query_FND_graph.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "22ffeb77",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "from pprint import pprint\n",
    "from tqdm import tqdm\n",
    "import time\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import json"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fcf96d5",
   "metadata": {},
   "source": [
    "## Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0dcc6408",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "from read_data import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6b7ffb29",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading data...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 48059/48059 [00:35<00:00, 1371.92it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N art re-listed: 1928\n",
      "N art resold: 138\n",
      "finished loading data...\n",
      "stats...\n",
      "N art minted: 50723\n",
      "N art listed: 48059\n",
      "N art sold: 15279\n",
      "N creators: 15366\n",
      "N buyers: 5531\n",
      "N bids: 37013\n"
     ]
    }
   ],
   "source": [
    "art_metadata_df, artist_metadata_df, invited_by_metadata,bidding_df, minting_df, listing_df, max_bid_df,total_artist_earning, total_buyer_spending = load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4d22d386",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5531\n",
      "(1681, 13)\n",
      "(0, 18)\n"
     ]
    }
   ],
   "source": [
    "print(total_buyer_spending.buyer.nunique())\n",
    "print(artist_metadata_df[artist_metadata_df.artist_id.isin(total_buyer_spending.buyer)].shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d96c2e07",
   "metadata": {},
   "source": [
    "# Query the Foundation and Twitter data\n",
    "\n",
    "- below we provide the script required to crawl the data... \n",
    "- the functions below will help get the \"latest\" data on the platform. \n",
    "- the read_data script helps load the data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "id": "b99036cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to use requests.post to make an API call to the subgraph url\n",
    "def run_query(q):\n",
    "\n",
    "    # endpoint where you are making the request\n",
    "    request = requests.post('https://api.thegraph.com/subgraphs/name/f8n/fnd'\n",
    "                            '',\n",
    "                            json={'query': q})\n",
    "    if request.status_code == 200:\n",
    "        return request.json()\n",
    "    else:\n",
    "        raise Exception('Query failed. return code is {}.      {}'.format(request.status_code, query))\n",
    "\n",
    "# given a token id return the metadata\n",
    "def get_metadata(t_id):\n",
    "    query = \"\"\"\n",
    "{\n",
    "  nfts(where: {tokenId: \\\"\"\"\"+str(t_id)+\"\"\"\\\" }) {\n",
    "    tokenId\n",
    "    dateMinted\n",
    "    creator {\n",
    "      id\n",
    "    }\n",
    "    owner {\n",
    "      id\n",
    "    }\n",
    "    netSalesInETH\n",
    "    netRevenueInETH\n",
    "    isFirstSale\n",
    "    nftHistory{\n",
    "    event\n",
    "    date\n",
    "    amountInETH\n",
    "    actorAccount{\n",
    "    id\n",
    "    }\n",
    "    }\n",
    "  }\n",
    "}\n",
    "\"\"\"\n",
    "    result = run_query(query)\n",
    "    return result['data']['nfts'][0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "da9a9227",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 20000/20000 [1:13:27<00:00,  4.54it/s]\n"
     ]
    }
   ],
   "source": [
    "nft_metadata = {}\n",
    "\n",
    "### i.e. brute force call all of the minted token ids\n",
    "for t_id in tqdm(range(0,20000)):\n",
    "    try:\n",
    "        nft_metadata[t_id] = get_metadata(t_id)\n",
    "    except:\n",
    "        continue\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "9a1580b7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N art minted: 50724\n"
     ]
    }
   ],
   "source": [
    "print(\"N art minted:\", np.max(list(nft_metadata.keys())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "5ec0c661",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('../new-data/nft_raw_data.txt', 'w') as outfile:\n",
    "    json.dump(nft_metadata, outfile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "c5a1de89",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N art minted: 50723\n"
     ]
    }
   ],
   "source": [
    "t = json.load(open('../new-data/nft_raw_data.txt','r'))\n",
    "#t = dict(t)\n",
    "print(\"N art minted:\", len(list(t.keys())))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39ae25b4",
   "metadata": {},
   "source": [
    "# Organize Data\n",
    "\n",
    "- take the raw data from above and organize it into readable form"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "bf0c3cde",
   "metadata": {},
   "outputs": [],
   "source": [
    "# given a nft return the nft metadata, minting data, bidding data, listing data\n",
    "def organize_dict(nft_data):\n",
    "    \n",
    "    # nft metadata\n",
    "    nft_id = int(nft_data['tokenId'])\n",
    "    owner_id = nft_data['owner']['id']\n",
    "    creator_id = nft_data['creator']['id']\n",
    "    mint_date = nft_data['dateMinted']\n",
    "    is_sold = not nft_data['isFirstSale']\n",
    "    net_artist_earning = nft_data['netRevenueInETH']\n",
    "    selling_price = nft_data['netSalesInETH']\n",
    "    \n",
    "    metadata_tmp = pd.DataFrame({'token_id':[nft_id],'creator':[creator_id],\n",
    "                                'is_sold':[is_sold],'net_artist_earn_eth':[net_artist_earning],\n",
    "                                'selling_price_eth':[selling_price], 'owner':[owner_id]})\n",
    "    mint_df_tmp = pd.DataFrame({'token_id':[nft_id],'mint_date':[mint_date]})\n",
    "    \n",
    "    \n",
    "    # event history\n",
    "    events = nft_data['nftHistory']\n",
    "    \n",
    "    bid_list_art_id = []\n",
    "    bid_list_actor_id = []\n",
    "    bid_list_eth = []\n",
    "    bid_list_date = []\n",
    "    bid_list_creator = []\n",
    "    \n",
    "    list_art_id = []\n",
    "    list_user_id = []\n",
    "    list_date = []\n",
    "    list_eth = []\n",
    "    \n",
    "    for e in events:\n",
    "        if e['event'] == 'Bid':\n",
    "            bid_list_art_id.append(nft_id)\n",
    "            bid_list_actor_id.append(e['actorAccount']['id'])\n",
    "            bid_list_date.append(e['date'])\n",
    "            bid_list_eth.append(e['amountInETH'])\n",
    "            bid_list_creator.append(creator_id)\n",
    "            \n",
    "        if e['event'] == 'Listed':\n",
    "            list_art_id.append(nft_id)\n",
    "            list_user_id.append(e['actorAccount']['id'])\n",
    "            list_date.append(e['date'])\n",
    "            list_eth.append(e['amountInETH'])\n",
    "    \n",
    "    list_df_tmp = pd.DataFrame({'token_id':list_art_id,'creator':list_user_id,\n",
    "                                'listing_date':list_date,'listing_amt':list_eth})\n",
    "    bid_df_tmp = pd.DataFrame({'token_id':bid_list_art_id,'bidder_id':bid_list_actor_id,\n",
    "                              'creator':bid_list_creator,'bidding_amt':bid_list_eth,\n",
    "                              'bid_date':bid_list_date})\n",
    "        \n",
    "    return metadata_tmp, mint_df_tmp, list_df_tmp, bid_df_tmp    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "8a288137",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 50723/50723 [17:01<00:00, 49.68it/s] \n"
     ]
    },
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>token_id</th>\n",
       "      <th>bidder_id</th>\n",
       "      <th>creator</th>\n",
       "      <th>bidding_amt</th>\n",
       "      <th>bid_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0xb188ee1daca51ce6b58ccf8a81ce4025a714bc73</td>\n",
       "      <td>0x2b65a808d0d5d54cdbb701b82d814374b812a4b8</td>\n",
       "      <td>0.43</td>\n",
       "      <td>1612394715</td>\n",
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       "    <tr>\n",
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       "      <td>2.0</td>\n",
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       "      <td>0.3735</td>\n",
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       "      <td>0x376884df6fb55bfa319d703bc1ac5091ef479ff5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1612437649</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.0</td>\n",
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       "      <td>3</td>\n",
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       "      <td>3.0</td>\n",
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       "      <td>0x376884df6fb55bfa319d703bc1ac5091ef479ff5</td>\n",
       "      <td>1.1201</td>\n",
