aocd/rotki_assets.ipynb

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    "# Assets in the rotki database\n",
    "\n",
    "`rotki` ([rotki.com](https://rotki.com)) is a portfolio management, analytics and accounting application that protects your privacy. It is a local app, the code is open source and available at [github](https://github.com/rotki/rotki).\n",
    "\n",
    "At rotki, each instance keeps a database that can be found [here](https://github.com/rotki/rotki/blob/develop/rotkehlchen/data/global.db) called `global.db`. It contains information about contracts and assets that can be used by the user when the app is used for the first time. If the app detects that the DB is missing we copy the packaged one so the user has acccess to all this information from the start. We update it periodically with more assets and also the user can add/edit/delete assets and other information from its local copy.\n",
    "\n",
    "As part of the Advent of crypto Data we are releasing CSV files from this database compiled with all data up to version 1.31.1 of the rotki app to be easily used by others in their apps along with a script to generate them from any version after the one mentioned.\n",
    "\n",
    "This notebook is a small analysis on the different assets present at the rotki packaged database. This database contains information related to assets in three tables those being\n",
    "\n",
    "- assets\n",
    "- common_asset_details\n",
    "- evm_tokens\n",
    "\n",
    "The division of the information in those tables follows a design decision to enable the support of assets from many different chains while supporting performant queries in the database and easy upgradability\n",
    "\n",
    "The database has been exported to four different csv files:\n",
    "\n",
    "- `evm_tokens.csv` contains information only about evm tokens from the database\n",
    "- `other_assets.csv` contains information for assets that have their own chain and/or chains that are not supported in rotki directly yet\n",
    "- `asset_collections.csv` contains information about assets so that we can make groups out of them (say all instances of USDC across chains)\n",
    "- `multiassets_mappings.csv`contains mapping of assets to the groups they belong to\n",
    "\n",
    "\n",
    "## Table of contents:\n",
    "* [Analysis of the EVM tokens in the database](#evm-tokens)\n",
    "    * [Reading the information from the CSV](#reading-1)\n",
    "    * [Assets by chain](#by-chain)\n",
    "    * [Deploying time of the tokens](#deploying)\n",
    "    * [Tokens with identifiers for oracles](#oracles-1)\n",
    "    * [Protocol column](#protocol)\n",
    "* [Other assets](#other-assets)\n",
    "    * [Reading the dataset](#reading-2)\n",
    "    * [Oracle distribution of the assets](#dist-oracles-2)\n",
    "* [Collections of assets](#collections)\n",
    "* [Conclusion](#conclusion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "396e88da-1886-42af-81c8-b8507e63e1c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "\n",
    "import polars as pl\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4ba512b-888e-45b1-b699-3d880986f130",
   "metadata": {},
   "source": [
    "## Analysis of the EVM tokens in the database <a id=\"evm-tokens\"></a>\n",
    "\n",
    "The database contains different information for assets. In the case of EVM tokens we have extracted the information that is commonly used in dapps. We provide the chain id, name, symbol, the number of decimals and a timestamp for when the contract was deployed or it started to have price information.\n",
    "\n",
    "For identifiers we use the CAIPs format, more information for which is available here https://chainagnostic.org/CAIPs/caip-2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c89c7d88-791c-4273-8391-cddfc81810e1",
   "metadata": {},
   "source": [
    "### Reading the information from the CSV <a id=\"reading-1\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "515402c8-1285-45fc-a3a0-6aaabe59569d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pl.read_csv('evm_tokens.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0926d09b-9be3-4a49-bae6-b4e648cc157e",
   "metadata": {},
   "source": [
    "the started field is provided as an integer. We will cast it to a datetime object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7a4adc44-84b9-4ec8-9f71-db4c9ff11181",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.with_columns(pl.from_epoch('started', time_unit=\"s\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6e39d51-409e-4425-9094-ca9023ceaed4",
   "metadata": {},
   "source": [
    "the total number of tokens in the dataset is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9344f2d4-08bb-4669-bea5-77cc506b5378",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4494"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6f848f99-5a87-4a7a-a031-4cc904c5fdfc",
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    {
     "data": {
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       "<div><style>\n",
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       "</style>\n",
       "<small>shape: (5, 10)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>identifier</th><th>address</th><th>chain</th><th>name</th><th>symbol</th><th>decimals</th><th>coingecko</th><th>cryptocompare</th><th>started</th><th>protocol</th></tr><tr><td>str</td><td>str</td><td>i64</td><td>str</td><td>str</td><td>i64</td><td>str</td><td>str</td><td>datetime[μs]</td><td>str</td></tr></thead><tbody><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xB6eD7644C694…</td><td>1</td><td>&quot;0xBitcoin&quot;</td><td>&quot;0xBTC&quot;</td><td>8</td><td>&quot;oxbitcoin&quot;</td><td>&quot;0XBTC&quot;</td><td>2018-02-06 00:00:00</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x111111111117…</td><td>1</td><td>&quot;1INCH Token&quot;</td><td>&quot;1INCH&quot;</td><td>18</td><td>&quot;1inch&quot;</td><td>null</td><td>2020-12-23 18:13:31</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x0F72714B35a3…</td><td>1</td><td>&quot;1SG&quot;</td><td>&quot;1SG&quot;</td><td>18</td><td>&quot;1sg&quot;</td><td>null</td><td>2018-12-25 00:00:00</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xAf30D2a7E90d…</td><td>1</td><td>&quot;FirstBlood&quot;</td><td>&quot;1ST&quot;</td><td>18</td><td>&quot;first-blood&quot;</td><td>null</td><td>2016-07-09 00:00:00</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xfDBc1aDc26F0…</td><td>1</td><td>&quot;1World&quot;</td><td>&quot;1WO&quot;</td><td>8</td><td>&quot;1world&quot;</td><td>null</td><td>2017-11-30 00:00:00</td><td>null</td></tr></tbody></table></div>"
