
 523 |        "      <td>0</td>\n",
 524 |        "      <td>0</td>\n",
 525 |        "      <td>0</td>\n",
 526 |        "      <td>0.0</td>\n",
 527 |        "      <td>0.0</td>\n",
 528 |        "    </tr>\n",
 529 |        "    <tr>\n",
 530 |        "      <th>116</th>\n",
 531 |        "      <td>35</td>\n",
 532 |        "      <td>117</td>\n",
 533 |        "      <td>Elcare India</td>\n",
 534 |        "      <td>Carenting for Elders</td>\n",
 535 |        "      <td>0</td>\n",
 536 |        "      <td>100.0</td>\n",
 537 |        "      <td>2.5</td>\n",
 538 |        "      <td>4000.0</td>\n",
 539 |        "      <td>0.0</td>\n",
 540 |        "      <td>0.0</td>\n",
 541 |        "      <td>...</td>\n",
 542 |        "      <td>0</td>\n",
 543 |        "      <td>0</td>\n",
 544 |        "      <td>0</td>\n",
 545 |        "      <td>0</td>\n",
 546 |        "      <td>0</td>\n",
 547 |        "      <td>0</td>\n",
 548 |        "      <td>0</td>\n",
 549 |        "      <td>0</td>\n",
 550 |        "      <td>0.0</td>\n",
 551 |        "      <td>0.0</td>\n",
 552 |        "    </tr>\n",
 553 |        "  </tbody>\n",
 554 |        "</table>\n",
 555 |        "<p>5 rows × 28 columns</p>\n",
 556 |        "</div>"
 557 |       ],
 558 |       "text/plain": [
 559 |        "     episode_number  pitch_number     brand_name                    idea  \\\n",
 560 |        "112              34           113  Green Protein     Plant-Based Protein   \n",
 561 |        "113              34           114        On2Cook  Fastest Cooking Device   \n",
 562 |        "114              35           115  Jain Shikanji                Lemonade   \n",
 563 |        "115              35           116          Woloo         Washroom Finder   \n",
 564 |        "116              35           117   Elcare India    Carenting for Elders   \n",
 565 |        "\n",
 566 |        "     deal  pitcher_ask_amount  ask_equity  ask_valuation  deal_amount  \\\n",
 567 |        "112     0                60.0         2.0         3000.0          0.0   \n",
 568 |        "113     0               100.0         1.0        10000.0          0.0   \n",
 569 |        "114     1                40.0         8.0          500.0         40.0   \n",
 570 |        "115     0                50.0         4.0         1250.0          0.0   \n",
 571 |        "116     0               100.0         2.5         4000.0          0.0   \n",
 572 |        "\n",
 573 |        "     deal_equity  ...  ashneer_deal  anupam_deal  aman_deal  namita_deal  \\\n",
 574 |        "112          0.0  ...             0            0          0            0   \n",
 575 |        "113          0.0  ...             0            0          0            0   \n",
 576 |        "114         30.0  ...             1            1          1            0   \n",
 577 |        "115          0.0  ...             0            0          0            0   \n",
 578 |        "116          0.0  ...             0            0          0            0   \n",
 579 |        "\n",
 580 |        "     vineeta_deal  peyush_deal  ghazal_deal  total_sharks_invested  \\\n",
 581 |        "112             0            0            0                      0   \n",
 582 |        "113             0            0            0                      0   \n",
 583 |        "114             1            0            0                      4   \n",
 584 |        "115             0            0            0                      0   \n",
 585 |        "116             0            0            0                      0   \n",
 586 |        "\n",
 587 |        "     amount_per_shark  equity_per_shark  \n",
 588 |        "112               0.0               0.0  \n",
 589 |        "113               0.0               0.0  \n",
 590 |        "114              10.0               7.5  \n",
 591 |        "115               0.0               0.0  \n",
 592 |        "116               0.0               0.0  \n",
 593 |        "\n",
 594 |        "[5 rows x 28 columns]"
 595 |       ]
 596 |      },
 597 |      "execution_count": 4,
 598 |      "metadata": {},
 599 |      "output_type": "execute_result"
 600 |     }
 601 |    ],
 602 |    "source": [
 603 |     "df.tail()"
 604 |    ]
 605 |   },
 606 |   {
 607 |    "cell_type": "code",
 608 |    "execution_count": 5,
 609 |    "id": "8f726d13",
 610 |    "metadata": {
 611 |     "execution": {
 612 |      "iopub.execute_input": "2022-03-26T06:50:59.683400Z",
 613 |      "iopub.status.busy": "2022-03-26T06:50:59.682685Z",
 614 |      "iopub.status.idle": "2022-03-26T06:50:59.705152Z",
 615 |      "shell.execute_reply": "2022-03-26T06:50:59.705856Z",
 616 |      "shell.execute_reply.started": "2022-03-26T06:30:59.581324Z"
 617 |     },
 618 |     "papermill": {
 619 |      "duration": 0.057784,
 620 |      "end_time": "2022-03-26T06:50:59.706036",
 621 |      "exception": false,
 622 |      "start_time": "2022-03-26T06:50:59.648252",
 623 |      "status": "completed"
 624 |     },
 625 |     "tags": []
 626 |    },
 627 |    "outputs": [
 628 |     {
 629 |      "name": "stdout",
 630 |      "output_type": "stream",
 631 |      "text": [
 632 |       "<class 'pandas.core.frame.DataFrame'>\n",
 633 |       "RangeIndex: 117 entries, 0 to 116\n",
 634 |       "Data columns (total 28 columns):\n",
 635 |       " #   Column                 Non-Null Count  Dtype  \n",
 636 |       "---  ------                 --------------  -----  \n",
 637 |       " 0   episode_number         117 non-null    int64  \n",
 638 |       " 1   pitch_number           117 non-null    int64  \n",
 639 |       " 2   brand_name             117 non-null    object \n",
 640 |       " 3   idea                   117 non-null    object \n",
 641 |       " 4   deal                   117 non-null    int64  \n",
 642 |       " 5   pitcher_ask_amount     117 non-null    float64\n",
 643 |       " 6   ask_equity             117 non-null    float64\n",
 644 |       " 7   ask_valuation          117 non-null    float64\n",
 645 |       " 8   deal_amount            117 non-null    float64\n",
 646 |       " 9   deal_equity            117 non-null    float64\n",
 647 |       " 10  deal_valuation         117 non-null    float64\n",
 648 |       " 11  ashneer_present        117 non-null    int64  \n",
 649 |       " 12  anupam_present         117 non-null    int64  \n",
 650 |       " 13  aman_present           117 non-null    int64  \n",
 651 |       " 14  namita_present         117 non-null    int64  \n",
 652 |       " 15  vineeta_present        117 non-null    int64  \n",
 653 |       " 16  peyush_present         117 non-null    int64  \n",
