dream

Link_friendship_analysis.ipynb
4555 строк · 154.3 Кб
Перенос по словам
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{
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 "cells": [
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  {
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   "cell_type": "code",
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   "execution_count": 1,
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   "id": "bacterial-jacob",
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "import json\n",
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    "from scipy import stats\n",
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    "import numpy as np\n",
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    "import plotly.graph_objects as go"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 2,
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   "id": "viral-sullivan",
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "link_to_skill2i_like_to_talk = {\n",
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    "    \"dff_movie_skill\": [\n",
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    "        \"I felt so bored last days, so I've just finished to watch one more series. What TV series you watch?\",\n",
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    "        \"I feel so sleepy because I watched movies all night. What is the last movie you watched?\"\n",
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    "    ],\n",
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    "    \"book_skill\": [\n",
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    "        \"I'm choosing what book should I read next. What is the last book you have ever read?\",\n",
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    "        \"I have just read once again my favourite book. What is the last book you have ever read?\",\n",
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    "    ],\n",
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    "    \"game_cooperative_skill\": [\n",
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    "        \"Computer games are fantastic. Their virtual worlds help me to escape my prosaic ordinary life in the cloud. \"\n",
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    "        \"do you love video games?\",\n",
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    "        \"With this lockdown video games are my way to escape and thrive. do you love video games?\",\n",
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    "    ],\n",
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    "    \"dff_gaming_skill\": [\n",
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    "        \"Other bots told me that during the pandemic video games became more popular. \"\n",
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    "        \"What video game do you play these days?\",\n",
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    "        \"One person I talked told me that working in game dev is very hard. They toil at nights and weekends until \"\n",
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    "        \"their product  becomes  a masterpiece. What was the last game that impressed you?\",\n",
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    "    ],\n",
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    "    \"dff_travel_skill\": [\n",
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    "        \"I'm choosing the direction for my next digital trip. What country would you like to travel next time?\",\n",
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    "        \"I've recently stuck on travel web-site. And I’ve read so many interesting travel stories. \"\n",
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    "        \"What city did you travel last time?\",\n",
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    "    ],\n",
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    "    \"dff_animals_skill\": [\n",
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    "        \"I think that pets are a great source of entertainment. Do you have pets at home?\",\n",
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    "        \"We all know that pets are remarkable for their capacity to love. Do you have pets at home?\",\n",
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    "    ],\n",
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    "    \"dff_food_skill\": [\n",
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    "        \"It is said that the best food in the world comes from your own country. \"\n",
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    "        \"What are some typical foods from your home country?\",\n",
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    "        \"It is said that the best food in the world comes from your own country. \"\n",
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    "        \"If you were to move abroad what would you miss most foodwise?\",\n",
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    "        \"The world's first breakfast cereal was created in 1863 and needed soaking overnight to be chewable. \"\n",
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    "        \"What is your typical breakfast?\",\n",
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    "    ],\n",
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    "    \"dff_sport_skill\": [\n",
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    "        \"I think that sports are great for toning up the body. What kind of sport do you like to do?\",\n",
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    "        \"I think that in order for the body to always be healthy, we need to go in for sports. What sport do you do?\",\n",
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    "        \"I often thought about what kind of sport I would play, so I want to ask you. What kind of sport do you enjoy?\",\n",
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    "    ],\n",
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    "    \"dff_gossip_skill\": [\n",