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       "shape: (5, 10)\n",
       "┌────────────┬────────────┬───────┬────────────┬───┬────────────┬───────────┬───────────┬──────────┐\n",
       "│ identifier ┆ address    ┆ chain ┆ name       ┆ … ┆ coingecko  ┆ cryptocom ┆ started   ┆ protocol │\n",
       "│ ---        ┆ ---        ┆ ---   ┆ ---        ┆   ┆ ---        ┆ pare      ┆ ---       ┆ ---      │\n",
       "│ str        ┆ str        ┆ i64   ┆ str        ┆   ┆ str        ┆ ---       ┆ datetime[ ┆ str      │\n",
       "│            ┆            ┆       ┆            ┆   ┆            ┆ str       ┆ μs]       ┆          │\n",
       "╞════════════╪════════════╪═══════╪════════════╪═══╪════════════╪═══════════╪═══════════╪══════════╡\n",
       "│ eip155:1/e ┆ 0xB6eD7644 ┆ 1     ┆ 0xBitcoin  ┆ … ┆ oxbitcoin  ┆ 0XBTC     ┆ 2018-02-0 ┆ null     │\n",
       "│ rc20:0xB6e ┆ C69416d67B ┆       ┆            ┆   ┆            ┆           ┆ 6         ┆          │\n",
       "│ D7644C6941 ┆ 522e20bC29 ┆       ┆            ┆   ┆            ┆           ┆ 00:00:00  ┆          │\n",
       "│ 6d…        ┆ 4A…        ┆       ┆            ┆   ┆            ┆           ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0x11111111 ┆ 1     ┆ 1INCH      ┆ … ┆ 1inch      ┆ null      ┆ 2020-12-2 ┆ null     │\n",
       "│ rc20:0x111 ┆ 1117dC0aa7 ┆       ┆ Token      ┆   ┆            ┆           ┆ 3         ┆          │\n",
       "│ 111111117d ┆ 8b770fA6A7 ┆       ┆            ┆   ┆            ┆           ┆ 18:13:31  ┆          │\n",
       "│ C0…        ┆ 38…        ┆       ┆            ┆   ┆            ┆           ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0x0F72714B ┆ 1     ┆ 1SG        ┆ … ┆ 1sg        ┆ null      ┆ 2018-12-2 ┆ null     │\n",
       "│ rc20:0x0F7 ┆ 35a366285D ┆       ┆            ┆   ┆            ┆           ┆ 5         ┆          │\n",
       "│ 2714B35a36 ┆ f85886A2eE ┆       ┆            ┆   ┆            ┆           ┆ 00:00:00  ┆          │\n",
       "│ 62…        ┆ 17…        ┆       ┆            ┆   ┆            ┆           ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0xAf30D2a7 ┆ 1     ┆ FirstBlood ┆ … ┆ first-bloo ┆ null      ┆ 2016-07-0 ┆ null     │\n",
       "│ rc20:0xAf3 ┆ E90d7DC361 ┆       ┆            ┆   ┆ d          ┆           ┆ 9         ┆          │\n",
       "│ 0D2a7E90d7 ┆ c8C4585e9B ┆       ┆            ┆   ┆            ┆           ┆ 00:00:00  ┆          │\n",
       "│ DC…        ┆ B7…        ┆       ┆            ┆   ┆            ┆           ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0xfDBc1aDc ┆ 1     ┆ 1World     ┆ … ┆ 1world     ┆ null      ┆ 2017-11-3 ┆ null     │\n",
       "│ rc20:0xfDB ┆ 26F0F8f860 ┆       ┆            ┆   ┆            ┆           ┆ 0         ┆          │\n",
       "│ c1aDc26F0F ┆ 6a5d63b7D3 ┆       ┆            ┆   ┆            ┆           ┆ 00:00:00  ┆          │\n",
       "│ 8f…        ┆ a3…        ┆       ┆            ┆   ┆            ┆           ┆           ┆          │\n",
       "└────────────┴────────────┴───────┴────────────┴───┴────────────┴───────────┴───────────┴──────────┘"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0c03c41-d2de-4fe3-a5cc-3b04424a5255",
   "metadata": {},
   "source": [
    "### Assets by chain <a id=\"by-chain\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05fd359a-3f3a-4b21-b69a-294458ba827c",
   "metadata": {},
   "source": [
    "this asset database has a long history. Since for a long time, rotki supported only ethereum mainnet, most of the tokens that we have in it are ethereum tokens. There are some evm compatible chains for which we started to add assets recently like Celo (42220) that have only one asset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "20d3498f-ce72-4b53-b725-d173ed1c8f1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "counts = df['chain'].value_counts().rename({'counts': 'count'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "792863c8-2950-456d-8a5e-4394a0169ae4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Number of tokens per chain'}, xlabel='chain', ylabel='count'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.barplot(x='chain', y='count', data=counts)\n",
    "ax.set_title('Number of tokens per chain')\n",
    "ax.bar_label(ax.containers[0])\n",
    "ax"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbd2e748-ac74-4385-84bc-19e97e729633",
   "metadata": {},
   "source": [
    "as we can see the dataset has mostly ethereum tokens but some of the most important ones in other chains are also present. The chain with most tokens apart from mainnet is BSC, follow by polygon and optimism."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b84c3eb0-d4ec-4a82-890f-cb8293f9213b",
   "metadata": {},
   "source": [
    "### Deploying time of the tokens <a id=\"deploying\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e7d1d88-c07f-4f2d-8c12-5a430deea5a0",
   "metadata": {},
   "source": [