 654 |       " 17  ghazal_present         117 non-null    int64  \n",
 655 |       " 18  ashneer_deal           117 non-null    int64  \n",
 656 |       " 19  anupam_deal            117 non-null    int64  \n",
 657 |       " 20  aman_deal              117 non-null    int64  \n",
 658 |       " 21  namita_deal            117 non-null    int64  \n",
 659 |       " 22  vineeta_deal           117 non-null    int64  \n",
 660 |       " 23  peyush_deal            117 non-null    int64  \n",
 661 |       " 24  ghazal_deal            117 non-null    int64  \n",
 662 |       " 25  total_sharks_invested  117 non-null    int64  \n",
 663 |       " 26  amount_per_shark       117 non-null    float64\n",
 664 |       " 27  equity_per_shark       117 non-null    float64\n",
 665 |       "dtypes: float64(8), int64(18), object(2)\n",
 666 |       "memory usage: 25.7+ KB\n"
 667 |      ]
 668 |     }
 669 |    ],
 670 |    "source": [
 671 |     "df.info()"
 672 |    ]
 673 |   },
 674 |   {
 675 |    "cell_type": "code",
 676 |    "execution_count": 6,
 677 |    "id": "6d21d274",
 678 |    "metadata": {
 679 |     "execution": {
 680 |      "iopub.execute_input": "2022-03-26T06:50:59.767288Z",
 681 |      "iopub.status.busy": "2022-03-26T06:50:59.766595Z",
 682 |      "iopub.status.idle": "2022-03-26T06:50:59.848654Z",
 683 |      "shell.execute_reply": "2022-03-26T06:50:59.849291Z",
 684 |      "shell.execute_reply.started": "2022-03-26T06:30:59.608103Z"
 685 |     },
 686 |     "papermill": {
 687 |      "duration": 0.1145,
 688 |      "end_time": "2022-03-26T06:50:59.849492",
 689 |      "exception": false,
 690 |      "start_time": "2022-03-26T06:50:59.734992",
 691 |      "status": "completed"
 692 |     },
 693 |     "tags": []
 694 |    },
 695 |    "outputs": [
 696 |     {
 697 |      "data": {
 698 |       "text/html": [
 699 |        "<div>\n",
 700 |        "<style scoped>\n",
 701 |        "    .dataframe tbody tr th:only-of-type {\n",
 702 |        "        vertical-align: middle;\n",
 703 |        "    }\n",
 704 |        "\n",
 705 |        "    .dataframe tbody tr th {\n",
 706 |        "        vertical-align: top;\n",
 707 |        "    }\n",
 708 |        "\n",
 709 |        "    .dataframe thead th {\n",
 710 |        "        text-align: right;\n",
 711 |        "    }\n",
 712 |        "</style>\n",
 713 |        "<table border=\"1\" class=\"dataframe\">\n",
 714 |        "  <thead>\n",
 715 |        "    <tr style=\"text-align: right;\">\n",
 716 |        "      <th></th>\n",
 717 |        "      <th>episode_number</th>\n",
 718 |        "      <th>pitch_number</th>\n",
 719 |        "      <th>deal</th>\n",
 720 |        "      <th>pitcher_ask_amount</th>\n",
 721 |        "      <th>ask_equity</th>\n",
 722 |        "      <th>ask_valuation</th>\n",
 723 |        "      <th>deal_amount</th>\n",
 724 |        "      <th>deal_equity</th>\n",
 725 |        "      <th>deal_valuation</th>\n",
 726 |        "      <th>ashneer_present</th>\n",
 727 |        "      <th>...</th>\n",
 728 |        "      <th>ashneer_deal</th>\n",
 729 |        "      <th>anupam_deal</th>\n",
 730 |        "      <th>aman_deal</th>\n",
 731 |        "      <th>namita_deal</th>\n",
 732 |        "      <th>vineeta_deal</th>\n",
 733 |        "      <th>peyush_deal</th>\n",
 734 |        "      <th>ghazal_deal</th>\n",
 735 |        "      <th>total_sharks_invested</th>\n",
 736 |        "      <th>amount_per_shark</th>\n",
 737 |        "      <th>equity_per_shark</th>\n",
 738 |        "    </tr>\n",
 739 |        "  </thead>\n",
 740 |        "  <tbody>\n",
 741 |        "    <tr>\n",
 742 |        "      <th>count</th>\n",
 743 |        "      <td>117.000000</td>\n",
 744 |        "      <td>117.000000</td>\n",
 745 |        "      <td>117.000000</td>\n",
 746 |        "      <td>117.000000</td>\n",
 747 |        "      <td>117.000000</td>\n",
 748 |        "      <td>117.000000</td>\n",
 749 |        "      <td>117.000000</td>\n",
 750 |        "      <td>117.000000</td>\n",
 751 |        "      <td>117.000000</td>\n",
 752 |        "      <td>117.000000</td>\n",
 753 |        "      <td>...</td>\n",
 754 |        "      <td>117.000000</td>\n",
 755 |        "      <td>117.000000</td>\n",
 756 |        "      <td>117.000000</td>\n",
 757 |        "      <td>117.000000</td>\n",
 758 |        "      <td>117.000000</td>\n",
 759 |        "      <td>117.000000</td>\n",
 760 |        "      <td>117.000000</td>\n",
 761 |        "      <td>117.000000</td>\n",
 762 |        "      <td>117.000000</td>\n",
 763 |        "      <td>117.000000</td>\n",
 764 |        "    </tr>\n",
 765 |        "    <tr>\n",
 766 |        "      <th>mean</th>\n",
 767 |        "      <td>18.735043</td>\n",
 768 |        "      <td>59.000000</td>\n",
 769 |        "      <td>0.555556</td>\n",
 770 |        "      <td>319.854709</td>\n",
 771 |        "      <td>5.188034</td>\n",
 772 |        "      <td>3852.462479</td>\n",
 773 |        "      <td>31.982915</td>\n",
 774 |        "      <td>8.963504</td>\n",
 775 |        "      <td>467.104872</td>\n",
 776 |        "      <td>0.837607</td>\n",
 777 |        "      <td>...</td>\n",
 778 |        "      <td>0.179487</td>\n",
 779 |        "      <td>0.205128</td>\n",
 780 |        "      <td>0.239316</td>\n",
 781 |        "      <td>0.188034</td>\n",
 782 |        "      <td>0.128205</td>\n",
 783 |        "      <td>0.230769</td>\n",
 784 |        "      <td>0.059829</td>\n",
 785 |        "      <td>1.230769</td>\n",
 786 |        "      <td>18.132481</td>\n",
 787 |        "      <td>5.583590</td>\n",
 788 |        "    </tr>\n",
 789 |        "    <tr>\n",
 790 |        "      <th>std</th>\n",
 791 |        "      <td>10.070778</td>\n",
 792 |        "      <td>33.919021</td>\n",
 793 |        "      <td>0.499041</td>\n",
 794 |        "      <td>2767.842777</td>\n",
 795 |        "      <td>3.892121</td>\n",
 796 |        "      <td>11931.601957</td>\n",
 797 |        "      <td>36.687391</td>\n",
 798 |        "      <td>13.106769</td>\n",
 799 |        "      <td>919.988864</td>\n",
 800 |        "      <td>0.370397</td>\n",
 801 |        "      <td>...</td>\n",
 802 |        "      <td>0.385410</td>\n",
 803 |        "      <td>0.405532</td>\n",
 804 |        "      <td>0.428501</td>\n",
 805 |        "      <td>0.392420</td>\n",
 806 |        "      <td>0.335756</td>\n",
 807 |        "      <td>0.423137</td>\n",
 808 |        "      <td>0.238190</td>\n",
 809 |        "      <td>1.410457</td>\n",
 810 |        "      <td>23.588682</td>\n",
 811 |        "      <td>10.803799</td>\n",
 812 |        "    </tr>\n",
 813 |        "    <tr>\n",
 814 |        "      <th>min</th>\n",
