FinalJupyterNotebookUkraine.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pprint\n",
    "from collections import defaultdict\n",
    "\n",
    "import binance.exceptions\n",
    "import requests\n",
    "\n",
    "from binance import Client, ThreadedWebsocketManager, ThreadedDepthCacheManager\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "pd.set_option('display.max_rows', 15)\n",
    "pd.set_option('display.min_rows', 15)\n",
    "\n",
    "import datetime\n",
    "\n",
    "import time\n",
    "\n",
    "import csv\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import numpy as np\n",
    "import dataframe_image as dfi\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "client = Client('', '') # Insert Binance API Key\n",
    "API_KEY = \"\" #Insert Etherscan API Key\n",
    "START = 0\n",
    "END = 14962372\n",
    "DONATION_ADDRESS = \"0x165CD37b4C644C2921454429E7F9358d18A45e14\"\n",
    "\n",
    "HIST_PRICES = {}\n",
    "STABLES = [\"BNB\", \"USDC\", \"USDT\", \"DAI\", \"FEI\", \"USDT\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#######\n",
    "#BTC @ Blockchain.com\n",
    "######\n",
    "\n",
    "def query_blockchainCom_api(adress,offset):\n",
    "    query = f\"https://blockchain.info/rawaddr/{adress}?format=json&offset={offset}&limit=50\"\n",
    "    result = requests.get(query)\n",
    "    txs = result.json()[\"txs\"]\n",
    "    return txs\n",
    "\n",
    "def get_BTC_txs(adress):\n",
    "    offset = 0\n",
    "    \n",
    "    txs = query_blockchainCom_api(adress,str(offset))\n",
    "    final_txs = txs\n",
    "    print(f'first Batch {offset} - {offset +50}')\n",
    "    offset += 50\n",
    "    time.sleep(4)\n",
    "    \n",
    "    while len(txs) == 50:\n",
    "        txs = query_blockchainCom_api(adress,str(offset))  \n",
    "        final_txs.extend(txs)\n",
    "        print(f'next Batch {offset} - {offset +50}')\n",
    "        offset += 50\n",
    "        time.sleep(4)\n",
    "        \n",
    "    return final_txs\n",
    "\n",
    "#######\n",
    "#ETH @ Etherscan.io\n",
    "######\n",
    "\n",
    "def query_api(start, end, action):\n",
    "    query = f\"https://api.etherscan.io/api?module=account&action={action}&address={DONATION_ADDRESS}&startblock={start}&endblock={end}&sort=asc&apikey={API_KEY}\"\n",
    "    result = requests.get(query)\n",
    "    txs = result.json()[\"result\"]\n",
    "    return txs\n",
    "\n",
    "\n",
    "def get_erc20():\n",
    "    txs = query_api(START, END, \"tokentx\")\n",
    "    last_block = txs[-1][\"blockNumber\"]\n",
    "    clean_txs = [tx for tx in txs if tx[\"blockNumber\"] != last_block]\n",
    "    second_batch = query_api(last_block, END, \"tokentx\")\n",
    "    clean_txs.extend(second_batch)\n",
    "    incoming_txs = [tx for tx in clean_txs if tx[\"to\"] == DONATION_ADDRESS.lower() and tx[\"from\"] != DONATION_ADDRESS.lower() and int(tx[\"value\"]) > 0] #originally this line was not there\n",
    "    print(len(incoming_txs)) # originally was clean_txs\n",
    "    return incoming_txs # originally was clean_txs\n",
    "\n",
    "\n",
    "def get_erc721():\n",
    "    txs = query_api(START, END, \"tokennfttx\")\n",
    "    print(len(txs))\n",
    "    return txs\n",
    "\n",
    "\n",
    "def get_erc1155():\n",
    "    txs = query_api(START, END, \"token1155tx\")\n",
    "    print(len(txs))\n",
    "    return txs\n",
    "\n",
    "\n",
    "def get_eth():\n",
    "    last_block = START\n",
    "    all_txs = []\n",
    "\n",
    "    while True:\n",
    "        txs = query_api(last_block, END, \"txlist\")\n",
    "        last_block = txs[-1][\"blockNumber\"]\n",
    "        clean_txs = [tx for tx in txs if tx[\"blockNumber\"] != last_block]\n",
    "        all_txs.extend(clean_txs)\n",
    "        if len(txs) < 10000:\n",
    "            break\n",
    "\n",
    "    incoming_txs = [tx for tx in all_txs if tx[\"to\"] == DONATION_ADDRESS.lower() and tx[\"from\"] != DONATION_ADDRESS.lower() and int(tx[\"value\"]) > 0]\n",
    "    print(\"All txs\", len(all_txs))\n",
    "    print(\"Incoming tx\", len(incoming_txs))\n",
    "    return incoming_txs\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def process_erc20(txs):\n",
    "    \n",
    "    results_list=[]\n",
    "    tokens = defaultdict(int)\n",
    "    i = 0\n",
    "    for tx in txs:\n",
    "        token = tx[\"tokenSymbol\"]\n",
    "        if token == \"WETH\":\n",
    "            token = \"ETH\"\n",
    "        if token == \"WBTC\":\n",
    "            token = \"BTC\"\n",
    "            \n",
    "        amount = int(tx[\"value\"]) / (10 ** int(tx[\"tokenDecimal\"]))\n",
    "        if token in STABLES:\n",
    "            spot = 1.0\n",
    "        else:\n",
    "            spot = get_historical_price(token, int(tx[\"timeStamp\"]) * 1000)\n",
    "        try:\n",
    "            tokens[token] += float(spot) * float(amount)\n",
    "        except:\n",
    "            continue\n",
    "\n",
    "        # print(f\"{amount} {token} @ {spot}: {float(amount) * float(spot)}\")\n",
    "        # progress\n",
    "        if i % 100 == 0:\n",
    "            print(f\"{i}/{len(txs)}\")\n",
    "        i += 1\n",
    "        \n",
    "        results_list.append([int(tx[\"timeStamp\"]),amount,token,float(spot) * float(amount)])\n",
    "\n",
    "    tokens = {k: v for k, v in tokens.items() if v > 0}\n",
    "    tokens_sorted = {k: v for k, v in sorted(tokens.items(), key=lambda item: float(item[1]), reverse=True)}\n",
    "    pprint.pprint(tokens_sorted)\n",
    "        # tokens[tx[\"tokenSymbol\"]] += int(tx[\"value\"]) / (10 ** int(tx[\"tokenDecimal\"]))\n",
    "        # tokentime[]\n",
    "    # tokens_sorted = {k: v for k, v in sorted(tokens.items(), key=lambda item: item[0])}\n",
    "    # pprint.pprint(tokens_sorted)\n",
    "\n",
    "    \n",
    "    df =pd.DataFrame(results_list, columns =['timestamp','amount','ticker','USD value at donation time'])\n",
    "    df['USD value at donation time'] = df['USD value at donation time'].round(decimals = 2)\n",
    "    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='s')    \n",
    "    \n",
    "    return df\n",
    "\n",
    "def process_eth(txs):\n",
    "    total = 0\n",
    "    \n",
    "    results_list=[]\n",
    "\n",
    "    for tx in txs:\n",
    "        amount = int(tx[\"value\"]) / (10 ** 18)\n",
    "        spot = get_historical_price(\"ETH\", int(tx[\"timeStamp\"]) * 1000)\n",
    "        donation_in_usd = float(spot) * float(amount)\n",
    "        total += donation_in_usd\n",
    "        results_list.append([int(tx[\"timeStamp\"]),amount,'ETH',donation_in_usd])\n",
    "\n",
    "    df =pd.DataFrame(results_list, columns =['timestamp','amount','ticker','USD value at donation time'])\n",
    "    df['USD value at donation time'] = df['USD value at donation time'].round(decimals = 2)\n",
    "    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='s')\n",
    "\n",
    "    return df\n",
    "\n",
    "\n",
    "\n",
    "#######\n",
    "#Prices @ Binance\n",
    "######\n",
    "\n",
    "def get_historical_price(token, timestamp):\n",
    "    if token not in HIST_PRICES:\n",
    "        pair = f\"BUSD{token}\"\n",
    "        try:\n",
    "            klines = client.get_historical_klines(pair, Client.KLINE_INTERVAL_1HOUR, \"1 Feb, 2022\")\n",
    "        except binance.exceptions.BinanceAPIException:\n",
    "            pair = f\"{token}BUSD\"\n",
    "            try:\n",
    "                klines = client.get_historical_klines(pair, Client.KLINE_INTERVAL_1HOUR, \"1 Feb, 2022\")\n",
    "            except binance.exceptions.BinanceAPIException:\n",
    "                HIST_PRICES[token] = \"invalid token\"\n",
    "                return 0\n",
    "\n",
    "        open_data = [l[:2] for l in klines]\n",
    "        HIST_PRICES[token] = open_data\n",
    "\n",
    "    if HIST_PRICES[token] == \"invalid token\":\n",
    "        return 0\n",
    "\n",
    "    # print(HIST_PRICES[token])\n",
    "    for date_price in HIST_PRICES[token]:\n",
    "        if date_price[0] > timestamp:\n",
    "            return date_price[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ETH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All txs 73852\n",
      "Incoming tx 73434\n"
     ]
    }
   ],
   "source": [
    "eth_txs = get_eth()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "        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>timestamp</th>\n",
       "      <th>amount</th>\n",
       "      <th>ticker</th>\n",
       "      <th>USD value at donation time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-02-26 11:54:48</td>\n",
       "      <td>0.014468</td>\n",
       "      <td>ETH</td>\n",
       "      <td>39.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-02-26 11:55:24</td>\n",
       "      <td>0.014688</td>\n",
       "      <td>ETH</td>\n",
       "      <td>40.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-02-26 11:56:16</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>ETH</td>\n",
       "      <td>550.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-02-26 12:00:40</td>\n",
       "      <td>0.036306</td>\n",
       "      <td>ETH</td>\n",
       "      <td>100.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-02-26 12:05:18</td>\n",
       "      <td>0.093750</td>\n",
       "      <td>ETH</td>\n",
       "      <td>259.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2022-02-26 12:08:27</td>\n",
       "      <td>0.021812</td>\n",
       "      <td>ETH</td>\n",
       "      <td>60.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022-02-26 12:09:14</td>\n",
       "      <td>1.229000</td>\n",
       "      <td>ETH</td>\n",
       "      <td>3396.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73427</th>\n",
       "      <td>2022-06-13 10:47:31</td>\n",
       "      <td>0.041000</td>\n",
       "      <td>ETH</td>\n",
       "      <td>49.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73428</th>\n",
       "      <td>2022-06-13 23:30:26</td>\n",
       "      <td>0.035000</td>\n",
       "      <td>ETH</td>\n",
       "      <td>42.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73429</th>\n",
       "      <td>2022-06-14 02:01:25</td>\n",
       "      <td>0.063723</td>\n",
       "      <td>ETH</td>\n",
       "      <td>71.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73430</th>\n",
       "      <td>2022-06-14 06:32:45</td>\n",
       "      <td>0.004200</td>\n",
       "      <td>ETH</td>\n",
       "      <td>5.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73431</th>\n",
       "      <td>2022-06-14 06:36:07</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>ETH</td>\n",
       "      <td>369.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73432</th>\n",
       "      <td>2022-06-14 07:54:02</td>\n",
       "      <td>0.099198</td>\n",
       "      <td>ETH</td>\n",
       "      <td>122.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73433</th>\n",
       "      <td>2022-06-14 08:34:41</td>\n",
       "      <td>0.158397</td>\n",
       "      <td>ETH</td>\n",
       "      <td>192.84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>73434 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                timestamp    amount ticker  USD value at donation time\n",
       "0     2022-02-26 11:54:48  0.014468    ETH                       39.83\n",
       "1     2022-02-26 11:55:24  0.014688    ETH                       40.44\n",
       "2     2022-02-26 11:56:16  0.200000    ETH                      550.60\n",
       "3     2022-02-26 12:00:40  0.036306    ETH                      100.34\n",
       "4     2022-02-26 12:05:18  0.093750    ETH                      259.10\n",
       "5     2022-02-26 12:08:27  0.021812    ETH                       60.28\n",
       "6     2022-02-26 12:09:14  1.229000    ETH                     3396.69\n",
       "...                   ...       ...    ...                         ...\n",
       "73427 2022-06-13 10:47:31  0.041000    ETH                       49.99\n",
       "73428 2022-06-13 23:30:26  0.035000    ETH                       42.27\n",
       "73429 2022-06-14 02:01:25  0.063723    ETH                       71.19\n",
       "73430 2022-06-14 06:32:45  0.004200    ETH                        5.17\n",
       "73431 2022-06-14 06:36:07  0.300000    ETH                      369.62\n",
       "73432 2022-06-14 07:54:02  0.099198    ETH                      122.94\n",
       "73433 2022-06-14 08:34:41  0.158397    ETH                      192.84\n",
       "\n",
       "[73434 rows x 4 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "donations_ETH_df = process_eth(eth_txs)\n",
    "donations_ETH_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "donations_ETH_df.to_pickle('donations_ETH_df')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ERC 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5140\n"
     ]
    }
   ],
   "source": [
    "erc20_txs = get_erc20()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0/5140\n",
      "100/5140\n",
      "200/5140\n",
      "300/5140\n",
      "400/5140\n",
      "500/5140\n",
      "600/5140\n",
      "700/5140\n",
      "800/5140\n",
      "900/5140\n",
      "1000/5140\n",
      "1100/5140\n",
      "1200/5140\n",
      "1300/5140\n",
      "1400/5140\n",
      "1500/5140\n",
      "1600/5140\n",
      "1700/5140\n",
      "1800/5140\n",
      "1900/5140\n",
      "2000/5140\n",
      "2100/5140\n",
      "2200/5140\n",
      "2300/5140\n",
      "2400/5140\n",
      "2500/5140\n",
      "2600/5140\n",
      "2700/5140\n",
      "2800/5140\n",
      "2900/5140\n",
      "3000/5140\n",
      "3100/5140\n",
      "3200/5140\n",
      "3300/5140\n",
      "3400/5140\n",
      "3500/5140\n",
      "3600/5140\n",
      "3700/5140\n",
      "3800/5140\n",
      "3900/5140\n",
      "4000/5140\n",
      "4100/5140\n",
      "4200/5140\n",
      "4300/5140\n",
      "4400/5140\n",
      "4500/5140\n",
      "4600/5140\n",
      "4700/5140\n",
      "4800/5140\n",
      "4900/5140\n",
      "5000/5140\n",
      "5100/5140\n",
      "{'1INCH': 357.8835507661764,\n",
      " 'AAVE': 254.38400692299996,\n",
      " 'AERGO': 0.402,\n",
      " 'AKRO': 614.25,\n",
      " 'API3': 29.781851204819997,\n",
      " 'BAL': 11653.117370803311,\n",
      " 'BAT': 433.02339722872995,\n",
      " 'BNT': 257.4752264136684,\n",
      " 'BTC': 155.805198206,\n",
      " 'CHZ': 10.057012542864001,\n",
      " 'CLV': 0.9863280365600001,\n",
      " 'COMP': 24.521360660852757,\n",
      " 'CRV': 10.01171875,\n",
      " 'DAI': 1073198.3029627907,\n",
      " 'DIA': 15.971571789026125,\n",
      " 'ENJ': 38.658,\n",
      " 'ENS': 3318.6185770606266,\n",
      " 'ETH': 32917.846212968376,\n",
      " 'FLUX': 13.51,\n",
      " 'FRONT': 0.8256,\n",
      " 'GRT': 813.26055553,\n",
      " 'IOTX': 27.126002603661398,\n",
      " 'KNC': 10.143593144190001,\n",
      " 'LINK': 2103.4322039144,\n",
      " 'LIT': 11931.1456,\n",
      " 'LPT': 104.14380275834125,\n",
      " 'LRC': 1180.65183638009,\n",
      " 'MANA': 61.206728805761,\n",
      " 'MATIC': 1304.952168953174,\n",
      " 'MDT': 578.4,\n",
      " 'OCEAN': 4559.0,\n",
      " 'OMG': 508.3055217160929,\n",
      " 'ORN': 97.30458598542,\n",
      " 'PEOPLE': 77.04,\n",
      " 'PERP': 0.8681119264,\n",
      " 'POLS': 13.899999999999999,\n",
      " 'POWR': 285.30140468260004,\n",
      " 'RGT': 44.55,\n",
      " 'RLC': 15.656,\n",
      " 'SAND': 11.101760378172392,\n",
      " 'SHIB': 1595.5832657731494,\n",
      " 'SKL': 158.91433418118098,\n",
      " 'SLP': 1.9300000000000002,\n",
      " 'SUSHI': 11.135434214155215,\n",
      " 'SXP': 3.8276810850030665,\n",
      " 'UNI': 6.3093,\n",
      " 'USDC': 1203278.136804,\n",
      " 'USDP': 500.0,\n",
      " 'USDT': 7750877.755669,\n",
      " 'UST': 242.29695,\n",
      " 'USTC': 96.38513289408759,\n",
      " 'YFI': 1413.02133,\n",
      " 'ZRX': 229.27435449452673}\n"
     ]
    },
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       "\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>timestamp</th>\n",
       "      <th>amount</th>\n",
       "      <th>ticker</th>\n",
       "      <th>USD value at donation time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-02-26 12:29:21</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>USDC</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-02-26 12:58:39</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>USDT</td>\n",
       "      <td>200.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-02-26 13:00:43</td>\n",
       "      <td>501.000000</td>\n",
       "      <td>DAI</td>\n",
       "      <td>501.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-02-26 14:51:12</td>\n",
       "      <td>12312.000000</td>\n",