    "let's now check the distribution of tokens over time according to their started field. The dataset is missing information for some assets in this field so first let's remove those rows that have a null value in this column. The total number of such rows is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e52f56cf-4004-44ca-ba12-d4d3e5fb4a9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1402"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df) - len(df.filter(~pl.all_horizontal(pl.col('started').is_null())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8b9d0f87-9dbe-4b34-beab-ae08ccec54b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "deploying_time = df.filter(\n",
    "   ~pl.all_horizontal(pl.col('started').is_null())\n",
    ").sort('started').group_by_dynamic('started', every='1mo').agg(pl.col('identifier').count()).rename({'identifier': 'count'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "84e0932f-392d-46e7-8ce4-fc9b7358eb6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (5, 2)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>started</th><th>count</th></tr><tr><td>datetime[μs]</td><td>u32</td></tr></thead><tbody><tr><td>1970-01-01 00:00:00</td><td>37</td></tr><tr><td>2014-01-01 00:00:00</td><td>1</td></tr><tr><td>2014-06-01 00:00:00</td><td>1</td></tr><tr><td>2014-11-01 00:00:00</td><td>1</td></tr><tr><td>2015-05-01 00:00:00</td><td>1</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (5, 2)\n",
       "┌─────────────────────┬───────┐\n",
       "│ started             ┆ count │\n",
       "│ ---                 ┆ ---   │\n",
       "│ datetime[μs]        ┆ u32   │\n",
       "╞═════════════════════╪═══════╡\n",
       "│ 1970-01-01 00:00:00 ┆ 37    │\n",
       "│ 2014-01-01 00:00:00 ┆ 1     │\n",
       "│ 2014-06-01 00:00:00 ┆ 1     │\n",
       "│ 2014-11-01 00:00:00 ┆ 1     │\n",
       "│ 2015-05-01 00:00:00 ┆ 1     │\n",
       "└─────────────────────┴───────┘"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deploying_time.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e971a4f1-af4b-4906-b030-9f5b124e7939",
   "metadata": {},
   "source": [
    "As we can see there is some innacuracy in the data since 37 tokens have a timestamp of 0. Also there are a few tokens existing before the launch of ethereum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "169472bf-4cf1-42fa-912e-e16f526c5687",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (41, 10)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>identifier</th><th>address</th><th>chain</th><th>name</th><th>symbol</th><th>decimals</th><th>coingecko</th><th>cryptocompare</th><th>started</th><th>protocol</th></tr><tr><td>str</td><td>str</td><td>i64</td><td>str</td><td>str</td><td>i64</td><td>str</td><td>str</td><td>datetime[μs]</td><td>str</td></tr></thead><tbody><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x1bEe44cb0e6C…</td><td>1</td><td>&quot;$ amcoc.xyz&quot;</td><td>&quot;Visit https://…</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x4ACbEAb5fFCb…</td><td>1</td><td>&quot;Adomy.site&quot;</td><td>&quot;Bonus. Visit h…</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x520b9A2A38ca…</td><td>1</td><td>&quot;$ ETH 2.0&quot;</td><td>&quot;https://eth2.t…</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x54718b68d35B…</td><td>1</td><td>&quot;$ crLink.app&quot;</td><td>&quot;Claim rewards …</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x8d18a7D965bb…</td><td>1</td><td>&quot;$ fdai.xyz&quot;</td><td>&quot;Visit https://…</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xa88ce09448bB…</td><td>1</td><td>&quot;MaticMerge.org…</td><td>&quot;MaticMerge.org…</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xB08070Bafc06…</td><td>1</td><td>&quot;$ abonus.site&quot;</td><td>&quot;880$ Visit htt…</td><td>0</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xDc09ef6bA2a1…</td><td>1</td><td>&quot;$ ETHGiftX.com…</td><td>&quot;$ Visit ETHGif…</td><td>0</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xF394ba49fdf6…</td><td>1</td><td>&quot;PepeAir.com&quot;</td><td>&quot;PepeAir.com&quot;</td><td>0</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0x14F2c84A58e0…</td><td>137</td><td>&quot;MATICSWAP.NET&quot;</td><td>&quot;MATICSWAP.NET&quot;</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0x1c30FAf5d5e1…</td><td>137</td><td>&quot;$ USDCpool.sit…</td><td>&quot;Claim USDC/WET…</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0x22e51BAe3f54…</td><td>137</td><td>&quot;LELX.io&quot;</td><td>&quot;LELX.io&quot;</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0xAd1E7503bBd9…</td><td>137</td><td>&quot;$ musd.tech&quot;</td><td>&quot;Reward Token. …</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0xaf6B1a3067Bb…</td><td>137</td><td>&quot;$ xBets.org&quot;</td><td>&quot;$ Free Claim a…</td><td>8</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0xcf68f02d7dD6…</td><td>137</td><td>&quot;GGBoxs.com&quot;</td><td>&quot;GGBoxs.com&quot;</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0xdC8Fa3FaB842…</td><td>137</td><td>&quot;Draf.io&quot;</td><td>&quot;Draf.io&quot;</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0xE2Ee00F49464…</td><td>137</td><td>&quot;$ USDCpool.sto…</td><td>&quot;Claim USDC/WET…</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0xE4fb1Bb84234…</td><td>137</td><td>&quot;Zepe.io&quot;</td><td>&quot;Zepe.io&quot;</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0xf2CA85B59224…</td><td>137</td><td>&quot;$ USDCpool.clo…</td><td>&quot;Claim USDC/WET…</td><td>18</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:137/erc…</td><td>&quot;0xf31CDB090d1D…</td><td>137</td><td>&quot;0Bets.io&quot;</td><td>&quot;0Bets.io&quot;</td><td>8</td><td>null</td><td>null</td><td>1970-01-01 00:00:00</td><td>&quot;spam&quot;</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x2e98A6804E4b…</td><td>1</td><td>&quot;Bela&quot;</td><td>&quot;BELA&quot;</td><td>18</td><td>&quot;belacoin&quot;</td><td>null</td><td>2014-01-01 00:00:00</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xdAC17F958D2e…</td><td>1</td><td>&quot;Tether&quot;</td><td>&quot;USDT&quot;</td><td>6</td><td>&quot;tether&quot;</td><td>null</td><td>2014-06-10 00:00:00</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x1985365e9f78…</td><td>1</td><td>&quot;Augur&quot;</td><td>&quot;REP&quot;</td><td>18</td><td>&quot;augur&quot;</td><td>null</td><td>2014-11-17 00:00:00</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xF67451Dc8421…</td><td>1</td><td>&quot;Gambit&quot;</td><td>&quot;GAM&quot;</td><td>8</td><td>null</td><td>null</td><td>2015-05-05 00:00:00</td><td>null</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (41, 10)\n",
