InstaBot - Part 2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1c0c9c75",
   "metadata": {},
   "source": [
    "# INSTABOT PART 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbf7d9c8",
   "metadata": {},
   "source": [
    "### (LOGIN FUNCTION) we willl need these two function to perform further"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "68fff631",
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "from selenium import webdriver\n",
    "from selenium.webdriver.common.by import By\n",
    "from bs4 import BeautifulSoup as bs\n",
    "from selenium.webdriver.support.ui import WebDriverWait\n",
    "from selenium.webdriver.support import expected_conditions as EC\n",
    "import chromedriver_autoinstaller\n",
    "\n",
    "chromedriver_autoinstaller.install()\n",
    "sample_username = 'USER_NAME'\n",
    "sample_psw = 'PASSWORD'\n",
    "driver = webdriver.Chrome()\n",
    "\n",
    "def login(sample_user, sample_pswd, driver):\n",
    "    driver.get(\"https://instagram.com\")\n",
    "    time.sleep(3)\n",
    "    driver.maximize_window()\n",
    "    \n",
    "    user = driver.find_elements(By.XPATH, '//input[contains(@class, \"_aa4b _add6 _ac4d\")]')[0]\n",
    "    psw = driver.find_elements(By.XPATH, '//input[contains(@class, \"_aa4b _add6 _ac4d\")]')[1]\n",
    "    \n",
    "    user.send_keys(sample_username)\n",
    "    psw.send_keys(sample_psw)\n",
    "    login = driver.find_element(By.XPATH, '//button[contains(@class, \"_acan _acap _acas _aj1-\")]')\n",
    "    login.click()\n",
    "\n",
    "login(sample_username, sample_psw, driver)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bae507e",
   "metadata": {},
   "source": [
    "### (SEARCH FOOD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "afab3995",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['food_tour_ent', 'bhopalfoodwalks', 'bhopalfoodlovers', 'indian_tasty_food', 'streetfoodbhopal', 'indore_streetfood', 'food', 'travelbitess', '_foodie.af_', 'bhopalfoodgram', 'foodenza_bhopal', 'food_street_indore', 'indori_foodiess', 'bhopalifoodguru', 'chocoheaven_deeply_divine', 'bhopali_foodies_', 'food_vlogs_and_recipes', 'food_blog_bhopal', 'foodpharmer', 'maldives.explores', 'china.travels', 'kawalpreet_kaur_kalsi', '__vaishali_sharma', 'usa.explores', 'explorer_bhaiya', 'roamingferalcat', 'bhookh_bakar_baithak', '_food.is.good._', 'ganeshamfastfoodbhopal', 'dietitiandeanna', '__food.fanatic__', 'indorefooddelicacy', 'rays.indorefoodcourt', 'food_unlock_official', 'japan.explores', 'thailand.explores', 'indorefoodexplorer', 'foodtemptationsbhopal', 'miami.explorers', 'paragbakery_and_fast_food', 'foodie_batra', 'chai_ke_aashik', 'foodie_traveler___', 'food_prismmm', 'ishita_neema', 'utsahfood', 'indori_food_rider', 'foodiliciouscravings', 'sweettweapon_']\n"
     ]
    }
   ],
   "source": [
    "def search(query, driver):\n",
    "    srch_button = driver.find_elements(By.CLASS_NAME, '_ab6-')[2]\n",
    "    srch_button.click()\n",
    "    srch_text = driver.find_element(By.XPATH, '//div//input[@aria-label=\"Search input\"]')\n",
    "    srch_text.send_keys(query) \n",
    "    time.sleep(4)\n",
    "    # Extracting all ig handles that comes when we search food or any query\n",
    "    all_ig_handle = driver.find_elements(By.XPATH, '//div[contains(@class, \"x9f619 xjbqb8w x78zum5 x168nmei x13lgxp2 x5pf9jr xo71vjh x1uhb9sk x1plvlek xryxfnj x1c4vz4f x2lah0s x1q0g3np xqjyukv x6s0dn4 x1oa3qoh x1nhvcw1\")]')\n",
    "    users_names = []\n",
    "    #printing all ig handles\n",
    "    for user in all_ig_handle:\n",
    "        handle_name = user.find_element(By.TAG_NAME, 'span').text\n",
    "        if handle_name != \"\":\n",
    "            users_names.append(handle_name)\n",
    "    driver.find_elements(By.CLASS_NAME, \"_ab6-\")[1].click()\n",
    "    return users_names\n",
    "\n",
    "query = 'food'\n",
    "print(search(query, driver))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4da8be15",
   "metadata": {},
   "source": [
    "### OPENING PROFILE OF ANY SEARCH QUERY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "295fab3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def search_user(query, driver):\n",
    "    \n",
    "    srch_button = driver.find_elements(By.CLASS_NAME, '_ab6-')[2]\n",
    "    srch_button.click()\n",
    "    WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "                                                    '//div[contains(@class, \"_aaw6\")]')))\n",
    "    time.sleep(3)\n",
    "    \n",
    "    srch_text = driver.find_element(By.XPATH, '//div//input[@aria-label=\"Search input\"]')\n",
    "    srch_text.send_keys(query)\n",
    "    \n",
    "    WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.XPATH, f'//span[text()=\"{query}\"]')))\n",
    "    \n",
    "    driver.find_element(By.XPATH, f'//span[text()=\"{query}\"]').click()\n",
    "    \n",
    "search_user(\"sodelhi\", driver)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ec71222",
   "metadata": {},
   "source": [
    "# INSTABOT PART 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a995cc45",
   "metadata": {},
   "source": [
    "### FIRST TASK (ANALYZE BEHAVIOR OF BLOGGERS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8ad7c12b",
   "metadata": {},
   "outputs": [],
   "source": [
    "login(sample_username, sample_psw, driver)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3378b96a",
   "metadata": {},