 815 |        "      <td>1.000000</td>\n",
 816 |        "      <td>1.000000</td>\n",
 817 |        "      <td>0.000000</td>\n",
 818 |        "      <td>0.001010</td>\n",
 819 |        "      <td>0.250000</td>\n",
 820 |        "      <td>0.010000</td>\n",
 821 |        "      <td>0.000000</td>\n",
 822 |        "      <td>0.000000</td>\n",
 823 |        "      <td>0.000000</td>\n",
 824 |        "      <td>0.000000</td>\n",
 825 |        "      <td>...</td>\n",
 826 |        "      <td>0.000000</td>\n",
 827 |        "      <td>0.000000</td>\n",
 828 |        "      <td>0.000000</td>\n",
 829 |        "      <td>0.000000</td>\n",
 830 |        "      <td>0.000000</td>\n",
 831 |        "      <td>0.000000</td>\n",
 832 |        "      <td>0.000000</td>\n",
 833 |        "      <td>0.000000</td>\n",
 834 |        "      <td>0.000000</td>\n",
 835 |        "      <td>0.000000</td>\n",
 836 |        "    </tr>\n",
 837 |        "    <tr>\n",
 838 |        "      <th>25%</th>\n",
 839 |        "      <td>10.000000</td>\n",
 840 |        "      <td>30.000000</td>\n",
 841 |        "      <td>0.000000</td>\n",
 842 |        "      <td>45.000000</td>\n",
 843 |        "      <td>2.500000</td>\n",
 844 |        "      <td>666.670000</td>\n",
 845 |        "      <td>0.000000</td>\n",
 846 |        "      <td>0.000000</td>\n",
 847 |        "      <td>0.000000</td>\n",
 848 |        "      <td>1.000000</td>\n",
 849 |        "      <td>...</td>\n",
 850 |        "      <td>0.000000</td>\n",
 851 |        "      <td>0.000000</td>\n",
 852 |        "      <td>0.000000</td>\n",
 853 |        "      <td>0.000000</td>\n",
 854 |        "      <td>0.000000</td>\n",
 855 |        "      <td>0.000000</td>\n",
 856 |        "      <td>0.000000</td>\n",
 857 |        "      <td>0.000000</td>\n",
 858 |        "      <td>0.000000</td>\n",
 859 |        "      <td>0.000000</td>\n",
 860 |        "    </tr>\n",
 861 |        "    <tr>\n",
 862 |        "      <th>50%</th>\n",
 863 |        "      <td>19.000000</td>\n",
 864 |        "      <td>59.000000</td>\n",
 865 |        "      <td>1.000000</td>\n",
 866 |        "      <td>50.000000</td>\n",
 867 |        "      <td>5.000000</td>\n",
 868 |        "      <td>1250.000000</td>\n",
 869 |        "      <td>25.000000</td>\n",
 870 |        "      <td>3.000000</td>\n",
 871 |        "      <td>100.000000</td>\n",
 872 |        "      <td>1.000000</td>\n",
 873 |        "      <td>...</td>\n",
 874 |        "      <td>0.000000</td>\n",
 875 |        "      <td>0.000000</td>\n",
 876 |        "      <td>0.000000</td>\n",
 877 |        "      <td>0.000000</td>\n",
 878 |        "      <td>0.000000</td>\n",
 879 |        "      <td>0.000000</td>\n",
 880 |        "      <td>0.000000</td>\n",
 881 |        "      <td>1.000000</td>\n",
 882 |        "      <td>10.000000</td>\n",
 883 |        "      <td>1.250000</td>\n",
 884 |        "    </tr>\n",
 885 |        "    <tr>\n",
 886 |        "      <th>75%</th>\n",
 887 |        "      <td>27.000000</td>\n",
 888 |        "      <td>88.000000</td>\n",
 889 |        "      <td>1.000000</td>\n",
 890 |        "      <td>80.000000</td>\n",
 891 |        "      <td>7.500000</td>\n",
 892 |        "      <td>2857.140000</td>\n",
 893 |        "      <td>50.000000</td>\n",
 894 |        "      <td>15.000000</td>\n",
 895 |        "      <td>500.000000</td>\n",
 896 |        "      <td>1.000000</td>\n",
 897 |        "      <td>...</td>\n",
 898 |        "      <td>0.000000</td>\n",
 899 |        "      <td>0.000000</td>\n",
 900 |        "      <td>0.000000</td>\n",
 901 |        "      <td>0.000000</td>\n",
 902 |        "      <td>0.000000</td>\n",
 903 |        "      <td>0.000000</td>\n",
 904 |        "      <td>0.000000</td>\n",
 905 |        "      <td>2.000000</td>\n",
 906 |        "      <td>25.000000</td>\n",
 907 |        "      <td>6.000000</td>\n",
 908 |        "    </tr>\n",
 909 |        "    <tr>\n",
 910 |        "      <th>max</th>\n",
 911 |        "      <td>35.000000</td>\n",
 912 |        "      <td>117.000000</td>\n",
 913 |        "      <td>1.000000</td>\n",
 914 |        "      <td>30000.000000</td>\n",
 915 |        "      <td>25.000000</td>\n",
 916 |        "      <td>120000.000000</td>\n",
 917 |        "      <td>150.000000</td>\n",
 918 |        "      <td>75.000000</td>\n",
 919 |        "      <td>6666.670000</td>\n",
 920 |        "      <td>1.000000</td>\n",
 921 |        "      <td>...</td>\n",
 922 |        "      <td>1.000000</td>\n",
 923 |        "      <td>1.000000</td>\n",
 924 |        "      <td>1.000000</td>\n",
 925 |        "      <td>1.000000</td>\n",
 926 |        "      <td>1.000000</td>\n",
 927 |        "      <td>1.000000</td>\n",
 928 |        "      <td>1.000000</td>\n",
 929 |        "      <td>5.000000</td>\n",
 930 |        "      <td>100.000000</td>\n",
 931 |        "      <td>75.000000</td>\n",
 932 |        "    </tr>\n",
 933 |        "  </tbody>\n",
 934 |        "</table>\n",
 935 |        "<p>8 rows × 26 columns</p>\n",
 936 |        "</div>"
 937 |       ],
 938 |       "text/plain": [
 939 |        "       episode_number  pitch_number        deal  pitcher_ask_amount  \\\n",
 940 |        "count      117.000000    117.000000  117.000000          117.000000   \n",
 941 |        "mean        18.735043     59.000000    0.555556          319.854709   \n",
 942 |        "std         10.070778     33.919021    0.499041         2767.842777   \n",
 943 |        "min          1.000000      1.000000    0.000000            0.001010   \n",
 944 |        "25%         10.000000     30.000000    0.000000           45.000000   \n",
 945 |        "50%         19.000000     59.000000    1.000000           50.000000   \n",
 946 |        "75%         27.000000     88.000000    1.000000           80.000000   \n",
 947 |        "max         35.000000    117.000000    1.000000        30000.000000   \n",
 948 |        "\n",
 949 |        "       ask_equity  ask_valuation  deal_amount  deal_equity  deal_valuation  \\\n",
 950 |        "count  117.000000     117.000000   117.000000   117.000000      117.000000   \n",
 951 |        "mean     5.188034    3852.462479    31.982915     8.963504      467.104872   \n",
 952 |        "std      3.892121   11931.601957    36.687391    13.106769      919.988864   \n",
 953 |        "min      0.250000       0.010000     0.000000     0.000000        0.000000   \n",
 954 |        "25%      2.500000     666.670000     0.000000     0.000000        0.000000   \n",
 955 |        "50%      5.000000    1250.000000    25.000000     3.000000      100.000000   \n",
 956 |        "75%      7.500000    2857.140000    50.000000    15.000000      500.000000   \n",