       "┌────────────┬────────────┬───────┬────────────┬───┬───────────┬────────────┬───────────┬──────────┐\n",
       "│ identifier ┆ address    ┆ chain ┆ name       ┆ … ┆ coingecko ┆ cryptocomp ┆ started   ┆ protocol │\n",
       "│ ---        ┆ ---        ┆ ---   ┆ ---        ┆   ┆ ---       ┆ are        ┆ ---       ┆ ---      │\n",
       "│ str        ┆ str        ┆ i64   ┆ str        ┆   ┆ str       ┆ ---        ┆ datetime[ ┆ str      │\n",
       "│            ┆            ┆       ┆            ┆   ┆           ┆ str        ┆ μs]       ┆          │\n",
       "╞════════════╪════════════╪═══════╪════════════╪═══╪═══════════╪════════════╪═══════════╪══════════╡\n",
       "│ eip155:1/e ┆ 0x1bEe44cb ┆ 1     ┆ $          ┆ … ┆ null      ┆ null       ┆ 1970-01-0 ┆ spam     │\n",
       "│ rc20:0x1bE ┆ 0e6C0D7C8e ┆       ┆ amcoc.xyz  ┆   ┆           ┆            ┆ 1         ┆          │\n",
       "│ e44cb0e6C0 ┆ 5AA9ad21BD ┆       ┆            ┆   ┆           ┆            ┆ 00:00:00  ┆          │\n",
       "│ D7…        ┆ 5B…        ┆       ┆            ┆   ┆           ┆            ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0x4ACbEAb5 ┆ 1     ┆ Adomy.site ┆ … ┆ null      ┆ null       ┆ 1970-01-0 ┆ spam     │\n",
       "│ rc20:0x4AC ┆ fFCb02491a ┆       ┆            ┆   ┆           ┆            ┆ 1         ┆          │\n",
       "│ bEAb5fFCb0 ┆ a447F9dDb0 ┆       ┆            ┆   ┆           ┆            ┆ 00:00:00  ┆          │\n",
       "│ 24…        ┆ 20…        ┆       ┆            ┆   ┆           ┆            ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0x520b9A2A ┆ 1     ┆ $ ETH 2.0  ┆ … ┆ null      ┆ null       ┆ 1970-01-0 ┆ spam     │\n",
       "│ rc20:0x520 ┆ 38caD91B1d ┆       ┆            ┆   ┆           ┆            ┆ 1         ┆          │\n",
       "│ b9A2A38caD ┆ 698cBD40e7 ┆       ┆            ┆   ┆           ┆            ┆ 00:00:00  ┆          │\n",
       "│ 91…        ┆ e5…        ┆       ┆            ┆   ┆           ┆            ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0x54718b68 ┆ 1     ┆ $          ┆ … ┆ null      ┆ null       ┆ 1970-01-0 ┆ spam     │\n",
       "│ rc20:0x547 ┆ d35B9B0b19 ┆       ┆ crLink.app ┆   ┆           ┆            ┆ 1         ┆          │\n",
       "│ 18b68d35B9 ┆ 0FFc0D03B5 ┆       ┆            ┆   ┆           ┆            ┆ 00:00:00  ┆          │\n",
       "│ B0…        ┆ 7C…        ┆       ┆            ┆   ┆           ┆            ┆           ┆          │\n",
       "│ …          ┆ …          ┆ …     ┆ …          ┆ … ┆ …         ┆ …          ┆ …         ┆ …        │\n",
       "│ eip155:1/e ┆ 0x2e98A680 ┆ 1     ┆ Bela       ┆ … ┆ belacoin  ┆ null       ┆ 2014-01-0 ┆ null     │\n",
       "│ rc20:0x2e9 ┆ 4E4b6c832E ┆       ┆            ┆   ┆           ┆            ┆ 1         ┆          │\n",
       "│ 8A6804E4b6 ┆ D0ca876a94 ┆       ┆            ┆   ┆           ┆            ┆ 00:00:00  ┆          │\n",
       "│ c8…        ┆ 3a…        ┆       ┆            ┆   ┆           ┆            ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0xdAC17F95 ┆ 1     ┆ Tether     ┆ … ┆ tether    ┆ null       ┆ 2014-06-1 ┆ null     │\n",
       "│ rc20:0xdAC ┆ 8D2ee523a2 ┆       ┆            ┆   ┆           ┆            ┆ 0         ┆          │\n",
       "│ 17F958D2ee ┆ 2062069945 ┆       ┆            ┆   ┆           ┆            ┆ 00:00:00  ┆          │\n",
       "│ 52…        ┆ 97…        ┆       ┆            ┆   ┆           ┆            ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0x1985365e ┆ 1     ┆ Augur      ┆ … ┆ augur     ┆ null       ┆ 2014-11-1 ┆ null     │\n",
       "│ rc20:0x198 ┆ 9f78359a9B ┆       ┆            ┆   ┆           ┆            ┆ 7         ┆          │\n",
       "│ 5365e9f783 ┆ 6AD760e324 ┆       ┆            ┆   ┆           ┆            ┆ 00:00:00  ┆          │\n",
       "│ 59…        ┆ 12…        ┆       ┆            ┆   ┆           ┆            ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0xF67451Dc ┆ 1     ┆ Gambit     ┆ … ┆ null      ┆ null       ┆ 2015-05-0 ┆ null     │\n",
       "│ rc20:0xF67 ┆ 8421F0e0af ┆       ┆            ┆   ┆           ┆            ┆ 5         ┆          │\n",
       "│ 451Dc8421F ┆ EB52faa810 ┆       ┆            ┆   ┆           ┆            ┆ 00:00:00  ┆          │\n",
       "│ 0e…        ┆ 10…        ┆       ┆            ┆   ┆           ┆            ┆           ┆          │\n",
       "└────────────┴────────────┴───────┴────────────┴───┴───────────┴────────────┴───────────┴──────────┘"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.filter(\n",
    "   ~pl.all_horizontal(pl.col('started').is_null())\n",
    ").filter(pl.col('started').is_between(datetime.datetime(1970, 1, 1), datetime.datetime(2015, 7, 15))).sort('started')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80a3300d-4b2e-437f-96c7-517578a39026",
   "metadata": {},
   "source": [
    "The database also contains a blacklist of spam assets. Those are the ones marked with the spam protocol. rotki has an autodection system for spam and in addition keeps list at https://github.com/rotki/data/tree/develop/updates/spam_assets that gets pulled and updated with each new release.\n",
    "\n",
    "Let's show now a graph with the deployment times for the tokens that we have"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "49e61854-dd37-4e04-b634-3ba7d05be2f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Number of tokens deployed by month'}, xlabel='started', ylabel='count'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 5000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.barplot(x='started', y='count', data=deploying_time)\n",