   "outputs": [],
   "source": [
    "first_10 = search('food', driver)[:10] # actually if i takes first 10 then there is not much user handles, so im first searching all handles\n",
    "# after searching all handles i will arrange it on descending order of their followers. and take out top 5 after that"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8ecc4525",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['food_tour_ent',\n",
       " 'bhopalfoodwalks',\n",
       " 'bhopalfoodlovers',\n",
       " 'indian_tasty_food',\n",
       " 'streetfoodbhopal',\n",
       " 'indore_streetfood',\n",
       " 'food',\n",
       " 'travelbitess',\n",
       " '_foodie.af_',\n",
       " 'bhopalfoodgram']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "first_10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a5d1a5ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "user_followers = {}\n",
    "def extract_followers_num(driver, all_handles):\n",
    "    for query in all_handles:\n",
    "        search_user(query, driver)\n",
    "        WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH, '//ul[contains(@class, \"x78zum5 x1q0g3np xieb3on\")]')))\n",
    "\n",
    "        html = driver.find_elements(By.XPATH, '//ul[contains(@class, \"x78zum5 x1q0g3np xieb3on\")]/li')[1].get_attribute('innerHTML')\n",
    "        data = bs(html, \"html.parser\")\n",
    "        follower_num = int(data.find('span')['title'].replace(',',\"\"))\n",
    "\n",
    "        user_followers[query] = follower_num\n",
    "        \n",
    "        home_btn = driver.find_element(By.CLASS_NAME, \"_ab6-\")\n",
    "        home_btn.click()\n",
    "        time.sleep(4)\n",
    "\n",
    "    return user_followers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f417599b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract_followers_num(driver, first_10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "22c0662f",
   "metadata": {},
   "outputs": [],
   "source": [
    "followers_count = extract_followers_num(driver,first_10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "48f7f47b",
   "metadata": {},
   "outputs": [],
   "source": [
    "followers_count = dict(sorted(followers_count.items(), key=lambda item: item[1], reverse = True)[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2b9c5f4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'food': 182580,\n",
       " 'bhopalfoodwalks': 30202,\n",
       " 'indian_tasty_food': 18907,\n",
       " '_foodie.af_': 14931,\n",
       " 'travelbitess': 12632}"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "followers_count # THESE ARE THE TOP 5 HANDLES WHICH HAVE MOST NUMBER OF FOLLOWERS IN DESCENDING ORDER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "12b6ad3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now we will find the number of posts they have did in previous 3 days\n",
    "import datetime\n",
    "today_date = datetime.date.today()\n",
    "_3_days_ago = today_date-datetime.timedelta(days = 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "58fe741c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date(2023, 6, 22)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_3_days_ago"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "id": "8f362e34",
   "metadata": {},
   "outputs": [],
   "source": [
    "# so we will compare if the date in post is greater than the _3_days_ago date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "e7cfddb2",
   "metadata": {},
   "outputs": [],
   "source": [
    "posts_date = driver.find_element(By.CLASS_NAME, \"_aaqe\").get_attribute('title')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0c1d5aed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date(2022, 3, 9)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now i will convert this date into datetime object\n",
    "date_object = datetime.datetime.strptime(posts_date, \"%b %d, %Y\").date()\n",
    "date_object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "2ee02e46",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_posts_count(driver, users):\n",
    "    posts_count = {}\n",
    "    for user in users:\n",
    "        posts_count[user] = 0\n",
    "        search_user(user, driver)\n",
    "        time.sleep(3)\n",
    "        WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH, '//div[contains(@class, \"_ac7v  _al3n\")]')))\n",
    "        driver.find_element(By.CLASS_NAME, '_aagu').click()\n",
    "\n",
    "        current_date = datetime.date.today()\n",
    "        _3_days_ago = current_date-datetime.timedelta(days = 3)\n",
    "        time.sleep(2)\n",
    "        posts_date = driver.find_element(By.CLASS_NAME, \"_aaqe\").get_attribute('title')\n",
    "        date_object = datetime.datetime.strptime(posts_date, \"%b %d, %Y\").date()\n",
    "\n",
    "        while date_object>=_3_days_ago:\n",
    "            if date_object == current_date:\n",
    "                WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "                    '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "                time.sleep(2)\n",
    "                posts_date = driver.find_element(By.CLASS_NAME, \"_aaqe\").get_attribute('title')\n",
    "                date_object = datetime.datetime.strptime(posts_date, \"%b %d, %Y\").date()\n",
    "            elif user in posts_count:\n",
    "                posts_count[user]+=1\n",