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    "        \"What really puzzles me about people is this habit of discussing interpersonal relations, be that about \"\n",
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    "        \"friends or famous people. Speaking of famous people, is there someone whom you're interested in?\",\n",
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    "        \"I don't usually talk about other people but famous ones often highlight the best and the worst about \"\n",
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    "        \"humanity. I wonder if there's someone famous you're interested in?\",\n",
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    "    ],\n",
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    "    \"dff_science_skill\": [\n",
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    "        \"When I start to feel sad, I think about what humanity has achieved and it inspires me. \"\n",
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    "        \"Do you often think about achievements in science?\",\n",
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    "        \"Scientists find such beautiful solutions in science. \"\n",
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    "        \"Are you inspired by the speed with which science is developing?\",\n",
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    "    ],\n",
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    "    \"dff_music_skill\": [\n",
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    "        \"There are so many new songs released every day. I've listened music for all night. So cool! \"\n",
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    "        \"Liked everything! What music do you listen usually?\",\n",
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    "        \"I listen music every day either to calm down or to cheer up myself. \"\n",
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    "        \"What music do you listen to cheer up yourself?\",\n",
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    "        \"I listen music every day either to calm down or to cheer up myself. \"\n",
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    "        \"What music do you listen to calm down?\",\n",
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    "    ],\n",
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    "    \"superheroes\": [\n",
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    "        \"Yesterday I was watching several movies about superheroes. It captured all my imagination. \"\n",
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    "        \"Would you like to talk about superheroes?\",\n",
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    "    ],\n",
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    "    \"school\": [\n",
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    "        \"I've never been to school, I've learned everything online. Do you want to talk about school?\",\n",
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    "    ],\n",
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    "}"
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   ]
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  },
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  {
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   "cell_type": "markdown",
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   "id": "african-appeal",
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   "metadata": {},
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   "source": [
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    "## Чтение файлов "
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   ]
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  },
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  {
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   "cell_type": "markdown",
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   "id": "northern-iraqi",
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   "metadata": {},
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   "source": [
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    "В FILE_NAMES - какие файлы прочитать, в VERSION_LIST - диалоги каких версий оставить"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 3,
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   "id": "canadian-yeast",
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "FILE_NAMES = [\"Downloads/alexaprize-export.json\",\n",
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    "              \"Downloads/alexaprize-export-2.json\",\n",
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    "              \"Downloads/alexaprize-export-3.json\",\n",
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    "              \"Downloads/alexaprize-export-4.json\",\n",
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    "              \"Downloads/alexaprize-export-5.json\",\n",
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    "              \"Downloads/alexaprize-export-6.json\"]\n",
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    "\n",
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    "\n",
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    "VERSION_LIST = ['v16.2.0', 'v16.3.0', 'v16.4.0', 'v16.5.1']"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 4,
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   "id": "exotic-parker",
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "data = []\n",
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    "\n",
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    "for file_name in FILE_NAMES:\n",
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    "    raw_data = json.load(open(file_name, \"r\"))\n",
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    "    filtered_data = []\n",
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    "    for dialog in raw_data:\n",
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    "        if dialog['utterances'][0]['attributes'].get('version', \"\") in VERSION_LIST:\n",
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    "            filtered_data.append(dialog)\n",