       "      <td>1612376298</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   token_id                                   bidder_id  \\\n",
       "0       2.0  0xb188ee1daca51ce6b58ccf8a81ce4025a714bc73   \n",
       "1       2.0  0x93730ce5ac9de1db9f3fbb73bf522a690629ccec   \n",
       "2       3.0  0x65c8c8b156a1d1a9488bd2be3798dfc417ecee45   \n",
       "3       3.0  0xc88ebc63c3126e9f37a46c1cf55b0e79c9cc20e2   \n",
       "4       3.0  0xeb4bd5231274aa4c2b97a4fa06bad9ecfcdad5e0   \n",
       "\n",
       "                                      creator bidding_amt    bid_date  \n",
       "0  0x2b65a808d0d5d54cdbb701b82d814374b812a4b8        0.43  1612394715  \n",
       "1  0x2b65a808d0d5d54cdbb701b82d814374b812a4b8      0.3735  1612378795  \n",
       "2  0x376884df6fb55bfa319d703bc1ac5091ef479ff5         3.5  1612437649  \n",
       "3  0x376884df6fb55bfa319d703bc1ac5091ef479ff5           3  1612376558  \n",
       "4  0x376884df6fb55bfa319d703bc1ac5091ef479ff5      1.1201  1612376298  "
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nft_metadata_df = pd.DataFrame()\n",
    "mint_df = pd.DataFrame()\n",
    "list_df = pd.DataFrame()\n",
    "bid_df = pd.DataFrame()\n",
    "\n",
    "for v in tqdm(list(nft_metadata.values())):\n",
    "    a, b, c, d = organize_dict(v)\n",
    "        \n",
    "    nft_metadata_df = nft_metadata_df.append(a, ignore_index = True)\n",
    "    mint_df = mint_df.append(b, ignore_index = True)\n",
    "    list_df = list_df.append(c, ignore_index = True)\n",
    "    bid_df = bid_df.append(d, ignore_index = True)\n",
    "    \n",
    "bid_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "6ae72a06",
   "metadata": {},
   "outputs": [],
   "source": [
    "### save data frames\n",
    "mint_df.to_csv(\"../new-data/mint_data.csv\", index = False)\n",
    "bid_df.to_csv(\"../new-data/bid_data.csv\", index = False)\n",
    "list_df.to_csv(\"../new-data/list_data.csv\", index = False)\n",
    "nft_metadata_df.to_csv(\"../new-data/nft_metadata.csv\", index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d1bb929f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "fc30b2fc",
   "metadata": {},
   "source": [
    "# Get Foundation Follow Counts\n",
    "\n",
    "- use Selenium to web crawl the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "8a248303",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N creators: 15366\n"
     ]
    }
   ],
   "source": [
    "creators_to_crawl = list(nft_metadata_df.creator.unique())\n",
    "print(\"N creators:\", len(creators_to_crawl))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b5c30233",
   "metadata": {},
   "outputs": [],
   "source": [
    "### packages to load\n",
    "import os\n",
    "import time\n",
    "import io\n",
    "import requests\n",
    "import pandas as pd\n",
    "from tqdm import tqdm\n",
    "import numpy as np\n",
    "import networkx as nx\n",
    "\n",
    "# selenium stuff\n",
    "import selenium\n",
    "from selenium import webdriver\n",
    "from webdriver_manager.chrome import ChromeDriverManager\n",
    "#from webdriver_manager.firefox import FirefoxDriverManager\n",
    "from selenium.common.exceptions import ElementClickInterceptedException\n",
    "from selenium.webdriver.support.ui import WebDriverWait\n",
    "from selenium.webdriver.common.by import By\n",
    "from selenium.webdriver.common.desired_capabilities import DesiredCapabilities\n",
    "from selenium.webdriver.common.keys import Keys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fcac513c",
   "metadata": {},
   "outputs": [],
   "source": [
    "####\n",
    "# get artists metadata\n",
    "####\n",
    "\n",
    "# given a artist page extract their metadata\n",
    "def artist_metadata(x):\n",
    "\n",
    "    page_link = 'https://foundation.app/' + str(x)\n",
    "    # remove @ in front of id if needed\n",
    "    driver.get(page_link)\n",
    "    #driver.execute_script(\"window.scrollTo(0, document.body.scrollHeight);\")\n",
    "    driver.execute_script(\"document.body.style.zoom='60 %'\")\n",
    "\n",
    "    time.sleep(2)\n",
    "\n",
    "    artist_id = x\n",
    "\n",
    "    # artist name\n",
    "    artist_name = driver.find_element_by_xpath('/html/body/div/div[2]/div[3]/div[1]/div[2]/div/div[1]/h2').text\n",
    "    artist_handle = driver.find_element_by_xpath('/html/body/div/div[2]/div[3]/div[1]/div[2]/div/div[1]/div/div').text\n",
    "    \n",
    "    # update page link\n",
    "    page_link = 'https://foundation.app/'+artist_handle\n",
    "    \n",
    "    artist_handle = artist_handle[1:]\n",
    "    \n",
    "    # about the artist\n",
    "    about = driver.find_element_by_xpath('/html/body/div/div[2]/div[3]/div[1]/div[2]/div/div[2]/div[2]/div/div[2]/div[2]/div').text\n",
    "\n",
    "    # web links\n",
    "    elems = driver.find_elements_by_xpath(\"//a[@href]\")\n",
    "    twitter_link = ''\n",
    "    instagram_link = ''\n",
    "\n",
    "    for elem in elems:\n",
    "        attr_name = elem.get_attribute(\"href\")\n",
    "        if 'instagram' in attr_name and 'foundation' not in attr_name:\n",
    "            instagram_link = attr_name\n",
    "        if 'twitter' in attr_name and 'foundation' not in attr_name:\n",
    "            twitter_link = attr_name\n",
    "    \n",
    "    n_following = driver.find_element_by_xpath('/html/body/div/div[2]/div[3]/div[1]/div[2]/div/div[2]/div[1]/div[2]/div[1]/div/div[1]').text\n",
    "    n_followers = driver.find_element_by_xpath('/html/body/div/div[2]/div[3]/div[1]/div[2]/div/div[2]/div[1]/div[2]/div[2]/div/div[1]').text\n",
    "    \n",
    "    try:\n",
    "        invited_artist = driver.find_element_by_xpath('/html/body/div/div[2]/div[3]/div[1]/div[2]/div/div[2]/div[2]/div/div[1]/div[3]/a/div/div[1]/div[2]')\n",
    "        invited_artist_name = invited_artist.text\n",
    "        \n",
    "    except:\n",
    "        invited_artist_name = ''\n",
    "    \n",
    "    return pd.DataFrame({'artist_id':[x],'artist_name':[artist_name],'artist_handle':[artist_handle],\n",
    "                         'page_link':[page_link],'description':[about],'invited_by':[invited_artist_name],\n",
    "                        'twitter':[twitter_link],'instagram':[instagram_link],\n",
    "                        'n_following':[n_following],'n_followers':[n_followers]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c46fb9f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "====== WebDriver manager ======\n",
      "Current google-chrome version is 100.0.4896\n",
      "Get LATEST driver version for 100.0.4896\n",
      "Driver [/Users/kishorevasan/.wdm/drivers/chromedriver/mac64/100.0.4896.60/chromedriver] found in cache\n"
     ]
    }
   ],
   "source": [
    "chrome_options = webdriver.ChromeOptions()\n",
    "prefs = {\"profile.managed_default_content_settings\":{\"images\": 0},\n",
    "        \"profile.default_content_settings\":{\"images\": 0}}\n",
    "\n",
    "\n",
    "chrome_options.add_experimental_option(\"prefs\", prefs)\n",
    "\n",
    "### ENSURE THAT THE WINDOW IS ATLEAST 920 x 920\n",
    "chrome_options.add_argument(\"window-size=920x920\")\n",
    "\n",
    "## web driver\n",
    "driver = webdriver.Chrome(ChromeDriverManager().install())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2734e183",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artist_id</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>artist_handle</th>\n",
       "      <th>page_link</th>\n",
       "      <th>description</th>\n",
       "      <th>invited_by</th>\n",
       "      <th>twitter</th>\n",
       "      <th>instagram</th>\n",
       "      <th>n_following</th>\n",
       "      <th>n_followers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x46E517ce5dAfBcA7D51cbCE115078E82F7B74963</td>\n",
       "      <td>BarabásiLab</td>\n",
       "      <td>BarabasiLab</td>\n",
       "      <td>https://foundation.app/@BarabasiLab</td>\n",
       "      <td>BarabásiLab is a scientist-artist collective d...</td>\n",
       "      <td>@weiler</td>\n",
       "      <td>https://twitter.com/barabasi</td>\n",
       "      <td>https://instagram.com/barabasi</td>\n",
       "      <td>43</td>\n",
       "      <td>220</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    artist_id  artist_name artist_handle  \\\n",
       "0  0x46E517ce5dAfBcA7D51cbCE115078E82F7B74963  BarabásiLab   BarabasiLab   \n",
       "\n",
       "                             page_link  \\\n",
       "0  https://foundation.app/@BarabasiLab   \n",
       "\n",
       "                                         description invited_by  \\\n",
       "0  BarabásiLab is a scientist-artist collective d...    @weiler   \n",
       "\n",
       "                        twitter                       instagram n_following  \\\n",
