kopia lustrzana https://github.com/bugout-dev/moonstream
improvements
Tim Pechersky
rodzic
9fc44de4b6
commit
7c4b1625f3
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@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 2,
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"metadata": {},
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@ -20,7 +20,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -29,195 +29,29 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"checkpoint = pd.read_sql_query(\"SELECT * FROM checkpoint\", conTXs)\n",
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"mints = pd.read_sql_query(\"SELECT * FROM mints\", conTXs)\n",
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"nfts = pd.read_sql_query(\"SELECT * FROM nfts\", conTXs)\n",
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"transfers = pd.read_sql_query(\"SELECT * FROM transfers\", conTXs)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" sql\n",
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"0 CREATE TABLE nfts\\n (\\n address TEXT...\n",
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"1 CREATE TABLE checkpoint\\n (\\n event_...\n",
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"2 CREATE TABLE mints\\n (\\n event_id TE...\n",
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"3 CREATE TABLE transfers\\n (\\n event_i...\n",
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"4 CREATE TABLE current_owners(\\n nft_address TE...\n",
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"5 CREATE TABLE current_market_values(\\n nft_add...\n",
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"6 CREATE TABLE market_values_distribution(\\n ad...\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"stolbiki = pd.read_sql_query(\"SELECT sql FROM sqlite_master where type='table'\", conTXs) \n",
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"print(stolbiki)"
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"num_df = (transfers[[\"transaction_value\", \"timestamp\"]].apply(pd.to_numeric, errors='coerce'))\n",
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"num_df[\"timestamp\"] = pd.to_datetime(num_df.timestamp, unit='s', errors='coerce')\n",
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"num_df.set_index(\"timestamp\")\n",
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"num_df = num_df.resample(\"1440min\", label='right', on='timestamp').sum()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>event_id</th>\n",
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" <th>transaction_hash</th>\n",
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" <th>block_number</th>\n",
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" <th>nft_address</th>\n",
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" <th>token_id</th>\n",
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" <th>from_address</th>\n",
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" <th>to_address</th>\n",
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" <th>transaction_value</th>\n",
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" <th>timestamp</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>ce7b6ba0-218f-40c7-8d8c-4e3bfc822a41</td>\n",
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" <td>0x804cee46e672b17b477658b99c25c8b75f31553278ad...</td>\n",
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" <td>11565099</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>0x629A673A8242c2AC4B7B8C5D8735fbeac21A6205</td>\n",
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" <td>0.0</td>\n",
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" <td>1609460206</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>d9494633-61fd-4cd6-bd42-e736e0982956</td>\n",
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" <td>11565044</td>\n",
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" <td>0x6Fa769EED284a94A73C15299e1D3719B29Ae2F52</td>\n",
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" <td>51060026</td>\n",
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" <td>0x9503DE24f4210dA79c5e5BCCD198B2727387a519</td>\n",
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" <td>0.0</td>\n",
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" <td>1609459570</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>801c3aae-9b72-4a4b-b40b-1cf93308eeea</td>\n",
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" <td>0xe74d08ee2cbe4b6b873258462ec5523999433569df66...</td>\n",
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" <td>11565042</td>\n",
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" <td>0xB2D6fb1Dc231F97F8cC89467B52F7C4F78484044</td>\n",
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" <td>4265098311422702060752376543910232329671779809...</td>\n",
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" <td>0x0BF988a6cc20af0CDD6f583aD2Fcf057895888e6</td>\n",
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" <td>0x0000000000000000000000000000000000000000</td>\n",
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" <td>0.0</td>\n",
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" <td>1609459545</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" event_id \\\n",
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"0 ce7b6ba0-218f-40c7-8d8c-4e3bfc822a41 \n",
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"1 c81d8767-a523-410e-9f4a-21a25f8e906f \n",
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"2 d9494633-61fd-4cd6-bd42-e736e0982956 \n",
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"3 801c3aae-9b72-4a4b-b40b-1cf93308eeea \n",
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"\n",
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" transaction_hash block_number \\\n",
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"0 0x804cee46e672b17b477658b99c25c8b75f31553278ad... 11565099 \n",
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"1 0x9b124e219f875fa0bb52d90ba937c5d8373ddc8a2c46... 11565099 \n",
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"2 0x64a82fe7402d2efd82085a10b6a99d6fcedcac21804e... 11565044 \n",
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"3 0xe74d08ee2cbe4b6b873258462ec5523999433569df66... 11565042 \n",
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"\n",
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" nft_address \\\n",
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"0 0x629A673A8242c2AC4B7B8C5D8735fbeac21A6205 \n",
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"1 0x629A673A8242c2AC4B7B8C5D8735fbeac21A6205 \n",
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"2 0x6Fa769EED284a94A73C15299e1D3719B29Ae2F52 \n",
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"3 0xB2D6fb1Dc231F97F8cC89467B52F7C4F78484044 \n",
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"\n",
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" token_id \\\n",
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"0 7287012905433418913509099434869470284131894829... \n",
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"1 1225542446027558019364995253890488984869511709... \n",
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"2 51060026 \n",
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"3 4265098311422702060752376543910232329671779809... \n",
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"\n",
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" from_address \\\n",
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"0 0x79A8b5Fcc051c843DFCB753eE38d113675E5367D \n",