       "      <td>PKG</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-02-26 14:51:45</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>USDT</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2022-02-26 14:54:04</td>\n",
       "      <td>5000.000000</td>\n",
       "      <td>USDT</td>\n",
       "      <td>5000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022-02-26 15:00:16</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>USDT</td>\n",
       "      <td>1000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5131</th>\n",
       "      <td>2022-06-08 13:27:57</td>\n",
       "      <td>312900.000000</td>\n",
       "      <td>XDB</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5132</th>\n",
       "      <td>2022-06-08 14:55:00</td>\n",
       "      <td>999000.000000</td>\n",
       "      <td>XDB</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5133</th>\n",
       "      <td>2022-06-09 09:58:08</td>\n",
       "      <td>394350.000000</td>\n",
       "      <td>XDB</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5134</th>\n",
       "      <td>2022-06-09 11:45:07</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>BAL</td>\n",
       "      <td>11535.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5135</th>\n",
       "      <td>2022-06-09 22:57:27</td>\n",
       "      <td>426.869552</td>\n",
       "      <td>HOP</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5136</th>\n",
       "      <td>2022-06-11 19:38:17</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>USDT</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5137</th>\n",
       "      <td>2022-06-13 09:56:31</td>\n",
       "      <td>126.612478</td>\n",
       "      <td>USDT</td>\n",
       "      <td>126.61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5138 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               timestamp         amount ticker  USD value at donation time\n",
       "0    2022-02-26 12:29:21     100.000000   USDC                      100.00\n",
       "1    2022-02-26 12:58:39     200.000000   USDT                      200.00\n",
       "2    2022-02-26 13:00:43     501.000000    DAI                      501.00\n",
       "3    2022-02-26 14:51:12   12312.000000    PKG                        0.00\n",
       "4    2022-02-26 14:51:45     100.000000   USDT                      100.00\n",
       "5    2022-02-26 14:54:04    5000.000000   USDT                     5000.00\n",
       "6    2022-02-26 15:00:16    1000.000000   USDT                     1000.00\n",
       "...                  ...            ...    ...                         ...\n",
       "5131 2022-06-08 13:27:57  312900.000000    XDB                        0.00\n",
       "5132 2022-06-08 14:55:00  999000.000000    XDB                        0.00\n",
       "5133 2022-06-09 09:58:08  394350.000000    XDB                        0.00\n",
       "5134 2022-06-09 11:45:07    1500.000000    BAL                    11535.00\n",
       "5135 2022-06-09 22:57:27     426.869552    HOP                        0.00\n",
       "5136 2022-06-11 19:38:17     100.000000   USDT                      100.00\n",
       "5137 2022-06-13 09:56:31     126.612478   USDT                      126.61\n",
       "\n",
       "[5138 rows x 4 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "donations_ERC20_df = process_erc20(erc20_txs)\n",
    "donations_ERC20_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "donations_ERC20_df.to_pickle('donations_ERC20_df')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cryptopunks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cryptopunks NFT  ERC20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "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>blockNumber</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>hash</th>\n",
       "      <th>nonce</th>\n",
       "      <th>blockHash</th>\n",
       "      <th>from</th>\n",
       "      <th>contractAddress</th>\n",
       "      <th>to</th>\n",
       "      <th>value</th>\n",
       "      <th>tokenName</th>\n",
       "      <th>tokenSymbol</th>\n",
       "      <th>tokenDecimal</th>\n",
       "      <th>transactionIndex</th>\n",
       "      <th>gas</th>\n",
       "      <th>gasPrice</th>\n",
       "      <th>gasUsed</th>\n",
       "      <th>cumulativeGasUsed</th>\n",
       "      <th>input</th>\n",
       "      <th>confirmations</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1522</th>\n",
       "      <td>14303023</td>\n",
       "      <td>1646163297</td>\n",
       "      <td>0x76458c5226e06e55df2087f0595aed04d86debade3caa48180d1e835692f37e3</td>\n",
       "      <td>75</td>\n",
       "      <td>0x00bef4025777302ac5f56bdfb17bd0fdb0ba66120f52b5f0e90f3cbcfddfe07c</td>\n",
       "      <td>0x67c4438c86c00257d3bca9bbfb3f6234bc961468</td>\n",
       "      <td>0xb47e3cd837ddf8e4c57f05d70ab865de6e193bbb</td>\n",
       "      <td>0x165cd37b4c644c2921454429e7f9358d18a45e14</td>\n",
       "      <td>1</td>\n",
       "      <td>CRYPTOPUNKS</td>\n",
       "      <td>Ͼ</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>200000</td>\n",
       "      <td>122000000000</td>\n",
       "      <td>65391</td>\n",
       "      <td>967662</td>\n",
       "      <td>deprecated</td>\n",
       "      <td>670743</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     blockNumber   timeStamp  \\\n",
       "1522    14303023  1646163297   \n",
       "\n",
       "                                                                    hash  \\\n",
       "1522  0x76458c5226e06e55df2087f0595aed04d86debade3caa48180d1e835692f37e3   \n",
       "\n",
       "     nonce  \\\n",
       "1522    75   \n",
       "\n",
       "                                                               blockHash  \\\n",
       "1522  0x00bef4025777302ac5f56bdfb17bd0fdb0ba66120f52b5f0e90f3cbcfddfe07c   \n",
       "\n",
       "                                            from  \\\n",
       "1522  0x67c4438c86c00257d3bca9bbfb3f6234bc961468   \n",
       "\n",
       "                                 contractAddress  \\\n",
       "1522  0xb47e3cd837ddf8e4c57f05d70ab865de6e193bbb   \n",
       "\n",
       "                                              to value    tokenName  \\\n",
       "1522  0x165cd37b4c644c2921454429e7f9358d18a45e14     1  CRYPTOPUNKS   \n",
       "\n",
       "     tokenSymbol tokenDecimal transactionIndex     gas      gasPrice gasUsed  \\\n",
       "1522           Ͼ            0                7  200000  122000000000   65391   \n",
       "\n",
       "     cumulativeGasUsed       input confirmations  \n",
       "1522            967662  deprecated        670743  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.options.display.max_colwidth = 100\n",
    "punks = pd.DataFrame(erc20_txs)\n",
    "punks = punks[(punks['tokenSymbol'] == \"Ͼ\")]\n",
    "punks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "punks.to_pickle('punks')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First Transaction \n",
    "https://etherscan.io/tx/0x76458c5226e06e55df2087f0595aed04d86debade3caa48180d1e835692f37e3\n",
    "https://cryptopunks.app/cryptopunks/details/5364\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "findfont: Font family ['Helvetica'] not found. Falling back to DejaVu Sans.\n",
      "findfont: Font family ['Helvetica'] not found. Falling back to DejaVu Sans.\n"
     ]
    }
   ],
   "source": [
    "dfi.export(punks,\"punks.png\", table_conversion='matplotlib')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ERC-721"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1613\n"
     ]
    }
   ],
   "source": [
    "ERC721 = get_erc721()\n",
    "\n",
    "ERC721_df = pd.DataFrame(ERC721)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Ethereum Name Service', 'Demonized Azuki', 'Mutant Floki',\n",
       "       'Stonks', 'MetaPhox', 'ShibElon', 'SecretSocietyNFT',\n",
       "       'Generative Floydies 2', 'SmolPhunks', 'Goat Soup',\n",
       "       'Chubbiverse Frens', 'Acclimated\\u200bMoonCats', 'BeaNFT Genesis',\n",
       "       'KRebels', 'KnownOriginDigitalAsset', 'Mao', 'On-Chain Monsters',\n",
       "       'Gucci', 'Elon Musk', 'InvisibIe Friends', 'ODDWORLDS',\n",
       "       'Power Musix Club', 'Louis Vuitton', 'Zora', 'The Valkyries NFT',\n",
       "       'CorinnaDAO', 'Bloxian #', 'Cyber Koala Collective',\n",
       "       'Loot (for mfers)', 'The Repus', 'Lord Angels', 'Shields',\n",
       "       'Typical Tigers', 'Nishikigoi', 'Doockles', 'Pixel Azuki',\n",
       "       'Visitors of Imma Degen', 'Larva Wolf', '0xWOW', 'Toad Punks',\n",
       "       'mfer', 'GLICPIXXXVER002 - GRAND COLLECTION',\n",
       "       'BASTARD GAN PUNKS V2', 'NFT AIA', 'Basic Buns', 'WenChangeDAO',\n",
       "       'Fury of the Fur', 'DoodMfers', 'Rarible', 'Givenchy', 'Coca Cola',\n",
       "       'Lamborghini', 'Gnomenclature', 'Jeet Punks', 'Sushi Nekko',\n",
       "       'Doji Crew', 'Zelenskiy DAO', 'Bubki for Ukraine',\n",
       "       'Healing Corgi Art', 'LaCollection', 'Villa de vendome',\n",
       "       'Afro Droids', 'August Sander 10K collection', '0xMAYC',\n",
       "       'Dolce Gabbana', 'Bored Ape Nike Club', 'Ultraman',\n",
       "       'Tribes Of Ogun', 'NBA', 'Adidas Bayc', 'Coach', 'Burberry',\n",
       "       'Nifty Ape Nation', 'Mcdonald', 'Super Shiba Club', 'Ukraine',\n",
       "       'Cartoons', 'D&amp;G', 'Braindom', 'BuildABetterFuture',\n",
       "       'Peaceful Ukraine', 'Elon Musk Rocket Factory', 'Chanel',\n",
       "       'TheMetaStars', 'The Other Side', 'Meme VIP', 'Louis Vuitton Ape',\n",
       "       'NFTText', 'Mercedes Benz', 'Ukraine Arsenal', 'Imaginary Ones',\n",
       "       'scorpio.world', 'Hermes', 'Dented Feels', 'RUDE KIDZ',\n",
       "       'NBA TOP SHOT', 'NIKE', 'Buzzed Bear Hideout', 'Crooked Cops',\n",
       "       'PATEK PHILIPPE', 'CHANEL', 'Global Bears Club', 'Meta-Jesus',\n",
       "       'ADIDAS',\n",
       "       'The Ethertales Third Collection by BakaArts - Artefacts of Etherea',\n",
       "       'Azuki Mfer', 'OMEGA', 'Murakami flowers', 'Benz',\n",
       "       'VictoriasSecret', 'TWD-WALKER-ACCESS-PASS', 'Bond on the Moon',\n",
       "       'BlockchainHamstersSquad', 'marvel', 'Drop Bears', 'Crunchy Cows',\n",
       "       'Rolls Royce', 'ARMANI RABBITS', 'Dorkis', 'DEGENERATE/REGENERATE',\n",
       "       'Miss Metaverse', 'Oscar', 'Grammy Awards', 'Walmart', 'xmfers',\n",
       "       'Cool Kids Walk NFT', 'Louis Vuitton Warner Bros',\n",
       "       'Paris Hilton NFT', 'LEGO', 'Yayoi Kusama', 'Budweiser',\n",
       "       'Murakami CloneX', 'APPLE', 'RTFKT MNLTH', 'Balenciaga',\n",
       "       'Pop Wonder World', 'steam', 'Haagen-Dazs', 'Tubby Kevins',\n",
       "       'Rolex', 'durex', 'LOUlS VUlTTON', 'Invisible Apes', 'Pirate Pals',\n",
       "       'Coca-CoIa', 'GutterPunks.co', 'NIKE APE', 'Sneaker Heads',\n",
       "       'Lets Walk', 'Power Mystery Box', 'Baby Ape Mutant Club',\n",
       "       'Shifters', 'LOUIS VUITTON', 'Coca-Cola', 'Warner Bros nft',\n",
       "       'WORLD OF WOMEN', 'Gutter Punks Flyer - CryptoPunks', 'KOPOKO',\n",
       "       'BVLGARI Octo Finissimo Ultra', \"L'Oreal Paris\", 'McDonald',\n",
       "       'Tom Sachs Rocket Factory', 'Louis Vuitton Watch', 'BFF',\n",
       "       'WoW Pixies', 'Louis Vuitton X Murakami', 'PUMA', 'Chill Frogs',\n",
       "       'Neko', 'Angry Boars', 'Angry Meerkats', 'Garbage Friends',\n",
       "       'BAYC Otherside Land', 'Phantom Network', 'Murakami X Hublot',\n",
       "       'Metavatar', 'Meta World', 'AnimeMetaverse', 'Azuki X BAYC',\n",
       "       'Nintendo', 'ApeX Predator NFT', 'G-Star RAW', 'Moonbird',\n",
       "       'MindBlowon', 'Ether', 'The Association NFT', 'Blvck Paris',\n",
       "       'BBRC', 'The Lunartics', 'DragoonzNFT', 'DGFamily', 'NIKE X RTFKT',\n",
       "       'MixTape Headz Ukraine Vol. 1', 'ApeDads', 'Otherside X BAYC',\n",
       "       'Yogies', 'LonelyPop', 'Yogies Genesis', 'Aswang Tribe', 'CubeX',\n",
       "       'KAHIRU', 'Llamascape Official', 'Flippr Access Pass',\n",
       "       'Karafuru 3D', 'Trippin Ape Tribe X BAYC', 'Mystics', 'GENESIS',\n",
       "       'Kuroki Nft', 'projectPXN', 'AneroVerse Official',\n",
       "       'Takashi Murakami X Hublot', 'Sushimi', 'Apple', 'Possessed',\n",
       "       'McLaren', 'Verb', 'STEPN', 'Forgotten Ethereal Worlds paradigm',\n",
       "       'JIKAN STUDIOS', 'B.F.Party', 'Trippin Ape Tribe',\n",
       "       'NotBoredApeSolanaClub', 'MoonCollective', 'Not Junkiez Meta'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ERC721_df.tokenName.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ERC-1155"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "221\n"
     ]
    }
   ],
   "source": [
    "ERC1155 = get_erc1155()\n",
    "\n",
    "ERC1155_df = pd.DataFrame(ERC1155)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['OpenSea Shared Storefront', '', 'Rarible', 'StandWithUkraine',\n",
       "       'Orthoverse', 'Ukraine Freedom Fund Universal', 'Gucci',\n",
       "       'BAYC Otherside Land', 'APPLE', 'G-Star RAW', 'Nintendo'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ERC1155_df.tokenName.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# BTC"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://bitcoin.stackexchange.com/questions/108254/how-can-i-retrieve-all-transactions-for-an-address-using-the-blockchain-api\n",
    "\n",
    "\n",
    "Cycle through all offsets untill all txs are there\n",
    "\n",
    "https://blockchain.info/rawaddr/357a3So9CbsNfBBgFYACGvxxS6tMaDoa1P?format=json&offset=50&limit=50\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "BTC_ADRESS = \"357a3So9CbsNfBBgFYACGvxxS6tMaDoa1P\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "first Batch 0 - 50\n",
      "next Batch 50 - 100\n",
      "next Batch 100 - 150\n",
      "next Batch 150 - 200\n",
      "next Batch 200 - 250\n",
      "next Batch 250 - 300\n",
      "next Batch 300 - 350\n",
      "next Batch 350 - 400\n",
      "next Batch 400 - 450\n",
      "next Batch 450 - 500\n",
      "next Batch 500 - 550\n",
      "next Batch 550 - 600\n",
      "next Batch 600 - 650\n",
      "next Batch 650 - 700\n",
      "next Batch 700 - 750\n",
      "next Batch 750 - 800\n",
      "next Batch 800 - 850\n",
      "next Batch 850 - 900\n",
      "next Batch 900 - 950\n",
      "next Batch 950 - 1000\n",
      "next Batch 1000 - 1050\n",
      "next Batch 1050 - 1100\n",
      "next Batch 1100 - 1150\n",
      "next Batch 1150 - 1200\n",
      "next Batch 1200 - 1250\n",
      "next Batch 1250 - 1300\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "next Batch 17300 - 17350\n",
      "next Batch 17350 - 17400\n",
      "next Batch 17400 - 17450\n",
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      "next Batch 18000 - 18050\n",
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      "next Batch 18100 - 18150\n",
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      "next Batch 18500 - 18550\n",
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      "next Batch 18600 - 18650\n",
      "next Batch 18650 - 18700\n"
     ]
    }
   ],
   "source": [
    "BTC_Transactions = get_BTC_txs(BTC_ADRESS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hash</th>\n",
       "      <th>ver</th>\n",
       "      <th>vin_sz</th>\n",
       "      <th>vout_sz</th>\n",
       "      <th>size</th>\n",
       "      <th>weight</th>\n",
       "      <th>fee</th>\n",
       "      <th>relayed_by</th>\n",
       "      <th>lock_time</th>\n",
       "      <th>tx_index</th>\n",
       "      <th>double_spend</th>\n",
       "      <th>time</th>\n",
       "      <th>block_index</th>\n",
       "      <th>block_height</th>\n",
       "      <th>inputs</th>\n",
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       "  <tbody>\n",
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       "      <td>[{'type': 0, 'spent': True, 'value': 1181901, 'spending_outpoints': [{'tx_index': 35244083814682...</td>\n",
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       "      <td>0.0.0.0</td>\n",
       "      <td>740930</td>\n",
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       "      <td>False</td>\n",
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       "      <td>[{'sequence': 4294967293, 'witness': '02473044022004fe748ed8868e747e05c9fafcf19ffa141d6ff688a5c2...</td>\n",
       "      <td>[{'type': 0, 'spent': False, 'value': 73845, 'spending_outpoints': [], 'n': 0, 'tx_index': 59047...</td>\n",
       "      <td>73845</td>\n",
       "      <td>12257064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>193</td>\n",
       "      <td>442</td>\n",
       "      <td>2442</td>\n",
       "      <td>0.0.0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2618556642987650</td>\n",
       "      <td>False</td>\n",