 957 |        "max     25.000000  120000.000000   150.000000    75.000000     6666.670000   \n",
 958 |        "\n",
 959 |        "       ashneer_present  ...  ashneer_deal  anupam_deal   aman_deal  \\\n",
 960 |        "count       117.000000  ...    117.000000   117.000000  117.000000   \n",
 961 |        "mean          0.837607  ...      0.179487     0.205128    0.239316   \n",
 962 |        "std           0.370397  ...      0.385410     0.405532    0.428501   \n",
 963 |        "min           0.000000  ...      0.000000     0.000000    0.000000   \n",
 964 |        "25%           1.000000  ...      0.000000     0.000000    0.000000   \n",
 965 |        "50%           1.000000  ...      0.000000     0.000000    0.000000   \n",
 966 |        "75%           1.000000  ...      0.000000     0.000000    0.000000   \n",
 967 |        "max           1.000000  ...      1.000000     1.000000    1.000000   \n",
 968 |        "\n",
 969 |        "       namita_deal  vineeta_deal  peyush_deal  ghazal_deal  \\\n",
 970 |        "count   117.000000    117.000000   117.000000   117.000000   \n",
 971 |        "mean      0.188034      0.128205     0.230769     0.059829   \n",
 972 |        "std       0.392420      0.335756     0.423137     0.238190   \n",
 973 |        "min       0.000000      0.000000     0.000000     0.000000   \n",
 974 |        "25%       0.000000      0.000000     0.000000     0.000000   \n",
 975 |        "50%       0.000000      0.000000     0.000000     0.000000   \n",
 976 |        "75%       0.000000      0.000000     0.000000     0.000000   \n",
 977 |        "max       1.000000      1.000000     1.000000     1.000000   \n",
 978 |        "\n",
 979 |        "       total_sharks_invested  amount_per_shark  equity_per_shark  \n",
 980 |        "count             117.000000        117.000000        117.000000  \n",
 981 |        "mean                1.230769         18.132481          5.583590  \n",
 982 |        "std                 1.410457         23.588682         10.803799  \n",
 983 |        "min                 0.000000          0.000000          0.000000  \n",
 984 |        "25%                 0.000000          0.000000          0.000000  \n",
 985 |        "50%                 1.000000         10.000000          1.250000  \n",
 986 |        "75%                 2.000000         25.000000          6.000000  \n",
 987 |        "max                 5.000000        100.000000         75.000000  \n",
 988 |        "\n",
 989 |        "[8 rows x 26 columns]"
 990 |       ]
 991 |      },
 992 |      "execution_count": 6,
 993 |      "metadata": {},
 994 |      "output_type": "execute_result"
 995 |     }
 996 |    ],
 997 |    "source": [
 998 |     "df.describe()"
 999 |    ]
1000 |   },
1001 |   {
1002 |    "cell_type": "code",
1003 |    "execution_count": 7,
1004 |    "id": "0c02f398",
1005 |    "metadata": {
1006 |     "execution": {
1007 |      "iopub.execute_input": "2022-03-26T06:50:59.915625Z",
1008 |      "iopub.status.busy": "2022-03-26T06:50:59.914787Z",
1009 |      "iopub.status.idle": "2022-03-26T06:50:59.922308Z",
1010 |      "shell.execute_reply": "2022-03-26T06:50:59.922848Z",
1011 |      "shell.execute_reply.started": "2022-03-26T06:30:59.687138Z"
1012 |     },
1013 |     "papermill": {
1014 |      "duration": 0.041231,
1015 |      "end_time": "2022-03-26T06:50:59.923022",
1016 |      "exception": false,
1017 |      "start_time": "2022-03-26T06:50:59.881791",
1018 |      "status": "completed"
1019 |     },
1020 |     "tags": []
1021 |    },
1022 |    "outputs": [
1023 |     {
1024 |      "data": {
1025 |       "text/plain": [
1026 |        "episode_number           0\n",
1027 |        "pitch_number             0\n",
1028 |        "brand_name               0\n",
1029 |        "idea                     0\n",
1030 |        "deal                     0\n",
1031 |        "pitcher_ask_amount       0\n",
1032 |        "ask_equity               0\n",
1033 |        "ask_valuation            0\n",
1034 |        "deal_amount              0\n",
1035 |        "deal_equity              0\n",
1036 |        "deal_valuation           0\n",
1037 |        "ashneer_present          0\n",
1038 |        "anupam_present           0\n",
1039 |        "aman_present             0\n",
1040 |        "namita_present           0\n",
1041 |        "vineeta_present          0\n",
1042 |        "peyush_present           0\n",
1043 |        "ghazal_present           0\n",
1044 |        "ashneer_deal             0\n",
1045 |        "anupam_deal              0\n",
1046 |        "aman_deal                0\n",
1047 |        "namita_deal              0\n",
1048 |        "vineeta_deal             0\n",
1049 |        "peyush_deal              0\n",
1050 |        "ghazal_deal              0\n",
1051 |        "total_sharks_invested    0\n",
1052 |        "amount_per_shark         0\n",
1053 |        "equity_per_shark         0\n",
1054 |        "dtype: int64"
1055 |       ]
1056 |      },
1057 |      "execution_count": 7,
1058 |      "metadata": {},
1059 |      "output_type": "execute_result"
1060 |     }
1061 |    ],
1062 |    "source": [
1063 |     "df.isnull().sum()"
1064 |    ]
1065 |   },
1066 |   {
1067 |    "cell_type": "markdown",
1068 |    "id": "11be0bbd",
1069 |    "metadata": {
1070 |     "papermill": {
1071 |      "duration": 0.029855,
1072 |      "end_time": "2022-03-26T06:50:59.982956",
1073 |      "exception": false,
1074 |      "start_time": "2022-03-26T06:50:59.953101",
1075 |      "status": "completed"
1076 |     },
1077 |     "tags": []
1078 |    },
1079 |    "source": [
1080 |     "# **Percentage of comapnies got investment or not?**"
1081 |    ]
1082 |   },
1083 |   {
1084 |    "cell_type": "code",
1085 |    "execution_count": 8,
1086 |    "id": "adc39189",
1087 |    "metadata": {
1088 |     "execution": {
1089 |      "iopub.execute_input": "2022-03-26T06:51:00.046097Z",
1090 |      "iopub.status.busy": "2022-03-26T06:51:00.045410Z",
1091 |      "iopub.status.idle": "2022-03-26T06:51:00.203347Z",
1092 |      "shell.execute_reply": "2022-03-26T06:51:00.204425Z",
1093 |      "shell.execute_reply.started": "2022-03-26T06:49:57.425857Z"
1094 |     },
1095 |     "papermill": {
1096 |      "duration": 0.191691,
1097 |      "end_time": "2022-03-26T06:51:00.204727",
1098 |      "exception": false,
1099 |      "start_time": "2022-03-26T06:51:00.013036",
1100 |      "status": "completed"
1101 |     },
1102 |     "tags": []
1103 |    },
1104 |    "outputs": [
1105 |     {
1106 |      "name": "stdout",
1107 |      "output_type": "stream",
1108 |      "text": [
1109 |       "The number of companies who got the investment:  65\n",