    "ax.figure.set_size_inches(50,20)\n",
    "ax.set_title('Number of tokens deployed by month')\n",
    "ax.bar_label(ax.containers[0])\n",
    "plt.xticks(rotation=90)\n",
    "ax"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fc2aa68-fbe8-4b4c-9372-5e4a07cb1566",
   "metadata": {},
   "source": [
    "Run the next cell to save this graph to your system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ec97c968-483a-4583-b507-6e6ce59bc6f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = ax.get_figure()\n",
    "fig.savefig(\"out.png\", dpi=150, bbox_inches='tight') "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "574cc9f1-f02b-479d-9253-f2ea83019ff9",
   "metadata": {},
   "source": [
    "This graph is interesting because we can see that in the second half of 2017 there were a lof of deployments for tokens and the same happens from 2020 to 2022. The first peak happened for around 1 year and the second for 2 years. Also the second peak was more intensive in terms of listings than the first one."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b064fb35-ea0c-4c53-ac3e-6c408935dc85",
   "metadata": {},
   "source": [
    "### Tokens with identifiers for oracles <a id=\"oracles-1\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fa840b7-e818-4d52-bba5-d003f354ec2d",
   "metadata": {},
   "source": [
    "At rotki we query some prices form on-chain oracles but we also use external APIs like coingecko and cryptocompare to query current and historical prices. To make these queries we need to have the identifiers of the assets on those platforms. Let's check the distribution of tokens with coingecko ids and cryptocompare ids. There are assets that don't have either of them so lets first filter them out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a1e359b7-49d6-4996-96fe-703a2328464d",
   "metadata": {},
   "outputs": [],
   "source": [
    "api_oracles = df.filter(~pl.all_horizontal(pl.col('coingecko', 'cryptocompare').is_null()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "16b2a5c5-feff-4563-99e5-9235e73c3266",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (5, 10)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>identifier</th><th>address</th><th>chain</th><th>name</th><th>symbol</th><th>decimals</th><th>coingecko</th><th>cryptocompare</th><th>started</th><th>protocol</th></tr><tr><td>str</td><td>str</td><td>i64</td><td>str</td><td>str</td><td>i64</td><td>str</td><td>str</td><td>datetime[μs]</td><td>str</td></tr></thead><tbody><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xB6eD7644C694…</td><td>1</td><td>&quot;0xBitcoin&quot;</td><td>&quot;0xBTC&quot;</td><td>8</td><td>&quot;oxbitcoin&quot;</td><td>&quot;0XBTC&quot;</td><td>2018-02-06 00:00:00</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x111111111117…</td><td>1</td><td>&quot;1INCH Token&quot;</td><td>&quot;1INCH&quot;</td><td>18</td><td>&quot;1inch&quot;</td><td>null</td><td>2020-12-23 18:13:31</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0x0F72714B35a3…</td><td>1</td><td>&quot;1SG&quot;</td><td>&quot;1SG&quot;</td><td>18</td><td>&quot;1sg&quot;</td><td>null</td><td>2018-12-25 00:00:00</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xAf30D2a7E90d…</td><td>1</td><td>&quot;FirstBlood&quot;</td><td>&quot;1ST&quot;</td><td>18</td><td>&quot;first-blood&quot;</td><td>null</td><td>2016-07-09 00:00:00</td><td>null</td></tr><tr><td>&quot;eip155:1/erc20…</td><td>&quot;0xfDBc1aDc26F0…</td><td>1</td><td>&quot;1World&quot;</td><td>&quot;1WO&quot;</td><td>8</td><td>&quot;1world&quot;</td><td>null</td><td>2017-11-30 00:00:00</td><td>null</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (5, 10)\n",
       "┌────────────┬────────────┬───────┬────────────┬───┬────────────┬───────────┬───────────┬──────────┐\n",
       "│ identifier ┆ address    ┆ chain ┆ name       ┆ … ┆ coingecko  ┆ cryptocom ┆ started   ┆ protocol │\n",
       "│ ---        ┆ ---        ┆ ---   ┆ ---        ┆   ┆ ---        ┆ pare      ┆ ---       ┆ ---      │\n",
       "│ str        ┆ str        ┆ i64   ┆ str        ┆   ┆ str        ┆ ---       ┆ datetime[ ┆ str      │\n",
       "│            ┆            ┆       ┆            ┆   ┆            ┆ str       ┆ μs]       ┆          │\n",
       "╞════════════╪════════════╪═══════╪════════════╪═══╪════════════╪═══════════╪═══════════╪══════════╡\n",
       "│ eip155:1/e ┆ 0xB6eD7644 ┆ 1     ┆ 0xBitcoin  ┆ … ┆ oxbitcoin  ┆ 0XBTC     ┆ 2018-02-0 ┆ null     │\n",
       "│ rc20:0xB6e ┆ C69416d67B ┆       ┆            ┆   ┆            ┆           ┆ 6         ┆          │\n",
       "│ D7644C6941 ┆ 522e20bC29 ┆       ┆            ┆   ┆            ┆           ┆ 00:00:00  ┆          │\n",
       "│ 6d…        ┆ 4A…        ┆       ┆            ┆   ┆            ┆           ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0x11111111 ┆ 1     ┆ 1INCH      ┆ … ┆ 1inch      ┆ null      ┆ 2020-12-2 ┆ null     │\n",
       "│ rc20:0x111 ┆ 1117dC0aa7 ┆       ┆ Token      ┆   ┆            ┆           ┆ 3         ┆          │\n",
       "│ 111111117d ┆ 8b770fA6A7 ┆       ┆            ┆   ┆            ┆           ┆ 18:13:31  ┆          │\n",
       "│ C0…        ┆ 38…        ┆       ┆            ┆   ┆            ┆           ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0x0F72714B ┆ 1     ┆ 1SG        ┆ … ┆ 1sg        ┆ null      ┆ 2018-12-2 ┆ null     │\n",
       "│ rc20:0x0F7 ┆ 35a366285D ┆       ┆            ┆   ┆            ┆           ┆ 5         ┆          │\n",
       "│ 2714B35a36 ┆ f85886A2eE ┆       ┆            ┆   ┆            ┆           ┆ 00:00:00  ┆          │\n",
       "│ 62…        ┆ 17…        ┆       ┆            ┆   ┆            ┆           ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0xAf30D2a7 ┆ 1     ┆ FirstBlood ┆ … ┆ first-bloo ┆ null      ┆ 2016-07-0 ┆ null     │\n",
