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wassname 4823df6028 init
2017-12-09 10:28:21 +08:00

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{
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{
"cell_type": "code",
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"metadata": {
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"start_time": "2017-12-08T22:54:34.152727Z"
},
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},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import numpy as np\n",
"from matplotlib import pyplot as plt\n",
"import pandas as pd\n",
"import json\n",
"from tqdm import tqdm\n",
"import os\n",
"\n",
"import datetime\n",
"import arrow\n",
"import time"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Load data\n",
"\n",
"See the scraping notebook for data but sales come from https://kittysales.herokuapp.com, genetics come from data on the etherium contract"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
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"end_time": "2017-12-08T23:06:25.400208Z",
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},
"scrolled": true
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"outputs": [
{
"data": {
"text/plain": [
"{'blockNumber': 4688676,\n",
" 'blocktimeStamp': 1512617298,\n",
" 'id': 'log_9357a0df',\n",
" 'rank': 1,\n",
" 'returnValues': {'0': '18',\n",
" '1': '253336776620370370370',\n",
" '2': '0xA6d3fdf423BbC578dd4d41220078475371626B22'},\n",
" 'soldPrice': 115197.04572803818}"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sales_data_file = '.cache/sales.json'\n",
"sales = json.load(open(sales_data_file))\n",
"len(sales)\n",
"sales['sales'][0]"
]
},
{
"cell_type": "code",
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"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T00:12:33.116720Z",
"start_time": "2017-12-09T00:12:32.499699Z"
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"outputs": [
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],
"text/plain": [
" sold_price_usd date kitty_id price_eth\n",
"kitty_id \n",
"18 1.151970e+05 2017-12-07 11:28:18 18 2.533368e+02\n",
"4 1.123156e+05 2017-12-07 03:41:57 4 2.470000e+02\n",
"1 1.144816e+05 2017-12-03 04:32:36 1 2.469255e+02\n",
"21 1.080061e+05 2017-12-08 17:31:03 21 2.375228e+02\n",
"22 1.023118e+05 2017-12-08 17:34:36 22 2.250000e+02\n",
"5 1.016005e+05 2017-12-06 00:45:01 5 2.220000e+02\n",
"7 8.767734e+04 2017-12-05 03:45:47 7 1.900468e+02\n",
"35 8.500053e+04 2017-12-06 15:18:02 35 1.888897e+02\n",
"87 8.142809e+04 2017-12-07 02:11:42 87 1.790734e+02\n",
"101 8.199325e+04 2017-12-04 11:28:49 101 1.757532e+02\n",
"30 7.792517e+04 2017-12-06 00:28:28 30 1.686849e+02\n",
"78 7.349530e+04 2017-12-05 14:49:17 78 1.568700e+02\n",
"14 7.048144e+04 2017-12-07 05:59:58 14 1.550000e+02\n",
"18 6.930015e+04 2017-12-06 10:37:44 18 1.540000e+02\n",
"19 6.930015e+04 2017-12-06 10:19:43 19 1.540000e+02\n",
"102 6.982621e+04 2017-12-08 16:18:33 102 1.535590e+02\n",
"2 7.016610e+04 2017-12-04 09:16:36 2 1.500000e+02\n",
"37 6.772737e+04 2017-12-05 16:14:40 37 1.432795e+02\n",
"23 6.293852e+04 2017-12-05 15:07:48 23 1.338756e+02\n",
"38 6.033274e+04 2017-12-05 20:59:48 38 1.300000e+02\n",
"102 5.991045e+04 2017-12-04 11:43:16 102 1.284185e+02\n",
"93 5.671367e+04 2017-12-06 15:26:53 93 1.260301e+02\n",
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"43 4.501718e+04 2017-12-07 23:51:39 43 9.900000e+01\n",
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"... ... ... ... ...\n",
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"6067 4.601970e-01 2017-11-26 11:11:44 6067 1.000000e-03\n",
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"8296 4.842060e-01 2017-11-29 11:15:34 8296 1.000000e-03\n",