       "      <td>1655309755</td>\n",
       "      <td>740931</td>\n",
       "      <td>740931</td>\n",
       "      <td>[{'sequence': 0, 'witness': '02483045022100a0003f3414b4794250cf2d53bfadc42d7c954ad26f65558d83bb5...</td>\n",
       "      <td>[{'type': 0, 'spent': False, 'value': 356558, 'spending_outpoints': [], 'n': 0, 'tx_index': 2618...</td>\n",
       "      <td>356558</td>\n",
       "      <td>12183219</td>\n",
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       "      <td>cca9608b8b3f08f055ab191f58abf3b0bb8913ffdfc6d04e85d3967a4e6cab76</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>False</td>\n",
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       "      <td>[{'type': 0, 'spent': True, 'value': 961758, 'spending_outpoints': [{'tx_index': 343853942502590...</td>\n",
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       "    <tr>\n",
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       "      <td>9001f9ebc205a89f0ab19ca3e787f80a152a13f76fced39f602d6b03c67dceb5</td>\n",
       "      <td>2</td>\n",
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       "      <td>0.0.0.0</td>\n",
       "      <td>0</td>\n",
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       "      <td>False</td>\n",
       "      <td>1655298049</td>\n",
       "      <td>740910</td>\n",
       "      <td>740910</td>\n",
       "      <td>[{'sequence': 4294967293, 'witness': '040047304402205c9e4dac9272831bf52c04645271ce45eb60bd72d605...</td>\n",
       "      <td>[{'type': 0, 'spent': True, 'value': 118651, 'spending_outpoints': [{'tx_index': 859241931452968...</td>\n",
       "      <td>163274</td>\n",
       "      <td>11709497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7fa537d5ec44cab1dfe4b126ed62a475eb27a37ec99031b451bd7dddd6d7ba43</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>192</td>\n",
       "      <td>441</td>\n",
       "      <td>143</td>\n",
       "      <td>0.0.0.0</td>\n",
       "      <td>740849</td>\n",
       "      <td>2383032453148599</td>\n",
       "      <td>False</td>\n",
       "      <td>1655270140</td>\n",
       "      <td>740851</td>\n",
       "      <td>740851</td>\n",
       "      <td>[{'sequence': 4294967293, 'witness': '0247304402201fb075638d32ce721fa550b77f81270e14b5c9eeedca10...</td>\n",
       "      <td>[{'type': 0, 'spent': False, 'value': 30722, 'spending_outpoints': [], 'n': 0, 'tx_index': 23830...</td>\n",
       "      <td>30722</td>\n",
       "      <td>11546223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>f84dcbbe087cc1ddd011be7612898a10fa2095e19392ff2e058039a029c161c1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>1303</td>\n",
       "      <td>4882</td>\n",
       "      <td>23330</td>\n",
       "      <td>0.0.0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>6804019095013168</td>\n",
       "      <td>False</td>\n",
       "      <td>1655185927</td>\n",
       "      <td>740718</td>\n",
       "      <td>740718</td>\n",
       "      <td>[{'sequence': 4294967295, 'witness': '02483045022100df2757e184424407bb73a4e689878e2b2af0910a5051...</td>\n",
       "      <td>[{'type': 0, 'spent': True, 'value': 1684544, 'spending_outpoints': [{'tx_index': 34096737149534...</td>\n",
       "      <td>12610</td>\n",
       "      <td>11515501</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",
       "      <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>18652</th>\n",
       "      <td>b757d92468fb4e3e6e2a5f3e09366afe041f875902cd63afb70bb84440841573</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>1192</td>\n",
       "      <td>4441</td>\n",
       "      <td>9968</td>\n",
       "      <td>0.0.0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4049160009979649</td>\n",
       "      <td>False</td>\n",
       "      <td>1645877752</td>\n",
       "      <td>725000</td>\n",
       "      <td>725000</td>\n",
       "      <td>[{'sequence': 4294967295, 'witness': '02473044022023e13b1214d06d948f8c500b78c28559d0705f3972c215...</td>\n",
       "      <td>[{'type': 0, 'spent': True, 'value': 1620000, 'spending_outpoints': [{'tx_index': 75744793838338...</td>\n",
       "      <td>398767</td>\n",
       "      <td>15966511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18653</th>\n",
       "      <td>4518e24b0c2e0af57ce2dfb2c583ad766d7afd0111738541903d590c73c7bee1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>247</td>\n",
       "      <td>661</td>\n",
       "      <td>1660</td>\n",
       "      <td>0.0.0.0</td>\n",
       "      <td>724999</td>\n",
       "      <td>7942704199732007</td>\n",
       "      <td>False</td>\n",
       "      <td>1645877752</td>\n",
       "      <td>725000</td>\n",
       "      <td>725000</td>\n",
       "      <td>[{'sequence': 4294967293, 'witness': '0247304402204c083356ac9b149961f03664d55befa60f59463f46a331...</td>\n",
       "      <td>[{'type': 0, 'spent': True, 'value': 63859, 'spending_outpoints': [{'tx_index': 7160664167463907...</td>\n",
       "      <td>63859</td>\n",
       "      <td>15567744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18654</th>\n",
       "      <td>ad234f4eda4a033e253af7eb9265481a95c703263c7710e439e133c953dcb44d</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>247</td>\n",
       "      <td>661</td>\n",
       "      <td>1660</td>\n",
       "      <td>0.0.0.0</td>\n",
       "      <td>724999</td>\n",
       "      <td>2734053949777532</td>\n",
       "      <td>False</td>\n",
       "      <td>1645877752</td>\n",
       "      <td>725000</td>\n",
       "      <td>725000</td>\n",
       "      <td>[{'sequence': 4294967293, 'witness': '02473044022017ea77a6e01c82eb8653926161150b506ce8787f297563...</td>\n",
       "      <td>[{'type': 0, 'spent': True, 'value': 76937, 'spending_outpoints': [{'tx_index': 7160664167463907...</td>\n",
       "      <td>76937</td>\n",
       "      <td>15503885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18655</th>\n",
       "      <td>f9c47b793aaf44e1f10cf5b54905830a7c990bbd9b84d9e7a3a34a7b42a02cce</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>193</td>\n",
       "      <td>442</td>\n",
       "      <td>1828</td>\n",
       "      <td>0.0.0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>7254114003020116</td>\n",
       "      <td>False</td>\n",
       "      <td>1645877752</td>\n",
       "      <td>725000</td>\n",
       "      <td>725000</td>\n",
       "      <td>[{'sequence': 4294967295, 'witness': '024830450221009b4c6efd2f690bb1c98c0e59350b0ecf9d8df9aae33b...</td>\n",
       "      <td>[{'type': 0, 'spent': True, 'value': 7708, 'spending_outpoints': [{'tx_index': 5535823491641762,...</td>\n",
       "      <td>7708</td>\n",
       "      <td>15426948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18656</th>\n",
       "      <td>31e7f42eed5536bb2287548c309427e049cb45f7f767c3c659d31a65e8036850</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>517</td>\n",
       "      <td>2068</td>\n",
       "      <td>11960</td>\n",
       "      <td>0.0.0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2829045516247898</td>\n",
       "      <td>False</td>\n",
       "      <td>1645877752</td>\n",
       "      <td>725000</td>\n",
       "      <td>725000</td>\n",
       "      <td>[{'sequence': 4294967295, 'witness': '', 'script': '47304402204fc898ba11475f3996e881ab2835442c7a...</td>\n",
       "      <td>[{'type': 0, 'spent': True, 'value': 32157, 'spending_outpoints': [{'tx_index': 176442771111476,...</td>\n",
       "      <td>32157</td>\n",
       "      <td>15419240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18657</th>\n",
       "      <td>98d4ec3604f8429cfe5ff93fe59a5ad6704af8cd30ff300d80bd621c917e9d8a</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>223</td>\n",
       "      <td>565</td>\n",
       "      <td>14200</td>\n",
       "      <td>0.0.0.0</td>\n",
       "      <td>724998</td>\n",
       "      <td>4877089214008407</td>\n",
       "      <td>False</td>\n",
       "      <td>1645876861</td>\n",
       "      <td>724999</td>\n",
       "      <td>724999</td>\n",
       "      <td>[{'sequence': 4294967294, 'witness': '0247304402203a8f9abd545ee0f5c5c115a288593d063733039eee98f9...</td>\n",
       "      <td>[{'type': 0, 'spent': True, 'value': 10387083, 'spending_outpoints': [{'tx_index': 3285730352233...</td>\n",
       "      <td>10387083</td>\n",
       "      <td>15387083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18658</th>\n",
       "      <td>aefcc9aab00e8622190c305e70f4b5ef2519091a3945430e6a409ac2c2a2af08</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>376</td>\n",
       "      <td>826</td>\n",
       "      <td>208</td>\n",
       "      <td>0.0.0.0</td>\n",
       "      <td>724664</td>\n",
       "      <td>305614175097672</td>\n",
       "      <td>False</td>\n",
       "      <td>1645716070</td>\n",
       "      <td>724758</td>\n",
       "      <td>724758</td>\n",
       "      <td>[{'sequence': 4294967293, 'witness': '0347304402201f49bd1db6a273887b2588b60811fd2cfd4d358745d061...</td>\n",
       "      <td>[{'type': 0, 'spent': True, 'value': 5000000, 'spending_outpoints': [{'tx_index': 32857303522334...</td>\n",
       "      <td>5000000</td>\n",
       "      <td>5000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18659 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                   hash  ver  \\\n",
       "0      e59161030eb04fd66bbe75d2f83487e267c4b633fb1e1ccbbf0a366657cf5a44    2   \n",
       "1      7318bb8899fdd4ee5c271505c323e32fdd64ffca08a6a7b872ae741295f1d2a7    2   \n",
       "2      6becfee4366f14fb92f2b1972686633582fe4bf444e78d779811743cd4816c4a    1   \n",
       "3      cca9608b8b3f08f055ab191f58abf3b0bb8913ffdfc6d04e85d3967a4e6cab76    1   \n",
       "4      9001f9ebc205a89f0ab19ca3e787f80a152a13f76fced39f602d6b03c67dceb5    2   \n",
       "5      7fa537d5ec44cab1dfe4b126ed62a475eb27a37ec99031b451bd7dddd6d7ba43    2   \n",
       "6      f84dcbbe087cc1ddd011be7612898a10fa2095e19392ff2e058039a029c161c1    1   \n",
       "...                                                                 ...  ...   \n",
       "18652  b757d92468fb4e3e6e2a5f3e09366afe041f875902cd63afb70bb84440841573    1   \n",
       "18653  4518e24b0c2e0af57ce2dfb2c583ad766d7afd0111738541903d590c73c7bee1    2   \n",
       "18654  ad234f4eda4a033e253af7eb9265481a95c703263c7710e439e133c953dcb44d    2   \n",
       "18655  f9c47b793aaf44e1f10cf5b54905830a7c990bbd9b84d9e7a3a34a7b42a02cce    2   \n",
       "18656  31e7f42eed5536bb2287548c309427e049cb45f7f767c3c659d31a65e8036850    1   \n",
       "18657  98d4ec3604f8429cfe5ff93fe59a5ad6704af8cd30ff300d80bd621c917e9d8a    2   \n",
       "18658  aefcc9aab00e8622190c305e70f4b5ef2519091a3945430e6a409ac2c2a2af08    2   \n",
       "\n",
       "       vin_sz  vout_sz  size  weight    fee relayed_by  lock_time  \\\n",
       "0           3        4   610    1471   8141    0.0.0.0     741028   \n",
       "1           1        1   192     441    774    0.0.0.0     740930   \n",
       "2           1        1   193     442   2442    0.0.0.0          0   \n",
       "3           1       63  2199    8469  44750    0.0.0.0          0   \n",
       "4           1       22  1041    3402  18834    0.0.0.0          0   \n",
       "5           1        1   192     441    143    0.0.0.0     740849   \n",
       "6           1       35  1303    4882  23330    0.0.0.0          0   \n",
       "...       ...      ...   ...     ...    ...        ...        ...   \n",
       "18652       1       32  1192    4441   9968    0.0.0.0          0   \n",
       "18653       1        2   247     661   1660    0.0.0.0     724999   \n",
       "18654       1        2   247     661   1660    0.0.0.0     724999   \n",
       "18655       1        1   193     442   1828    0.0.0.0          0   \n",
       "18656       3        2   517    2068  11960    0.0.0.0          0   \n",
       "18657       1        2   223     565  14200    0.0.0.0     724998   \n",
       "18658       1        2   376     826    208    0.0.0.0     724664   \n",
       "\n",
       "               tx_index  double_spend        time  block_index  block_height  \\\n",
       "0      2405018123421377         False  1655371891       741029        741029   \n",
       "1      5904782017580693         False  1655309858       740932        740932   \n",
       "2      2618556642987650         False  1655309755       740931        740931   \n",
       "3      4175316114166490         False  1655309709       740931        740931   \n",
       "4      6396751296621925         False  1655298049       740910        740910   \n",
       "5      2383032453148599         False  1655270140       740851        740851   \n",
       "6      6804019095013168         False  1655185927       740718        740718   \n",
       "...                 ...           ...         ...          ...           ...   \n",
       "18652  4049160009979649         False  1645877752       725000        725000   \n",
       "18653  7942704199732007         False  1645877752       725000        725000   \n",
       "18654  2734053949777532         False  1645877752       725000        725000   \n",
       "18655  7254114003020116         False  1645877752       725000        725000   \n",
       "18656  2829045516247898         False  1645877752       725000        725000   \n",
       "18657  4877089214008407         False  1645876861       724999        724999   \n",
       "18658   305614175097672         False  1645716070       724758        724758   \n",
       "\n",
       "                                                                                                    inputs  \\\n",
       "0      [{'sequence': 4294967294, 'witness': '0247304402203dc23229f7a5582f5c8aaa50677c9757f0a3ddef6a8f91...   \n",
       "1      [{'sequence': 4294967293, 'witness': '02473044022004fe748ed8868e747e05c9fafcf19ffa141d6ff688a5c2...   \n",
       "2      [{'sequence': 0, 'witness': '02483045022100a0003f3414b4794250cf2d53bfadc42d7c954ad26f65558d83bb5...   \n",
       "3      [{'sequence': 4294967295, 'witness': '024730440220053b74d371e3537aad499d806136e0ea44e4c21863ede5...   \n",
       "4      [{'sequence': 4294967293, 'witness': '040047304402205c9e4dac9272831bf52c04645271ce45eb60bd72d605...   \n",
       "5      [{'sequence': 4294967293, 'witness': '0247304402201fb075638d32ce721fa550b77f81270e14b5c9eeedca10...   \n",
       "6      [{'sequence': 4294967295, 'witness': '02483045022100df2757e184424407bb73a4e689878e2b2af0910a5051...   \n",
       "...                                                                                                    ...   \n",
       "18652  [{'sequence': 4294967295, 'witness': '02473044022023e13b1214d06d948f8c500b78c28559d0705f3972c215...   \n",
       "18653  [{'sequence': 4294967293, 'witness': '0247304402204c083356ac9b149961f03664d55befa60f59463f46a331...   \n",
       "18654  [{'sequence': 4294967293, 'witness': '02473044022017ea77a6e01c82eb8653926161150b506ce8787f297563...   \n",
       "18655  [{'sequence': 4294967295, 'witness': '024830450221009b4c6efd2f690bb1c98c0e59350b0ecf9d8df9aae33b...   \n",
       "18656  [{'sequence': 4294967295, 'witness': '', 'script': '47304402204fc898ba11475f3996e881ab2835442c7a...   \n",
       "18657  [{'sequence': 4294967294, 'witness': '0247304402203a8f9abd545ee0f5c5c115a288593d063733039eee98f9...   \n",
       "18658  [{'sequence': 4294967293, 'witness': '0347304402201f49bd1db6a273887b2588b60811fd2cfd4d358745d061...   \n",
       "\n",
       "                                                                                                       out  \\\n",
       "0      [{'type': 0, 'spent': True, 'value': 1181901, 'spending_outpoints': [{'tx_index': 35244083814682...   \n",
       "1      [{'type': 0, 'spent': False, 'value': 73845, 'spending_outpoints': [], 'n': 0, 'tx_index': 59047...   \n",
       "2      [{'type': 0, 'spent': False, 'value': 356558, 'spending_outpoints': [], 'n': 0, 'tx_index': 2618...   \n",
       "3      [{'type': 0, 'spent': True, 'value': 961758, 'spending_outpoints': [{'tx_index': 343853942502590...   \n",
       "4      [{'type': 0, 'spent': True, 'value': 118651, 'spending_outpoints': [{'tx_index': 859241931452968...   \n",
       "5      [{'type': 0, 'spent': False, 'value': 30722, 'spending_outpoints': [], 'n': 0, 'tx_index': 23830...   \n",
       "6      [{'type': 0, 'spent': True, 'value': 1684544, 'spending_outpoints': [{'tx_index': 34096737149534...   \n",
       "...                                                                                                    ...   \n",
       "18652  [{'type': 0, 'spent': True, 'value': 1620000, 'spending_outpoints': [{'tx_index': 75744793838338...   \n",
       "18653  [{'type': 0, 'spent': True, 'value': 63859, 'spending_outpoints': [{'tx_index': 7160664167463907...   \n",