1110 |       "The number of companies who didn't got the investment:  52\n",
1111 |       "\n",
1112 |       "---------\n",
1113 |       "\n"
1114 |      ]
1115 |     },
1116 |     {
1117 |      "data": {
1118 |       "image/png": 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\n",
1119 |       "text/plain": [
1120 |        "<Figure size 432x288 with 1 Axes>"
1121 |       ]
1122 |      },
1123 |      "metadata": {},
1124 |      "output_type": "display_data"
1125 |     }
1126 |    ],
1127 |    "source": [
1128 |     "got_in=df[df['deal_amount']>0.0].shape\n",
1129 |     "not_in=df[df['deal_amount']==0.0].shape\n",
1130 |     "\n",
1131 |     "print(\"The number of companies who got the investment: \", got_in[0])\n",
1132 |     "print(\"The number of companies who didn't got the investment: \", not_in[0])\n",
1133 |     "print(\"\\n---------\\n\")\n",
1134 |     "list1=[\"Got Investment\", \"Not Recieved Investment\"]\n",
1135 |     "plt.pie([got_in[0],not_in[0]], labels=list1, autopct='%.1f%%')\n",
1136 |     "plt.title('Number of comapnies which got investment or not:')\n",
1137 |     "plt.show()"
1138 |    ]
1139 |   },
1140 |   {
1141 |    "cell_type": "markdown",
1142 |    "id": "0a5f68c0",
1143 |    "metadata": {
1144 |     "papermill": {
1145 |      "duration": 0.030733,
1146 |      "end_time": "2022-03-26T06:51:00.292931",
1147 |      "exception": false,
1148 |      "start_time": "2022-03-26T06:51:00.262198",
1149 |      "status": "completed"
1150 |     },
1151 |     "tags": []
1152 |    },
1153 |    "source": [
1154 |     "# **Five Shark Deal:**"
1155 |    ]
1156 |   },
1157 |   {
1158 |    "cell_type": "code",
1159 |    "execution_count": 9,
1160 |    "id": "a1099cb4",
1161 |    "metadata": {
1162 |     "execution": {
1163 |      "iopub.execute_input": "2022-03-26T06:51:00.362181Z",
1164 |      "iopub.status.busy": "2022-03-26T06:51:00.361473Z",
1165 |      "iopub.status.idle": "2022-03-26T06:51:01.571743Z",
1166 |      "shell.execute_reply": "2022-03-26T06:51:01.572286Z",
1167 |      "shell.execute_reply.started": "2022-03-26T06:30:59.698349Z"
1168 |     },
1169 |     "papermill": {
1170 |      "duration": 1.247858,
1171 |      "end_time": "2022-03-26T06:51:01.572497",
1172 |      "exception": false,
1173 |      "start_time": "2022-03-26T06:51:00.324639",
1174 |      "status": "completed"
1175 |     },
1176 |     "tags": []
1177 |    },
1178 |    "outputs": [
1179 |     {
1180 |      "data": {
1181 |       "text/html": [
1182 |        "        <script type=\"text/javascript\">\n",
1183 |        "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
1184 |        "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
1185 |        "        if (typeof require !== 'undefined') {\n",
1186 |        "        require.undef(\"plotly\");\n",
1187 |        "        requirejs.config({\n",
1188 |        "            paths: {\n",
1189 |        "                'plotly': ['https://cdn.plot.ly/plotly-2.9.0.min']\n",
1190 |        "            }\n",
1191 |        "        });\n",
1192 |        "        require(['plotly'], function(Plotly) {\n",
1193 |        "            window._Plotly = Plotly;\n",
1194 |        "        });\n",
1195 |        "        }\n",
1196 |        "        </script>\n",
1197 |        "        "
1198 |       ]
1199 |      },
1200 |      "metadata": {},
1201 |      "output_type": "display_data"
1202 |     },
1203 |     {
1204 |      "data": {
1205 |       "text/html": [
1206 |        "<div>                            <div id=\"dfe0a10b-881b-4e61-aabb-7f2f25e16f8b\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"dfe0a10b-881b-4e61-aabb-7f2f25e16f8b\")) {                    Plotly.newPlot(                        \"dfe0a10b-881b-4e61-aabb-7f2f25e16f8b\",                        [{\"alignmentgroup\":\"True\",\"hovertemplate\":\"brand_name=%{x}<br>deal_amount=%{y}<br>pitcher_ask_amount=%{marker.color}<extra></extra>\",\"legendgroup\":\"\",\"marker\":{\"color\":[45.0,50.0,50.0,100.0],\"coloraxis\":\"coloraxis\",\"pattern\":{\"shape\":\"\"}},\"name\":\"\",\"offsetgroup\":\"\",\"orientation\":\"v\",\"showlegend\":false,\"textposition\":\"auto\",\"texttemplate\":\"%{y}\",\"x\":[\"Skippi Pops\",\"Find Your Kicks 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1207 |        "                            \n",
1208 |        "var gd = document.getElementById('dfe0a10b-881b-4e61-aabb-7f2f25e16f8b');\n",
1209 |        "var x = new MutationObserver(function (mutations, observer) {{\n",
1210 |        "        var display = window.getComputedStyle(gd).display;\n",
1211 |        "        if (!display || display === 'none') {{\n",
1212 |        "            console.log([gd, 'removed!']);\n",
1213 |        "            Plotly.purge(gd);\n",
1214 |        "            observer.disconnect();\n",
1215 |        "        }}\n",
1216 |        "}});\n",
1217 |        "\n",
1218 |        "// Listen for the removal of the full notebook cells\n",
1219 |        "var notebookContainer = gd.closest('#notebook-container');\n",
1220 |        "if (notebookContainer) {{\n",
1221 |        "    x.observe(notebookContainer, {childList: true});\n",
1222 |        "}}\n",
1223 |        "\n",
1224 |        "// Listen for the clearing of the current output cell\n",
1225 |        "var outputEl = gd.closest('.output');\n",
1226 |        "if (outputEl) {{\n",
1227 |        "    x.observe(outputEl, {childList: true});\n",
1228 |        "}}\n",
1229 |        "\n",
1230 |        "                        })                };                });            </script>        </div>"
1231 |       ]
1232 |      },
1233 |      "metadata": {},
1234 |      "output_type": "display_data"
1235 |     }
1236 |    ],
1237 |    "source": [
1238 |     "#Total Shark Deal:\n",
1239 |     "total_shark=df[df[\"total_sharks_invested\"]==5]\n",
1240 |     "figure=px.bar(total_shark, x='brand_name', y='deal_amount',title=\"Five Shark Deal Brands and the total investment:\",text_auto=True, color='pitcher_ask_amount',\n",
1241 |     "                    template=\"plotly_dark\")\n",
1242 |     "figure.show()"
1243 |    ]
1244 |   },
1245 |   {
1246 |    "cell_type": "markdown",
1247 |    "id": "e5295ef5",
1248 |    "metadata": {
1249 |     "papermill": {
1250 |      "duration": 0.032208,
1251 |      "end_time": "2022-03-26T06:51:01.637007",
1252 |      "exception": false,
1253 |      "start_time": "2022-03-26T06:51:01.604799",
1254 |      "status": "completed"
1255 |     },
1256 |     "tags": []
1257 |    },
1258 |    "source": [
1259 |     "From above plot, we get to know that there are all total 4 five shark deal brands and also with the pitcher deal amount and the deal amount of the brand."