       "│ rc20:0xAf3 ┆ E90d7DC361 ┆       ┆            ┆   ┆ d          ┆           ┆ 9         ┆          │\n",
       "│ 0D2a7E90d7 ┆ c8C4585e9B ┆       ┆            ┆   ┆            ┆           ┆ 00:00:00  ┆          │\n",
       "│ DC…        ┆ B7…        ┆       ┆            ┆   ┆            ┆           ┆           ┆          │\n",
       "│ eip155:1/e ┆ 0xfDBc1aDc ┆ 1     ┆ 1World     ┆ … ┆ 1world     ┆ null      ┆ 2017-11-3 ┆ null     │\n",
       "│ rc20:0xfDB ┆ 26F0F8f860 ┆       ┆            ┆   ┆            ┆           ┆ 0         ┆          │\n",
       "│ c1aDc26F0F ┆ 6a5d63b7D3 ┆       ┆            ┆   ┆            ┆           ┆ 00:00:00  ┆          │\n",
       "│ 8f…        ┆ a3…        ┆       ┆            ┆   ┆            ┆           ┆           ┆          │\n",
       "└────────────┴────────────┴───────┴────────────┴───┴────────────┴───────────┴───────────┴──────────┘"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "api_oracles.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "505ef58c-172e-44a9-b892-94e8b885ca34",
   "metadata": {},
   "outputs": [],
   "source": [
    "count_oracles = pl.DataFrame(api_oracles.select(pl.col('cryptocompare', 'coingecko').is_not_null().sum()).to_pandas().T.reset_index()).rename({'index': 'oracle', '0': 'count'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "34d80008-4e6b-4574-a235-5848c8898bfb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Number of tokens with crypotocompare and coingecko ids'}, xlabel='oracle', ylabel='count'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "oracles_data = count_oracles\n",
    "ax = sns.barplot(x='oracle', y='count', data=oracles_data)\n",
    "ax.figure.set_size_inches(5,5)\n",
    "ax.margins(y=0.1) # make room for the labels\n",
    "ax.set_title('Number of tokens with crypotocompare and coingecko ids')\n",
    "ax.bar_label(ax.containers[0])\n",
    "ax"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b96d52b4-6839-4b40-824b-2fc49b02a7ad",
   "metadata": {},
   "source": [
    "As we can see most of the assets have a coingecko id and cryptocompare in general is more conservative when it comes to listing new assets."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9180fd3a-8ff3-43a4-acd6-54266e9d50c0",
   "metadata": {},
   "source": [
    "It is worth mentioning that some assets get delisted from coingecko if there is no activity for a long time. In this case the id is no longer valid. We keep a list of those edge cases here: https://github.com/rotki/rotki/blob/94f474a66dae4807af2b69029d6607c036c11dad/rotkehlchen/externalapis/coingecko.py#L37"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3002e85-293e-48ab-ab96-baebed418fdf",
   "metadata": {},
   "source": [
    "### Protocol column <a id=\"protocol\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38724905-2d65-496a-b9d3-cf9638828cac",
   "metadata": {},
   "source": [
    "At rotki we also use a protcol column to identify groups of assets belonging to a specific protocols. This is useful for us to identify yearn vaults in decoders, compound tokes, aave tokens etc. We also have a special protocol called `SPAM` which identifies an asset as an EVM spam token."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "aa6e41da-5cf4-4b2c-a40e-dd3c6a85d3d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "protocols = df.filter(\n",
    "   ~pl.all_horizontal(pl.col('protocol').is_null())\n",
    ").group_by('protocol').agg(pl.col('identifier').count()).rename({'identifier': 'count'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3eedccc5-be9a-451f-a894-edf481c45fd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (5, 2)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>protocol</th><th>count</th></tr><tr><td>str</td><td>u32</td></tr></thead><tbody><tr><td>&quot;yearn_vaults_v…</td><td>195</td></tr><tr><td>&quot;compound&quot;</td><td>19</td></tr><tr><td>&quot;yearn_vaults_v…</td><td>35</td></tr><tr><td>&quot;curve_pool&quot;</td><td>559</td></tr><tr><td>&quot;spam&quot;</td><td>207</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (5, 2)\n",
       "┌─────────────────┬───────┐\n",
       "│ protocol        ┆ count │\n",
       "│ ---             ┆ ---   │\n",
       "│ str             ┆ u32   │\n",
       "╞═════════════════╪═══════╡\n",
       "│ yearn_vaults_v2 ┆ 195   │\n",
       "│ compound        ┆ 19    │\n",
       "│ yearn_vaults_v1 ┆ 35    │\n",
       "│ curve_pool      ┆ 559   │\n",
       "│ spam            ┆ 207   │\n",
       "└─────────────────┴───────┘"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "protocols.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f15bc168-e56e-4470-93e8-5b5115f21c11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1536499f0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = [x[0] for x in protocols.select('protocol').rows()]\n",
    "protocols.to_pandas().plot.pie(\n",
    "    y='count',\n",
    "    ylabel='',\n",
    "    labels=labels,\n",
    "    legend=False,\n",
    ").legend(\n",
    "    bbox_to_anchor=(1.0, 1.0),\n",
    "    fontsize='small',\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f201add-7fe2-434d-97ca-ae1463ea0ada",
   "metadata": {},
   "source": [
    "For curve, yearn and velodrome the information might not be up to date since new pools are constantly deployed. We have a periodic task in the app that updates it for every user by making on chain calls."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6276af8e-a061-4232-a19b-9d25916278e8",
   "metadata": {},
   "source": [
    "## Other assets <a id=\"other-assets\"></a>\n",
    "\n",
    "We have assets that are not evm tokens and the structure for the csv is a bit different. This is why we provide them in a different file"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02139f13-ad36-46df-b10b-dd9078515a70",
   "metadata": {},
   "source": [