       "18654  [{'type': 0, 'spent': True, 'value': 76937, 'spending_outpoints': [{'tx_index': 7160664167463907...   \n",
       "18655  [{'type': 0, 'spent': True, 'value': 7708, 'spending_outpoints': [{'tx_index': 5535823491641762,...   \n",
       "18656  [{'type': 0, 'spent': True, 'value': 32157, 'spending_outpoints': [{'tx_index': 176442771111476,...   \n",
       "18657  [{'type': 0, 'spent': True, 'value': 10387083, 'spending_outpoints': [{'tx_index': 3285730352233...   \n",
       "18658  [{'type': 0, 'spent': True, 'value': 5000000, 'spending_outpoints': [{'tx_index': 32857303522334...   \n",
       "\n",
       "         result   balance  \n",
       "0        200000  12457064  \n",
       "1         73845  12257064  \n",
       "2        356558  12183219  \n",
       "3        117164  11826661  \n",
       "4        163274  11709497  \n",
       "5         30722  11546223  \n",
       "6         12610  11515501  \n",
       "...         ...       ...  \n",
       "18652    398767  15966511  \n",
       "18653     63859  15567744  \n",
       "18654     76937  15503885  \n",
       "18655      7708  15426948  \n",
       "18656     32157  15419240  \n",
       "18657  10387083  15387083  \n",
       "18658   5000000   5000000  \n",
       "\n",
       "[18659 rows x 18 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BTC_Transactions_df = pd.DataFrame(BTC_Transactions)\n",
    "BTC_Transactions_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#Dropping columns and converting from sat to btc\n",
    "pd.options.display.max_colwidth = 100\n",
    "BTC_Transactions_cleaned_df = BTC_Transactions_df.drop(['vout_sz', 'fee','tx_index','ver','vin_sz', 'size', 'weight','lock_time','block_index','relayed_by','double_spend', 'inputs','out'], axis=1)\n",
    "BTC_Transactions_cleaned_df['result'] = BTC_Transactions_cleaned_df['result'] / (1.0 * 10**(8))\n",
    "BTC_Transactions_cleaned_df['balance'] = BTC_Transactions_cleaned_df['result'] / (1.0 * 10**(8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fetch Binance Prices for each Transaction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "btcprices = []\n",
    "\n",
    "for i in range (len(BTC_Transactions_cleaned_df)):\n",
    "    tx_ammount = BTC_Transactions_cleaned_df.iloc[i, 3]\n",
    "    tx_timestamp = BTC_Transactions_cleaned_df.iloc[i, 1]\n",
    "    spot_price_value = get_historical_price('BTC', int(tx_timestamp) * 1000)\n",
    "    spot_USD_Value = (tx_ammount * float(spot_price_value)).round(decimals = 2)\n",
    "    btcprices.append(spot_USD_Value)\n",
    "btcprices\n",
    "\n",
    "BTC_Transactions_cleaned_df['USD_Value at Donation time'] = btcprices\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cleaning up, negative & positive inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'BTC_Transactions_cleaned_df' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mNameError\u001B[0m                                 Traceback (most recent call last)",
      "\u001B[1;32m<ipython-input-2-13a0eeea0333>\u001B[0m in \u001B[0;36m<module>\u001B[1;34m\u001B[0m\n\u001B[0;32m      2\u001B[0m \u001B[1;31m#BTC_Transactions_cleaned_df[BTC_Transactions_cleaned_df[\"hash\"] == 'b9670b1b04f559d8f48da7f1f5e49f1b04ed067a3d2e5815d4f369bf8c81138e']['result']\u001B[0m\u001B[1;33m\u001B[0m\u001B[1;33m\u001B[0m\u001B[1;33m\u001B[0m\u001B[0m\n\u001B[0;32m      3\u001B[0m \u001B[1;33m\u001B[0m\u001B[0m\n\u001B[1;32m----> 4\u001B[1;33m \u001B[0mBTCInputTXs\u001B[0m \u001B[1;33m=\u001B[0m \u001B[0mBTC_Transactions_cleaned_df\u001B[0m\u001B[1;33m[\u001B[0m\u001B[0mBTC_Transactions_cleaned_df\u001B[0m\u001B[1;33m[\u001B[0m\u001B[1;34m'result'\u001B[0m\u001B[1;33m]\u001B[0m\u001B[1;33m>\u001B[0m\u001B[1;36m0\u001B[0m\u001B[1;33m]\u001B[0m\u001B[1;33m\u001B[0m\u001B[1;33m\u001B[0m\u001B[0m\n\u001B[0m\u001B[0;32m      5\u001B[0m \u001B[0mBTCOutputTXs\u001B[0m \u001B[1;33m=\u001B[0m \u001B[0mBTC_Transactions_cleaned_df\u001B[0m\u001B[1;33m[\u001B[0m\u001B[0mBTC_Transactions_cleaned_df\u001B[0m\u001B[1;33m[\u001B[0m\u001B[1;34m'result'\u001B[0m\u001B[1;33m]\u001B[0m\u001B[1;33m<\u001B[0m\u001B[1;36m0\u001B[0m\u001B[1;33m]\u001B[0m\u001B[1;33m\u001B[0m\u001B[1;33m\u001B[0m\u001B[0m\n\u001B[0;32m      6\u001B[0m \u001B[0mBTCNeutralTXs\u001B[0m \u001B[1;33m=\u001B[0m \u001B[0mBTC_Transactions_cleaned_df\u001B[0m\u001B[1;33m[\u001B[0m\u001B[0mBTC_Transactions_cleaned_df\u001B[0m\u001B[1;33m[\u001B[0m\u001B[1;34m'result'\u001B[0m\u001B[1;33m]\u001B[0m\u001B[1;33m==\u001B[0m\u001B[1;36m0\u001B[0m\u001B[1;33m]\u001B[0m\u001B[1;33m\u001B[0m\u001B[1;33m\u001B[0m\u001B[0m\n",
      "\u001B[1;31mNameError\u001B[0m: name 'BTC_Transactions_cleaned_df' is not defined"
     ]
    }
   ],
   "source": [
    "#Negative Transactions are there too\n",
    "#BTC_Transactions_cleaned_df[BTC_Transactions_cleaned_df[\"hash\"] == 'b9670b1b04f559d8f48da7f1f5e49f1b04ed067a3d2e5815d4f369bf8c81138e']['result'] \n",
    "\n",
    "BTCInputTXs = BTC_Transactions_cleaned_df[BTC_Transactions_cleaned_df['result']>0]\n",
    "BTCOutputTXs = BTC_Transactions_cleaned_df[BTC_Transactions_cleaned_df['result']<0]\n",
    "BTCNeutralTXs = BTC_Transactions_cleaned_df[BTC_Transactions_cleaned_df['result']==0]\n",
    "\n",
    "btc_input = BTCInputTXs['result'].sum()\n",
    "btc_output =BTCOutputTXs['result'].sum()\n",
    "print(f'BTC Input Transactions are   {btc_input}. \\nBTC Output Transactions are {btc_output}. \\nCheck Values here: https://www.blockchain.com/btc/address/357a3So9CbsNfBBgFYACGvxxS6tMaDoa1P')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "BTC_Transactions_cleaned_df.to_pickle('BTC_Transactions_cleaned_df')\n",
    "BTCInputTXs.to_pickle('BTCInputTXs')\n",
    "BTCOutputTXs.to_pickle('BTCOutputTXs')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Final Results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### importing pickles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "donations_ETH_df = pd.read_pickle('donations_ETH_df')\n",
    "donations_ERC20_df = pd.read_pickle('donations_ERC20_df')\n",
    "BTCInputTXs = pd.read_pickle('BTCInputTXs')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Total Donations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_Donations = []\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### BTC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['BTC', 479.90741358, 19621510.77]]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_Donations.append(['BTC',BTCInputTXs['result'].sum(),BTCInputTXs['USD_Value at Donation time'].sum()])\n",
    "total_Donations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ETH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['BTC', 479.90741358, 19621510.77], ['ETH', 7723.819765805032, 22545519.85]]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_Donations.append(['ETH',donations_ETH_df['amount'].sum(),donations_ETH_df['USD value at donation time'].sum()])\n",
    "\n",
    "total_Donations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ERC-20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "ticker USDT sum amount 7750877.755669 sum usd value 7750877.78\n",
      "ticker DAI sum amount 1073198.3029627907 sum usd value 1073198.2999999998\n",
      "ticker PKG sum amount 12312.0 sum usd value 0.0\n",
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      "ticker VSP sum amount 3.443958843131734 sum usd value 0.0\n",
      "ticker ANTIWAR sum amount 60354800000.0 sum usd value 0.0\n",
      "ticker OUCHI sum amount 100000.0 sum usd value 0.0\n",
      "ticker CNDL sum amount 200000069.0 sum usd value 0.0\n",
      "ticker UCC sum amount 100000.0 sum usd value 0.0\n",
      "ticker B20 sum amount 5.0 sum usd value 0.0\n",
      "ticker SKT sum amount 1000000.0 sum usd value 0.0\n",
      "ticker IOTF sum amount 257257.0 sum usd value 0.0\n",
      "ticker SLR sum amount 1000.0 sum usd value 0.0\n",
      "ticker O3 sum amount 17.98815488869698 sum usd value 0.0\n",
      "ticker WHALE sum amount 5.0 sum usd value 0.0\n",
      "ticker WAX sum amount 1091.83352988 sum usd value 0.0\n",
      "ticker World sum amount 100000000000000.0 sum usd value 0.0\n",
      "ticker MFT sum amount 2000.0 sum usd value 0.0\n",
      "ticker HFSP sum amount 775574500.0627165 sum usd value 0.0\n",
      "ticker KRAUSE sum amount 100.0 sum usd value 0.0\n",
      "ticker ALBT sum amount 1674.9341 sum usd value 0.0\n",
      "ticker NTVRK sum amount 20.0 sum usd value 0.0\n",
      "ticker eRSDL sum amount 10000.0 sum usd value 0.0\n",
      "ticker Prada sum amount 2887594689585.991 sum usd value 0.0\n",
      "ticker CENNZ sum amount 500.0 sum usd value 0.0\n",
      "ticker CHY sum amount 14727095.738882987 sum usd value 0.0\n",
      "ticker LNC sum amount 7000.0 sum usd value 0.0\n",
      "ticker Hermes sum amount 3503986571160.2524 sum usd value 0.0\n",
      "ticker NWT sum amount 3000000.0 sum usd value 0.0\n",
      "ticker Chanel sum amount 2500982854803.662 sum usd value 0.0\n",
      "ticker Gucci sum amount 2044300072792.4353 sum usd value 0.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ticker $HSUKRAINE sum amount 0.9 sum usd value 0.0\n",
      "ticker CRYN sum amount 10.0 sum usd value 0.0\n",
      "ticker Dior sum amount 2925041283047.277 sum usd value 0.0\n",
      "ticker Cartier sum amount 2959847517469.441 sum usd value 0.0\n",
      "ticker IBM sum amount 2340534211459.535 sum usd value 0.0\n",
      "ticker UKRHODL sum amount 540796.241274107 sum usd value 0.0\n",
      "ticker PASS sum amount 874854750.9 sum usd value 0.0\n",
      "ticker FPC sum amount 17.35 sum usd value 0.0\n",
      "ticker FLUX sum amount 10.0 sum usd value 13.51\n",
      "ticker DELL sum amount 3926699417419.1387 sum usd value 0.0\n",
      "ticker BMW sum amount 3201566869819.875 sum usd value 0.0\n",
      "ticker LNP sum amount 90000000000.0 sum usd value 0.0\n",
      "ticker xSUSHI sum amount 2.6262997660072456 sum usd value 0.0\n",
      "ticker CLIFF sum amount 1000000000.0 sum usd value 0.0\n",
      "ticker FRX sum amount 10000.0 sum usd value 0.0\n",
      "ticker USDP sum amount 500.0 sum usd value 500.0\n",
      "ticker ERC20 sum amount 2.97 sum usd value 0.0\n",
      "ticker KIEV sum amount 500000000.0 sum usd value 0.0\n",
      "ticker CBX sum amount 253.2 sum usd value 0.0\n",
      "ticker YFNP sum amount 60.59499686451759 sum usd value 0.0\n",
      "ticker META sum amount 490000000.0 sum usd value 0.0\n",
      "ticker SZC sum amount 0.66666 sum usd value 0.0\n",
      "ticker PLU sum amount 20.00128203 sum usd value 0.0\n",
      "ticker KILLPUTIN sum amount 100000000000000.0 sum usd value 0.0\n",
      "ticker ASH sum amount 12.0 sum usd value 0.0\n",
      "ticker USD sum amount 1.157920892373162e+77 sum usd value 0.0\n",
      "ticker RBST sum amount 40000000.0 sum usd value 0.0\n",
      "ticker TON sum amount 20000.0 sum usd value 0.0\n",
      "ticker NOIA sum amount 1000.0 sum usd value 0.0\n",
      "ticker UST sum amount 241.5 sum usd value 242.3\n",
      "ticker Peace sum amount 3500000000.0 sum usd value 0.0\n",
      "ticker BABYDOGE sum amount 8745468444.515396 sum usd value 0.0\n",
      "ticker SAITAMA sum amount 2821574908.5070643 sum usd value 0.0\n",
      "ticker mfers-DAO.io sum amount 5555.0 sum usd value 0.0\n",
      "ticker SMORK sum amount 10000000000000.0 sum usd value 0.0\n",
      "ticker $CMD sum amount 100000000000000.0 sum usd value 0.0\n",
      "ticker CKING sum amount 500000000000000.0 sum usd value 0.0\n",
      "ticker CASH sum amount 18.0 sum usd value 0.0\n",
      "ticker JGN sum amount 775832.9329862201 sum usd value 0.0\n",
      "ticker WXRP sum amount 169.0 sum usd value 0.0\n",
      "ticker ZAPP sum amount 1.0 sum usd value 0.0\n",
      "ticker SKINU sum amount 2985146553242.0 sum usd value 0.0\n",
      "ticker HXRO sum amount 1370.5744326766674 sum usd value 0.0\n",
      "ticker GOSH sum amount 790.9933641 sum usd value 0.0\n",
      "ticker KHUYLO sum amount 14099999990000.0 sum usd value 0.0\n",
      "ticker BASTARD sum amount 21420.0 sum usd value 0.0\n",
      "ticker UKRAINE sum amount 4400000.0 sum usd value 0.0\n",
      "ticker GUMP sum amount 10400000000.0 sum usd value 0.0\n",
      "ticker SLC sum amount 99984.15 sum usd value 0.0\n",
      "ticker SLV sum amount 1.0 sum usd value 0.0\n",
      "ticker UKR sum amount 500000000000000.0 sum usd value 0.0\n",
      "ticker XDB sum amount 2064700.0 sum usd value 0.0\n",
      "ticker HOP sum amount 426.869552485249 sum usd value 0.0\n"
     ]
    }
   ],
   "source": [
    "ERC20_currencies = donations_ERC20_df.ticker.unique()\n",
    "\n",
    "donations_ERC20_df[(donations_ERC20_df['ticker'] == 'USDC')]\n",
    "\n",
    "for i in range (len(ERC20_currencies)):\n",
    "    \n",
    "    ticker = ERC20_currencies[i]\n",
    "    \n",
    "    sum_amount = donations_ERC20_df[(donations_ERC20_df['ticker'] == ticker)]['amount'].sum()\n",
    "    \n",
    "    sum_usd_value = donations_ERC20_df[(donations_ERC20_df['ticker'] == ticker)]['USD value at donation time'].sum()\n",
    "    print(f'ticker {ticker} sum amount {sum_amount} sum usd value {sum_usd_value}')\n",
    "    total_Donations.append([ticker,sum_amount,sum_usd_value])\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grouped into Top 4 and producing Pie Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Ticker</th>\n",
       "      <th>Total Amount (nominal)</th>\n",
       "      <th>Total Amount (USD value at donation time)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ETH</td>\n",
       "      <td>7.723820e+03</td>\n",
       "      <td>22545519.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BTC</td>\n",
       "      <td>4.799074e+02</td>\n",
       "      <td>19621510.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>USDT</td>\n",
       "      <td>7.750878e+06</td>\n",
       "      <td>7750877.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>USDC</td>\n",
       "      <td>1.203278e+06</td>\n",
       "      <td>1203278.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DAI</td>\n",
       "      <td>1.073198e+06</td>\n",
       "      <td>1073198.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>ETH</td>\n",
       "      <td>1.144334e+01</td>\n",
       "      <td>32917.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>LIT</td>\n",
       "      <td>8.094400e+03</td>\n",
       "      <td>11931.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>BAL</td>\n",
       "      <td>1.509051e+03</td>\n",
       "      <td>11653.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>OCEAN</td>\n",
       "      <td>1.000000e+04</td>\n",
       "      <td>4559.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>ENS</td>\n",
       "      <td>2.202344e+02</td>\n",
       "      <td>3318.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>LINK</td>\n",
       "      <td>1.409680e+02</td>\n",
       "      <td>2103.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>SHIB</td>\n",
       "      <td>6.203191e+07</td>\n",
       "      <td>1595.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>YFI</td>\n",
       "      <td>6.900000e-02</td>\n",
       "      <td>1413.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>MATIC</td>\n",
       "      <td>8.019695e+02</td>\n",
       "      <td>1304.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>LRC</td>\n",
       "      <td>1.533264e+03</td>\n",
       "      <td>1180.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>GRT</td>\n",
       "      <td>2.374074e+03</td>\n",
       "      <td>813.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>AKRO</td>\n",
       "      <td>1.750000e+05</td>\n",
       "      <td>614.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MDT</td>\n",
       "      <td>1.000000e+04</td>\n",
       "      <td>578.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>OMG</td>\n",
       "      <td>1.283575e+02</td>\n",
       "      <td>508.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>USDP</td>\n",
       "      <td>5.000000e+02</td>\n",
       "      <td>500.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>BAT</td>\n",
       "      <td>5.958638e+02</td>\n",
       "      <td>433.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>1INCH</td>\n",
       "      <td>2.485766e+02</td>\n",
       "      <td>357.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>POWR</td>\n",
       "      <td>5.662118e+02</td>\n",
       "      <td>285.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>BNT</td>\n",
       "      <td>1.046222e+02</td>\n",
       "      <td>257.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>AAVE</td>\n",
       "      <td>1.856188e+00</td>\n",
       "      <td>254.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>UST</td>\n",
       "      <td>2.415000e+02</td>\n",
       "      <td>242.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>ZRX</td>\n",
       "      <td>4.258325e+02</td>\n",