       "0  https://twitter.com/barabasi  https://instagram.com/barabasi          43   \n",
       "\n",
       "  n_followers  \n",
       "0         220  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### example::: \n",
    "artist_metadata('0x46E517ce5dAfBcA7D51cbCE115078E82F7B74963')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "id": "00df8c25",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 15366/15366 [1:45:48<00:00,  2.42it/s]   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N artists crawled: 14856\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artist_id</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>artist_handle</th>\n",
       "      <th>page_link</th>\n",
       "      <th>description</th>\n",
       "      <th>invited_by</th>\n",
       "      <th>twitter</th>\n",
       "      <th>instagram</th>\n",
       "      <th>n_following</th>\n",
       "      <th>n_followers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0xcf0949bf6d2adf8032260fd08039c879cf71c128</td>\n",
       "      <td>Sarah Zucker</td>\n",
       "      <td>thesarahshow</td>\n",
       "      <td>https://foundation.app/@thesarahshow</td>\n",
       "      <td>artist + writer 🅞🅟🅔🅝🅘🅝🅖 🅟🅞🅡🅣🅐🅛🅢 between cuttin...</td>\n",
       "      <td></td>\n",
       "      <td>https://twitter.com/thesarahshow</td>\n",
       "      <td>https://instagram.com/thesarahshow</td>\n",
       "      <td>8</td>\n",
       "      <td>165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x2b65a808d0d5d54cdbb701b82d814374b812a4b8</td>\n",
       "      <td>Michael Shillingburg</td>\n",
       "      <td>shilly</td>\n",
       "      <td>https://foundation.app/@shilly</td>\n",
       "      <td>Designer &amp; 3D illustrator creating interactive...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>https://instagram.com/planet.gif</td>\n",
       "      <td>2</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x376884df6fb55bfa319d703bc1ac5091ef479ff5</td>\n",
       "      <td>Sven Eberwein</td>\n",
       "      <td>sveneberwein</td>\n",
       "      <td>https://foundation.app/@sveneberwein</td>\n",
       "      <td>Working at the intersection of computer graphi...</td>\n",
       "      <td></td>\n",
       "      <td>https://twitter.com/sven_eberwein</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x080b6202c0a5c464799e1e5a4aa7325eace9a5e1</td>\n",
       "      <td>Jessica Ticchio</td>\n",
       "      <td>jessicaticchio</td>\n",
       "      <td>https://foundation.app/@jessicaticchio</td>\n",
       "      <td>Jessica Ticchio is a multidisciplinary creativ...</td>\n",
       "      <td></td>\n",
       "      <td>https://twitter.com/jessticchio_art</td>\n",
       "      <td>https://instagram.com/jessicaticchio</td>\n",
       "      <td>47</td>\n",
       "      <td>300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x87042da39c06b0f85b435e5ec8ce2b15ec7bd700</td>\n",
       "      <td>HY𝒜M</td>\n",
       "      <td>hyam</td>\n",
       "      <td>https://foundation.app/@hyam</td>\n",
       "      <td>hyam is an experimental artist working with mi...</td>\n",
       "      <td></td>\n",
       "      <td>https://twitter.com/hyumankind</td>\n",
       "      <td>https://instagram.com/hyumankind</td>\n",
       "      <td>6</td>\n",
       "      <td>1371</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    artist_id           artist_name  \\\n",
       "0  0xcf0949bf6d2adf8032260fd08039c879cf71c128          Sarah Zucker   \n",
       "0  0x2b65a808d0d5d54cdbb701b82d814374b812a4b8  Michael Shillingburg   \n",
       "0  0x376884df6fb55bfa319d703bc1ac5091ef479ff5         Sven Eberwein   \n",
       "0  0x080b6202c0a5c464799e1e5a4aa7325eace9a5e1       Jessica Ticchio   \n",
       "0  0x87042da39c06b0f85b435e5ec8ce2b15ec7bd700                  HY𝒜M   \n",
       "\n",
       "    artist_handle                               page_link  \\\n",
       "0    thesarahshow    https://foundation.app/@thesarahshow   \n",
       "0          shilly          https://foundation.app/@shilly   \n",
       "0    sveneberwein    https://foundation.app/@sveneberwein   \n",
       "0  jessicaticchio  https://foundation.app/@jessicaticchio   \n",
       "0            hyam            https://foundation.app/@hyam   \n",
       "\n",
       "                                         description invited_by  \\\n",
       "0  artist + writer 🅞🅟🅔🅝🅘🅝🅖 🅟🅞🅡🅣🅐🅛🅢 between cuttin...              \n",
       "0  Designer & 3D illustrator creating interactive...              \n",
       "0  Working at the intersection of computer graphi...              \n",
       "0  Jessica Ticchio is a multidisciplinary creativ...              \n",
       "0  hyam is an experimental artist working with mi...              \n",
       "\n",
       "                               twitter                             instagram  \\\n",
       "0     https://twitter.com/thesarahshow    https://instagram.com/thesarahshow   \n",
       "0                                           https://instagram.com/planet.gif   \n",
       "0    https://twitter.com/sven_eberwein                                         \n",
       "0  https://twitter.com/jessticchio_art  https://instagram.com/jessicaticchio   \n",
       "0       https://twitter.com/hyumankind      https://instagram.com/hyumankind   \n",
       "\n",
       "  n_following n_followers  \n",
       "0           8         165  \n",
       "0           2         141  \n",
       "0           0          99  \n",
       "0          47         300  \n",
       "0           6        1371  "
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#artist_metadata_df = pd.DataFrame()\n",
    "\n",
    "for a in tqdm(creators_to_crawl):\n",
    "    try:\n",
    "        if a in artist_metadata_df.artist_id.tolist() and artist_metadata_df[artist_metadata_df.artist_id == a].n_following.tolist()[0] == '':\n",
    "            artist_metadata_df = artist_metadata_df.append(artist_metadata(a))\n",
    "    except:\n",
    "        continue\n",
    "\n",
    "print(\"N artists crawled:\", artist_metadata_df.artist_id.nunique())\n",
    "artist_metadata_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "id": "9485a115",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#artist_metadata_df.to_csv(\"../new-data/artist_metadata.csv\", index = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f78424ae",
   "metadata": {},
   "source": [
    "## Crawl Invited Artists \n",
    "\n",
    "- get the metadata about the invited artists."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "id": "401b4df1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artist_id</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>artist_handle</th>\n",
       "      <th>page_link</th>\n",
       "      <th>description</th>\n",
       "      <th>invited_by</th>\n",
       "      <th>twitter</th>\n",
       "      <th>instagram</th>\n",
       "      <th>n_following</th>\n",
       "      <th>n_followers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>0xa8a33539960ef4779cb0eceded8002c1ecd40582</td>\n",
       "      <td>Collin LaFleche</td>\n",
       "      <td>usually</td>\n",
       "      <td>https://foundation.app/@usually</td>\n",
       "      <td>Collin LaFleche is a filmmaker from New York.</td>\n",
       "      <td>jessewldn</td>\n",
       "      <td>https://twitter.com/collinlafleche</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>0x63a811487f7a84ec2dfcd1851e24acd75d2431c8</td>\n",
       "      <td>Griffin Frazen</td>\n",
       "      <td>griffinfrazen</td>\n",
       "      <td>https://foundation.app/@griffinfrazen</td>\n",
       "      <td>Griffin Frazen is an Emmy award winning design...</td>\n",
       "      <td>jessewldn</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>0x48f0efe12a93d43fbf81d1fff7c22b4b0a06661e</td>\n",
       "      <td>Bella - Piano and the Fox</td>\n",
       "      <td>pianoandthefox</td>\n",
       "      <td>https://foundation.app/@pianoandthefox</td>\n",
       "      <td>U.K based passionate 3D artist, animator, and ...</td>\n",
       "      <td>wonderkatzi</td>\n",
       "      <td>https://twitter.com/pianoandthefox</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>0x01df805afe4325d7ebab11d2a41433eb6e278631</td>\n",
       "      <td>ZiP Visuals</td>\n",
       "      <td>zip_visuals</td>\n",
       "      <td>https://foundation.app/@zip_visuals</td>\n",
       "      <td>I am a self-taught 3D artist from Brooklyn, Ne...</td>\n",
       "      <td>peenpoon</td>\n",
       "      <td>https://twitter.com/zip_visuals</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>0x7c1ab760a4126e827dd3ed88c2baf21ee4de5f3b</td>\n",
       "      <td>Aaron Leroy</td>\n",
       "      <td>onderwish</td>\n",
       "      <td>https://foundation.app/@onderwish</td>\n",