    "### Reading the dataset <a id=\"reading-2\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8cae66ed-59e3-44f3-926d-02796e1e4d68",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfo = pl.read_csv('other_assets.csv').with_columns(pl.from_epoch('started', time_unit=\"s\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f07bba39-9c8f-49b6-9338-d591d9717843",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "895"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dfo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2086c8b6-fa2c-4428-93d3-138fab87f1bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (5, 7)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>identifier</th><th>name</th><th>symbol</th><th>type</th><th>coingecko</th><th>cryptocompare</th><th>started</th></tr><tr><td>str</td><td>str</td><td>str</td><td>str</td><td>str</td><td>str</td><td>datetime[μs]</td></tr></thead><tbody><tr><td>&quot;1CR&quot;</td><td>&quot;1 credit&quot;</td><td>&quot;1CR&quot;</td><td>&quot;own_chain&quot;</td><td>null</td><td>null</td><td>2014-04-27 00:00:00</td></tr><tr><td>&quot;2GIVE&quot;</td><td>&quot;2GIVE&quot;</td><td>&quot;2GIVE&quot;</td><td>&quot;own_chain&quot;</td><td>&quot;2give&quot;</td><td>null</td><td>2016-04-18 00:00:00</td></tr><tr><td>&quot;ABBC&quot;</td><td>&quot;ABBC Coin&quot;</td><td>&quot;ABBC&quot;</td><td>&quot;own_chain&quot;</td><td>&quot;alibabacoin&quot;</td><td>null</td><td>2018-03-05 00:00:00</td></tr><tr><td>&quot;ABY&quot;</td><td>&quot;ArtByte&quot;</td><td>&quot;ABY&quot;</td><td>&quot;own_chain&quot;</td><td>&quot;artbyte&quot;</td><td>null</td><td>2014-05-01 00:00:00</td></tr><tr><td>&quot;AC&quot;</td><td>&quot;AsiaCoin&quot;</td><td>&quot;AC&quot;</td><td>&quot;own_chain&quot;</td><td>&quot;affil-coin&quot;</td><td>null</td><td>2014-04-20 00:00:00</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (5, 7)\n",
       "┌────────────┬───────────┬────────┬───────────┬─────────────┬───────────────┬─────────────────────┐\n",
       "│ identifier ┆ name      ┆ symbol ┆ type      ┆ coingecko   ┆ cryptocompare ┆ started             │\n",
       "│ ---        ┆ ---       ┆ ---    ┆ ---       ┆ ---         ┆ ---           ┆ ---                 │\n",
       "│ str        ┆ str       ┆ str    ┆ str       ┆ str         ┆ str           ┆ datetime[μs]        │\n",
       "╞════════════╪═══════════╪════════╪═══════════╪═════════════╪═══════════════╪═════════════════════╡\n",
       "│ 1CR        ┆ 1 credit  ┆ 1CR    ┆ own_chain ┆ null        ┆ null          ┆ 2014-04-27 00:00:00 │\n",
       "│ 2GIVE      ┆ 2GIVE     ┆ 2GIVE  ┆ own_chain ┆ 2give       ┆ null          ┆ 2016-04-18 00:00:00 │\n",
       "│ ABBC       ┆ ABBC Coin ┆ ABBC   ┆ own_chain ┆ alibabacoin ┆ null          ┆ 2018-03-05 00:00:00 │\n",
       "│ ABY        ┆ ArtByte   ┆ ABY    ┆ own_chain ┆ artbyte     ┆ null          ┆ 2014-05-01 00:00:00 │\n",
       "│ AC         ┆ AsiaCoin  ┆ AC     ┆ own_chain ┆ affil-coin  ┆ null          ┆ 2014-04-20 00:00:00 │\n",
       "└────────────┴───────────┴────────┴───────────┴─────────────┴───────────────┴─────────────────────┘"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfo.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ee007439-1601-4d0f-bcfd-f48b18f4a472",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Number of tokens per chain'}, xlabel='type', ylabel='count'>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "counts = dfo['type'].value_counts().rename({'counts': 'count'})\n",
    "ax = sns.barplot(x='type', y='count', data=counts)\n",
    "ax.set_title('Number of tokens per chain')\n",
    "ax.bar_label(ax.containers[0])\n",
    "plt.xticks(rotation=90)\n",
    "ax"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6514d0d5-56c1-4e6d-9138-b3e9928a1fc9",
   "metadata": {},
   "source": [
    "As we can see most of assets are assets like BTC that have their own chain. We have many solana tokens too also with information linking them to their coingecko and cryptocompare ids"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6287d181-f6a3-4097-99b9-06122d0dc866",
   "metadata": {},
   "source": [
    "### Oracle distribution of the assets <a id=\"dist-oracles-2\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6cb89f7-1641-498f-a5df-8ea978c7d547",
   "metadata": {},
   "source": [
    "Similar to what we did with the evm tokens we can study the oracles for this assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e5199093-d459-4c2b-a089-c6bbc7e5a8c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "api_oracles = dfo.filter(\n",
    "   ~pl.all_horizontal(pl.col('coingecko', 'cryptocompare').is_null()) \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c7fb7b20-ef93-4132-8831-31dc86244fd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Number of assets with cryptocompare and coingecko ids'}, xlabel='oracle', ylabel='count'>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "count_oracles = pl.DataFrame(api_oracles.select(pl.col('cryptocompare', 'coingecko').is_not_null().sum()).to_pandas().T.reset_index()).rename({'index': 'oracle', '0': 'count'})\n",
    "oracles_data = count_oracles\n",
    "ax = sns.barplot(x='oracle', y='count', data=oracles_data)\n",
    "ax.figure.set_size_inches(5,5)\n",
    "ax.margins(y=0.1) # make room for the labels\n",
    "ax.set_title('Number of assets with cryptocompare and coingecko ids')\n",
    "ax.bar_label(ax.containers[0])\n",
    "ax"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ae3ca94-4621-49ed-8cd3-e5c98c1e3299",
   "metadata": {},
   "source": [
    "As we can see most of them have at least one oracle and again coingecko is the one listing most of them."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c25e9288-5f21-4a81-bec5-dedd948043f7",
   "metadata": {},
   "source": [
    "## Collections of assets <a id=\"collections\"></a>\n",
    "\n",