       "      <td>229.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>SKL</td>\n",
       "      <td>1.357082e+03</td>\n",
       "      <td>158.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>BTC</td>\n",
       "      <td>3.563350e-03</td>\n",
       "      <td>155.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>LPT</td>\n",
       "      <td>4.322949e+00</td>\n",
       "      <td>104.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>ORN</td>\n",
       "      <td>2.969796e+01</td>\n",
       "      <td>97.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>USTC</td>\n",
       "      <td>3.600489e+03</td>\n",
       "      <td>96.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>PEOPLE</td>\n",
       "      <td>1.100000e+03</td>\n",
       "      <td>77.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>MANA</td>\n",
       "      <td>2.275431e+01</td>\n",
       "      <td>61.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>RGT</td>\n",
       "      <td>2.500000e+00</td>\n",
       "      <td>44.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>ENJ</td>\n",
       "      <td>2.600000e+01</td>\n",
       "      <td>38.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>API3</td>\n",
       "      <td>4.544766e+00</td>\n",
       "      <td>29.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>IOTX</td>\n",
       "      <td>3.638273e+02</td>\n",
       "      <td>27.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>COMP</td>\n",
       "      <td>1.828075e-01</td>\n",
       "      <td>24.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>DIA</td>\n",
       "      <td>1.508175e+01</td>\n",
       "      <td>15.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>RLC</td>\n",
       "      <td>8.000000e+00</td>\n",
       "      <td>15.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>POLS</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>13.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>FLUX</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>13.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>SUSHI</td>\n",
       "      <td>3.261697e+00</td>\n",
       "      <td>11.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>SAND</td>\n",
       "      <td>3.465726e+00</td>\n",
       "      <td>11.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>KNC</td>\n",
       "      <td>3.673884e+00</td>\n",
       "      <td>10.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>CHZ</td>\n",
       "      <td>5.701254e+01</td>\n",
       "      <td>10.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>CRV</td>\n",
       "      <td>3.906250e+00</td>\n",
       "      <td>10.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>UNI</td>\n",
       "      <td>6.300000e-01</td>\n",
       "      <td>6.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>SXP</td>\n",
       "      <td>2.974111e+00</td>\n",
       "      <td>3.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>SLP</td>\n",
       "      <td>1.000000e+02</td>\n",
       "      <td>1.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>CLV</td>\n",
       "      <td>2.970868e+00</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>PERP</td>\n",
       "      <td>1.991082e-01</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>FRONT</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>0.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>AERGO</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>0.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>278</th>\n",
       "      <td>SLV</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>SKT</td>\n",
       "      <td>1.000000e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>B20</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>onedayrug</td>\n",
       "      <td>9.133490e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>UCC</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>CNDL</td>\n",
       "      <td>2.000001e+08</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>PDOGE</td>\n",
       "      <td>4.975433e+13</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>OUCHI</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>276</th>\n",
       "      <td>GUMP</td>\n",
       "      <td>1.040000e+10</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>VNLA</td>\n",
       "      <td>4.750000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>ANTIWAR</td>\n",
       "      <td>6.035480e+10</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>VSP</td>\n",
       "      <td>3.443959e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>XRT</td>\n",
       "      <td>1.188356e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>SLC</td>\n",
       "      <td>9.998415e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>SNOW</td>\n",
       "      <td>6.508895e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>BUNNY</td>\n",
       "      <td>2.608063e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>$CMD</td>\n",
       "      <td>1.000000e+14</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>SGT</td>\n",
       "      <td>1.563243e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>FREE</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>GERO</td>\n",
       "      <td>8.000000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>TKING</td>\n",
       "      <td>2.377000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>ZUM</td>\n",
       "      <td>9.450001e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>XDB</td>\n",
       "      <td>2.064700e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>JUSTICE</td>\n",
       "      <td>5.000000e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>uDOO</td>\n",
       "      <td>1.428690e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>IJC</td>\n",
       "      <td>1.000000e+08</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>CMCT</td>\n",
       "      <td>4.253012e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>CATE</td>\n",
       "      <td>1.015519e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>WORLD</td>\n",
       "      <td>1.397456e+10</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>BLOCKS</td>\n",
       "      <td>5.365653e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>ECU</td>\n",
       "      <td>2.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>OBTC</td>\n",
       "      <td>1.148532e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>279</th>\n",
       "      <td>UKR</td>\n",
       "      <td>5.000000e+14</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>BitANT</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>CUBE</td>\n",
       "      <td>9.402150e-01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>HAPI</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>HDRN</td>\n",
       "      <td>4.200000e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>KPF</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>UBI</td>\n",
       "      <td>2.789160e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>RAI</td>\n",
       "      <td>7.107529e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>wsGaas</td>\n",
       "      <td>1.967802e-02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>SLR</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>STAKE</td>\n",
       "      <td>2.948274e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>IOTF</td>\n",
       "      <td>2.572570e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>World</td>\n",
       "      <td>1.000000e+14</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>O3</td>\n",
       "      <td>1.798815e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>UKRHODL</td>\n",
       "      <td>5.407962e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>FPC</td>\n",
       "      <td>1.735000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>DELL</td>\n",
       "      <td>3.926699e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>BMW</td>\n",
       "      <td>3.201567e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>LNP</td>\n",
       "      <td>9.000000e+10</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267</th>\n",
       "      <td>JGN</td>\n",
       "      <td>7.758329e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>xSUSHI</td>\n",
       "      <td>2.626300e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>CLIFF</td>\n",
       "      <td>1.000000e+09</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>FRX</td>\n",
       "      <td>1.000000e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>ERC20</td>\n",
       "      <td>2.970000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>KIEV</td>\n",
       "      <td>5.000000e+08</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>CBX</td>\n",
       "      <td>2.532000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>YFNP</td>\n",
       "      <td>6.059500e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>META</td>\n",
       "      <td>4.900000e+08</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>SZC</td>\n",
       "      <td>6.666600e-01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>PLU</td>\n",
       "      <td>2.000128e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>KILLPUTIN</td>\n",
       "      <td>1.000000e+14</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>ASH</td>\n",
       "      <td>1.200000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>USD</td>\n",
       "      <td>1.157921e+77</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>RBST</td>\n",
       "      <td>4.000000e+07</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>TON</td>\n",
       "      <td>2.000000e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>NOIA</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266</th>\n",
       "      <td>CASH</td>\n",
       "      <td>1.800000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>Peace</td>\n",
       "      <td>3.500000e+09</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>BABYDOGE</td>\n",
       "      <td>8.745468e+09</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>SAITAMA</td>\n",
       "      <td>2.821575e+09</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>mfers-DAO.io</td>\n",
       "      <td>5.555000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>SMORK</td>\n",
       "      <td>1.000000e+13</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>PASS</td>\n",
       "      <td>8.748548e+08</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>IBM</td>\n",
       "      <td>2.340534e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>WHALE</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>268</th>\n",
       "      <td>WXRP</td>\n",
       "      <td>1.690000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>UKRAINE</td>\n",
       "      <td>4.400000e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>WAX</td>\n",
       "      <td>1.091834e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>CKING</td>\n",
       "      <td>5.000000e+14</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>BASTARD</td>\n",
       "      <td>2.142000e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>MFT</td>\n",
       "      <td>2.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>HFSP</td>\n",
       "      <td>7.755745e+08</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>KRAUSE</td>\n",
       "      <td>1.000000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>ALBT</td>\n",
       "      <td>1.674934e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>KHUYLO</td>\n",
       "      <td>1.410000e+13</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>NTVRK</td>\n",
       "      <td>2.000000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>eRSDL</td>\n",
       "      <td>1.000000e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>Prada</td>\n",
       "      <td>2.887595e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>CENNZ</td>\n",
       "      <td>5.000000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>CHY</td>\n",
       "      <td>1.472710e+07</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>LNC</td>\n",
       "      <td>7.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>Hermes</td>\n",
       "      <td>3.503987e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>$WEAPON</td>\n",
       "      <td>3.000000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>Chanel</td>\n",
       "      <td>2.500983e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>Gucci</td>\n",
       "      <td>2.044300e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>$HSUKRAINE</td>\n",
       "      <td>9.000000e-01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>GOSH</td>\n",
       "      <td>7.909934e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>HXRO</td>\n",
       "      <td>1.370574e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270</th>\n",
       "      <td>SKINU</td>\n",
       "      <td>2.985147e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>ZAPP</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>CRYN</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>Dior</td>\n",
       "      <td>2.925041e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>Cartier</td>\n",
       "      <td>2.959848e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>NWT</td>\n",
       "      <td>3.000000e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>BEPRO</td>\n",
       "      <td>3.411782e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>CUDOS</td>\n",
       "      <td>4.206900e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>MOONEY</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>OHM</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>HELP UKRAİNE</td>\n",
       "      <td>2.400000e+15</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>KLEE</td>\n",
       "      <td>1.470000e+13</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>carbon</td>\n",
       "      <td>6.372540e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>anyUSDC</td>\n",
       "      <td>2.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>XYO</td>\n",
       "      <td>2.722570e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Cloudbit Token</td>\n",
       "      <td>1.800000e+08</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>ACCEL</td>\n",
       "      <td>1.111000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>BANANA</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>MOD</td>\n",
       "      <td>1.000000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>XLAB</td>\n",
       "      <td>3.738950e+07</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>SUD</td>\n",
       "      <td>1.362166e+07</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>PSY</td>\n",
       "      <td>6.135437e+09</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>OCTO</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>CIRUS</td>\n",
       "      <td>3.000000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>YFV</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>KUNU</td>\n",
       "      <td>2.074048e+14</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>FLOKI</td>\n",
       "      <td>2.000000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>STARL</td>\n",
       "      <td>5.609869e+09</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>BIOP</td>\n",
       "      <td>9.597700e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Marvel</td>\n",
       "      <td>4.742937e+13</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>Nigger</td>\n",
       "      <td>7.469064e+13</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>MAHA</td>\n",
       "      <td>1.010000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>ICH</td>\n",
       "      <td>2.500000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>MIM</td>\n",
       "      <td>2.740406e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>PIST</td>\n",
       "      <td>6.000000e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>AXUS</td>\n",
       "      <td>2.000000e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>LEAN</td>\n",
       "      <td>1.080000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>ELON</td>\n",
       "      <td>2.477418e+07</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>GAS</td>\n",
       "      <td>1.939416e+07</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1-UP</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>PKG</td>\n",
       "      <td>1.231200e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>SAITOKI</td>\n",
       "      <td>3.580565e+09</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>eMTRG</td>\n",
       "      <td>1.888000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>KNDX</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>RFX</td>\n",