       "      <td>🟨Spreading art across the cosmos 🎨🚀\\n🟡Working ...</td>\n",
       "      <td>sergeposters</td>\n",
       "      <td>https://twitter.com/onderwish</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>280.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16548</th>\n",
       "      <td>0xd8cd983d81f38e620389f3204f67a348dbf051c5</td>\n",
       "      <td>bruce getty</td>\n",
       "      <td>gettyartistsf</td>\n",
       "      <td>https://foundation.app/@gettyartistsf</td>\n",
       "      <td>Oh boy! My name is Bruce Getty. I am a Bay Are...</td>\n",
       "      <td>jstnptrs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://instagram.com/gettyphotography</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16549</th>\n",
       "      <td>0x19c1c2b4f2444ad04eb535cdab188c901bf9ec15</td>\n",
       "      <td>Master Control Program</td>\n",
       "      <td>mastercontrolprogram</td>\n",
       "      <td>https://foundation.app/@mastercontrolprogram</td>\n",
       "      <td>I touch on minimalist compositions, retro-futu...</td>\n",
       "      <td>Boxhead</td>\n",
       "      <td>https://twitter.com/MCP_Art</td>\n",
       "      <td>https://instagram.com/master_control_program</td>\n",
       "      <td>111.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16550</th>\n",
       "      <td>0x1d8d0c731fd00f39a5f7be7b3cb4d8785947724f</td>\n",
       "      <td>Marco Brambillla</td>\n",
       "      <td>marcobrambilla</td>\n",
       "      <td>https://foundation.app/@marcobrambilla</td>\n",
       "      <td>Marco Brambilla is an artist. His pioneering u...</td>\n",
       "      <td>dom</td>\n",
       "      <td>https://twitter.com/BrambillaStudio</td>\n",
       "      <td>https://instagram.com/marcobrambillastudio</td>\n",
       "      <td>35.0</td>\n",
       "      <td>579.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16551</th>\n",
       "      <td>0x7a8f54fc16511ec86429e6197b7835ad6047a6ef</td>\n",
       "      <td>Penelope</td>\n",
       "      <td>pmnoe</td>\n",
       "      <td>https://foundation.app/@pmnoe</td>\n",
       "      <td>PM is a multimedia artist who channels postmod...</td>\n",
       "      <td>zendamage</td>\n",
       "      <td>https://twitter.com/penelopeMNT</td>\n",
       "      <td>https://instagram.com/pmnoeart</td>\n",
       "      <td>86.0</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16552</th>\n",
       "      <td>0xb32044d6911effab4f19a143a9cecd886403003e</td>\n",
       "      <td>Gabriella Morton</td>\n",
       "      <td>gabriellamorton</td>\n",
       "      <td>https://foundation.app/@gabriellamorton</td>\n",
       "      <td>Bridging the gap between art and science to cr...</td>\n",
       "      <td>reuko</td>\n",
       "      <td>https://twitter.com/gabriellamort</td>\n",
       "      <td>https://instagram.com/gabriellamorton</td>\n",
       "      <td>212.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14116 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        artist_id                artist_name  \\\n",
       "62     0xa8a33539960ef4779cb0eceded8002c1ecd40582            Collin LaFleche   \n",
       "64     0x63a811487f7a84ec2dfcd1851e24acd75d2431c8             Griffin Frazen   \n",
       "66     0x48f0efe12a93d43fbf81d1fff7c22b4b0a06661e  Bella - Piano and the Fox   \n",
       "68     0x01df805afe4325d7ebab11d2a41433eb6e278631                ZiP Visuals   \n",
       "71     0x7c1ab760a4126e827dd3ed88c2baf21ee4de5f3b                Aaron Leroy   \n",
       "...                                           ...                        ...   \n",
       "16548  0xd8cd983d81f38e620389f3204f67a348dbf051c5                bruce getty   \n",
       "16549  0x19c1c2b4f2444ad04eb535cdab188c901bf9ec15     Master Control Program   \n",
       "16550  0x1d8d0c731fd00f39a5f7be7b3cb4d8785947724f           Marco Brambillla   \n",
       "16551  0x7a8f54fc16511ec86429e6197b7835ad6047a6ef                   Penelope   \n",
       "16552  0xb32044d6911effab4f19a143a9cecd886403003e           Gabriella Morton   \n",
       "\n",
       "              artist_handle                                     page_link  \\\n",
       "62                  usually               https://foundation.app/@usually   \n",
       "64            griffinfrazen         https://foundation.app/@griffinfrazen   \n",
       "66           pianoandthefox        https://foundation.app/@pianoandthefox   \n",
       "68              zip_visuals           https://foundation.app/@zip_visuals   \n",
       "71                onderwish             https://foundation.app/@onderwish   \n",
       "...                     ...                                           ...   \n",
       "16548         gettyartistsf         https://foundation.app/@gettyartistsf   \n",
       "16549  mastercontrolprogram  https://foundation.app/@mastercontrolprogram   \n",
       "16550        marcobrambilla        https://foundation.app/@marcobrambilla   \n",
       "16551                 pmnoe                 https://foundation.app/@pmnoe   \n",
       "16552       gabriellamorton       https://foundation.app/@gabriellamorton   \n",
       "\n",
       "                                             description    invited_by  \\\n",
       "62         Collin LaFleche is a filmmaker from New York.     jessewldn   \n",
       "64     Griffin Frazen is an Emmy award winning design...     jessewldn   \n",
       "66     U.K based passionate 3D artist, animator, and ...   wonderkatzi   \n",
       "68     I am a self-taught 3D artist from Brooklyn, Ne...      peenpoon   \n",
       "71     🟨Spreading art across the cosmos 🎨🚀\\n🟡Working ...  sergeposters   \n",
       "...                                                  ...           ...   \n",
       "16548  Oh boy! My name is Bruce Getty. I am a Bay Are...      jstnptrs   \n",
       "16549  I touch on minimalist compositions, retro-futu...       Boxhead   \n",
       "16550  Marco Brambilla is an artist. His pioneering u...           dom   \n",
       "16551  PM is a multimedia artist who channels postmod...     zendamage   \n",
       "16552  Bridging the gap between art and science to cr...         reuko   \n",
       "\n",
       "                                   twitter  \\\n",
       "62      https://twitter.com/collinlafleche   \n",
       "64                                     NaN   \n",
       "66      https://twitter.com/pianoandthefox   \n",
       "68         https://twitter.com/zip_visuals   \n",
       "71           https://twitter.com/onderwish   \n",
       "...                                    ...   \n",
       "16548                                  NaN   \n",
       "16549          https://twitter.com/MCP_Art   \n",
       "16550  https://twitter.com/BrambillaStudio   \n",
       "16551      https://twitter.com/penelopeMNT   \n",
       "16552    https://twitter.com/gabriellamort   \n",
       "\n",
       "                                          instagram  n_following  n_followers  \n",
       "62                                              NaN          1.0          9.0  \n",
       "64                                              NaN          0.0          4.0  \n",
       "66                                              NaN         12.0        114.0  \n",
       "68                                              NaN         22.0         46.0  \n",
       "71                                              NaN          2.0        280.0  \n",
       "...                                             ...          ...          ...  \n",
       "16548        https://instagram.com/gettyphotography          4.0          8.0  \n",
       "16549  https://instagram.com/master_control_program        111.0        100.0  \n",
       "16550    https://instagram.com/marcobrambillastudio         35.0        579.0  \n",
       "16551                https://instagram.com/pmnoeart         86.0         98.0  \n",
       "16552         https://instagram.com/gabriellamorton        212.0        149.0  \n",
       "\n",
       "[14116 rows x 10 columns]"
      ]
     },
     "execution_count": 302,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "artist_metadata_df[~artist_metadata_df.invited_by.isna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "id": "8e4af19c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1643"
      ]
     },
     "execution_count": 305,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "invited_by_list = list(artist_metadata_df[~artist_metadata_df.invited_by.isna()].invited_by.unique())\n",
    "\n",
    "invited_by_list = [i for i in invited_by_list if i not in artist_metadata_df.artist_handle.tolist()]\n",
    "len(invited_by_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "id": "a9a9ca12",
   "metadata": {},
   "outputs": [],
   "source": [
    "####\n",
    "# get artists metadata\n",
    "####\n",
    "\n",