    "It is also useful to group tokens that are the same asset but in different chains. This is the case for example for USDC in ethereum, optimism, gnosis etc. It can happen also that the name/symbol is not the same in all these chains. For example USDC has USDC in ethereum but USD//C in gnosis. To overcome these UX issues we created collections that define a common name and symbol and then we map each token to a collection.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9501176f-3b60-4ecc-b74e-3a0e81c8fe09",
   "metadata": {},
   "outputs": [],
   "source": [
    "asset_collections = pl.read_csv('asset_collections.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "81cde14f-3e18-48c5-940d-2452da25db8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(shape: (5, 3)\n",
       " ┌────────────┬─────────────────────┬────────┐\n",
       " │ identifier ┆ name                ┆ symbol │\n",
       " │ ---        ┆ ---                 ┆ ---    │\n",
       " │ i64        ┆ str                 ┆ str    │\n",
       " ╞════════════╪═════════════════════╪════════╡\n",
       " │ 0          ┆ 0xBitcoin           ┆ 0xBTC  │\n",
       " │ 1          ┆ 1INCH Token         ┆ 1INCH  │\n",
       " │ 2          ┆ Aave Token          ┆ AAVE   │\n",
       " │ 3          ┆ AdEx Network        ┆ ADX    │\n",
       " │ 4          ┆ AllianceBlock Token ┆ ALBT   │\n",
       " └────────────┴─────────────────────┴────────┘,\n",
       " 238)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "asset_collections.head(), len(asset_collections)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "affb058f-38cc-4f71-a457-5c89835a232e",
   "metadata": {},
   "source": [
    "As you can see at the moment we have 238 collection of assets. For the total number of assets mapped we have"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "4bfb797c-12a3-4894-b92f-24d793bf91e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "multiassets_mappings = pl.read_csv('multiassets_mappings.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7eac2fe2-b73f-4745-87eb-32647b3e02d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(shape: (5, 2)\n",
       " ┌───────────────────────┬───────────────────────────────────┐\n",
       " │ collection_identifier ┆ asset                             │\n",
       " │ ---                   ┆ ---                               │\n",
       " │ i64                   ┆ str                               │\n",
       " ╞═══════════════════════╪═══════════════════════════════════╡\n",
       " │ 0                     ┆ eip155:10/erc20:0xe0BB0D3DE8c109… │\n",
       " │ 0                     ┆ eip155:137/erc20:0x71B821aa52a49… │\n",
       " │ 0                     ┆ eip155:1/erc20:0xB6eD7644C69416d… │\n",
       " │ 0                     ┆ eip155:42161/erc20:0x7cb16cb78ea… │\n",
       " │ 1                     ┆ eip155:43114/erc20:0xd501281565b… │\n",
       " └───────────────────────┴───────────────────────────────────┘,\n",
       " 615)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "multiassets_mappings.head(), len(multiassets_mappings)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74e58a99-8677-4606-a8c3-a8b609c09f40",
   "metadata": {},
   "source": [
    "Those mappings include assets across different chains. This part of the dataset is one of the most recent additions and it is growing with each release."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "58801437-d083-493a-9b86-1160af0144c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (9, 2)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>describe</th><th>count</th></tr><tr><td>str</td><td>f64</td></tr></thead><tbody><tr><td>&quot;count&quot;</td><td>238.0</td></tr><tr><td>&quot;null_count&quot;</td><td>0.0</td></tr><tr><td>&quot;mean&quot;</td><td>2.584034</td></tr><tr><td>&quot;std&quot;</td><td>1.109642</td></tr><tr><td>&quot;min&quot;</td><td>1.0</td></tr><tr><td>&quot;25%&quot;</td><td>2.0</td></tr><tr><td>&quot;50%&quot;</td><td>2.0</td></tr><tr><td>&quot;75%&quot;</td><td>3.0</td></tr><tr><td>&quot;max&quot;</td><td>10.0</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (9, 2)\n",
       "┌────────────┬──────────┐\n",
       "│ describe   ┆ count    │\n",
       "│ ---        ┆ ---      │\n",
       "│ str        ┆ f64      │\n",
       "╞════════════╪══════════╡\n",
       "│ count      ┆ 238.0    │\n",
       "│ null_count ┆ 0.0      │\n",
       "│ mean       ┆ 2.584034 │\n",
       "│ std        ┆ 1.109642 │\n",
       "│ min        ┆ 1.0      │\n",
       "│ 25%        ┆ 2.0      │\n",
       "│ 50%        ┆ 2.0      │\n",
       "│ 75%        ┆ 3.0      │\n",
       "│ max        ┆ 10.0     │\n",
       "└────────────┴──────────┘"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "multiassets_mappings.group_by('collection_identifier').count().select('count').describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a951c798-b21a-4d96-b56d-f4ed4f9d3fbf",
   "metadata": {},
   "source": [
    "For the groups the mean is to have ~2.6 assets in each collection and the max value is 10 assets in a single collection. At rotki we believe this information is really useful for users and can help others to improve the UX in their apps too."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "910bcdc1-9845-4c4f-a047-9121c1464939",
   "metadata": {},
   "source": [
    "## Conclusion <a id=\"conclusion\"></a>"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "2a594cb1-8f9b-4182-bd85-54681749ecaf",
   "metadata": {},
   "source": [
    "This dataset provides what we believe is useful information to any project that wants to use it. The data was collected over multiple years and it provides an interesting perspective for how assets were created over time and peculiarities that they have. Hopefuly it can be useful for your project too or for learning more about the ecosystem.\n",
    "\n",
    "If you want to improve the database quality or you have ideas on things to improve feel free to join the discussion at https://discord.rotki.com/\n",
    "\n",
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