       "      <td>1.500000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>MIC</td>\n",
       "      <td>1.085944e-04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>DSD</td>\n",
       "      <td>6.355204e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>AWO</td>\n",
       "      <td>1.000000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>CUMINU</td>\n",
       "      <td>1.624167e-03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>STRM</td>\n",
       "      <td>1.362178e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>bWETH</td>\n",
       "      <td>1.700000e-17</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>AOM</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>KOIN</td>\n",
       "      <td>1.069810e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>EURS</td>\n",
       "      <td>5.000000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>INUS</td>\n",
       "      <td>1.388400e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>anyUSDT</td>\n",
       "      <td>2.185226e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>DYP</td>\n",
       "      <td>2.500000e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>JBX</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>GEL</td>\n",
       "      <td>4.800000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>$CHINU</td>\n",
       "      <td>9.999990e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>PAPER</td>\n",
       "      <td>6.969000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>UKG</td>\n",
       "      <td>6.000000e+07</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>SPD</td>\n",
       "      <td>1.985000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0xBTC</td>\n",
       "      <td>3.742460e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>DETF</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>GRC</td>\n",
       "      <td>1.848000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>NVIDIA</td>\n",
       "      <td>4.385674e+13</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>CRO</td>\n",
       "      <td>4.357822e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>MGH</td>\n",
       "      <td>3.000000e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>JEX</td>\n",
       "      <td>1.955000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>MNET</td>\n",
       "      <td>1.545750e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>alUSD</td>\n",
       "      <td>1.010000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>RFR</td>\n",
       "      <td>2.123764e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>NOW</td>\n",
       "      <td>1.500000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>GAO</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>RNTB</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>UDF</td>\n",
       "      <td>8.000000e+10</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>HEX</td>\n",
       "      <td>3.757500e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>ESD</td>\n",
       "      <td>8.148599e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>OTB</td>\n",
       "      <td>1.700000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>LIX</td>\n",
       "      <td>1.700000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>DRYDOGE</td>\n",
       "      <td>1.823949e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>GUILD</td>\n",
       "      <td>6.386902e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>SARCO</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>PICKLE</td>\n",
       "      <td>4.086533e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>RND</td>\n",
       "      <td>4.536000e+08</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>RAZE</td>\n",
       "      <td>5.000000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>XNN</td>\n",
       "      <td>5.212566e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>ZEON</td>\n",
       "      <td>2.700000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>TQUEEN</td>\n",
       "      <td>5.308842e+11</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>LEEDO</td>\n",
       "      <td>1.000000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>TUBE2</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>DOOR</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>UBT</td>\n",
       "      <td>1.000000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>BT</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>BYTES</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>WBNB</td>\n",
       "      <td>5.000000e-02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>ECZZ</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>Coval</td>\n",
       "      <td>3.486057e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>SUPRA</td>\n",
       "      <td>5.000000e+07</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>MM</td>\n",
       "      <td>1.200000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>eBay</td>\n",
       "      <td>4.836176e+09</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>UNT</td>\n",
       "      <td>2.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>VOLT</td>\n",
       "      <td>4.073034e+17</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>SLM</td>\n",
       "      <td>3.000000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>UFO</td>\n",
       "      <td>1.000000e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>DOE</td>\n",
       "      <td>1.548514e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>ZADDY</td>\n",
       "      <td>7.768104e+12</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>SOS</td>\n",
       "      <td>1.845382e+08</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>BOOTY</td>\n",
       "      <td>6.900000e-01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>FloMoCoin</td>\n",
       "      <td>1.000000e+06</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>GER</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>CHAI</td>\n",
       "      <td>5.500000e+01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>ARTERA</td>\n",
       "      <td>1.000000e+07</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>CAPS</td>\n",
       "      <td>1.100000e+05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>Ͼ</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>BED</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>UAD</td>\n",
       "      <td>6.500000e+11</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>MORK</td>\n",
       "      <td>6.800300e+00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>PNT</td>\n",
       "      <td>1.000000e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>Porn</td>\n",
       "      <td>5.217516e+07</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>Laika</td>\n",
       "      <td>3.286583e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>BOGE</td>\n",
       "      <td>1.190349e+08</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>UCD</td>\n",
       "      <td>5.000000e+09</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>HOGE</td>\n",
       "      <td>9.799902e+04</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>MT</td>\n",
       "      <td>1.128000e+03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>281</th>\n",
       "      <td>HOP</td>\n",
       "      <td>4.268696e+02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Ticker  Total Amount (nominal)  \\\n",
       "1               ETH            7.723820e+03   \n",
       "0               BTC            4.799074e+02   \n",
       "3              USDT            7.750878e+06   \n",
       "2              USDC            1.203278e+06   \n",
       "4               DAI            1.073198e+06   \n",
       "20              ETH            1.144334e+01   \n",
       "126             LIT            8.094400e+03   \n",
       "111             BAL            1.509051e+03   \n",
       "75            OCEAN            1.000000e+04   \n",
       "76              ENS            2.202344e+02   \n",
       "73             LINK            1.409680e+02   \n",
       "30             SHIB            6.203191e+07   \n",
       "21              YFI            6.900000e-02   \n",
       "89            MATIC            8.019695e+02   \n",
       "57              LRC            1.533264e+03   \n",
       "74              GRT            2.374074e+03   \n",
       "116            AKRO            1.750000e+05   \n",
       "6               MDT            1.000000e+04   \n",
       "44              OMG            1.283575e+02   \n",
       "244            USDP            5.000000e+02   \n",
       "106             BAT            5.958638e+02   \n",
       "155           1INCH            2.485766e+02   \n",
       "97             POWR            5.662118e+02   \n",
       "113             BNT            1.046222e+02   \n",
       "72             AAVE            1.856188e+00   \n",
       "258             UST            2.415000e+02   \n",
       "94              ZRX            4.258325e+02   \n",
       "67              SKL            1.357082e+03   \n",
       "162             BTC            3.563350e-03   \n",
       "69              LPT            4.322949e+00   \n",
       "41              ORN            2.969796e+01   \n",
       "64             USTC            3.600489e+03   \n",
       "8            PEOPLE            1.100000e+03   \n",
       "173            MANA            2.275431e+01   \n",
       "112             RGT            2.500000e+00   \n",
       "87              ENJ            2.600000e+01   \n",
       "9              API3            4.544766e+00   \n",
       "190            IOTX            3.638273e+02   \n",
       "110            COMP            1.828075e-01   \n",
       "131             DIA            1.508175e+01   \n",
       "197             RLC            8.000000e+00   \n",
       "175            POLS            1.000000e+01   \n",
       "237            FLUX            1.000000e+01   \n",
       "174           SUSHI            3.261697e+00   \n",
       "195            SAND            3.465726e+00   \n",
       "198             KNC            3.673884e+00   \n",
       "25              CHZ            5.701254e+01   \n",
       "114             CRV            3.906250e+00   \n",
       "163             UNI            6.300000e-01   \n",
       "18              SXP            2.974111e+00   \n",
       "146             SLP            1.000000e+02   \n",
       "50              CLV            2.970868e+00   \n",
       "187            PERP            1.991082e-01   \n",
       "26            FRONT            2.000000e+00   \n",
       "199           AERGO            2.000000e+00   \n",
       "278             SLV            1.000000e+00   \n",
       "208             SKT            1.000000e+06   \n",
       "207             B20            5.000000e+00   \n",
       "193       onedayrug            9.133490e+05   \n",
       "206             UCC            1.000000e+05   \n",
       "205            CNDL            2.000001e+08   \n",
       "194           PDOGE            4.975433e+13   \n",
       "204           OUCHI            1.000000e+05   \n",
       "276            GUMP            1.040000e+10   \n",
       "196            VNLA            4.750000e+01   \n",
       "203         ANTIWAR            6.035480e+10   \n",
       "202             VSP            3.443959e+00   \n",
       "200             XRT            1.188356e+01   \n",
       "277             SLC            9.998415e+04   \n",
       "201            SNOW            6.508895e+00   \n",
       "192           BUNNY            2.608063e+05   \n",
       "264            $CMD            1.000000e+14   \n",
       "191             SGT            1.563243e+03   \n",
       "177            FREE            1.000000e+05   \n",
       "164            GERO            8.000000e+02   \n",
       "165           TKING            2.377000e+03   \n",
       "166             ZUM            9.450001e+06   \n",
       "280             XDB            2.064700e+06   \n",
       "167         JUSTICE            5.000000e+04   \n",
       "168            uDOO            1.428690e+03   \n",
       "169             IJC            1.000000e+08   \n",
       "170            CMCT            4.253012e+03   \n",
       "171            CATE            1.015519e+04   \n",
       "172           WORLD            1.397456e+10   \n",
       "176          BLOCKS            5.365653e+05   \n",
       "178             ECU            2.000000e+03   \n",
       "189            OBTC            1.148532e+06   \n",
       "279             UKR            5.000000e+14   \n",
       "179          BitANT            1.000000e+03   \n",
       "180            CUBE            9.402150e-01   \n",
       "181            HAPI            1.000000e+01   \n",
       "182            HDRN            4.200000e+06   \n",
       "183             KPF            1.000000e+05   \n",
       "184             UBI            2.789160e+03   \n",
       "185             RAI            7.107529e+00   \n",
       "186          wsGaas            1.967802e-02   \n",
       "210             SLR            1.000000e+03   \n",
       "188           STAKE            2.948274e+00   \n",
       "209            IOTF            2.572570e+05   \n",
       "214           World            1.000000e+14   \n",
       "211              O3            1.798815e+01   \n",
       "234         UKRHODL            5.407962e+05   \n",
       "236             FPC            1.735000e+01   \n",
       "238            DELL            3.926699e+12   \n",
       "239             BMW            3.201567e+12   \n",
       "240             LNP            9.000000e+10   \n",
       "267             JGN            7.758329e+05   \n",
       "241          xSUSHI            2.626300e+00   \n",
       "242           CLIFF            1.000000e+09   \n",
       "243             FRX            1.000000e+04   \n",
       "245           ERC20            2.970000e+00   \n",
       "246            KIEV            5.000000e+08   \n",
       "247             CBX            2.532000e+02   \n",
       "248            YFNP            6.059500e+01   \n",
       "249            META            4.900000e+08   \n",
       "250             SZC            6.666600e-01   \n",
       "251             PLU            2.000128e+01   \n",
       "252       KILLPUTIN            1.000000e+14   \n",
       "253             ASH            1.200000e+01   \n",
       "254             USD            1.157921e+77   \n",
       "255            RBST            4.000000e+07   \n",
       "256             TON            2.000000e+04   \n",
       "257            NOIA            1.000000e+03   \n",
       "266            CASH            1.800000e+01   \n",
       "259           Peace            3.500000e+09   \n",
       "260        BABYDOGE            8.745468e+09   \n",
       "261         SAITAMA            2.821575e+09   \n",
       "262    mfers-DAO.io            5.555000e+03   \n",
       "263           SMORK            1.000000e+13   \n",
       "235            PASS            8.748548e+08   \n",
       "233             IBM            2.340534e+12   \n",
       "212           WHALE            5.000000e+00   \n",
       "268            WXRP            1.690000e+02   \n",
       "275         UKRAINE            4.400000e+06   \n",
       "213             WAX            1.091834e+03   \n",
       "265           CKING            5.000000e+14   \n",
       "274         BASTARD            2.142000e+04   \n",
       "215             MFT            2.000000e+03   \n",
       "216            HFSP            7.755745e+08   \n",
       "217          KRAUSE            1.000000e+02   \n",
       "218            ALBT            1.674934e+03   \n",
       "273          KHUYLO            1.410000e+13   \n",
       "219           NTVRK            2.000000e+01   \n",
       "220           eRSDL            1.000000e+04   \n",
       "221           Prada            2.887595e+12   \n",
       "222           CENNZ            5.000000e+02   \n",
       "223             CHY            1.472710e+07   \n",
       "224             LNC            7.000000e+03   \n",
       "225          Hermes            3.503987e+12   \n",
       "161         $WEAPON            3.000000e+01   \n",
       "227          Chanel            2.500983e+12   \n",
       "228           Gucci            2.044300e+12   \n",
       "229      $HSUKRAINE            9.000000e-01   \n",
       "272            GOSH            7.909934e+02   \n",
       "271            HXRO            1.370574e+03   \n",
       "270           SKINU            2.985147e+12   \n",
       "269            ZAPP            1.000000e+00   \n",
       "230            CRYN            1.000000e+01   \n",
       "231            Dior            2.925041e+12   \n",
       "232         Cartier            2.959848e+12   \n",
       "226             NWT            3.000000e+06   \n",