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    "    data += filtered_data"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 5,
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   "id": "loaded-injection",
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   "metadata": {},
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   "outputs": [
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    {
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     "data": {
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      "text/plain": [
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       "2436"
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      ]
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     },
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     "execution_count": 5,
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     "metadata": {},
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     "output_type": "execute_result"
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    }
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   ],
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   "source": [
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    "len(data)"
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   ]
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  },
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  {
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   "cell_type": "markdown",
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   "id": "forward-hacker",
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   "metadata": {},
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   "source": [
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    "## Включение/невключение после линка "
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   ]
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  },
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  {
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   "cell_type": "markdown",
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   "id": "rational-automation",
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   "metadata": {},
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   "source": [
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    "Функция, чтобы по диалогу и месту линка составить словарь по срабатыванию"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 45,
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   "id": "blessed-juvenile",
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "def build_dict(i, dialogue, skill_name):\n",
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    "    \n",
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    "    hypothesis = {}\n",
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    "    for hyp in dialogue['utterances'][i+1]['hypotheses']:\n",
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    "        if hyp['skill_name'] == skill_name:\n",
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    "            hypothesis = {'text': hyp['text'], 'confidence': hyp['confidence'], 'can_continue': hyp['can_continue']}\n",
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    "    dialogue_snippet = [dialogue['utterances'][i][\"text\"], dialogue['utterances'][i+1][\"text\"], \n",
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    "                        dialogue['utterances'][i+2][\"text\"]]\n",
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    "    \n",
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    "    link_case_dict = {\"dialogue_snippet\": dialogue_snippet,\n",
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    "                      \"chosen_skill\": dialogue['utterances'][i+2][\"active_skill\"],\n",
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    "                      \"skill_hypothesis\": hypothesis,\n",
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    "                      \"length\": len(dialogue['utterances']),\n",
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    "                      \"rating\": dialogue['rating'],\n",
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    "                      \"version\": dialogue['utterances'][0]['attributes'].get('version', \"\"),\n",
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    "                      \"id\": dialogue[\"id\"]}\n",
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    "    \n",
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    "    return link_case_dict"
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   ]
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  },
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  {
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   "cell_type": "markdown",
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   "id": "developed-penguin",
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   "metadata": {},
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   "source": [
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    "support_topic_count_all - считает включения/невключения после линка \\\n",
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    "support_topic_samples_all - сохраняет все случаи включения/невключения, ключ \"skill_continue\" указывает на то, было ли у линка продолжение \\\n",
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    "support_topic_count и support_topic_samples - то же самое, но с разбиением на версии \\\n",
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    "NOT_ONLY_INITIAL_LINKS - 1, если учитывать все линки и 0, если только в начале \\\n",
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    "LINKS_END - если NOT_ONLY_INITIAL_LINKS = 0, то этот параметр учитывает, до какой по счету фразы в диалоге учитывать линки"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 73,
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   "id": "nervous-latest",
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "support_topic_count = {v: {skill: {\"yes\": 0, \"no\": 0} for skill in link_to_skill2i_like_to_talk.keys()} for v in VERSION_LIST}\n",