    "                WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "                    '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "                time.sleep(2)\n",
    "                posts_date = driver.find_element(By.CLASS_NAME, \"_aaqe\").get_attribute('title')\n",
    "                date_object = datetime.datetime.strptime(posts_date, \"%b %d, %Y\").date()\n",
    "\n",
    "            else:\n",
    "                posts_count[user] = 1\n",
    "                WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "                    '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "                time.sleep(2)\n",
    "                posts_date = driver.find_element(By.CLASS_NAME, \"_aaqe\").get_attribute('title')\n",
    "                date_object = datetime.datetime.strptime(posts_date, \"%b %d, %Y\").date()\n",
    "        driver.back()\n",
    "        driver.back()\n",
    "\n",
    "    WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH, '//div//span[text() = \"Home\"]'))).click()\n",
    "    return posts_count\n",
    "\n",
    "users = []\n",
    "for x in followers_count.keys():\n",
    "    users.append(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "e84f3234",
   "metadata": {},
   "outputs": [],
   "source": [
    "posts_count = extract_posts_count(driver,users)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "8b8d0f92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'food': 2,\n",
       " 'bhopalfoodwalks': 0,\n",
       " 'indian_tasty_food': 0,\n",
       " '_foodie.af_': 0,\n",
       " 'travelbitess': 0}"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "posts_count"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "350d838c",
   "metadata": {},
   "source": [
    "#### Plotting graph of handles vs number of followers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "991f9f8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "2590eea7",
   "metadata": {},
   "outputs": [],
   "source": [
    "users = list(followers_count.keys())\n",
    "followers = list(followers_count.values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "985727ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(users,followers, color = 'blue')\n",
    "plt.xticks(rotation = 45)\n",
    "plt.xlabel(\"Instagram Handle\",fontweight = \"bold\", size = 13)\n",
    "plt.ylabel(\"Followers\", fontweight = \"bold\", size = 13)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c86a1a8",
   "metadata": {},
   "source": [
    "#### Plotting graph of instagram handle vs posts count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "548bb1e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "user_name = list(posts_count.keys())\n",
    "post_count = list(posts_count.values())\n",
    "plt.bar(user_name, post_count, color = 'red')\n",
    "plt.xticks(rotation = 45) # Here the users haven't posted anything that's why some bars are not visible\n",
    "plt.xlabel(\"Instagram Handle\",fontweight = \"bold\", size = 13)\n",
    "plt.ylabel(\"Followers\", fontweight = \"bold\", size = 13)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5ae1cc2",
   "metadata": {},
   "source": [
    "### Second Task ( LIST OF HASHTAGS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "a15d399b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_hash_tags(handle_names, driver):\n",
    "    tags = {}\n",
    "    for user in handle_names:\n",
    "        search_user(user, driver)\n",
    "        time.sleep(3)\n",
    "        WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH, '//div[contains(@class, \"_ac7v  _al3n\")]')))\n",
    "        driver.find_element(By.CLASS_NAME, '_aagu').click()\n",
    "        \n",
    "        for i in range(10):\n",
    "            hash_tags = driver.find_elements(By.XPATH, '//a[contains(@class, \"x1i10hfl xjbqb8w x6umtig x1b1mbwd xaqea5y xav7gou x9f619 x1ypdohk xt0psk2 xe8uvvx xdj266r x11i5rnm xat24cr x1mh8g0r xexx8yu x4uap5 x18d9i69 xkhd6sd x16tdsg8 x1hl2dhg xggy1nq x1a2a7pz  _aa9_ _a6hd\")]')\n",
    "            for tag in hash_tags:\n",
    "                tag = tag.text.split(\"#\")[1]\n",
    "                if tag in tags:\n",
    "                    tags[tag]+=1\n",
    "                else:\n",
    "                    tags[tag] = 1\n",
    "            WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "                                            '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "        driver.back()\n",
    "        driver.back()\n",
    "        \n",
    "    return tags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "93f10fc6",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_hash_tags = extract_hash_tags(list(followers_count.keys()), driver)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "9832d3b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "372"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_hash_tags)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "64545f63",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.DataFrame({\"Word\":list(all_hash_tags.keys()), \"frequency\":list(all_hash_tags.values())})\n",
    "df = df.sort_values(by='frequency', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "523cc068",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('Words.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "8d2dfd91",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['bhopal', 'bhopalblogger', 'bhopalfoodblogger', 'bhopalfoodies', 'bhopalfoodwalk']\n"