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"1 0x2c338BAf69A57A17E69dB86933310e92f64ab69d \n",
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"2 0x9503DE24f4210dA79c5e5BCCD198B2727387a519 \n",
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"3 0x0BF988a6cc20af0CDD6f583aD2Fcf057895888e6 \n",
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"\n",
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" to_address transaction_value timestamp \n",
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"0 0x433f7e8DeFBbCB5459DDD8C6597493e41550F37f 0.0 1609460206 \n",
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"1 0x433f7e8DeFBbCB5459DDD8C6597493e41550F37f 0.0 1609460206 \n",
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"2 0x8B36486EA2E0b70A505D92d30c31CC3197ba5707 0.0 1609459570 \n",
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"3 0x0000000000000000000000000000000000000000 0.0 1609459545 "
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"transfers.head(4)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [],
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"source": [
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"num_df = (transfers[[\"transaction_value\", \"timestamp\"]].apply(pd.to_numeric, errors='coerce'))\n",
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"\n",
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"num_df[\"timestamp\"] = pd.to_datetime(num_df.timestamp, unit='s', errors='coerce')\n",
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"num_df.set_index(\"timestamp\")\n",
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"num_df = num_df.resample(\"1440min\", label='right', on='timestamp').sum()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"data": {
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@ -225,7 +59,7 @@
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"Text(0.5, 1.0, 'NFT transfers value over time')"
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]
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},
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"execution_count": 10,
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"execution_count": 6,
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{
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"0xcDA72070E455bb31C7690a170224Ce43623d0B6f 76645.0 36116.0"
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]
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},
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"execution_count": 133,
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{
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"0x327305A797d92a39cEe1a225D7E2A1cC42B1a8fA NaN 106620.0"
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]
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},
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"execution_count": 134,
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"outputs": [
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{
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"0xcDA72070E455bb31C7690a170224Ce43623d0B6f 76645.0 36116.0"
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]
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},
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"execution_count": 137,
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"execution_count": 138,
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"metadata": {},
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"outputs": [
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{
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@ -741,7 +575,7 @@
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"0xb1690C08E213a35Ed9bAb7B318DE14420FB57d8C 14124.0 23128.0"
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]
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},
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"execution_count": 138,
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"execution_count": 19,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -761,6 +595,121 @@
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"[0xb1690C08E213a35Ed9bAb7B318DE14420FB57d8C](https://etherscan.io/address/0xb1690C08E213a35Ed9bAb7B318DE14420FB57d8C) / not a contract! / info: `CryptoKitties: Sales Auction `\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"outputs": [],
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"source": [
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"#transfers not transactions\n",
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"transactions_per_nft = transfers[\"nft_address\"].groupby(transfers[\"nft_address\"]).size()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"0 0.000000e+00\n",
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"1 0.000000e+00\n",
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"3 0.000000e+00\n",
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"4 0.000000e+00\n",
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"5 6.180000e+18\n",
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"6 0.000000e+00\n",
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"7 0.000000e+00\n",
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"8 3.000000e+16\n",
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"9 0.000000e+00\n",
|
||||
"10 0.000000e+00\n",
|
||||
"11 0.000000e+00\n",
|
||||
"12 0.000000e+00\n",
|
||||
"13 0.000000e+00\n",
|
||||
"14 0.000000e+00\n",
|
||||
"Name: transaction_value, dtype: float64"
|
||||
]
|
||||
},
|
||||
"execution_count": 24,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"transfers[\"transaction_value\"] = pd.to_numeric(transfers[\"transaction_value\"])\n",
|
||||
"transfers[\"transaction_value\"] = transfers[\"transaction_value\"].fillna(0)\n",
|
||||
"transfers[\"transaction_value\"].head(15)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"total_value_per_nft = transfers[\"nft_address\"].groupby(transfers[\"transaction_value\"]).sum()\n",
|
||||
"total_value_per_nft.head(4)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"most_popular_nfts = transactions_per_nft.sort_values(ascending=False).head(8)\n",
|
||||
"most_valuable_nfts = total_value_per_nft.sort_values(ascending=False).head(8)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"#get frame with values over time\n",
|
||||
"num_df = pd.DataFrame()\n",
|
||||
"#cast to numeric\n",
|
||||
"num_df = (transfers[[\"transaction_value\", \"timestamp\"]].apply(pd.to_numeric, errors='coerce'))\n",
|
||||
"#add nft_address column to it\n",
|
||||
"num_df[\"nft_address\"]=transfers[\"nft_address\"]\n",
|
||||
"#filter out only ones that are in most_popular_nft variable\n",
|
||||
"num_df = num_df[num_df.nft_address.isin(list(most_valuable_nfts.index))]\n",
|
||||
"#convert timestamp in to date time\n",
|
||||
"num_df[\"timestamp\"] = pd.to_datetime(num_df.timestamp, unit='s', errors='coerce')\n",
|
||||
"#set index as timestamp\n",
|
||||
"num_df = num_df.set_index(\"timestamp\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"#group timestamps by day, create column per each nft_address, aggregate transaction value by count and sum\n",
|
||||
"new_df = num_df.groupby([pd.Grouper(freq='d'), 'nft_address'])['transaction_value'].agg(transaction_value=\"sum\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plt.figure(figsize=(24, 12))\n",
|
||||
"# new_df.unstack()\n",
|
||||
"# ax = sns.lineplot(data=new_df, x='timestamp', y='transaction_value', hue='nft_address',)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
|
|
|
|||
Ładowanie…
Reference in New Issue