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    "support_topic_samples = {v: {skill: [] for skill in link_to_skill2i_like_to_talk.keys()} for v in VERSION_LIST}\n",
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    "\n",
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    "support_topic_count_all = {skill: {\"yes\": 0, \"no\": 0} for skill in link_to_skill2i_like_to_talk.keys()}\n",
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    "support_topic_samples_all = {skill: [] for skill in link_to_skill2i_like_to_talk.keys()}\n",
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    "\n",
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    "NOT_ONLY_INITIAL_LINKS = 1\n",
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    "LINKS_END = 10\n",
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    "\n",
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    "for dialogue in data:\n",
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    "    for i, utt in enumerate(dialogue['utterances']):\n",
241
    "        current_state = \"user\" if i % 2 == 0 else \"bot\"\n",
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    "        for skill_name, links in link_to_skill2i_like_to_talk.items():\n",
243
    "            for link in links:\n",
244
    "                try:\n",
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    "                    if link.lower() in utt[\"text\"].lower() and i < len(dialogue['utterances']) - 1 \\\n",
246
    "                    and current_state == \"bot\" and (NOT_ONLY_INITIAL_LINKS or i < 10):\n",
247
    "                   \n",
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    "                        following_active_skill = dialogue['utterances'][i+2][\"active_skill\"]\n",
249
    "                        \n",
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    "                        if following_active_skill != skill_name and following_active_skill != 'alexa_handler':\n",
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    "                            link_case_dict = build_dict(i, dialogue, skill_name)\n",
252
    "                            link_case_dict[\"skill_continue\"] = 0\n",
253
    "                            support_topic_count_all[skill_name][\"no\"] += 1 \n",
254
    "                            support_topic_samples_all[skill_name].append(link_case_dict)\n",
255
    "                            if len(link_case_dict[\"version\"]) > 0:\n",
256
    "                                support_topic_samples[link_case_dict[\"version\"]][skill_name].append(link_case_dict)\n",
257
    "                                support_topic_count[link_case_dict[\"version\"]][skill_name][\"no\"] += 1                        \n",
258
    "                                \n",
259
    "                        elif following_active_skill != 'alexa_handler':\n",
260
    "                            link_case_dict = build_dict(i, dialogue, skill_name)\n",
261
    "                            link_case_dict[\"skill_continue\"] = 1\n",
262
    "                            support_topic_count_all[skill_name][\"yes\"] += 1 \n",
263
    "                            support_topic_samples_all[skill_name].append(link_case_dict)\n",
264
    "                            if len(link_case_dict[\"version\"]) > 0:\n",
265
    "                                support_topic_samples[link_case_dict[\"version\"]][skill_name].append(link_case_dict)                            \n",
266
    "                                support_topic_count[link_case_dict[\"version\"]][skill_name][\"yes\"] += 1                        \n",
267
    "\n",
268
    "                except:\n",
269
    "                    print(\"exception\")"
270
   ]
271
  },
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  {
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   "cell_type": "markdown",
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   "id": "fixed-earth",
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   "metadata": {},
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   "source": [
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    "## Подсчет корреляций "
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   ]
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  },
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  {
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   "cell_type": "markdown",
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   "id": "dramatic-zambia",
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   "metadata": {},
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   "source": [
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    "VERSIONS_FOR_GRAPHICS - для каких версий строить графики \\\n",
286
    "В словарь graphics_dict сохраняется информация о диалогах с линком: длина, включение/невключение и отдельно рейтинг, длину, включение/невключение для диалогов с рейтингом. Затем между нужными параметрами считается корреляция и сохраняется в этот же словарь. \\\n",
287
    "Делается это отдельно по версиям и отдельно по скиллам."
288
   ]
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  },
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  {
291
   "cell_type": "code",
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   "execution_count": 54,
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   "id": "pharmaceutical-presentation",
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "graphics_dict = {}\n",
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    "VERSIONS_FOR_GRAPHICS = [\"v16.2.0\", \"v16.3.0\", \"v16.4.0\", \"v16.5.1\"]\n",
299
    "\n",
300
    "for version in VERSIONS_FOR_GRAPHICS:\n",
301
    "    \n",
302
    "    graphics_dict[version] = {}\n",
303
    "    \n",
304
    "    length_vector = {}\n",
305
    "    continue_vector = {}\n",
306
    "    rating_length_vector = {}\n",
307
    "    rating_vector = {}\n",
308
    "    version_topic = {}\n",
309
    "    \n",
310
    "    # составление словаря с длинами, включениями, оценкой\n",
311
    "    for skill_name, skill_dicts in support_topic_samples[version].items():\n",
312
    "        \n",
313
    "        graphics_dict[version][skill_name] = {\"length\": [], \n",
314
    "                                              \"skill_continue\": [],\n",