1260 |    ]
1261 |   },
1262 |   {
1263 |    "cell_type": "markdown",
1264 |    "id": "fa7957df",
1265 |    "metadata": {
1266 |     "papermill": {
1267 |      "duration": 0.032334,
1268 |      "end_time": "2022-03-26T06:51:01.701859",
1269 |      "exception": false,
1270 |      "start_time": "2022-03-26T06:51:01.669525",
1271 |      "status": "completed"
1272 |     },
1273 |     "tags": []
1274 |    },
1275 |    "source": [
1276 |     "# **Highest Pitch Ask Amount:**"
1277 |    ]
1278 |   },
1279 |   {
1280 |    "cell_type": "code",
1281 |    "execution_count": 10,
1282 |    "id": "92f6138f",
1283 |    "metadata": {
1284 |     "execution": {
1285 |      "iopub.execute_input": "2022-03-26T06:51:01.771072Z",
1286 |      "iopub.status.busy": "2022-03-26T06:51:01.770340Z",
1287 |      "iopub.status.idle": "2022-03-26T06:51:01.837908Z",
1288 |      "shell.execute_reply": "2022-03-26T06:51:01.837201Z",
1289 |      "shell.execute_reply.started": "2022-03-26T06:31:00.674948Z"
1290 |     },
1291 |     "papermill": {
1292 |      "duration": 0.103375,
1293 |      "end_time": "2022-03-26T06:51:01.838065",
1294 |      "exception": false,
1295 |      "start_time": "2022-03-26T06:51:01.734690",
1296 |      "status": "completed"
1297 |     },
1298 |     "tags": []
1299 |    },
1300 |    "outputs": [
1301 |     {
1302 |      "data": {
1303 |       "text/html": [
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1305 |        "                            \n",
1306 |        "var gd = document.getElementById('c4171f4a-95e6-470d-8298-896233a8bb84');\n",
1307 |        "var x = new MutationObserver(function (mutations, observer) {{\n",
1308 |        "        var display = window.getComputedStyle(gd).display;\n",
1309 |        "        if (!display || display === 'none') {{\n",
1310 |        "            console.log([gd, 'removed!']);\n",
1311 |        "            Plotly.purge(gd);\n",
1312 |        "            observer.disconnect();\n",
1313 |        "        }}\n",
1314 |        "}});\n",
1315 |        "\n",
1316 |        "// Listen for the removal of the full notebook cells\n",
1317 |        "var notebookContainer = gd.closest('#notebook-container');\n",
1318 |        "if (notebookContainer) {{\n",
1319 |        "    x.observe(notebookContainer, {childList: true});\n",
1320 |        "}}\n",
1321 |        "\n",
1322 |        "// Listen for the clearing of the current output cell\n",
1323 |        "var outputEl = gd.closest('.output');\n",
1324 |        "if (outputEl) {{\n",
1325 |        "    x.observe(outputEl, {childList: true});\n",
1326 |        "}}\n",
1327 |        "\n",
1328 |        "                        })                };                });            </script>        </div>"
1329 |       ]
1330 |      },
1331 |      "metadata": {},
1332 |      "output_type": "display_data"
1333 |     }
1334 |    ],
1335 |    "source": [
1336 |     "#Highest Pitch Ask Amount \n",
1337 |     "high=df[df[\"pitcher_ask_amount\"]>100]\n",
1338 |     "figure=px.bar(high, x='brand_name', y='pitcher_ask_amount',title=\"Highest Pitch Ask Amount:\",text_auto=True, color='deal_amount',\n",
1339 |     "                    template=\"plotly_dark\")\n",
1340 |     "figure.show()"
1341 |    ]
1342 |   },
1343 |   {
1344 |    "cell_type": "markdown",
1345 |    "id": "94c01295",
1346 |    "metadata": {
1347 |     "papermill": {
1348 |      "duration": 0.033068,
1349 |      "end_time": "2022-03-26T06:51:01.904749",
1350 |      "exception": false,
1351 |      "start_time": "2022-03-26T06:51:01.871681",
1352 |      "status": "completed"
1353 |     },
1354 |     "tags": []
1355 |    },
1356 |    "source": [
1357 |     "# **Ask Equity and Deal Equity:**"
1358 |    ]
1359 |   },
1360 |   {
1361 |    "cell_type": "code",
1362 |    "execution_count": 11,
1363 |    "id": "30b49ee6",
1364 |    "metadata": {
1365 |     "execution": {
1366 |      "iopub.execute_input": "2022-03-26T06:51:01.982522Z",
1367 |      "iopub.status.busy": "2022-03-26T06:51:01.981747Z",
1368 |      "iopub.status.idle": "2022-03-26T06:51:02.043825Z",
1369 |      "shell.execute_reply": "2022-03-26T06:51:02.043251Z",
1370 |      "shell.execute_reply.started": "2022-03-26T06:31:00.744911Z"
1371 |     },
1372 |     "papermill": {
1373 |      "duration": 0.104255,
1374 |      "end_time": "2022-03-26T06:51:02.043969",
1375 |      "exception": false,
1376 |      "start_time": "2022-03-26T06:51:01.939714",
1377 |      "status": "completed"
1378 |     },
1379 |     "tags": []
1380 |    },
1381 |    "outputs": [
1382 |     {
1383 |      "data": {
1384 |       "text/html": [
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1386 |        "                            \n",
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1390 |        "        if (!display || display === 'none') {{\n",
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1392 |        "            Plotly.purge(gd);\n",
1393 |        "            observer.disconnect();\n",
1394 |        "        }}\n",
1395 |        "}});\n",
1396 |        "\n",
1397 |        "// Listen for the removal of the full notebook cells\n",
1398 |        "var notebookContainer = gd.closest('#notebook-container');\n",
1399 |        "if (notebookContainer) {{\n",
1400 |        "    x.observe(notebookContainer, {childList: true});\n",
1401 |        "}}\n",
1402 |        "\n",
1403 |        "// Listen for the clearing of the current output cell\n",
1404 |        "var outputEl = gd.closest('.output');\n",
1405 |        "if (outputEl) {{\n",
1406 |        "    x.observe(outputEl, {childList: true});\n",
1407 |        "}}\n",
1408 |        "\n",
1409 |        "                        })                };                });            </script>        </div>"
1410 |       ]
1411 |      },
1412 |      "metadata": {},
1413 |      "output_type": "display_data"
1414 |     }
1415 |    ],
1416 |    "source": [
1417 |     "#Ask Equity and Deal Equity of Highest Pitch Ask AMount Brand\n",
1418 |     "figure=px.bar(high, x='brand_name', y='ask_equity',title=\"Ask Equity & Deal Equity of Highest Pitch Ask Amount Brand:\",text_auto=True, color='deal_equity',\n",
1419 |     "                    template=\"plotly_dark\")\n",
1420 |     "figure.show()"
1421 |    ]
1422 |   },
1423 |   {
1424 |    "cell_type": "markdown",
1425 |    "id": "5b4556dc",
1426 |    "metadata": {
1427 |     "papermill": {
1428 |      "duration": 0.033611,
1429 |      "end_time": "2022-03-26T06:51:02.111833",
1430 |      "exception": false,
1431 |      "start_time": "2022-03-26T06:51:02.078222",
1432 |      "status": "completed"
1433 |     },
1434 |     "tags": []
1435 |    },
1436 |    "source": [
1437 |     "Most of the brand asking for the high amount had not received the investment from the shark, we clearly got to know by the blue color plot which shows that no deal happened except \"Aas Vidyalaya\"."