     ]
    }
   ],
   "source": [
    "ans = df['Word'].to_list()[:5] # extracting top 5 hashtags\n",
    "print(ans)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "8bea9c66",
   "metadata": {},
   "outputs": [],
   "source": [
    "# SINCE THE QUESTION ASK ME TO FIND THE NUMBER OF TIMES THE HASHTAG HAS BEEN USED BY ALL 5 USER I HAVE TO AGAIN CHECK IT BY SCRAPING POSTS\n",
    "\n",
    "def hash_tags_count(handle_names, driver, tags):\n",
    "    hash_user_count = {}\n",
    "    for user in handle_names:\n",
    "        count = 0\n",
    "        search_user(user, driver)\n",
    "        time.sleep(4)\n",
    "        WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH, '//div[contains(@class, \"_ac7v  _al3n\")]')))\n",
    "        driver.find_element(By.CLASS_NAME, '_aagu').click()\n",
    "        \n",
    "        tags_lst = []\n",
    "        for i in range(10):\n",
    "            hash_tags = driver.find_elements(By.XPATH, '//a[contains(@class, \"x1i10hfl xjbqb8w x6umtig x1b1mbwd xaqea5y xav7gou x9f619 x1ypdohk xt0psk2 xe8uvvx xdj266r x11i5rnm xat24cr x1mh8g0r xexx8yu x4uap5 x18d9i69 xkhd6sd x16tdsg8 x1hl2dhg xggy1nq x1a2a7pz  _aa9_ _a6hd\")]')\n",
    "            for tag in hash_tags:\n",
    "                tag = tag.text.split(\"#\")[1]\n",
    "                tags_lst.append(tag)\n",
    "            \n",
    "            for pop_tag in tags:\n",
    "                if pop_tag in tags_lst:\n",
    "                    count+=tags_lst.count(pop_tag)\n",
    "                    \n",
    "            WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "                                            '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "        hash_user_count[user] = count\n",
    "        driver.back()\n",
    "    return hash_user_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "f7444b68",
   "metadata": {},
   "outputs": [],
   "source": [
    "hash_tag_count = hash_tags_count(list(followers_count.keys()), driver, ans)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "9a7835f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "tags_used_count = list(hash_tag_count.values())\n",
    "user_handle = list(hash_tag_count.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2433215c",
   "metadata": {},
   "source": [
    "#### plotting the number of times the bloggers used these top 5 tags as a summation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "dcf4c02c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie(tags_used_count, labels = user_handle, autopct = \"%1.1f%%\")\n",
    "plt.title('Top 5 Hashtags Counts used by bloggers')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d12761e3",
   "metadata": {},
   "source": [
    "### THIRD TASK (LIKES OF TOP 10 POSTS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "88e387ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "def average_follower_like(handle_names, driver):\n",
    "    likes_per_post = {}\n",
    "    follower_count = []\n",
    "    for user in user_handles:\n",
    "        search_user(user, driver)\n",
    "        time.sleep(4)        \n",
    "        \n",
    "        html = driver.find_elements(By.XPATH, '//ul[contains(@class, \"x78zum5 x1q0g3np xieb3on\")]/li')[1].get_attribute('innerHTML')\n",
    "        data = bs(html, \"html.parser\")\n",
    "        follower_num = int(data.find('span')['title'].replace(',',\"\"))\n",
    "        follower_count.append(follower_num)\n",
    "        \n",
    "        WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH, '//div[contains(@class, \"_ac7v  _al3n\")]')))\n",
    "        \n",
    "        driver.find_element(By.CLASS_NAME, '_aagu').click()\n",
    "        \n",
    "        likes_lst = []\n",
    "        \n",
    "        while len(likes_lst)<10:\n",
    "            try:\n",
    "                likes_element = driver.find_element(By.XPATH, \"//span[contains(@class, 'x193iq5w xeuugli x1fj9vlw x13faqbe x1vvkbs xt0psk2 x1i0vuye xvs91rp x1s688f x5n08af x10wh9bi x1wdrske x8viiok x18hxmgj')]\")\n",
    "                if \"likes\" in likes_element.text:\n",
    "                    \n",
    "                    likes_lst.append(int(likes_element.text.split('likes')[0].replace(',',\"\").strip()))\n",
    "                    \n",
    "                    WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "                                            '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "                else:\n",
    "                    WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "                                '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "            except NoSuchElementException:\n",
    "                WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "                                '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "        \n",
    "        likes_per_post[user] = likes_lst\n",
    "        driver.back()\n",
    "        driver.back()\n",
    "    return likes_per_post, follower_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "bdeb9290",
   "metadata": {},
   "outputs": [],
   "source": [
    "# from selenium.common.exceptions import NoSuchElementException\n",
    "# lst = []\n",
    "# while len(lst)<10:\n",
    "#     try:\n",
    "#         likes_element = driver.find_element(By.XPATH, \"//span[contains(@class, 'x193iq5w xeuugli x1fj9vlw x13faqbe x1vvkbs xt0psk2 x1i0vuye xvs91rp x1s688f x5n08af x10wh9bi x1wdrske x8viiok x18hxmgj')]\")\n",