       "141           BEPRO            3.411782e+03   \n",
       "160           CUDOS            4.206900e+02   \n",
       "159          MOONEY            1.000000e+03   \n",
       "46              OHM            1.000000e+01   \n",
       "47     HELP UKRAİNE            2.400000e+15   \n",
       "48             KLEE            1.470000e+13   \n",
       "49           carbon            6.372540e+06   \n",
       "51          anyUSDC            2.000000e+03   \n",
       "52              XYO            2.722570e+03   \n",
       "53   Cloudbit Token            1.800000e+08   \n",
       "54            ACCEL            1.111000e+03   \n",
       "55           BANANA            2.000000e+00   \n",
       "56              MOD            1.000000e+02   \n",
       "58             XLAB            3.738950e+07   \n",
       "59              SUD            1.362166e+07   \n",
       "60              PSY            6.135437e+09   \n",
       "61             OCTO            2.000000e+00   \n",
       "62            CIRUS            3.000000e+02   \n",
       "63              YFV            2.000000e+00   \n",
       "65             KUNU            2.074048e+14   \n",
       "66            FLOKI            2.000000e+05   \n",
       "68            STARL            5.609869e+09   \n",
       "70             BIOP            9.597700e+02   \n",
       "71           Marvel            4.742937e+13   \n",
       "77           Nigger            7.469064e+13   \n",
       "78             MAHA            1.010000e+03   \n",
       "79              ICH            2.500000e+02   \n",
       "80              MIM            2.740406e+01   \n",
       "81             PIST            6.000000e+04   \n",
       "82             AXUS            2.000000e+04   \n",
       "45             LEAN            1.080000e+03   \n",
       "43             ELON            2.477418e+07   \n",
       "42              GAS            1.939416e+07   \n",
       "23             1-UP            1.000000e+03   \n",
       "5               PKG            1.231200e+04   \n",
       "7           SAITOKI            3.580565e+09   \n",
       "10            eMTRG            1.888000e+01   \n",
       "11             KNDX            1.000000e+00   \n",
       "12              RFX            1.500000e+05   \n",
       "13              MIC            1.085944e-04   \n",
       "14              DSD            6.355204e+01   \n",
       "15              AWO            1.000000e+02   \n",
       "16           CUMINU            1.624167e-03   \n",
       "17             STRM            1.362178e+01   \n",
       "19            bWETH            1.700000e-17   \n",
       "22              AOM            1.000000e+03   \n",
       "24             KOIN            1.069810e+00   \n",
       "40             EURS            5.000000e+01   \n",
       "27             INUS            1.388400e+12   \n",
       "28          anyUSDT            2.185226e+03   \n",
       "29              DYP            2.500000e+04   \n",
       "31              JBX            1.000000e+03   \n",
       "32              GEL            4.800000e+03   \n",
       "33           $CHINU            9.999990e+05   \n",
       "34            PAPER            6.969000e+03   \n",
       "35              UKG            6.000000e+07   \n",
       "36              SPD            1.985000e+03   \n",
       "37            0xBTC            3.742460e+02   \n",
       "38             DETF            1.000000e+03   \n",
       "39              GRC            1.848000e+05   \n",
       "83           NVIDIA            4.385674e+13   \n",
       "84              CRO            4.357822e+02   \n",
       "85              MGH            3.000000e+04   \n",
       "143             JEX            1.955000e+03   \n",
       "129            MNET            1.545750e+03   \n",
       "130           alUSD            1.010000e+03   \n",
       "132             RFR            2.123764e+03   \n",
       "133             NOW            1.500000e+02   \n",
       "134             GAO            1.000000e+03   \n",
       "135            RNTB            1.000000e+05   \n",
       "136             UDF            8.000000e+10   \n",
       "137             HEX            3.757500e+03   \n",
       "138             ESD            8.148599e+01   \n",
       "139             OTB            1.700000e+02   \n",
       "140             LIX            1.700000e+01   \n",
       "142         DRYDOGE            1.823949e+06   \n",
       "144           GUILD            6.386902e+02   \n",
       "127           SARCO            1.000000e+01   \n",
       "145          PICKLE            4.086533e+00   \n",
       "147             RND            4.536000e+08   \n",
       "148            RAZE            5.000000e+02   \n",
       "149             XNN            5.212566e+02   \n",
       "150            ZEON            2.700000e+01   \n",
       "151          TQUEEN            5.308842e+11   \n",
       "152           LEEDO            1.000000e+02   \n",
       "153           TUBE2            1.000000e+00   \n",
       "154            DOOR            1.000000e+05   \n",
       "156             UBT            1.000000e+02   \n",
       "157              BT            1.000000e+05   \n",
       "158           BYTES            5.000000e+00   \n",
       "128            WBNB            5.000000e-02   \n",
       "125            ECZZ            1.000000e+05   \n",
       "86            Coval            3.486057e+02   \n",
       "103           SUPRA            5.000000e+07   \n",
       "88               MM            1.200000e+02   \n",
       "90             eBay            4.836176e+09   \n",
       "91              UNT            2.000000e+03   \n",
       "92             VOLT            4.073034e+17   \n",
       "93              SLM            3.000000e+03   \n",
       "95              UFO            1.000000e+02   \n",
       "96              DOE            1.548514e+06   \n",
       "98            ZADDY            7.768104e+12   \n",
       "99              SOS            1.845382e+08   \n",
       "100           BOOTY            6.900000e-01   \n",
       "101       FloMoCoin            1.000000e+06   \n",
       "102             GER            5.000000e+00   \n",
       "104            CHAI            5.500000e+01   \n",
       "124          ARTERA            1.000000e+07   \n",
       "105            CAPS            1.100000e+05   \n",
       "107               Ͼ            1.000000e+00   \n",
       "108             BED            2.000000e+00   \n",
       "109             UAD            6.500000e+11   \n",
       "115            MORK            6.800300e+00   \n",
       "117             PNT            1.000000e+04   \n",
       "118            Porn            5.217516e+07   \n",
       "119           Laika            3.286583e+03   \n",
       "120            BOGE            1.190349e+08   \n",
       "121             UCD            5.000000e+09   \n",
       "122            HOGE            9.799902e+04   \n",
       "123              MT            1.128000e+03   \n",
       "281             HOP            4.268696e+02   \n",
       "\n",
       "     Total Amount (USD value at donation time)  \n",
       "1                                  22545519.85  \n",
       "0                                  19621510.77  \n",
       "3                                   7750877.78  \n",
       "2                                   1203278.16  \n",
       "4                                   1073198.30  \n",
       "20                                    32917.87  \n",
       "126                                   11931.15  \n",
       "111                                   11653.12  \n",
       "75                                     4559.00  \n",
       "76                                     3318.61  \n",
       "73                                     2103.43  \n",
       "30                                     1595.60  \n",
       "21                                     1413.02  \n",
       "89                                     1304.95  \n",
       "57                                     1180.65  \n",
       "74                                      813.26  \n",
       "116                                     614.25  \n",
       "6                                       578.40  \n",
       "44                                      508.30  \n",
       "244                                     500.00  \n",
       "106                                     433.02  \n",
       "155                                     357.88  \n",
       "97                                      285.30  \n",
       "113                                     257.48  \n",
       "72                                      254.38  \n",
       "258                                     242.30  \n",
       "94                                      229.27  \n",
       "67                                      158.91  \n",
       "162                                     155.81  \n",
       "69                                      104.14  \n",
       "41                                       97.31  \n",
       "64                                       96.40  \n",
       "8                                        77.04  \n",
       "173                                      61.20  \n",
       "112                                      44.55  \n",
       "87                                       38.66  \n",
       "9                                        29.78  \n",
       "190                                      27.13  \n",
       "110                                      24.53  \n",
       "131                                      15.97  \n",
       "197                                      15.66  \n",
       "175                                      13.90  \n",
       "237                                      13.51  \n",
       "174                                      11.14  \n",
       "195                                      11.10  \n",
       "198                                      10.14  \n",
       "25                                       10.06  \n",
       "114                                      10.01  \n",
       "163                                       6.31  \n",
       "18                                        3.83  \n",
       "146                                       1.93  \n",
       "50                                        0.99  \n",
       "187                                       0.87  \n",
       "26                                        0.83  \n",
       "199                                       0.40  \n",
       "278                                       0.00  \n",
       "208                                       0.00  \n",
       "207                                       0.00  \n",
       "193                                       0.00  \n",
       "206                                       0.00  \n",
       "205                                       0.00  \n",
       "194                                       0.00  \n",
       "204                                       0.00  \n",
       "276                                       0.00  \n",
       "196                                       0.00  \n",
       "203                                       0.00  \n",
       "202                                       0.00  \n",
       "200                                       0.00  \n",
       "277                                       0.00  \n",
       "201                                       0.00  \n",
       "192                                       0.00  \n",
       "264                                       0.00  \n",
       "191                                       0.00  \n",
       "177                                       0.00  \n",
       "164                                       0.00  \n",
       "165                                       0.00  \n",
       "166                                       0.00  \n",
       "280                                       0.00  \n",
       "167                                       0.00  \n",
       "168                                       0.00  \n",
       "169                                       0.00  \n",
       "170                                       0.00  \n",
       "171                                       0.00  \n",
       "172                                       0.00  \n",
       "176                                       0.00  \n",
       "178                                       0.00  \n",
       "189                                       0.00  \n",
       "279                                       0.00  \n",
       "179                                       0.00  \n",
       "180                                       0.00  \n",
       "181                                       0.00  \n",
       "182                                       0.00  \n",
       "183                                       0.00  \n",
       "184                                       0.00  \n",
       "185                                       0.00  \n",
       "186                                       0.00  \n",
       "210                                       0.00  \n",
       "188                                       0.00  \n",
       "209                                       0.00  \n",
       "214                                       0.00  \n",
       "211                                       0.00  \n",
       "234                                       0.00  \n",
       "236                                       0.00  \n",
       "238                                       0.00  \n",
       "239                                       0.00  \n",
       "240                                       0.00  \n",
       "267                                       0.00  \n",
       "241                                       0.00  \n",
       "242                                       0.00  \n",
       "243                                       0.00  \n",
       "245                                       0.00  \n",
       "246                                       0.00  \n",
       "247                                       0.00  \n",
       "248                                       0.00  \n",
       "249                                       0.00  \n",
       "250                                       0.00  \n",
       "251                                       0.00  \n",
       "252                                       0.00  \n",
       "253                                       0.00  \n",
       "254                                       0.00  \n",
       "255                                       0.00  \n",
       "256                                       0.00  \n",
       "257                                       0.00  \n",
       "266                                       0.00  \n",
       "259                                       0.00  \n",
       "260                                       0.00  \n",
       "261                                       0.00  \n",
       "262                                       0.00  \n",
       "263                                       0.00  \n",
       "235                                       0.00  \n",
       "233                                       0.00  \n",
       "212                                       0.00  \n",
       "268                                       0.00  \n",
       "275                                       0.00  \n",
       "213                                       0.00  \n",
       "265                                       0.00  \n",
       "274                                       0.00  \n",
       "215                                       0.00  \n",
       "216                                       0.00  \n",
       "217                                       0.00  \n",
       "218                                       0.00  \n",
       "273                                       0.00  \n",
       "219                                       0.00  \n",
       "220                                       0.00  \n",
       "221                                       0.00  \n",
       "222                                       0.00  \n",
       "223                                       0.00  \n",
       "224                                       0.00  \n",
       "225                                       0.00  \n",
       "161                                       0.00  \n",
       "227                                       0.00  \n",
       "228                                       0.00  \n",
       "229                                       0.00  \n",
       "272                                       0.00  \n",
       "271                                       0.00  \n",
       "270                                       0.00  \n",
       "269                                       0.00  \n",
       "230                                       0.00  \n",
       "231                                       0.00  \n",
       "232                                       0.00  \n",