    "# given a artist page extract their metadata\n",
    "def artist_metadata(x):\n",
    "\n",
    "    page_link = 'https://foundation.app/' + str(x)\n",
    "    # remove @ in front of id if needed\n",
    "    driver.get(page_link)\n",
    "    #driver.execute_script(\"window.scrollTo(0, document.body.scrollHeight);\")\n",
    "    driver.execute_script(\"document.body.style.zoom='60 %'\")\n",
    "\n",
    "    time.sleep(2)\n",
    "    \n",
    "    # blockchain address\n",
    "    btn = driver.find_element_by_xpath('/html/body/div/div[2]/div[4]/div[1]/div[1]/div/div/div[3]')\n",
    "    chains = ActionChains(driver)\n",
    "    chains.click(btn).perform()\n",
    "    chains.send_keys(Keys.CONTROL + 'c').perform()\n",
    "    artist_id = pyperclip.paste()\n",
    "\n",
    "    # artist name\n",
    "    artist_name = driver.find_element_by_xpath('/html/body/div/div[2]/div[4]/div[1]/div[2]/div/div[1]/div[1]/div/div').text\n",
    "    artist_handle = driver.find_element_by_xpath('/html/body/div/div[2]/div[4]/div[1]/div[2]/div/div[1]/div[2]/div').text\n",
    "    \n",
    "    # update page link\n",
    "    page_link = 'https://foundation.app/'+artist_handle\n",
    "    \n",
    "    artist_handle = artist_handle[1:]\n",
    "    \n",
    "    # about the artist\n",
    "    about = driver.find_element_by_xpath('/html/body/div/div[2]/div[4]/div[1]/div[2]/div/div[2]/div[2]/div/div[2]/div[2]/div').text\n",
    "\n",
    "    # web links\n",
    "    elems = driver.find_elements_by_xpath(\"//a[@href]\")\n",
    "    twitter_link = ''\n",
    "    instagram_link = ''\n",
    "\n",
    "    for elem in elems:\n",
    "        attr_name = elem.get_attribute(\"href\")\n",
    "        if 'instagram' in attr_name and 'foundation' not in attr_name:\n",
    "            instagram_link = attr_name\n",
    "        if 'twitter' in attr_name and 'withfnd' not in attr_name:\n",
    "            twitter_link = attr_name\n",
    "    \n",
    "    n_following = driver.find_element_by_xpath('/html/body/div/div[2]/div[4]/div[1]/div[2]/div/div[2]/div[1]/div[2]/div[1]/div/div[1]').text\n",
    "    n_followers = driver.find_element_by_xpath('/html/body/div/div[2]/div[4]/div[1]/div[2]/div/div[2]/div[1]/div[2]/div[2]/div/div[1]').text\n",
    "\n",
    "    # get the invited artist\n",
    "    invited_artist_page = driver.find_elements_by_class_name('css-h6hd16')\n",
    "    if len(invited_artist_page)>0:\n",
    "        invited_artist_page = invited_artist_page[0].get_attribute('href')\n",
    "        invited_artist_page = list(invited_artist_page)\n",
    "        idx = len(invited_artist_page) - 1 - invited_artist_page[::-1].index('/')\n",
    "        invited_artist_name = ''.join(invited_artist_page[idx+1:])\n",
    "        invited_artist_name = invited_artist_name[1:]\n",
    "    else:\n",
    "        invited_artist_name = ''\n",
    "\n",
    "    \n",
    "    return pd.DataFrame({'artist_id':[artist_id],'artist_name':[artist_name],'artist_handle':[artist_handle],\n",
    "                         'page_link':[page_link],'description':[about],'invited_by':[invited_artist_name],\n",
    "                        'twitter':[twitter_link],'instagram':[instagram_link],\n",
    "                        'n_following':[n_following],'n_followers':[n_followers]})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c9e73a9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "btn = driver.find_element_by_xpath('/html/body/div/div[2]/div[4]/div[1]/div[1]/div/div/div[3]')\n",
    "ActionChains = ActionChains(driver)\n",
    "ActionChains.double_click(btn).perform()\n",
    "ActionChains.send_keys(Keys.CONTROL + 'c').perform()\n",
    "text = pyperclip.paste()\n",
    "print(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "id": "b3b7179b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1643/1643 [2:04:05<00:00,  4.53s/it]  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N artists crawled: 1469\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artist_id</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>artist_handle</th>\n",
       "      <th>page_link</th>\n",
       "      <th>description</th>\n",
       "      <th>invited_by</th>\n",
       "      <th>twitter</th>\n",
       "      <th>instagram</th>\n",
       "      <th>n_following</th>\n",
       "      <th>n_followers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0xe7925D190aea9279400cD9a005E33CEB9389Cc2b</td>\n",
       "      <td>Jesse Walden</td>\n",
       "      <td>jessewldn</td>\n",
       "      <td>https://foundation.app/@jessewldn</td>\n",
       "      <td>variant.fund</td>\n",
       "      <td></td>\n",
       "      <td>https://twitter.com/jessewldn</td>\n",
       "      <td></td>\n",
       "      <td>3</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0xb88ba009241c4ae57A265E8bD1932E41B20e5570</td>\n",
       "      <td>Adam Lisagor</td>\n",
       "      <td>adamlisagor</td>\n",
       "      <td>https://foundation.app/@adamlisagor</td>\n",
       "      <td>sandwich.co</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>6</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x11c75F3480E23755ee25273e1344875499260c6e</td>\n",
       "      <td>Sam Clover</td>\n",
       "      <td>planttdaddii</td>\n",
       "      <td>https://foundation.app/@planttdaddii</td>\n",
       "      <td>Sam Clover aka PLANTTDADDII is a digital sculp...</td>\n",
       "      <td></td>\n",
       "      <td>https://twitter.com/planttdaddii</td>\n",
       "      <td>https://instagram.com/planttdaddii</td>\n",
       "      <td>15</td>\n",
       "      <td>384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x7d42611012FDbE366Bf4A0481FC0E1aBf15E245A</td>\n",
       "      <td>Jeff Davis</td>\n",
       "      <td>jeffgdavis</td>\n",
       "      <td>https://foundation.app/@jeffgdavis</td>\n",
       "      <td>Artist / CCO at Art Blocks / Founder at Davis ...</td>\n",
       "      <td>jeffgdavis</td>\n",
       "      <td>https://twitter.com/jeffgdavis</td>\n",
       "      <td></td>\n",
       "      <td>20</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0xfA3A28bc7BEedf3E196B0EfB8804313c285B33dC</td>\n",
       "      <td>ATM</td>\n",
       "      <td>atm</td>\n",
       "      <td>https://foundation.app/@atm</td>\n",
       "      <td>Dillon \"ATM\" is a new media artist who tells h...</td>\n",
       "      <td></td>\n",
       "      <td>https://twitter.com/dillonatm</td>\n",
       "      <td>https://instagram.com/dillonatm</td>\n",
       "      <td>32</td>\n",
       "      <td>692</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    artist_id   artist_name artist_handle  \\\n",
       "0  0xe7925D190aea9279400cD9a005E33CEB9389Cc2b  Jesse Walden     jessewldn   \n",
       "0  0xb88ba009241c4ae57A265E8bD1932E41B20e5570  Adam Lisagor   adamlisagor   \n",
       "0  0x11c75F3480E23755ee25273e1344875499260c6e    Sam Clover  planttdaddii   \n",
       "0  0x7d42611012FDbE366Bf4A0481FC0E1aBf15E245A    Jeff Davis    jeffgdavis   \n",
       "0  0xfA3A28bc7BEedf3E196B0EfB8804313c285B33dC           ATM           atm   \n",
       "\n",
       "                              page_link  \\\n",
       "0     https://foundation.app/@jessewldn   \n",
       "0   https://foundation.app/@adamlisagor   \n",
       "0  https://foundation.app/@planttdaddii   \n",
       "0    https://foundation.app/@jeffgdavis   \n",
       "0           https://foundation.app/@atm   \n",
       "\n",
       "                                         description  invited_by  \\\n",
       "0                                       variant.fund               \n",
       "0                                        sandwich.co               \n",
       "0  Sam Clover aka PLANTTDADDII is a digital sculp...               \n",
       "0  Artist / CCO at Art Blocks / Founder at Davis ...  jeffgdavis   \n",
       "0  Dillon \"ATM\" is a new media artist who tells h...               \n",
       "\n",
       "                            twitter                           instagram  \\\n",
       "0     https://twitter.com/jessewldn                                       \n",
       "0                                                                         \n",
       "0  https://twitter.com/planttdaddii  https://instagram.com/planttdaddii   \n",
       "0    https://twitter.com/jeffgdavis                                       \n",
       "0     https://twitter.com/dillonatm     https://instagram.com/dillonatm   \n",
       "\n",
       "  n_following n_followers  \n",
       "0           3          54  \n",
       "0           6         135  \n",
       "0          15         384  \n",
       "0          20          32  \n",
       "0          32         692  "
      ]
     },
     "execution_count": 331,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# crawl the invited people\n",