    "#         if \"likes\" in likes_element.text:\n",
    "#             lst.append(int(likes_element.text.split('likes')[0].replace(',',\"\").strip()))\n",
    "#             WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "#                                     '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "#         else:\n",
    "#             WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "#                         '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "#     except NoSuchElementException:\n",
    "#         WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH,\n",
    "#                         '//button[contains(@class, \"_abl-\")]//*[@aria-label=\"Next\"]'))).click()\n",
    "# driver.back()\n",
    "# driver.back()\n",
    "# print(lst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "cf55f9ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "user_handles = list(followers_count.keys())\n",
    "user_likes, follower_count = average_follower_like(user_handles, driver)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "c0cf6bea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'food': [85, 291, 512, 212, 181, 841, 220, 378, 884, 470],\n",
       " 'bhopalfoodwalks': [3364, 125, 2117, 784, 230, 359, 354, 1044, 569, 1199],\n",
       " 'indian_tasty_food': [255, 180, 245, 197, 274, 191, 380, 235, 165, 34],\n",
       " '_foodie.af_': [1490, 4386, 204, 934, 402, 1547, 477, 2178, 889, 429],\n",
       " 'travelbitess': [296, 423, 190, 10701, 650, 296, 240, 1076, 310, 12260]}"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_likes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "8444a69c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'food': 407,\n",
       " 'bhopalfoodwalks': 1014,\n",
       " 'indian_tasty_food': 215,\n",
       " '_foodie.af_': 1293,\n",
       " 'travelbitess': 2644}"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "average_likes_handle = {}\n",
    "for user in user_likes.keys():\n",
    "    average_likes_handle[user] = sum(user_likes[user])//10\n",
    "average_likes_handle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "5762fafc",
   "metadata": {},
   "outputs": [],
   "source": [
    "average_likes_follower = {}\n",
    "for user, f_count in zip(average_likes_handle.keys(), follower_count):\n",
    "    average_likes_follower[user] = f_count//average_likes_handle[user]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "728d7e6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'food': 448,\n",
       " 'bhopalfoodwalks': 29,\n",
       " 'indian_tasty_food': 87,\n",
       " '_foodie.af_': 11,\n",
       " 'travelbitess': 4}"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "average_likes_follower"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41daed34",
   "metadata": {},
   "source": [
    "#### Plotting the above gathered information in bar chart( average likes of handles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "fa542529",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "user_handle = list(average_likes_handle.keys())\n",
    "avg_likes = list(average_likes_handle.values())\n",
    "plt.bar(user_handle, avg_likes, color = 'cyan')\n",
    "plt.xticks(rotation = 45)\n",
    "plt.xlabel(\"Instagram Handle\",fontweight = \"bold\", size = 13)\n",
    "plt.ylabel(\"Average Likes\", fontweight = \"bold\", size = 13)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f676350",
   "metadata": {},
   "source": [
    "#### Plotting the above gathered information in bar chart( Followers : Likes ratio )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "67235a39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAFFCAYAAAD2NXpMAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAzWklEQVR4nO3dd5hcddn/8feHIkU6BAwlJBRFQFAJVUSKdASkozwGBcOjoIDiI6BUQdEfCjaQIhJQlNBBVER6R5AiTekhEkOXHki4f3/c34FhnWzOJjs5s7Of13XlmpmzMzv37GbPfb71VkRgZmbW0yx1B2BmZp3JCcLMzFpygjAzs5acIMzMrCUnCDMza2m2ugPoL4ssskgMHz687jDMzAaU22+//ZmIGNLqa12TIIYPH85tt91WdxhmZgOKpMen9jV3MZmZWUtOEGZm1pIThJmZteQEYWZmLVUepJb0PuALwDBgHPCriJjQrsDMzKxelRKEpOHArcDCTYf3l7RmRDzSjsDMzKxeVbuYjgYWAZ4jE8WzZLL4TpviMjOzmlXtYloXuBNYJyJelzQncEM5bmZmXahqC2Jh4PaIeB2g3N7Bu7uczMysi1RtQTwKbC/pUuBeYCVgu3K8KxyhI+oOoV8cFofVHYKZdYmqCeIM4PvAeT2OH9O/4ZiZWaeo2sV0PDAWUNO/c4Hj2hOWmZnVrVILIiLeBHaRdABlHUREjG9rZGZmVqupJghJw4AXI+KFcr9hPDBL41hEjGtzjGZmVoPeWhCPkl1LXwceA6LFc2Ia38PMzAao3k7ujbGG5setnmNmZl2otwQxAnix6b6ZmQ0iU53FFBGPR8Tz5eEo4APl2OMR8TgwF7kewszMulDVaa6HA5v1OLYXcEm/RmNmZh2j1wHmHrOX5mt6PAvwQVoPXJuZWReY1gykxlYaAXy+/Gv2r36PyMzMOsK0EkRjllLw3zOWXge6YwMjMzP7L9NKECPIxPAIcBrv1H+YDEyMiMltjM3MzGrUa4Ios5WQtAEwvvHYzMy6X9W9mK6RtL6kPYDFaOp6iog92hadmZnVpmpN6tHAiT0Pk2MTThBmZl2o6jqIfchk8FR5/ADwBnBNO4IyM7P6VU0QywMXAr8DiIiVgJuBq9oTlpmZ1a1qggB4EngVQNLCwBNky6IySbNKukPS78vjhSRdLunBcrtg03MPkvSQpH9I2rQv72NmZjOuaoJ4BliQXBgnsvWwA/CePr7fvsD9TY8PBK6IiOWBK8pjJK0I7ELu9bQZcIKkWfv4XmZmNgOqJoi7gY8AF5FjD8sCcwAXV30jSUsCWwKnNh3eBhhT7o8Btm06/ruImBQRjwIPAWtUfS8zM5txVae5btm4L+njwK5kl9NP+/BexwP/B8zbdGyxiJhQ3mOCpEXL8SXIVkrD+HLsXcrsqtEAw4YN6/llMzObAdNsQUiaXdIVko4CiIi/RsTXIuLYiJhU5U0kbQU8FRG3V4yrVSGi/9oYMCJOjoiRETFyyJAhFb+1mZlVMc0WRES8KWlV4MEZeJ+PAVtL2gKYk9wZ9tfARElDS+thKO9Mox0PLNX0+iXJFouZmc0kVccgxgAbS1poet4kIg6KiCUjYjg5+HxlROxGjmGMKk8bRY5xUI7vImkOSSPIaba3Ts97m5nZ9Kk0BgGsDiwNPCbpHnInV8itNjaagfc/BhhbtvAYB+xYvum9ksYC95EbA+4dEVNm4H3MzKyPqiaIdcvtPMBaTcf7XDAoIq4Gri73nwVaJpiIOBo4uq/f38zM+kfVBOG6D2Zmg0zVaa5OEGZmg0xfttowM7NBxAnCzMxacoIwM7OWnCDMzKylPiUIScMkfaxdwZiZWeeolCAkzSnpPOBR4BpJy0p6WNLe7Q3PzMzqUrUFcRDwaXITPUXEw8ArwM7tCszMzOpVNUHsAvwT+HXTsbuAD/R7RGZm1hGqJoglgRuAZ5uOvUZuvWFmZl2oaoIYR27YNweApKXI6nDj2hSXmZnVrGqCuBBYGdirPH4EeB9wXhtiMjOzDlA1QRxNlgBV+TcrWZ/h+22Ky8zMalZ1N9f5I2KdsgZiabJr6Qaym+n37QrOzMzqUzVBXC5p3Yi4gUwMSNoGOJssIWpmZl2mahfTCsCfJM0DbyeHscDs7QrMzMzqVTVB/AYYCVwkaVfgHDI5HNCuwMzMrF5Vu5hGkQPTuwDrk6VGR0fEqW2Ky8zMajbVBCFpvR6HTgVWJbubTgX+KWm9iLi2jfGZmVlNemtBXE22FFr5YvkX0/geZmY2QE3r5K4Z/LqZmQ1QU00QEeFiQmZmg5iTgJmZtdTbIPWVwDkRcWK530pExEbtCc3MzOrU2xjE+sCdTfdbmdogtpmZDXC9JYgjgJvK/SNxMjAzG1R6G6Q+oun+4TMlGjMz6xh9WSjXkhfKmZl1p+ldKNfghXJmZl3KC+XMzKwlL5QzM7OWnATMzKwlJwgzM2vJCcLMzFpygjAzs5acIMzMrKXKCULSapJOk/RnSYtK+pyk5Su+dk5Jt0q6S9K9ko4oxxeSdLmkB8vtgk2vOUjSQ5L+IWnTvn80MzObEZUShKQ1gRuA3YGNgJeBnwHfrPg+k4ANI2JV4MPAZpLWAg4EroiI5YErymMkrUjWv14J2Aw4QdKsFd/LzMz6QdUWxFHkoriHACLiVeA64BNVXhzp5fJw9vIvgG2AMeX4GGDbcn8b4HcRMSkiHi3vu0bFWM3MrB9UTRAfBS4BLm06Ng5YvOobSZpV0p3AU8DlEXELsFhETAAot4uWpy8BPNH08vHlWM/vOVrSbZJue/rpp6uGYmZmFVRNEFNaHBsBvFT1jSJiSkR8GFgSWEPSyr08vdUWHv+1L1REnBwRIyNi5JAhQ6qGYmZmFVRNEH8HNgc+DiDpZGAT4O6+vmFEvEBuBLgZMFHS0PI9h5KtC8gWw1JNL1sSeLKv72VmZtOvaoI4ApgT+Eh5vCd5RX90lRdLGiJpgXJ/LuCTwAPAxcCo8rRRwEXl/sXALpLmkDQCWB64tWKsZmbWDypt1R0R10raCvg6MIwcfzguIq6p+D5DgTFlJtIswNiI+L2km4CxkvYo33PH8n73ShoL3AdMBvaOiFbdXGZm1iaVazlExB+BP07Pm0TE3bzT+mg+/iw5bbbVa46mYgvFzMz6X6UEIenQqXxpMvAIcEFETOq3qMzMrHZVWxCH03t1uQclfay0CMzMrAtUHaS+DngLeI4cLH6OTBi3Ai+Sg8gHtSNAMzOrR9UEcRU51XVYRKxNDlTfBVwGLE0OJm/ZlgjNzKwWVRPEl4C7IuI1gHJ7F/CliHgRuIBMGmZm1iUqz2ICdpZ0N3AP8EFgZ95ZST038EY/x2ZmZjWqmiDOBvYBjm06JuDUsrZha3Lhm5mZdYmqCeIAclB6T2Au4FXgFHK77zmBLwL/bkeAZmZWj6orqd8A9pW0H7BIRDRvnfoGUHVFtZmZDRCVxyAkzQIsBywm6YON4xFxbTsCMzOzelVdSb0yOVNpmR5fiqrfw8zMBpaqJ/f/ByzbzkDMzKyzVF0HsSa57uFMstWwNvAYsFt7wjIzs7pVTRDzADfwTkGf24G/AAe2IygzM6tf1S6mF4E5yJoNAN8FNqQPNanNzGxgqdqCeJicwXQTuUDu62RN6nvbFJeZmdWsagvia8DiEXGdpB+T5UGfBPZqW2RmZlarabYgJM1OzmB6ESAi9o+IhSJi5Yj4W7sDNDOzekwzQUTEm8DJwHbtD8fMzDpF1TGIm8kxBzMzGySqjkFcDxwo6SzgauD1xhci4ow2xGVmZjWrmiAOJhfI7Vz+NQTgBGFm1oWqJohxZDIwM7NBoup238PbHIeZmXWYqoPUKK0n6bPtDMjMzDpDpQQhaQHgFuAqYIykZSVNkXR4G2MzM7MaVW1BHAmMJLfZUEQ8DNwGbN6uwMzMrF5VE8RWwB3ACU3H7sM1IszMulbVBLEoWQ/izR7H39O/4ZiZWaeomiAeBdYDFgaQtA6wTTluZmZdqGqCOIOsR92YwXQdMD9ZYc7MzLpQ1QRxPDCWMkhd/p0H/Lg9YZmZWd2qLpR7E9hF0gHAMGBcRIxva2RmZlarqusg7pa0N/BSRNzo5GBm1v2qdjGtDPwEeFLSaZLWbmNMZmbWAaomiP2BvwFzAbsD10v6u6R92hWYmZnVq1KCiIgfR8TqwIrAMcB4YCVy8NrMzLpQ5c36iteAV4FJ5bGqvEjSUpKuknS/pHsl7VuOLyTpckkPltsFm15zkKSHJP1D0qZ9jNPMzGZQ1UHqPSVdAzwMHAEsBzwEHFTxfSYDX4+IDwJrAXtLWhE4ELgiIpYHriiPKV/bhWylbAacIGnWyp/KzMxmWNWCQSeX2zeAC4BTIuLKqm8SEROACeX+S5LuB5YgV2OvX542hixn+s1y/HcRMQl4VNJDwBrATVXf08zMZkzVBPFP4BTg9Ih4dkbeUNJw4CPk9uGLleRBREyQtGh52hLAzU0vG1+O9fxeo4HRAMOGDZuRsMzMrIeqC+VW6I83kzQPuQJ7v4h4UZrqEEarL/xXydOIOJnSuhk5cqRLopqZ9aOqLQgk7Q5sAizGOyfwiIiNKr5+djI5/CYizi+HJ0oaWloPQ4GnyvHxwFJNL18SeLJqrGZmNuMqJQhJ3yYHp98+VG4rXbUrmwq/BO6PiB81feliYBQ5dXYUcFHT8bMk/QhYHFgeuLXKe5mZWf+o2oL4HDm19QlyBtNlwAbkBn5VfAz4H+Dvku4sxw4mE8NYSXsA44AdASLiXkljyaJEk4G9I2JKxfcyM7N+UDVBLA2cQ3YB7RsRm0u6BPhPlRdHxPVMfc1Eyy6qiDgaOLpifGZm1s+qLpSbDDwPvAwgaUngdWC3NsVlZmY1q9qCeAoYAtxJtgTuAeYFnmtPWGZmVreqLYi/kAniArIlMR+ZKMa0KS4zM6tZ1XUQX2zcl7QasDXwZESc267AzMysXpXXQTRExGNkbQgzM+tifd3N1czMBgknCDMza8kJwszMWnKCMDOzlpwgzMyspaoV5d6SNFnS+8vjD0iaImlye8MzM7O69GWaa8+9lCrVozYzs4GpaoL4fLmd0HT7+ak818zMukDVldRjejx+EW+zYWbW1aqOQSwoaVi5v4ikgyXtJcmD3GZmXapqF9NvgI8AQ8kN+9Ypx4cDB/V/WGZmVreqLYCVgZskLUAmhxvJXV13alNcZmZWs6oJYlHgSeAD5fGXgHPJetFmZtaFqiaIl4EPkdt8TwEeBGYn61SbmVkXqjoGcTuwMbAucGtETJK0HPB42yIzM7NaVU0Q+wEnAnMAX5U0B/AGcFab4jIzs5pNM0FImh1YHfheRFzW9KWN2xaVmZnVbppjEBHxJnAy8On2h2NmZp2i6iD1zcAy7QzEzMw6S9UxiOuBAyWdBVwNvN74QkSc0Ya4zMysZlUTxMFAADuXfw0BOEGYmXWhqgliHJkMzMxskKi6m+vwNsdhZmYdpvJurErrSfpsOwMyM7POUHW77wWAW4CrgDGSli0lRw9vY2xmZlajqi2II4GRZJlRRcTDwG3A5u0KzMzM6lU1QWwF3AGc0HTsPmDZfo/IzMw6Ql+2+74LeLPH8ff0bzhmZtYpqiaIR4H1gIUBJK0DbFOOm5lZF6qaIM4gt9pozGC6DpgfOLMdQZmZWf2qJojjgbGUQery7zzgx+0Jy8zM6lZ1odybwC6SDgCGAeMiYnxbIzMzs1pVXQdxjqQvAu+JiBv7mhwknSbpKUn3NB1bSNLlkh4stws2fe0gSQ9J+oekTfvyXmZm1j+qdjFtD/wCeFDSw5JOkrSDpIUqvv50YLMexw4EroiI5YErymMkrQjsAqxUXnOCpFkrvo+ZmfWTqgniB8CtwBRgBLAncDYwscqLI+Ja4Lkeh7cBxpT7Y4Btm47/LiImRcSjwEPAGhXjNDOzflIpQUTEgRGxNrAA8Dngn+RAdeW9nFpYLCImlO8/gVxrAbAE8ETT88aXY2ZmNhNVGqSW9GlgA2B9sutHwDPANW2ISS2OtdxqXNJoYDTAsGHD2hCKmdngVbUexHnkSfp+YF/g6oi4p/eXTNNESUMjYoKkocBT5fh4YKmm5y0JPNnqG0TEyWS9bEaOHOl6FWZm/ahqF9HdZIJYETgEOEzS3pI+NAPvfTEwqtwfBVzUdHwXSXNIGgEsT45/mJnZTFR1HcSHy5bfnyC7mTYHtiOTxjS/h6TfltctImk8cBhwDDBW0h5kxbody3vdK2ksuRngZGDviJjSp09lZmYzrOoYxDzAmuXfGuRMplZjBS1FxK5T+dJGU3n+0cDRVb+/mZn1v6pjEM8BjbUIjcRwD3B5v0dkZmYdoWqCmA34F7mg7XLgLxFRaQ2EWSc7QkfUHUK/OSwOqzsE6zJVE8RKEXF/WyMxM7OOUnWQ+v4yY+krlM36gJ9HxF3tDM7MzOpTdZB6FeAmYE5yDCKA3SSt7SRhZtadqq6D+A4wFzn19GzgXjJZHNmmuMzMrGZVxyBGAtdFxCcaByRdA6zelqjMzKx2VVsQ8wKP9Dj2KPDe/g3HzMw6RdUWxIPAzpLuIruXVgJ2IvdmMjOzLlQ1QZwAnAL8sMfxX/RvOGZm1imqdjGdRhYNep2cxfQ6cGxEnNKuwMzMrF5V10EEcKCkQ4AhwDMR8UZbIzMzs1pNNUFIWq+X1y0n5ZZMpZyomZl1md5aEFczlUpuTSpt921mZgPPtE7u09rSu/KW32ZmNrBMNUFERNUBbDMz60JOAmZm1lJvg9RXVnh9RETLqnBmZjaw9TYGsX6F109rENvMzAao3hJE95TaMjOzPuttkNoJwsxsEKs8SC1pU0l/lvSApMskbdbOwMzMrF5VK8qtB/yh8RB4P7CRpI0i4pp2BWdmZvWp2oI4lEwMfwS+D1xaXntIm+IyM7OaVd0mYxXgDxGxVeOApEuANdsSlZmZ1a5qC2I24KUex17B+zCZmXWtqif4B4AdJE3knYpy2wN/bVdgZmZWr6oJ4gfA+cBXehw/tn/DsTocoe6Z0XxYHFZ3CGZdo1IXU0RcCHwZeAyYAjwK7BMR57ctMjMzq1XlMYSI+AWuQW1mNmj02oKQ9Iikb5X7u0r65cwJy8zM6jatLqbhwMLl/hrA7u0MxszMOofrQZiZWUtOEGZm1lKVQepNJJ1GWTVd7jdEROzRlsjMzKxWVRLEB8s/lcejyq3IgkFOEGZmXWhaCeJaXDXOrGt1yyJJL5Bsj14TRESsP5PiMDOzDtPRg9SSNpP0D0kPSTqw7njMzAaTjt2NVdKswM+BjYHxwF8lXRwR99UbmZl1g27pXoP2dbF1cgtiDeChiHgkIt4AfgdsU3NMZmaDhiI6cwxa0g7AZhGxZ3n8P8CaEbFP03NGA6PLww8A/5jpgfbNIsAzdQdRk8H82WFwf/7B/Nmh8z//0hExpNUXOraLiXem1TZ7VzaLiJOBk2dOODNO0m0RMbLuOOowmD87DO7PP5g/Owzsz9/JXUzjgaWaHi8JPFlTLGZmg04nJ4i/AstLGiHpPcAuwMU1x2RmNmh0bBdTREyWtA9wGTArcFpE3FtzWDNqwHSHtcFg/uwwuD//YP7sMIA/f8cOUpuZWb06uYvJzMxq5ARhZmYtOUHUSFKrqbxmZh3BCaIGklaXtGBEhJOEmbXSCecGJ4h6fBm4XNICThL9o/EzlLSCpHnqjqcOZUr4hnXHYTNOkqLMIJI0b11xOEHMRGUDQiLi88ATwK/dkugf5We4BfB7YJm646nJR4ALJG0EnXEFatOnKTn8L3CspDkkzfTztRPETBQRU+DtfaUmkpX6rnKSmHGSVgV+BOwQEXdLWkLS0Dr+qOogaZaIOB84AjhR0mYxAOewSxouaUTdcXSCsg7s88CxETEJmL0cn2nniUHxx9NJJH0c+BZwKLA8cAfwZyeJvmuc/EvLbDJwDrCqpIOAS4HjgQ1qC3Amioi3JG0OrERuWnlBaVENmJaEpKWBm4DB2kWopvuzAx8FdgbelPRF4DpJG8/MxO8E0WYt/jifAm4G/hMRb5XupjeB6xtjEjM9yAFG0hzw9klxfeBIYBIwJ7AD8FC5fRwYVk+UM4/SUOB7wJkR8SnyyvNXkrYYQP+nhgJ/BlaQdAy8cxHQ7XqMOawCTAH+DVwD/BCYF7gA+PbMHJMYFD/8uvT4pc8paW5gAjACWL/pqb8itwMelFdOfSFpfrLFtU45NDvwSkQ8BBwObBcR55DJ4pPAo7UEOhOV/2MTgTuBpyXNGhG/A04Afj+ABq4fBBYAfkLZuj8i3ur5pMZY3kBpGVXRdJ74GtlNuGhEHEwm+tER8SPgRuBleuxq3U5OEG3U9Ev/Klnw6FLg4+QV7/clHSbpB8BOwC4RMb62YAcASbNFxH+AS4CfSlqd3BZ+foCIeCUi3iytip8C34mIq2sKt62aZm0tKGneciKdBPwP0DipXg78gWyhDgQvkC3s64AFJK3c8wkl+U2RtCBwUqM12Q0kbQdsD+wWEf+WtChwZ0Q8K+lgssv0oIh4eabFNHBanwNT+aV/k/zDXZYso/pV4AFgQ3Ic4lcupdo7SYuQYwyjI+JBSXsDXyCb4JPJ5vdb5EXPXMCTEfFAcyuu20jaEjiEPKk+Tl54nEXOkHsa2BTYIyJu79SfQyMuSYtFxERJc5Jb+38Z+A8wNiLuL89tJIcFyP8Lx0TEFbUFP4OaPvsspbv0S8CHyd/hRsC6ZNfSpsB2wE0ze8NSJ4g2KzOWVoiIb5XHawLnARtFRKdXwOsoko4H1iFbW49I2ovsd38d+BmwNtlF8dWIuKOuOGcGSSsBZwJfAe4HziYvOr4ObAUsAdw3EE6gkrYCvgbcBdxOnvyXBz5Htn5+07iAKi2Hs8nW4XX1RDzjenQ/LxkR4yUtDxxMdkGfANwKHACcUNcFZMdu9z3QlCa/WvSZPgOsKGmOiJgUEbdIuoTcwtwqaFxhRcR+kr4HnCdp+4g4SdJrwP7AbyPiu516pdwGU4B7gJvL9OmNJf2V7J44rd7Qqiuz+o4i681/F9ibbEEcD/wG2B14ozx3NuBc4KiBnBzgXd3PewObSrqHLJK2Z/n6FEnbk70Mx9QVpxNE/3lvo2+wTElbgmweHkxOVTtd0hhyVs0nyD8Gm4Zywn9L0twR8WpEHCQpgPMlbRcRZ5S+2t9LWg94kYHT515ZjyvOWYDnyRPpqsDfytPOJLvbBoRyUfV+MgmsSNaVP4H8e5mNTBKHNP6uSo2YnSOik+s7V1a6n3cGtiW7SO8pieG9ysWOR5Hremobm3QXUz+QtDWwTUTsIWkU2ew/hLwamJOshve/5DS+ZcmBJo85TENTH+1WwMbkif+oiHhB0hHAFsCuEfGQpGERMa7WgNukqe99C/JkMjfwfbK/el/gF+TP5pvAVwZCt1JDSXZzACcBh0bEY5LOB14CjoyIh2sNsI0kfY68oJkf+CywVUS8IWkF4DVgSt0TV5wgZpCkhck+0f2AZ8k5yxdFxNnl66cBQ8rcdCTNGRGv1xTugKNc/HUMsCvZN/0omWD/XmaAbQGsHhGv1RhmW0haCpgUEU9J+hg5weEwYDiZGLYnx1w2JFumZ0XEZfVEO/2Ui8KuAK4nB2h/AuwfEXfVGlg/KpMsNomIsyTtTE5LDnKK+78i4uPleV8F3gccFhG1t4TdxTTj3iCb9YeSv/CJwOJNX9+T3HPpvRHxCjkV0SooV5dbAnsAS5NXlU8BP5e0T0T8n6RTujQ5jCCnRX+e/MxLAX+JiIvK18cDFwFrR8RVjXGa2gKeTiXuNyXtCZxKztw5rsuSw2wR8YyknUrLdwKwNbmG5yJgchmLGQ6MAkZ1QnIAJ4gZFhEvSbqCvLI7AhgL/KH8AV9HbvWwPOVnPUgGUGeYpBWBhcnuuiWAY4GNy8/7MeBrkr4SEQ/WGGZblL75dYCLgackfYG8sBiidzZ8PK/0Uy9IXoF2bHJo6ir8GLmh4J3AQxHxb8qir4j4p6RNgHkj4ulumWwgaSQ5u+6nwI+BM4A3IuKF8vWzgdWAA8lpvbtHxD31RPvfvFCuf4wl+4b3BNYEvkSuezgW2Af4fFngZdWtC3yynCQmkbN2VpP0QXL63wkR8VKdAbZL+czXkOs8bgGuJbtehpHTelcsA/IbkQsFO1ZpIUTpKjyFTAinAts1fe2jknaKiNcj4mnoqgupx4BzJL2f7IL+EDC7pEsBIuJm4PyI2JJsOfy9tkhbcILoBxHxeET8BfgMOTtpcXJ19JeBbTvpiqDTSVpZuYL2AmAd5a6kT5NX098km+SnRcStdcbZTqWV8BTwd3LweZVywtweWIxsVX0X+FqnnVAaJC0Gb++XNS85jXULcsbV6+RJsdHqEbmwr2uoKDOu/gP8kkwAL0TEJ8iV4udJ2pWc4TgvHTgDzYPU/Uy57fSVwLcj4sS64xlIykDeRcBC5KyOZclpwtuSq4MXBxbs1JNifytjMCsDFwLfi4hTJL2HXDG+cERMrDO+VhrrgciYD4iIf5bjhwCrkK2gHSNinKRtgInlKrqr6J3V0XNHxKvl//YJwDjgm2VW2unkjLTvdOr/abcg+lkZXPsEuSulVSRpvnK19SOyG+JwctzmFTJZzBER4zv1D6k/lZMs5AXc3eRA9QGS9oqINyJiMtnC6ETzlZbBdsAskk4ox/9JDsJ+rySH1YEfAO+pJ8z2UJYTnr8kh72BscqdaVcjf48jgO+W2Yy704HdSs3cgrBaSHofcD65vkHAccC95dhKZDGle4FvkFfRK0bEc/VEW5+mK9ENgDHkrKV/1R1XK5LmIidmnBERP5G0ELn1+kllgeNRwHLk2qBlgYMj4pL6Iu5/kn5GJoMfArsBJ5NJ4ZPkdPg/kK3kq8iWQ0efgJ0grDaSziRX0K4BrE7udLsT8EeyXsYPy/M+Et2/t9IqZCvpry2+1kgSC0bE8zWEN01NM5VWI7fI+G7kKveFyHGHMyPikLK24/3AhIi4r4tmK32EXAn9pqTvkuORR0TEr8r4whrkivHdyXGkWSPiibrircoJwmY6SbOXP6QhwNXAc+QU1tfLoN3e5DTPH0TEgd1yEpka5ZbVBwBPlJPqrFHK0zY9Z7bStdSRmpLYcmTX0VbANyLixyVJ3AJcGRF71Rpom0i6mGwZbVn+b48B1gNWKmMQ85KzHfePiAfqjLUvPAZhM135A/oUWSPjJ2QX0x1lQO+3wGjyhHlZeX7XJgeAyHrD/wK+VMZieiaHWSP3IVpQ0m71RNm7khw+TnafHEvO4Du4rFV5DlgL2FzSSuqiKnGN8aKI2Jos5nNOSeajgD8BV0v6MLkWYglyseeA0TW/KBtwtiF3YD0pItYlaxFfJ2muyH2qfhq5Qrij5/lPj8ZnkrSMcstyIuJ0cvbbruVrb9fbLjNe5idPvh05/lAsCVwTETdGxKnk7/gYSftGxLPAMhFxb3Twor6+6NmyjYjtyGnJF5RW8pfILdj/BnwK2L5Tx4+mxgnC6vIc7y6xegS5B80t5eQ4Gbqr9SBpHklDS1/9x8iys1tJOkfSTuTJZVF4+4q8uUDOueSg7lV1xd9Ti+T9JLCYpLlLl9PNwG+Bb0panHcq3Q14zclB0paStpG0fETsSG6012hJfI7cuPNHMQBX/XsMwtquaQBz1XLoVbIexo3kNL9LyrTH9YHrI+KmmkJtqzIQ/T1yBstO5LYK9ym30piHXHW/OFk176zymrmBG8giSB1TA6Hpd/pJctbZXGTX0q/IRHACuUvpTsDPu3WSgaQDyP3CbiRX/38jIm6VdA4whBxb64h9laaHWxDWduVEshk5u+V/yZrSK5O7kP5A0qlklb07ujU5AJQ1DXeSW3X/qnSlERGnRcRPyO1ZfkhOAW1coU8GPtNJyQHe/p1uSNZseJ2cgXYuOcFgHLnB4neAC7spOTS3miQtDawVERuQ28G8RFbFo7QkxpGt4gHLLQhru9JFcjG5v/9fJH2A3GtoFNk/Ox8wdycvGJoRTVfbSwIjySvuz5AthRvKcxqzgJYFTiNXG3fqYjgAJB0HPFqSG2XmzgIRsU15vHBEPNuNs9DKOp4XyC00XiVrvWwfEZOU23n/IbpgrzC3IGxmeJnctOwRgMha3F8GPhURT0fEw4MgOWxDdrs8EBFHk7UdTpf0IUnrAseXq9NFgGUYGH+bT9I0jlRm7kwu05chx5m6ahwJ3q4HfhT52Z8gd6jdvySHL5Dbw8zTy7cYMLzdt/Wrpml/IWko8GJEvCJpIrmL54aNpwILt5rz302aBqQPB/4nIh4o03lPkPQsmTTmIheWhaS7gI9HboXdMZpaOB8l6xi8Bvwe+F2J+Vpy9fuy5etdkxhatIBmI7dZn59s7c1CJvtbgU2AnSJiwsyPtP+5i8naoow5HAXcR9bm3oFsjo8gB2m3Jzct+0NtQc4kZfHfusDp5HqArcgT7B7kz+atyP2JOi5ZSpqjrNNA0qZkXYNLKF1kZOvwW2RrYmWyElpXbZ/RIGl4RDxW7h9C7rm2BZng1yInXtwfEY/WFmQ/c4KwfqHc737NiDiz3L+A7Ea6k9yaulE4ZWuyBvG/I+KaLu2fbnQrNa66h5Mn0XXIPaeeIE8uF0YHb1teulIOBL5K1uM4H/hhRPxRuaXGueTv+Bqy9Om8EfGPLv2drkruCwY50WI24GvAZY1xpG7kBGEzrPQ5/wn4IlnDYCi53fnopuf8Brg2Ik6qJ8qZoyk5bEUmxFnJ9QtvSVooIp5T7ttzFtnldFutAU+FcuO9M8kNAm8gT4jfJpPC9eXzbE3uLbTzQJ7K2UqPdQ4iu80WJGegBfBv4MPAbRFxSF1xtttAGAizzrckuQ9No+LZosC6krZtes5dZMuhq5XksCXZvXY2sCNwsaRFgeeVleB+R86X78jkUAQ5fXU78nPMQ07l3JPsUoHsXppSnts1eiSHL5HrO/aLiImRW3SfCjxIbjA5StJCLRYNdgUPUtt0kzQsIsZFxB2SHiCvLkdFxG2SvgGcIWkEOZvls2STvKtJmp3cYuILwFJk33yje2ZHYCKwS/mZdWxXTOTGiReS4ybnR8QjwDcknQuMkTSBXPtwaHTwJoLToyk57A3sQraMb5K0DDmZ4AbgBkl/A56JLt6G3l1MNt0knQWsFhEfkLQvuQ/+RsAGkUXoNwA2J1sXf4yIP9YYbluUrphPRq4GX5VsPV1PdrP9hlxJ+7KkZ8giUrtHxBv1RVydpLWAhYGjgYsj4tByfEuyy+WpiLixkxNdX/RoOcxJTqr4GpnYtyVLh04mu9oe6obPPC1uQdh0i4jPSLpY0p8iYjMA5V7410paJ3KzvWsbM3O65UTSwxTgo5KOLI93jojXJL1Kbqw3Qllj+nyykM6ASA4AUUqBltbhxZImR8SREXFpj+cN+N9pj+RwADmW9gWyTOr2EbGBpIWBR8mJFz8EBszvcnp5DMKmSznpNbY5RtIt5fHBwEnA3ZJGNE/b7IYTSU/lhH85WQTmlSg1mMm/rX8AB5HTQsdGxPUDra+6TL19mJya+wVJh9UdUzs0JYeNgTXJ6aqTyHGX2ZSbDa5O/i5/PZAS/YxwF5P1SdMsnfcBczbNC78UWDgi1iqPvwf8JSKuqC/amUO5lciy5ADu4uQ2GW+URWVPkz+XO+uLcMbonV1llwGWiohr6o6pv5TJA0Mi4l5JuwP/R3YfNS58hpDTfD9GrnLfKQZQwZ8Z5QRhfVamN34beAp4PCL2LscvIvf8/1DTc7uxW+ltjbUO5f58wI/JcYjvA/sBe0XE0/VF2D+aF/Gpw6vb9YWk5cltTyaQs/BOI39vY+KdPaYWJDfdezkGQJnQ/uQuJusTSeuTtRu2JQuw7yXpFIDITdr+JWmdxvO7OTlA1m1ouv8isBfwOHAMcFo3JIdm5WT5a0nvrTuW/hBZo+Fu4NNkN+CZ5MXPhpK+Wp7zfETcP9iSA7gFYX0kaWS5uxi5KdkXyVXTd0XETrUFVoPm1kOLry0SEc90QwtK7y5cNBY4JiKurDmsfqOso702OWPpmIg4u6wUPwE4PrIM7qDkWUzWq6Yxh3nIPYNuKwOtpwAnRBa8OQ0YrayoNeCqZlXR9HMYAbw3Iu5plRyU1fAiIp5pHGKALyQryWFBcsHcd6LDalPMqIh4CHhI0gvA0eV2TnKW0s01hlY7JwjrVTkpbk3uPzOfpB+RO3feDXxM0mzkrI8duzU5wLtWSP8IeEPSjcDeLfriFbkNxXzAouXkM6CVGWtnkFfXXZUcmpW1LG+SK6dfAfaILtp4b3q4i8l6pSyTeRy5Udkq5OrZG4CHyR1KNwN+EF26g2eDssjR94FvknUt/gTcQ26Z8UZ5TqMrZn7gSuDLEXFLXTH3J0nzR8R/6o5jZigzm6Lbxo+mhxOETZVyF9LDyWmanyrHNiV3Z921rJZ+b2S9hwHf1z41khYBDiUT4m6lW21+4ByyENI+wOTScpifXBR3WERcX1fMZv3Bs5jsXXos5HqeXDU6j6SdSxK4DLidrKIFWW6x62YrNf8cynjCr8kNBz8lablyNb0T8AFguabk8BecHKxLuAVhb2saiF2XnPc9JSIuKNP9licTxp/IbaB3i4ibagy3bZp+Dp8E1iCLz18IrAB8jqzncFFpQTWvD1iVHMC+sabQzfqVWxD2tnJS3Jjczvj9wHcl/T9yxtJ95MZ7o4HREXFTmbHTdcrPYStyLcN4snraz8lxl9PIZLm9pLkpM5TKlNe7nBysm3TlH7j1ndLsZBnMIyPiu2RBlI8Dh0TEicBvye2q54Z3LxIb6CQNLYsAKZuybU+WSX0JGELWPjiR3KztF2QL4tXGz6CbfhZmDU4Qg1iPfvaIrAr2WNOxScDO5OwlyNoALwFrSZp35kU6U6wNPCVpnoh4llxN+95yuzNwMjnucjpwd0TcV1egZjOL10EMYo2BZUkrkFfIz5AD0PtJurXM4V+cXP+wQGS5zJ8Cs0bES7UF3o8kLQEsERHnl5bDzyRdEhHnSVqILCn5SNk+5FJyj56u2IfIbFqcIAahMn11h4g4VtIm5CKoP5P1k0eTm839QtI48qr5sIh4oQzeds1c+DKGsiG5CvxbwI3A34BNJL0BXA2sI+lUYAuyWt5ddcVrNrN5FtMgJGlp4BayIP2b5MykfwJ7k+MOnwPmI6uiTY6Iv3XrOoeSJPYhE8A3ycVvewJrkWMOD5BJ8rWIuLWuOM3q4AQxyEiaIyImSRpKFj/5D1kveiKwEHmy/ASwZ2Qd4q7UNJV1E3KM4YPk+MrhZPLcgyyf+ptuXyVuNjUepB4kGoPKJTmsT14V/5QsdLNDGaR+lpzOeR1Zi7hrleSwDNlK+BlZFOZCclB6VXIw+hpy626zQcktiEGgzNf/E1nM5u/AueX2CWA9YDngqHinQMrsZUZTV2pqPawAHBcRm5fjQ8n9lpYF9neXkg12HqQeBCLiVUnHAQeS3SijI+Lmsg/+E8A6wIGlhsGh3ZocmsZR5ibrRz8gaS5JR5bPPUHS7eT2Ib5yskHPXUyDRERcQHafrA58shx+nEwQD5M1d/9cT3QzR2k1bA6cK+kIScsC+wPLSvq1pE8BuwMnRsRf64zVrBM4QQwiEXE5eQLcXdKupaXwArAV8FxEXN9js76uUGpWIGkNMiGcASxDDkQvQFYSe54cnD/MU1nNkscgBqFypTyGnOf/AnB+RPy+zpjaoXShTYyIlyQtBZwFXBYRR0l6HzkwPRtwbvN4Q7dO6TXrK7cgBqEybXNPcnD6xIj4fTe2HMi62R8qn+1JchHcbpJWjYh/k4WQZgN2Laumge7butxserkFMYhJWiginqs7jnYq03vvAlaLiOfLiumRZFfS3ZKGAAtFxD9qDdSsAzlBWNeTtA25dfdawIvkiukNyXKhHm8wmwpPc7WuFxEXlWL0t5Gth+8Ds+P//2a9cgvCBg1JmwG/Albopk0HzdrFCcIGFUlbkovkrq47FrNO5wRhg5KnsppNmxOEmZm15HUQZmbWkhOEmZm15ARhZmYtOUGY2TRJekxSSNq9PN69PH6s3sisnZwgrO0kXV1OJqf38/eN8m/9/vy+nUTS6eUzXj2V44/VE5kNBk4QZn0g6T11x2A2szhBWC2arv6/IekaSS9K+rukdZqes6ekeyW9Kumlcv8wScMlNc/Pvqq5hSLpUknjJb1e/v1d0l493n9bSfdJek3SHyUd0vOKvKlb5ejSCpoEfEbSupJukfSspDclPS/pT5I+1PTaxhX+2FKM6FVJD0raSNJny/d+QdIpjXoV/fAzPVLSPyW9XOIaJ+k4SXP08ee+oKSzyud6QtI+Fd9/UUknSnq4fN57Je0nadb++Hw283kvGqvb0cBYYBFgZeDXwDKSRgCnAG8Cvy237ycr3/2UrK+9b/ke5wHjgUZNhxHANWQRoMWBbYBfSHowIq6UtFp5zSzAteQGfof2EuNBwJVkoaGJ5Xu+DlwITCoxbQosL+kDETG56bU7AJeTO8quBZwPvFVeuwu57fpNwGnT+DktJ+n4psdrtHoOcA/wF7Ks6jbAfmSZ2Z6fr+XPvXztDLKI1PNklcGvAEv1Fpyy7vlN5Xv8FbgO2IjcUn1pslCTDTBOEFa3I0sBn5HkiWWEpIWBxlXvS8DFwP3Ag2S5hsnAfpIaCeJnPbbO2IQ8OS4BTAaeJmtDbEKe6L9IJod7gPVLKdITgf+dSoznRMTOzQck/RtYGxhCnvxXIU+OywEPND317ojYVNIq5XnzAftGxE8kvRfYkSwDO60EsQTvJMSpGQ1sW2KYnywlu1r53D0TxNR+7rOTyQFgj4i4QNJiZALurcdhO/Lzvw7cWI79DVgS+JKkAyNi0jTitw7jBGF1u6XcPtt0bN6IeEDSgWTVt3PL8VfJK9JvT+2bKcuKXss7CabZYuV2WLm9p2m7jd62/b6qx3scR16Zt7IY704Q95Tb55uO3VduXyy38/by3g3XRMT6TTGcDoxqerwAeUIeMZWYemr5cwcW7RlnREyU9Azwvl7iW7rczsl/J7I5yvd9opfXWwfyGITV7c1y+649X0q/9Q8jYgny5LI5efL5lqQly9OmlNvm/8e7kiekR8rrZiFbHwCNqnmPl9sVml63Si8xvt7j8e7l9oflvdZuDr3HcxvdTdHiWH/6BO8kh4+Sn/ukqcQEU/m58+6T+IoApQUxZBrvP67cPg/MFxFq/AOWiwgnhwHILQjrVEsBt0u6FphA9vvPQp7YXirPeZzs1jha0i1kS+PJ8rUlydbGUsCyPb73KWR3zIclXUF2QW3fh9ieBBYAPk125XyyLx+sTSY03T+GrDX+qb5+k4iYIOkPwBbAL5W7336caV9Mng8cCQwH7ig/1/nJ+hvjgfX7GovVzy0I61QvkgOdqwFfICvA3Qps31TLYX+ypbA62a3xYXIA+9fkVf+m5JjDTc3fOCL+Rg4ePwCsQ57sv1++XOXqfhTZnbMEOfA81S6vmSUibiUr5U0E1iVbBidO57f7HHA2eX7YgmyJjOvtBRHxCtmSOpFssYwik8KjwMnTGYfVzLu52qAkacGIeL7p8a/IrqPLI2KT2gIz6yDuYrLB6kZJfyVnRn2IbFG8RY4rmBluQdggJemXZPfJwuQYxF3A0RFxQ62BmXUQJwgzM2vJg9RmZtaSE4SZmbXkBGFmZi05QZiZWUtOEGZm1tL/B+2cnV0ZHd3OAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "user_handle = list(average_likes_follower.keys())\n",
    "avg_likes = list(average_likes_follower.values())\n",
    "plt.bar(user_handle, avg_likes, color = 'purple')\n",
    "plt.xticks(rotation = 45)\n",
    "plt.xlabel(\"Instagram Handle\",fontweight = \"bold\", size = 13)\n",
    "plt.ylabel(\"Followers: average like ratio\", fontweight = \"bold\", size = 13)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c4660126",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}