1438 |    ]
1439 |   },
1440 |   {
1441 |    "cell_type": "markdown",
1442 |    "id": "babc6b96",
1443 |    "metadata": {
1444 |     "papermill": {
1445 |      "duration": 0.034217,
1446 |      "end_time": "2022-03-26T06:51:02.180104",
1447 |      "exception": false,
1448 |      "start_time": "2022-03-26T06:51:02.145887",
1449 |      "status": "completed"
1450 |     },
1451 |     "tags": []
1452 |    },
1453 |    "source": [
1454 |     "# **Least Pitch Amount Asked:**"
1455 |    ]
1456 |   },
1457 |   {
1458 |    "cell_type": "code",
1459 |    "execution_count": 12,
1460 |    "id": "4703b298",
1461 |    "metadata": {
1462 |     "execution": {
1463 |      "iopub.execute_input": "2022-03-26T06:51:02.317632Z",
1464 |      "iopub.status.busy": "2022-03-26T06:51:02.276449Z",
1465 |      "iopub.status.idle": "2022-03-26T06:51:02.326354Z",
1466 |      "shell.execute_reply": "2022-03-26T06:51:02.325786Z",
1467 |      "shell.execute_reply.started": "2022-03-26T06:31:00.815830Z"
1468 |     },
1469 |     "papermill": {
1470 |      "duration": 0.112236,
1471 |      "end_time": "2022-03-26T06:51:02.326517",
1472 |      "exception": false,
1473 |      "start_time": "2022-03-26T06:51:02.214281",
1474 |      "status": "completed"
1475 |     },
1476 |     "tags": []
1477 |    },
1478 |    "outputs": [
1479 |     {
1480 |      "data": {
1481 |       "text/html": [
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1483 |        "                            \n",
1484 |        "var gd = document.getElementById('4b5aca8f-d88c-427d-b02f-26261a8a3f62');\n",
1485 |        "var x = new MutationObserver(function (mutations, observer) {{\n",
1486 |        "        var display = window.getComputedStyle(gd).display;\n",
1487 |        "        if (!display || display === 'none') {{\n",
1488 |        "            console.log([gd, 'removed!']);\n",
1489 |        "            Plotly.purge(gd);\n",
1490 |        "            observer.disconnect();\n",
1491 |        "        }}\n",
1492 |        "}});\n",
1493 |        "\n",
1494 |        "// Listen for the removal of the full notebook cells\n",
1495 |        "var notebookContainer = gd.closest('#notebook-container');\n",
1496 |        "if (notebookContainer) {{\n",
1497 |        "    x.observe(notebookContainer, {childList: true});\n",
1498 |        "}}\n",
1499 |        "\n",
1500 |        "// Listen for the clearing of the current output cell\n",
1501 |        "var outputEl = gd.closest('.output');\n",
1502 |        "if (outputEl) {{\n",
1503 |        "    x.observe(outputEl, {childList: true});\n",
1504 |        "}}\n",
1505 |        "\n",
1506 |        "                        })                };                });            </script>        </div>"
1507 |       ]
1508 |      },
1509 |      "metadata": {},
1510 |      "output_type": "display_data"
1511 |     }
1512 |    ],
1513 |    "source": [
1514 |     "#Least Pitch Amount Asked \n",
1515 |     "low=df[df[\"pitcher_ask_amount\"]<20]\n",
1516 |     "figure=px.bar(low, x='brand_name', y='pitcher_ask_amount',title=\"Lowest Pitch Ask Amount:\",text_auto=True, color='deal_amount',\n",
1517 |     "                    template=\"plotly_dark\")\n",
1518 |     "figure.show()"
1519 |    ]
1520 |   },
1521 |   {
1522 |    "cell_type": "markdown",
1523 |    "id": "7dce56d7",
1524 |    "metadata": {
1525 |     "papermill": {
1526 |      "duration": 0.034864,
1527 |      "end_time": "2022-03-26T06:51:02.396359",
1528 |      "exception": false,
1529 |      "start_time": "2022-03-26T06:51:02.361495",
1530 |      "status": "completed"
1531 |     },
1532 |     "tags": []
1533 |    },
1534 |    "source": [
1535 |     "Among the lowest pitch amout made by the brands, only \"Cocofit\" and \"Watt Technovations\" got the investment."
1536 |    ]
1537 |   },
1538 |   {
1539 |    "cell_type": "markdown",
1540 |    "id": "b22922a5",
1541 |    "metadata": {
1542 |     "papermill": {
1543 |      "duration": 0.034471,
1544 |      "end_time": "2022-03-26T06:51:02.466919",
1545 |      "exception": false,
1546 |      "start_time": "2022-03-26T06:51:02.432448",
1547 |      "status": "completed"
1548 |     },
1549 |     "tags": []
1550 |    },
1551 |    "source": [
1552 |     "The lowest amount pitch which sharks had made deal was Cocofit and Watt Technovations."
1553 |    ]
1554 |   },
1555 |   {
1556 |    "cell_type": "markdown",
1557 |    "id": "79403d41",
1558 |    "metadata": {
1559 |     "papermill": {
1560 |      "duration": 0.034891,
1561 |      "end_time": "2022-03-26T06:51:02.537052",
1562 |      "exception": false,
1563 |      "start_time": "2022-03-26T06:51:02.502161",
1564 |      "status": "completed"
1565 |     },
1566 |     "tags": []
1567 |    },
1568 |    "source": [
1569 |     "# **No. of brands the sharks have invested:**"
1570 |    ]
1571 |   },
1572 |   {
1573 |    "cell_type": "code",
1574 |    "execution_count": 13,
1575 |    "id": "bc849fb6",
1576 |    "metadata": {
1577 |     "execution": {
1578 |      "iopub.execute_input": "2022-03-26T06:51:02.610759Z",
1579 |      "iopub.status.busy": "2022-03-26T06:51:02.610011Z",
1580 |      "iopub.status.idle": "2022-03-26T06:51:02.711892Z",
1581 |      "shell.execute_reply": "2022-03-26T06:51:02.711212Z",
1582 |      "shell.execute_reply.started": "2022-03-26T06:31:10.334212Z"
1583 |     },
1584 |     "papermill": {
1585 |      "duration": 0.139792,
1586 |      "end_time": "2022-03-26T06:51:02.712038",
1587 |      "exception": false,
1588 |      "start_time": "2022-03-26T06:51:02.572246",
1589 |      "status": "completed"
1590 |     },
1591 |     "tags": []
1592 |    },
1593 |    "outputs": [
1594 |     {
1595 |      "data": {
1596 |       "text/html": [
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of deals done by individual shark:\"},\"barmode\":\"relative\"},                        {\"responsive\": true}                    ).then(function(){\n",
1598 |        "                            \n",
1599 |        "var gd = document.getElementById('dc22b382-1406-4a6e-a28f-1bfbfdc63956');\n",
1600 |        "var x = new MutationObserver(function (mutations, observer) {{\n",
1601 |        "        var display = window.getComputedStyle(gd).display;\n",
1602 |        "        if (!display || display === 'none') {{\n",
1603 |        "            console.log([gd, 'removed!']);\n",
1604 |        "            Plotly.purge(gd);\n",
1605 |        "            observer.disconnect();\n",
1606 |        "        }}\n",
1607 |        "}});\n",
1608 |        "\n",
1609 |        "// Listen for the removal of the full notebook cells\n",
1610 |        "var notebookContainer = gd.closest('#notebook-container');\n",
1611 |        "if (notebookContainer) {{\n",
1612 |        "    x.observe(notebookContainer, {childList: true});\n",
1613 |        "}}\n",
1614 |        "\n",
1615 |        "// Listen for the clearing of the current output cell\n",
1616 |        "var outputEl = gd.closest('.output');\n",
1617 |        "if (outputEl) {{\n",
1618 |        "    x.observe(outputEl, {childList: true});\n",