    "\n",
    "####\n",
    "## Remember to get the ether wallet id of these people\n",
    "####\n",
    "\n",
    "\n",
    "invited_by_metadata_df = pd.DataFrame()\n",
    "\n",
    "for a in tqdm(invited_by_list):\n",
    "    try:\n",
    "        invited_by_metadata_df = invited_by_metadata_df.append(artist_metadata(a))\n",
    "    except:\n",
    "        continue\n",
    "\n",
    "print(\"N artists crawled:\", invited_by_metadata_df.artist_id.nunique())\n",
    "invited_by_metadata_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "id": "8ef192ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "#invited_by_metadata_df.to_csv(\"../new-data/invited_by_metadata.csv\", index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "id": "f889dfd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "from selenium.webdriver.common.keys import Keys\n",
    "from selenium.webdriver.common.action_chains import ActionChains\n",
    "import pyperclip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "id": "baf4ca3a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0xe7925D190aea9279400cD9a005E33CEB9389Cc2b\n"
     ]
    }
   ],
   "source": [
    "btn = driver.find_element_by_xpath('/html/body/div/div[2]/div[4]/div[1]/div[1]/div/div/div[3]')\n",
    "ActionChains = ActionChains(driver)\n",
    "ActionChains.double_click(btn).perform()\n",
    "ActionChains.send_keys(Keys.CONTROL + 'c').perform()\n",
    "text = pyperclip.paste()\n",
    "print(text)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f8a3867",
   "metadata": {},
   "source": [
    "# Crawl Twitter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "id": "736b984f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artist_id</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>artist_handle</th>\n",
       "      <th>page_link</th>\n",
       "      <th>description</th>\n",
       "      <th>invited_by</th>\n",
       "      <th>twitter</th>\n",
       "      <th>instagram</th>\n",
       "      <th>n_following</th>\n",
       "      <th>n_followers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0xe7925D190aea9279400cD9a005E33CEB9389Cc2b</td>\n",
       "      <td>Jesse Walden</td>\n",
       "      <td>jessewldn</td>\n",
       "      <td>https://foundation.app/@jessewldn</td>\n",
       "      <td>variant.fund</td>\n",
       "      <td></td>\n",
       "      <td>https://twitter.com/jessewldn</td>\n",
       "      <td></td>\n",
       "      <td>3</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x11c75F3480E23755ee25273e1344875499260c6e</td>\n",
       "      <td>Sam Clover</td>\n",
       "      <td>planttdaddii</td>\n",
       "      <td>https://foundation.app/@planttdaddii</td>\n",
       "      <td>Sam Clover aka PLANTTDADDII is a digital sculp...</td>\n",
       "      <td></td>\n",
       "      <td>https://twitter.com/planttdaddii</td>\n",
       "      <td>https://instagram.com/planttdaddii</td>\n",
       "      <td>15</td>\n",
       "      <td>384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x7d42611012FDbE366Bf4A0481FC0E1aBf15E245A</td>\n",
       "      <td>Jeff Davis</td>\n",
       "      <td>jeffgdavis</td>\n",
       "      <td>https://foundation.app/@jeffgdavis</td>\n",
       "      <td>Artist / CCO at Art Blocks / Founder at Davis ...</td>\n",
       "      <td>jeffgdavis</td>\n",
       "      <td>https://twitter.com/jeffgdavis</td>\n",
       "      <td></td>\n",
       "      <td>20</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0xfA3A28bc7BEedf3E196B0EfB8804313c285B33dC</td>\n",
       "      <td>ATM</td>\n",
       "      <td>atm</td>\n",
       "      <td>https://foundation.app/@atm</td>\n",
       "      <td>Dillon \"ATM\" is a new media artist who tells h...</td>\n",
       "      <td></td>\n",
       "      <td>https://twitter.com/dillonatm</td>\n",
       "      <td>https://instagram.com/dillonatm</td>\n",
       "      <td>32</td>\n",
       "      <td>692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x7c1ab760a4126E827dD3eD88C2BaF21EE4de5F3B</td>\n",
       "      <td>Aaron Leroy</td>\n",
       "      <td>onderwish</td>\n",
       "      <td>https://foundation.app/@onderwish</td>\n",
       "      <td>🟨Spreading art across the cosmos 🎨🚀\\n🟡Working ...</td>\n",
       "      <td>sergeposters</td>\n",
       "      <td>https://twitter.com/onderwish</td>\n",
       "      <td></td>\n",
       "      <td>2</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    artist_id   artist_name artist_handle  \\\n",
       "0  0xe7925D190aea9279400cD9a005E33CEB9389Cc2b  Jesse Walden     jessewldn   \n",
       "0  0x11c75F3480E23755ee25273e1344875499260c6e    Sam Clover  planttdaddii   \n",
       "0  0x7d42611012FDbE366Bf4A0481FC0E1aBf15E245A    Jeff Davis    jeffgdavis   \n",
       "0  0xfA3A28bc7BEedf3E196B0EfB8804313c285B33dC           ATM           atm   \n",
       "0  0x7c1ab760a4126E827dD3eD88C2BaF21EE4de5F3B   Aaron Leroy     onderwish   \n",
       "\n",
       "                              page_link  \\\n",
       "0     https://foundation.app/@jessewldn   \n",
       "0  https://foundation.app/@planttdaddii   \n",
       "0    https://foundation.app/@jeffgdavis   \n",
       "0           https://foundation.app/@atm   \n",
       "0     https://foundation.app/@onderwish   \n",
       "\n",
       "                                         description    invited_by  \\\n",
       "0                                       variant.fund                 \n",
       "0  Sam Clover aka PLANTTDADDII is a digital sculp...                 \n",
       "0  Artist / CCO at Art Blocks / Founder at Davis ...    jeffgdavis   \n",
       "0  Dillon \"ATM\" is a new media artist who tells h...                 \n",
       "0  🟨Spreading art across the cosmos 🎨🚀\\n🟡Working ...  sergeposters   \n",
       "\n",
       "                            twitter                           instagram  \\\n",
       "0     https://twitter.com/jessewldn                                       \n",
       "0  https://twitter.com/planttdaddii  https://instagram.com/planttdaddii   \n",
       "0    https://twitter.com/jeffgdavis                                       \n",
       "0     https://twitter.com/dillonatm     https://instagram.com/dillonatm   \n",
       "0     https://twitter.com/onderwish                                       \n",
       "\n",
       "  n_following n_followers  \n",
       "0           3          54  \n",
       "0          15         384  \n",
       "0          20          32  \n",
       "0          32         692  \n",
       "0           2         281  "
      ]
     },
     "execution_count": 339,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "invited_by_metadata_df[invited_by_metadata_df.twitter !=''].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "id": "2819c8a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import the module\n",
    "import tweepy\n",
    "  \n",
    "# assign the values accordingly\n",
    "# Add your API key here\n",
    "consumer_key = \"\"\n",
    "\n",
    "# Add your API secret key here\n",
    "consumer_secret = \"\"\n",
    "\n",
    "\n",
    "access_token = \"\"\n",
    "access_token_secret = \"\"\n",
    "  \n",
    "# authorization of consumer key and consumer secret\n",
    "auth = tweepy.OAuthHandler(consumer_key, consumer_secret)\n",
    "  \n",
    "# set access to user's access key and access secret \n",
    "auth.set_access_token(access_token, access_token_secret)\n",
    "  \n",
    "# calling the api \n",
    "api = tweepy.API(auth,wait_on_rate_limit=True, wait_on_rate_limit_notify=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 341,
   "id": "0a441ba1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# given a user return the user metadata\n",
    "def get_twitter_metadata(x):\n",
    "    \n",
    "    user = api.get_user(x)\n",
    "\n",
    "    location = user.location\n",
    "    user_bio = user.description\n",
    "    profile_location = user.profile_location\n",
    "    followers_count = user.followers_count\n",
    "    following_count = user.friends_count\n",
    "    \n",
    "    created_at = user.created_at\n",
    "    \n",
    "    verified = user.verified\n",
    "    \n",
    "    #latest_tweet = user.status\n",
    "    \n",
    "    #status_dict = latest_tweet._json\n",
    "    \n",
    "#    place_from_tweet = status_dict['place']\n",
    "    \n",
    "    return pd.DataFrame({'user_name':[x],'bio':[user_bio], 'created_at':[created_at],'location':[location],\n",
    "                         'profile_location':[profile_location], 'followers_count':[followers_count],\n",
    "                         'following_count':[following_count], 'verified':[verified]})\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "id": "90b44d1a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13487"