       "226                                       0.00  \n",
       "141                                       0.00  \n",
       "160                                       0.00  \n",
       "159                                       0.00  \n",
       "46                                        0.00  \n",
       "47                                        0.00  \n",
       "48                                        0.00  \n",
       "49                                        0.00  \n",
       "51                                        0.00  \n",
       "52                                        0.00  \n",
       "53                                        0.00  \n",
       "54                                        0.00  \n",
       "55                                        0.00  \n",
       "56                                        0.00  \n",
       "58                                        0.00  \n",
       "59                                        0.00  \n",
       "60                                        0.00  \n",
       "61                                        0.00  \n",
       "62                                        0.00  \n",
       "63                                        0.00  \n",
       "65                                        0.00  \n",
       "66                                        0.00  \n",
       "68                                        0.00  \n",
       "70                                        0.00  \n",
       "71                                        0.00  \n",
       "77                                        0.00  \n",
       "78                                        0.00  \n",
       "79                                        0.00  \n",
       "80                                        0.00  \n",
       "81                                        0.00  \n",
       "82                                        0.00  \n",
       "45                                        0.00  \n",
       "43                                        0.00  \n",
       "42                                        0.00  \n",
       "23                                        0.00  \n",
       "5                                         0.00  \n",
       "7                                         0.00  \n",
       "10                                        0.00  \n",
       "11                                        0.00  \n",
       "12                                        0.00  \n",
       "13                                        0.00  \n",
       "14                                        0.00  \n",
       "15                                        0.00  \n",
       "16                                        0.00  \n",
       "17                                        0.00  \n",
       "19                                        0.00  \n",
       "22                                        0.00  \n",
       "24                                        0.00  \n",
       "40                                        0.00  \n",
       "27                                        0.00  \n",
       "28                                        0.00  \n",
       "29                                        0.00  \n",
       "31                                        0.00  \n",
       "32                                        0.00  \n",
       "33                                        0.00  \n",
       "34                                        0.00  \n",
       "35                                        0.00  \n",
       "36                                        0.00  \n",
       "37                                        0.00  \n",
       "38                                        0.00  \n",
       "39                                        0.00  \n",
       "83                                        0.00  \n",
       "84                                        0.00  \n",
       "85                                        0.00  \n",
       "143                                       0.00  \n",
       "129                                       0.00  \n",
       "130                                       0.00  \n",
       "132                                       0.00  \n",
       "133                                       0.00  \n",
       "134                                       0.00  \n",
       "135                                       0.00  \n",
       "136                                       0.00  \n",
       "137                                       0.00  \n",
       "138                                       0.00  \n",
       "139                                       0.00  \n",
       "140                                       0.00  \n",
       "142                                       0.00  \n",
       "144                                       0.00  \n",
       "127                                       0.00  \n",
       "145                                       0.00  \n",
       "147                                       0.00  \n",
       "148                                       0.00  \n",
       "149                                       0.00  \n",
       "150                                       0.00  \n",
       "151                                       0.00  \n",
       "152                                       0.00  \n",
       "153                                       0.00  \n",
       "154                                       0.00  \n",
       "156                                       0.00  \n",
       "157                                       0.00  \n",
       "158                                       0.00  \n",
       "128                                       0.00  \n",
       "125                                       0.00  \n",
       "86                                        0.00  \n",
       "103                                       0.00  \n",
       "88                                        0.00  \n",
       "90                                        0.00  \n",
       "91                                        0.00  \n",
       "92                                        0.00  \n",
       "93                                        0.00  \n",
       "95                                        0.00  \n",
       "96                                        0.00  \n",
       "98                                        0.00  \n",
       "99                                        0.00  \n",
       "100                                       0.00  \n",
       "101                                       0.00  \n",
       "102                                       0.00  \n",
       "104                                       0.00  \n",
       "124                                       0.00  \n",
       "105                                       0.00  \n",
       "107                                       0.00  \n",
       "108                                       0.00  \n",
       "109                                       0.00  \n",
       "115                                       0.00  \n",
       "117                                       0.00  \n",
       "118                                       0.00  \n",
       "119                                       0.00  \n",
       "120                                       0.00  \n",
       "121                                       0.00  \n",
       "122                                       0.00  \n",
       "123                                       0.00  \n",
       "281                                       0.00  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_results = pd.DataFrame(total_Donations).sort_values(by=[2], ascending=False)\n",
    "final_results.rename(columns = {0:'Ticker', 1:'Total Amount (nominal)', 2:'Total Amount (USD value at donation time)'}, inplace = True)\n",
    "pd.set_option(\"display.max_rows\", None, \"display.max_columns\", None)\n",
    "final_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Grouped into 4\n",
    "\n",
    "grouped_results = []\n",
    "\n",
    "#Filters\n",
    "\n",
    "Stables_filter = ['USDC','DAI','USDT','USDP']\n",
    "Remaining_filter = ['USDC','DAI','USDT','USDP','BTC','ETH']\n",
    "\n",
    "\n",
    "#BTC:\n",
    "\n",
    "BTC_Nom = final_results.loc[final_results['Ticker'] == 'BTC', 'Total Amount (nominal)'].sum()\n",
    "BTC_Spot = final_results.loc[final_results['Ticker'] == 'BTC', 'Total Amount (USD value at donation time)'].sum()\n",
    "\n",
    "grouped_results.append(['BTC', BTC_Nom, BTC_Spot])\n",
    "\n",
    "#ETH:\n",
    "\n",
    "ETH_Nom = final_results.loc[final_results['Ticker'] == 'ETH', 'Total Amount (nominal)'].sum()\n",
    "ETH_Spot = final_results.loc[final_results['Ticker'] == 'ETH', 'Total Amount (USD value at donation time)'].sum()\n",
    "\n",
    "grouped_results.append(['ETH', ETH_Nom, ETH_Spot])\n",
    "\n",
    "\n",
    "#Stables:\n",
    "\n",
    "Stables_df = final_results[final_results['Ticker'].isin(Stables_filter)]\n",
    "\n",
    "\n",
    "Stables_Nom = Stables_df['Total Amount (nominal)'].sum()\n",
    "Stables_Spot = Stables_df['Total Amount (nominal)'].sum()\n",
    "\n",
    "grouped_results.append(['Stablecoins', Stables_Nom, Stables_Spot])\n",
    "\n",
    "\n",
    "#Remaining\n",
    "\n",
    "Remaining_df = final_results[~final_results['Ticker'].isin(Remaining_filter)]\n",
    "\n",
    "\n",
    "Remaining_Nom = Remaining_df['Total Amount (nominal)'].sum()\n",
    "Remaining_Spot = Remaining_df['Total Amount (USD value at donation time)'].sum()\n",
    "\n",
    "grouped_results.append(['Others', Remaining_Nom, Remaining_Spot])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "Stables_df = final_results[final_results['Ticker'].isin(Stables_filter)]\n",
    "Remaining_df = final_results[~final_results['Ticker'].isin(Remaining_filter)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Ticker</th>\n",
       "      <th>Total Amount (nominal)</th>\n",
       "      <th>Total Amount (USD value at donation time)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>USDT</td>\n",
       "      <td>7.750878e+06</td>\n",
       "      <td>7750877.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>USDC</td>\n",
       "      <td>1.203278e+06</td>\n",
       "      <td>1203278.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DAI</td>\n",
       "      <td>1.073198e+06</td>\n",
       "      <td>1073198.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>USDP</td>\n",
       "      <td>5.000000e+02</td>\n",
       "      <td>500.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Ticker  Total Amount (nominal)  Total Amount (USD value at donation time)\n",
       "3     USDT            7.750878e+06                                 7750877.78\n",
       "2     USDC            1.203278e+06                                 1203278.16\n",
       "4      DAI            1.073198e+06                                 1073198.30\n",
       "244   USDP            5.000000e+02                                     500.00"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Stables_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Asset</th>\n",
       "      <th>Total Amount (nominal)</th>\n",
       "      <th>Total Amount (USD Value at Donation Time)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ETH</td>\n",
       "      <td>7735.26310</td>\n",
       "      <td>22578437.72000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BTC</td>\n",
       "      <td>479.91098</td>\n",
       "      <td>19621666.58000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Stablecoins</td>\n",
       "      <td>10027854.19544</td>\n",
       "      <td>10027854.19544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Others</td>\n",
       "      <td>11579208923731619542357098500868790785326998466...</td>\n",
       "      <td>44519.67000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Asset                             Total Amount (nominal)  \\\n",
       "0          ETH                                         7735.26310   \n",
       "1          BTC                                          479.91098   \n",
       "2  Stablecoins                                     10027854.19544   \n",
       "3       Others 11579208923731619542357098500868790785326998466...   \n",
       "\n",
       "   Total Amount (USD Value at Donation Time)  \n",
       "0                             22578437.72000  \n",
       "1                             19621666.58000  \n",
       "2                             10027854.19544  \n",
       "3                                44519.67000  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_results_df = pd.DataFrame(grouped_results).sort_values(by=[2], ascending=False)\n",
    "grouped_results_df.rename(columns = {0:'Asset', 1:'Total Amount (nominal)', 2:'Total Amount (USD Value at Donation Time)'}, inplace = True)\n",
    "\n",
    "pd.set_option('display.float_format', lambda x: '%.5f' % x)\n",
    "\n",
    "grouped_results_df = grouped_results_df.reset_index(drop=True)\n",
    "\n",
    "\n",
    "grouped_results_df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "findfont: Font family ['Helvetica'] not found. Falling back to DejaVu Sans.\n",
      "findfont: Font family ['Helvetica'] not found. Falling back to DejaVu Sans.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Asset</th>        <th class=\"col_heading level0 col1\" >Total Amount (nominal)</th>        <th class=\"col_heading level0 col2\" >Total Amount (USD Value at Donation Time)</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row0_col0\" class=\"data row0 col0\" >ETH</td>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row0_col1\" class=\"data row0 col1\" >7,735.26</td>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row0_col2\" class=\"data row0 col2\" >$22,578,437.72</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row1_col0\" class=\"data row1 col0\" >BTC</td>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row1_col1\" class=\"data row1 col1\" >479.91</td>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row1_col2\" class=\"data row1 col2\" >$19,621,666.58</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row2_col0\" class=\"data row2 col0\" >Stablecoins</td>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row2_col1\" class=\"data row2 col1\" >10,027,854.20</td>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row2_col2\" class=\"data row2 col2\" >$10,027,854.20</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row3_col0\" class=\"data row3 col0\" >Others</td>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row3_col1\" class=\"data row3 col1\" >115,792,089,237,316,195,423,570,985,008,687,907,853,269,984,665,640,564,039,457,584,007,913,129,639,936.00</td>\n",
       "                        <td id=\"T_441381ac_ee21_11ec_8101_e0d4e8ea6d47row3_col2\" class=\"data row3 col2\" >$44,519.67</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1a802665df0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "styled_Dataframe = grouped_results_df\n",
    "\n",
    "\n",
    "styled_Dataframe = styled_Dataframe.style.format({'Total Amount (USD Value at Donation Time)':'${0:,.2f}', 'Total Amount (nominal)':'{0:,.2f}' })\n",
    "dfi.export(styled_Dataframe,\"Top4.png\", table_conversion='matplotlib')\n",
    "styled_Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = 'ETH', 'BTC', 'Stablecoins', 'Other'\n",
    "sizes = grouped_results_df['Total Amount (USD Value at Donation Time)']\n",
    "\n",
    "chart_ETH = float(grouped_results_df['Total Amount (USD Value at Donation Time)'][0])\n",
    "chart_BTC = float(grouped_results_df['Total Amount (USD Value at Donation Time)'][1])\n",
    "chart_Stab = float(grouped_results_df['Total Amount (USD Value at Donation Time)'][2])\n",
    "chart_Rem = float(grouped_results_df['Total Amount (USD Value at Donation Time)'][3])\n",
    "\n",
    "chartinput= [chart_ETH,chart_BTC,chart_Stab,chart_Rem]\n",
    "\n",
    "colors = ['#F75F3B', 'gold', 'mediumseagreen','cornflowerblue']\n",
    "\n",
    "\n",
    "explode = (0.1, 0.1, 0.1, 0.1)\n",
    "\n",
    "textprops={\"color\":\"white\",\"weight\":\"bold\"}  \n",
    "\n",
    "\n",
    "fig1, ax1 = plt.subplots(figsize=(4, 4), dpi=200)\n",
    "ax1.pie(sizes, explode=explode, labels=labels, colors=colors , autopct='%1.1f%%',\n",
    "        shadow=False, startangle=90, textprops = textprops )\n",
    "ax1.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "plt.legend(title = \"Variation Rate\")\n",
    "\n",
    "plt.legend(bbox_to_anchor=(1.45, 1.45 ), loc='upper right', borderaxespad=0, fontsize=8)\n",
    "plt.title\n",
    "plt.show()\n",
    "\n",
    "\n",
    "#grouped_results_df.plot(kind='pie', y='Total Amount (USD Value at Donation Time)', autopct='%1.0f%%',colors = ['gold', 'lightgrey', 'mediumseagreen','cornflowerblue'],title='Cummulated Amount donated to Addresses know to be belonging to Ukraine (valued in USD at Donation Time)',explode = explode)"
   ]
  }
 ],
 "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}