1619 |        "}}\n",
1620 |        "\n",
1621 |        "                        })                };                });            </script>        </div>"
1622 |       ]
1623 |      },
1624 |      "metadata": {},
1625 |      "output_type": "display_data"
1626 |     }
1627 |    ],
1628 |    "source": [
1629 |     "#No. of brands the sharks have invested:\n",
1630 |     "num_deal_shark=[df.ashneer_deal.sum(), df.anupam_deal.sum(), df.aman_deal.sum(), df.namita_deal.sum(), df.vineeta_deal.sum(), df.peyush_deal.sum(), df.ghazal_deal.sum()]\n",
1631 |     "all_sharks=[\"Ashneer\", \"Anupam\", \"Aman\", \"Namita\", \"Vineeta\", \"Peyush\", \"Ghazal\"]\n",
1632 |     "figure=px.bar(total_shark, x=all_sharks, y=num_deal_shark,title=\"Number of deals done by individual shark:\",color=all_sharks,text_auto=True,\n",
1633 |     "                    template=\"plotly_dark\")\n",
1634 |     "figure.show()"
1635 |    ]
1636 |   },
1637 |   {
1638 |    "cell_type": "markdown",
1639 |    "id": "97ebb13a",
1640 |    "metadata": {
1641 |     "papermill": {
1642 |      "duration": 0.035325,
1643 |      "end_time": "2022-03-26T06:51:02.783497",
1644 |      "exception": false,
1645 |      "start_time": "2022-03-26T06:51:02.748172",
1646 |      "status": "completed"
1647 |     },
1648 |     "tags": []
1649 |    },
1650 |    "source": [
1651 |     "# **Above 50% Equity taken by the shark in which brand:**"
1652 |    ]
1653 |   },
1654 |   {
1655 |    "cell_type": "code",
1656 |    "execution_count": 14,
1657 |    "id": "fada87e2",
1658 |    "metadata": {
1659 |     "execution": {
1660 |      "iopub.execute_input": "2022-03-26T06:51:02.865255Z",
1661 |      "iopub.status.busy": "2022-03-26T06:51:02.864564Z",
1662 |      "iopub.status.idle": "2022-03-26T06:51:02.933306Z",
1663 |      "shell.execute_reply": "2022-03-26T06:51:02.932705Z",
1664 |      "shell.execute_reply.started": "2022-03-26T06:36:50.105759Z"
1665 |     },
1666 |     "papermill": {
1667 |      "duration": 0.11439,
1668 |      "end_time": "2022-03-26T06:51:02.933466",
1669 |      "exception": false,
1670 |      "start_time": "2022-03-26T06:51:02.819076",
1671 |      "status": "completed"
1672 |     },
1673 |     "tags": []
1674 |    },
1675 |    "outputs": [
1676 |     {
1677 |      "data": {
1678 |       "text/html": [
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50% Equity taken by the shark in which brand:\"},\"barmode\":\"relative\"},                        {\"responsive\": true}                    ).then(function(){\n",
1680 |        "                            \n",
1681 |        "var gd = document.getElementById('d37ffba7-0550-4fb0-aad4-9ba3ce6135f6');\n",
1682 |        "var x = new MutationObserver(function (mutations, observer) {{\n",
1683 |        "        var display = window.getComputedStyle(gd).display;\n",
1684 |        "        if (!display || display === 'none') {{\n",
1685 |        "            console.log([gd, 'removed!']);\n",
1686 |        "            Plotly.purge(gd);\n",
1687 |        "            observer.disconnect();\n",
1688 |        "        }}\n",
1689 |        "}});\n",
1690 |        "\n",
1691 |        "// Listen for the removal of the full notebook cells\n",
1692 |        "var notebookContainer = gd.closest('#notebook-container');\n",
1693 |        "if (notebookContainer) {{\n",
1694 |        "    x.observe(notebookContainer, {childList: true});\n",
1695 |        "}}\n",
1696 |        "\n",
1697 |        "// Listen for the clearing of the current output cell\n",
1698 |        "var outputEl = gd.closest('.output');\n",
1699 |        "if (outputEl) {{\n",
1700 |        "    x.observe(outputEl, {childList: true});\n",
1701 |        "}}\n",
1702 |        "\n",
1703 |        "                        })                };                });            </script>        </div>"
1704 |       ]
1705 |      },
1706 |      "metadata": {},
1707 |      "output_type": "display_data"
1708 |     }
1709 |    ],
1710 |    "source": [
1711 |     "#Above 50% Equity taken by the shark in which brand?:\n",
1712 |     "df_equity=df[df['equity_per_shark']>=50]\n",
1713 |     "figure=px.bar(df_equity, x='brand_name', y='equity_per_shark',title=\"Above 50% Equity taken by the shark in which brand:\",text_auto=True, color='deal_amount',\n",
1714 |     "                    template=\"plotly_dark\")\n",
1715 |     "figure.show()"
1716 |    ]
1717 |   },
1718 |   {
1719 |    "cell_type": "code",
1720 |    "execution_count": 15,
1721 |    "id": "e180c83b",
1722 |    "metadata": {
1723 |     "execution": {
1724 |      "iopub.execute_input": "2022-03-26T06:51:03.021144Z",
1725 |      "iopub.status.busy": "2022-03-26T06:51:03.020361Z",
1726 |      "iopub.status.idle": "2022-03-26T06:51:03.023248Z",
1727 |      "shell.execute_reply": "2022-03-26T06:51:03.023812Z"
1728 |     },
1729 |     "papermill": {
1730 |      "duration": 0.050704,
1731 |      "end_time": "2022-03-26T06:51:03.023981",
1732 |      "exception": false,
1733 |      "start_time": "2022-03-26T06:51:02.973277",
1734 |      "status": "completed"
1735 |     },
1736 |     "tags": []
1737 |    },
1738 |    "outputs": [],
1739 |    "source": [
1740 |     "# Will do more analysis later on!!!"
1741 |    ]
1742 |   },
1743 |   {
1744 |    "attachments": {
1745 |     "605640ab-f43b-4c55-9264-3c41411c828c.jpg": {
1746 |      "image/jpeg": 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"
1747 |     }
1748 |    },
1749 |    "cell_type": "markdown",
1750 |    "id": "aa0e2583",
1751 |    "metadata": {
1752 |     "papermill": {
1753 |      "duration": 0.036344,
1754 |      "end_time": "2022-03-26T06:51:03.096973",
1755 |      "exception": false,
1756 |      "start_time": "2022-03-26T06:51:03.060629",
1757 |      "status": "completed"
1758 |     },
1759 |     "tags": []
1760 |    },
1761 |    "source": [
1762 |     "![2.jpg](attachment:605640ab-f43b-4c55-9264-3c41411c828c.jpg)"
1763 |    ]
1764 |   }
1765 |  ],
1766 |  "metadata": {
1767 |   "kernelspec": {
1768 |    "display_name": "Python 3",
1769 |    "language": "python",
1770 |    "name": "python3"
1771 |   },
1772 |   "language_info": {
1773 |    "codemirror_mode": {
1774 |     "name": "ipython",
1775 |     "version": 3
1776 |    },
1777 |    "file_extension": ".py",
1778 |    "mimetype": "text/x-python",
1779 |    "name": "python",
1780 |    "nbconvert_exporter": "python",
1781 |    "pygments_lexer": "ipython3",
1782 |    "version": "3.7.12"
1783 |   },
1784 |   "papermill": {
1785 |    "default_parameters": {},
1786 |    "duration": 16.657092,
1787 |    "end_time": "2022-03-26T06:51:03.944176",
1788 |    "environment_variables": {},
1789 |    "exception": null,
1790 |    "input_path": "__notebook__.ipynb",
1791 |    "output_path": "__notebook__.ipynb",
1792 |    "parameters": {},
1793 |    "start_time": "2022-03-26T06:50:47.287084",
1794 |    "version": "2.3.3"
1795 |   }
1796 |  },
1797 |  "nbformat": 4,
1798 |  "nbformat_minor": 5
1799 | }
1800 | 


--------------------------------------------------------------------------------