      ]
     },
     "execution_count": 348,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(artist_metadata_df[~artist_metadata_df.twitter.isna()].twitter.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "id": "4c6ca907",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/13487 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N twitter profiles: 13487\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  7%|▋         | 899/13487 [04:39<1:04:30,  3.25it/s]Rate limit reached. Sleeping for: 584\n",
      " 13%|█▎        | 1799/13487 [18:50<54:59,  3.54it/s]    Rate limit reached. Sleeping for: 638\n",
      " 20%|██        | 2699/13487 [33:54<53:46,  3.34it/s]     Rate limit reached. Sleeping for: 639\n",
      " 27%|██▋       | 3599/13487 [49:02<47:52,  3.44it/s]     Rate limit reached. Sleeping for: 636\n",
      " 33%|███▎      | 4499/13487 [1:04:13<45:50,  3.27it/s]   Rate limit reached. Sleeping for: 631\n",
      " 40%|████      | 5399/13487 [1:19:20<39:30,  3.41it/s]     Rate limit reached. Sleeping for: 629\n",
      " 47%|████▋     | 6299/13487 [1:34:27<35:07,  3.41it/s]     Rate limit reached. Sleeping for: 627\n",
      " 53%|█████▎    | 7199/13487 [1:49:39<32:59,  3.18it/s]     Rate limit reached. Sleeping for: 621\n",
      " 60%|██████    | 8099/13487 [2:04:35<29:33,  3.04it/s]     Rate limit reached. Sleeping for: 630\n",
      " 67%|██████▋   | 8999/13487 [2:19:45<20:48,  3.59it/s]     Rate limit reached. Sleeping for: 625\n",
      " 73%|███████▎  | 9899/13487 [2:34:55<16:49,  3.56it/s]     Rate limit reached. Sleeping for: 620\n",
      " 80%|████████  | 10799/13487 [2:50:25<13:41,  3.27it/s]    Rate limit reached. Sleeping for: 595\n",
      " 87%|████████▋ | 11699/13487 [3:05:07<09:34,  3.11it/s]     Rate limit reached. Sleeping for: 618\n",
      " 93%|█████████▎| 12599/13487 [3:20:06<04:29,  3.29it/s]    Rate limit reached. Sleeping for: 624\n",
      "100%|██████████| 13487/13487 [3:35:14<00:00,  1.04it/s]    "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N users crawled: 13155\n",
      "N users not found: 332\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_name</th>\n",
       "      <th>bio</th>\n",
       "      <th>created_at</th>\n",
       "      <th>location</th>\n",
       "      <th>profile_location</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>following_count</th>\n",
       "      <th>verified</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>thesarahshow</td>\n",
       "      <td>artist + writer 🅞🅟🅔🅝🅘🅝🅖 🅟🅞🅡🅣🅐🅛🅢 between cuttin...</td>\n",
       "      <td>2011-02-26 00:38:02</td>\n",
       "      <td>thesarahshow.eth</td>\n",
       "      <td>None</td>\n",
       "      <td>8578</td>\n",
       "      <td>1016</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sven_eberwein</td>\n",
       "      <td>Works of the internet, by the internet, for th...</td>\n",
       "      <td>2020-06-12 17:06:09</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>None</td>\n",
       "      <td>2228</td>\n",
       "      <td>1564</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>jessticchio_art</td>\n",
       "      <td>3D Artist creating boundless dreamscapes &amp; vir...</td>\n",
       "      <td>2021-01-10 06:59:02</td>\n",
       "      <td>Sydney, New South Wales</td>\n",
       "      <td>None</td>\n",
       "      <td>495</td>\n",
       "      <td>415</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>hyumankind</td>\n",
       "      <td>✧ 𝔡𝔢𝔷𝔦𝔤𝔫 ✧ @macro_hq</td>\n",
       "      <td>2011-01-06 05:29:54</td>\n",
       "      <td>San Francisco, CA</td>\n",
       "      <td>None</td>\n",
       "      <td>14108</td>\n",
       "      <td>2695</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FrancoiseGamma</td>\n",
       "      <td>https://t.co/xCZ5E9VBTu\\nhttps://t.co/7L8WDLpa...</td>\n",
       "      <td>2019-12-24 11:11:54</td>\n",
       "      <td>Internet</td>\n",
       "      <td>None</td>\n",
       "      <td>1311</td>\n",
       "      <td>364</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_name                                                bio  \\\n",
       "0     thesarahshow  artist + writer 🅞🅟🅔🅝🅘🅝🅖 🅟🅞🅡🅣🅐🅛🅢 between cuttin...   \n",
       "1    sven_eberwein  Works of the internet, by the internet, for th...   \n",
       "2  jessticchio_art  3D Artist creating boundless dreamscapes & vir...   \n",
       "3       hyumankind                               ✧ 𝔡𝔢𝔷𝔦𝔤𝔫 ✧ @macro_hq   \n",
       "4   FrancoiseGamma  https://t.co/xCZ5E9VBTu\\nhttps://t.co/7L8WDLpa...   \n",
       "\n",
       "           created_at                 location profile_location  \\\n",
       "0 2011-02-26 00:38:02         thesarahshow.eth             None   \n",
       "1 2020-06-12 17:06:09              Los Angeles             None   \n",
       "2 2021-01-10 06:59:02  Sydney, New South Wales             None   \n",
       "3 2011-01-06 05:29:54        San Francisco, CA             None   \n",
       "4 2019-12-24 11:11:54                 Internet             None   \n",
       "\n",
       "   followers_count  following_count  verified  \n",
       "0             8578             1016     False  \n",
       "1             2228             1564     False  \n",
       "2              495              415     False  \n",
       "3            14108             2695     False  \n",
       "4             1311              364     False  "
      ]
     },
     "execution_count": 350,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_urls = artist_metadata_df[~artist_metadata_df.twitter.isna()].twitter.tolist()\n",
    "print(\"N twitter profiles:\", len(twitter_urls))\n",
    "\n",
    "\n",
    "twitter_df = pd.DataFrame()\n",
    "counter = 0\n",
    "\n",
    "n_users_not_found = 0\n",
    "for u in tqdm(twitter_urls):  \n",
    "    u = list(u)\n",
    "    idx = len(u) - 1 - u[::-1].index('/')\n",
    "    u = ''.join(u[idx+1:])\n",
    "\n",
    "    counter +=1\n",
    "    try:\n",
    "        twitter_df = twitter_df.append(get_twitter_metadata(u), ignore_index = True)\n",
    "    except:\n",
    "        n_users_not_found +=1\n",
    "        continue\n",
    "\n",
    "print(\"N users crawled:\", len(twitter_df))\n",
    "print(\"N users not found:\", n_users_not_found)\n",
    "twitter_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "id": "561f5967",
   "metadata": {},
   "outputs": [],
   "source": [
    "twitter_df.to_csv(\"../new-data/artist_twitter_metadata.csv\", index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "id": "fd61cd18",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/1339 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N twitter profiles: 1339\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 67%|██████▋   | 900/1339 [04:35<02:08,  3.43it/s]Rate limit reached. Sleeping for: 624\n",
      "100%|██████████| 1339/1339 [17:19<00:00,  1.29it/s]   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N users crawled: 1301\n",
      "N users not found: 38\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_name</th>\n",
       "      <th>bio</th>\n",
       "      <th>created_at</th>\n",
       "      <th>location</th>\n",
       "      <th>profile_location</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>following_count</th>\n",
       "      <th>verified</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>jessewldn</td>\n",
       "      <td>founder @variantfund; via @a16z, @spotify, @me...</td>\n",
       "      <td>2009-03-24 01:50:46</td>\n",
       "      <td>New York</td>\n",
       "      <td>None</td>\n",
       "      <td>22665</td>\n",
       "      <td>1287</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>planttdaddii</td>\n",
       "      <td>🌕🔶🟩🟣🌕 🕳ᵗʰⁱˢ ⁱˢ ᵃˡˡ ᶠᵒʳ ʸᵒᵘ ╹◡╹</td>\n",
       "      <td>2019-01-17 08:08:21</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>None</td>\n",
       "      <td>3660</td>\n",
       "      <td>378</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>jeffgdavis</td>\n",
       "      <td>Artist / CCO @artblocks_io / Founder @davisedi...</td>\n",
       "      <td>2007-11-21 06:11:59</td>\n",
       "      <td>Tempe, AZ, USA</td>\n",
       "      <td>None</td>\n",
       "      <td>3104</td>\n",
       "      <td>896</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>dillonatm</td>\n",
       "      <td>#AKU 22 - he/him. visionary. new media artist....</td>\n",
       "      <td>2012-12-07 15:54:35</td>\n",
       "      <td>Nashville, TN</td>\n",
       "      <td>None</td>\n",
       "      <td>3232</td>\n",
       "      <td>1000</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>onderwish</td>\n",
       "      <td>🟨Spreading art across the cosmos 🎨🚀\\n⚪Explorin...</td>\n",
       "      <td>2016-02-27 21:56:55</td>\n",
       "      <td>Montreal</td>\n",
       "      <td>None</td>\n",