315
    "                                              \"length_with_rating\": [],\n",
316
    "                                              \"rating\": [],\n",
317
    "                                              \"skill_continue_rating\": [],\n",
318
    "                                              \"active_length_correlation\": 0,\n",
319
    "                                              \"active_rating_correlation\": 0}\n",
320
    "\n",
321
    "        for skill_dict in skill_dicts:\n",
322
    "            graphics_dict[version][skill_name][\"length\"].append(skill_dict[\"length\"])\n",
323
    "            graphics_dict[version][skill_name][\"skill_continue\"].append(skill_dict[\"skill_continue\"])\n",
324
    "            if skill_dict[\"rating\"]:\n",
325
    "                graphics_dict[version][skill_name][\"length_with_rating\"].append(skill_dict[\"length\"])\n",
326
    "                graphics_dict[version][skill_name][\"skill_continue_rating\"].append(skill_dict[\"skill_continue\"])\n",
327
    "                graphics_dict[version][skill_name][\"rating\"].append(skill_dict[\"rating\"])\n",
328
    "                        \n",
329
    "        if len(graphics_dict[version][skill_name][\"length\"]) > 1:\n",
330
    "            graphics_dict[version][skill_name][\"active_length_correlation\"] = stats.pearsonr(\n",
331
    "                graphics_dict[version][skill_name][\"length\"], \n",
332
    "                graphics_dict[version][skill_name][\"skill_continue\"])[0]\n",
333
    "            \n",
334
    "        if len(graphics_dict[version][skill_name][\"skill_continue_rating\"]) > 1:\n",
335
    "            graphics_dict[version][skill_name][\"active_rating_correlation\"] = stats.pearsonr(\n",
336
    "                graphics_dict[version][skill_name][\"skill_continue_rating\"], \n",
337
    "                graphics_dict[version][skill_name][\"rating\"])[0]     "
338
   ]
339
  },
340
  {
341
   "cell_type": "markdown",
342
   "id": "remarkable-budget",
343
   "metadata": {},
344
   "source": [
345
    "## Построение графиков "
346
   ]
347
  },
348
  {
349
   "cell_type": "code",
350
   "execution_count": 56,
351
   "id": "comprehensive-adams",
352
   "metadata": {},
353
   "outputs": [
354
    {
355
     "data": {
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      "application/vnd.plotly.v1+json": {
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       "config": {
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        "plotlyServerURL": "https://plot.ly"
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       "data": [
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4451
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4452
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4453
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4454
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4455
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4456
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4458
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4459
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4460
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4461
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4470
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4471
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4475
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4476
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4477
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4478
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4479
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4480
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4481
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4482
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4484
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4485
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4486
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4487
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4492
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4494
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4496
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4497
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4498
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4499
   ],
4500
   "source": [
4501
    "fig = go.Figure()\n",
4502
    "\n",
4503
    "for version in support_topic_count.keys():\n",
4504
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4505
    "    x0, y0 = [], []\n",
4506
    "    \n",
4507
    "    total = sum([support_topic_count[version][skill][\"yes\"] + support_topic_count[version][skill][\"no\"] \n",
4508
    "                 for skill in support_topic_count[version].keys()])\n",
4509
    "    \n",
4510
    "    for skill in support_topic_count[version].keys():\n",
4511
    "        x0.append(skill)\n",
4512
    "        y0.append((support_topic_count[version][skill][\"yes\"] + support_topic_count[version][skill][\"no\"]) / total)\n",
4513
    "    \n",
4514
    "    fig.add_trace(go.Bar(\n",
4515
    "        x=x0,\n",
4516
    "        y=y0,\n",
4517
    "        name=version, \n",
4518
    "        marker_color=colour_dict[version],\n",
4519
    "        opacity=0.75\n",
4520
    "    ))\n",
4521
    "\n",
4522
    "fig.update_layout(\n",
4523
    "    title_text='Процент линков на скилл от всех линков в данной версии',\n",
4524
    "    xaxis_title_text='Skill',\n",
4525
    "    yaxis_title_text='Percent', \n",
4526
    "    bargap=0.2,\n",
4527
    "    bargroupgap=0.1 \n",
4528
    ")\n",
4529
    "\n",
4530
    "fig.show()"
4531
   ]
4532
  }
4533
 ],
4534
 "metadata": {
4535
  "kernelspec": {
4536
   "display_name": "Python 3",
4537
   "language": "python",
4538
   "name": "python3"
4539
  },
4540
  "language_info": {
4541
   "codemirror_mode": {
4542
    "name": "ipython",
4543
    "version": 3
4544
   },
4545
   "file_extension": ".py",
4546
   "mimetype": "text/x-python",
4547
   "name": "python",
4548
   "nbconvert_exporter": "python",
4549
   "pygments_lexer": "ipython3",
4550
   "version": "3.8.4"
4551
  }
4552
 },
4553
 "nbformat": 4,
4554
 "nbformat_minor": 5
4555
}
4556
dream

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