       "      <td>573</td>\n",
       "      <td>502</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_name                                                bio  \\\n",
       "0     jessewldn  founder @variantfund; via @a16z, @spotify, @me...   \n",
       "1  planttdaddii                     🌕🔶🟩🟣🌕 🕳ᵗʰⁱˢ ⁱˢ ᵃˡˡ ᶠᵒʳ ʸᵒᵘ ╹◡╹   \n",
       "2    jeffgdavis  Artist / CCO @artblocks_io / Founder @davisedi...   \n",
       "3     dillonatm  #AKU 22 - he/him. visionary. new media artist....   \n",
       "4     onderwish  🟨Spreading art across the cosmos 🎨🚀\\n⚪Explorin...   \n",
       "\n",
       "           created_at        location profile_location  followers_count  \\\n",
       "0 2009-03-24 01:50:46        New York             None            22665   \n",
       "1 2019-01-17 08:08:21     Seattle, WA             None             3660   \n",
       "2 2007-11-21 06:11:59  Tempe, AZ, USA             None             3104   \n",
       "3 2012-12-07 15:54:35   Nashville, TN             None             3232   \n",
       "4 2016-02-27 21:56:55        Montreal             None              573   \n",
       "\n",
       "   following_count  verified  \n",
       "0             1287     False  \n",
       "1              378     False  \n",
       "2              896     False  \n",
       "3             1000     False  \n",
       "4              502     False  "
      ]
     },
     "execution_count": 353,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_urls = invited_by_metadata_df[invited_by_metadata_df.twitter!= ''].twitter.tolist()\n",
    "print(\"N twitter profiles:\", len(twitter_urls))\n",
    "\n",
    "twitter_df = pd.DataFrame()\n",
    "counter = 0\n",
    "\n",
    "n_users_not_found = 0\n",
    "for u in tqdm(twitter_urls):  \n",
    "    u = list(u)\n",
    "    idx = len(u) - 1 - u[::-1].index('/')\n",
    "    u = ''.join(u[idx+1:])\n",
    "\n",
    "    counter +=1\n",
    "    try:\n",
    "        twitter_df = twitter_df.append(get_twitter_metadata(u), ignore_index = True)\n",
    "    except:\n",
    "        n_users_not_found +=1\n",
    "        continue\n",
    "\n",
    "print(\"N users crawled:\", len(twitter_df))\n",
    "print(\"N users not found:\", n_users_not_found)\n",
    "twitter_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "id": "8d2d4d93",
   "metadata": {},
   "outputs": [],
   "source": [
    "#twitter_df.to_csv(\"../new-data/invited_by_twitter_metadata.csv\", index = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bafb2be",
   "metadata": {},
   "source": [
    "# Descriptive Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "45b8c44d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>token_id</th>\n",
       "      <th>creator</th>\n",
       "      <th>listing_date</th>\n",
       "      <th>listing_amt</th>\n",
       "      <th>list_dt</th>\n",
       "      <th>list_d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0xb188ee1daca51ce6b58ccf8a81ce4025a714bc73</td>\n",
       "      <td>1622312534</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2021-05-29 18:22:14</td>\n",
       "      <td>2021-05-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0x2b65a808d0d5d54cdbb701b82d814374b812a4b8</td>\n",
       "      <td>1611689577</td>\n",
       "      <td>0.373468</td>\n",
       "      <td>2021-01-26 19:32:57</td>\n",
       "      <td>2021-01-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0x376884df6fb55bfa319d703bc1ac5091ef479ff5</td>\n",
       "      <td>1611272958</td>\n",
       "      <td>1.12</td>\n",
       "      <td>2021-01-21 23:49:18</td>\n",
       "      <td>2021-01-21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</td>\n",
       "      <td>0x080b6202c0a5c464799e1e5a4aa7325eace9a5e1</td>\n",
       "      <td>1611286202</td>\n",
       "      <td>1.75</td>\n",
       "      <td>2021-01-22 03:30:02</td>\n",
       "      <td>2021-01-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>0x87042da39c06b0f85b435e5ec8ce2b15ec7bd700</td>\n",
       "      <td>1611292587</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2021-01-22 05:16:27</td>\n",
       "      <td>2021-01-22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   token_id                                     creator listing_date  \\\n",
       "0       2.0  0xb188ee1daca51ce6b58ccf8a81ce4025a714bc73   1622312534   \n",
       "1       2.0  0x2b65a808d0d5d54cdbb701b82d814374b812a4b8   1611689577   \n",
       "2       3.0  0x376884df6fb55bfa319d703bc1ac5091ef479ff5   1611272958   \n",
       "3       4.0  0x080b6202c0a5c464799e1e5a4aa7325eace9a5e1   1611286202   \n",
       "4       5.0  0x87042da39c06b0f85b435e5ec8ce2b15ec7bd700   1611292587   \n",
       "\n",
       "  listing_amt             list_dt      list_d  \n",
       "0         2.5 2021-05-29 18:22:14  2021-05-29  \n",
       "1    0.373468 2021-01-26 19:32:57  2021-01-26  \n",
       "2        1.12 2021-01-21 23:49:18  2021-01-21  \n",
       "3        1.75 2021-01-22 03:30:02  2021-01-22  \n",
       "4         0.1 2021-01-22 05:16:27  2021-01-22  "
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_df['list_dt'] = list_df.listing_date.apply(lambda x: datetime.utcfromtimestamp(int(x)))\n",
    "list_df['list_d'] = list_df.list_dt.apply(lambda x: x.date())\n",
    "list_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "2e307632",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>list_d</th>\n",
       "      <th>tokenid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-01-26</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-01-21</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-01-22</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-01-22</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-01-22</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       list_d  tokenid\n",
       "0  2021-01-26      2.0\n",
       "1  2021-01-21      3.0\n",
       "2  2021-01-22      4.0\n",
       "3  2021-01-22      5.0\n",
       "4  2021-01-22      6.0"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "first_list_df = list_df.groupby('token_id').list_d.min().to_frame()\n",
    "first_list_df['tokenid'] = first_list_df.index\n",
    "first_list_df.index = range(len(first_list_df))\n",
    "first_list_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "1989dcca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>list_d</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>1</td>\n",
       "      <td>2021-01-21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>6</td>\n",
       "      <td>2021-01-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>3</td>\n",
       "      <td>2021-01-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>4</td>\n",
       "      <td>2021-01-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-01-25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     list_d           d\n",
       "146       1  2021-01-21\n",
       "141       6  2021-01-22\n",
       "144       3  2021-01-23\n",
       "143       4  2021-01-24\n",
       "145       2  2021-01-25"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_list_date = first_list_df.list_d.value_counts().to_frame()\n",
    "n_list_date['d'] = n_list_date.index\n",
    "n_list_date.index = range(len(n_list_date))\n",
    "n_list_date = n_list_date.sort_values('d')\n",
    "n_list_date.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "id": "6f89eb4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date(2021, 6, 18)"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_list_date.d.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "id": "0ba98521",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "bcb95d71",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_moving_average(x):\n",
    "    \n",
    "    moving_averages = []\n",
    "    for i in range(len(x)):\n",
    "        if i == 0:\n",
    "            this_window = x[:4]\n",
    "        if i == 1:\n",
    "            this_window = x[i-1:5]\n",
    "        elif i == 2:\n",
    "            this_window = x[i-2:6]\n",
    "        else:\n",
    "            this_window = x[i-3:i+4]\n",
    "        #print(this_window)\n",
    "        moving_averages.append(np.mean(this_window))\n",
    "    return moving_averages\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "id": "c06a30a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(20,10))\n",
    "plt.plot(n_list_date.d, n_list_date.list_d, marker='*')\n",
    "\n",
    "y = get_moving_average(n_list_date.list_d)\n",
    "plt.plot(n_list_date.d, y)\n",
    "plt.tick_params(axis='both',which='major',labelsize=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "619e1d35",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "120d5732",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f0184e3a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}