"11172 4.611260e-01 2017-11-30 09:38:46 11172 1.000000e-03\n",
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"113539 1.684144e-02 2017-12-07 22:52:26 113539 3.703704e-05\n",
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"41574 5.365162e-03 2017-12-05 23:11:30 41574 1.157407e-05\n",
"30173 4.558781e-03 2017-12-04 07:13:30 30173 9.785880e-06\n",
"91591 3.526177e-03 2017-12-07 14:02:35 91591 7.754630e-06\n",
"136018 1.539413e-03 2017-12-08 05:03:21 136018 3.385417e-06\n",
"127036 3.947214e-04 2017-12-08 00:26:49 127036 8.680556e-07\n",
"111960 3.157771e-04 2017-12-08 11:45:07 111960 6.944444e-07\n",
"45652 1.023946e-13 2017-12-06 01:29:05 45652 2.220000e-16\n",
"\n",
"[78124 rows x 4 columns]"
]
},
"execution_count": 129,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# convert to dataframe\n",
"df = pd.DataFrame(sales['sales'])\n",
"\n",
"# convert to pandas timestamp\n",
"datetimes = df['blocktimeStamp'].apply(datetime.datetime.fromtimestamp)\n",
"df['date'] = pd.to_datetime(datetimes)\n",
"\n",
"# grab some of the fields under return values for the dataframe\n",
"df2=pd.DataFrame.from_records(df['returnValues'].values)\n",
"df2.columns=['kitty_id','price_18eth','address']\n",
"df2['price_eth']=df2['price_18eth'].apply(lambda x:float(x)*1e-18)\n",
"df2['kitty_id'] = pd.to_numeric(df2['kitty_id'])\n",
"for col in ['kitty_id','price_eth']:\n",
" df[col] = df2[col]\n",
" \n",
"# rename cols\n",
"df['soldPrice'] = df['soldPrice'].rename('soldPrice_USD')\n",
"df = df.rename(columns={\"soldPrice\":\"sold_price_usd\"})\n",
"df.index = df['kitty_id']\n",
"\n",
"# drop uneeded columns\n",
"df = df.drop(['id', 'blockNumber', 'rank', 'returnValues', 'blocktimeStamp'], axis=1)\n",
"df_sales = df\n",
"df_sales"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-08T23:25:07.624214Z",
"start_time": "2017-12-08T23:25:07.595375Z"
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-08T22:51:35.868258Z",
"start_time": "2017-12-08T22:51:35.410539Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"10024"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# haven't finished scraping\n",
"# api_data_file = '.cache/api_data.json'\n",
"# api_data = json.load(open(api_data_file))\n",
"# len(api_data)"
]
},
{
"cell_type": "code",
"execution_count": 109,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T00:07:43.349887Z",
"start_time": "2017-12-09T00:07:43.048072Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"43488"
]
},
"execution_count": 109,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"genetics_file = '.cache/genes.json'\n",
"genetics = json.load(open(genetics_file))\n",
"len(genetics)"
]
},
{
"cell_type": "code",
"execution_count": 496,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:49:06.810924Z",
"start_time": "2017-12-09T01:49:03.676050Z"
},
"scrolled": true
},
"outputs": [
{
"data": {
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" birth_time matron_id sire_id generation \\\n",
"1 1511417999 0 0 0 \n",
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"... ... ... ... ... \n",
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"\n",
" genes \n",
"1 6268376211548016160889809226598771686091543863... \n",
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"... ... \n",
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"\n",
"[43468 rows x 5 columns]"
]
},
"execution_count": 496,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# convert to dataframe\n",
"df = pd.DataFrame.from_dict(genetics).T\n",
"df.columns=['is_gestating', 'is_ready', 'cooldown_index', 'next_action_at', 'siring_with_id', 'birth_time', 'matron_id', 'sire_id', 'generation', 'genes']\n",
"df.index = pd.to_numeric(df.index)\n",
"df['generation'] = pd.to_numeric(df['generation'])\n",
"df['matron_id'] = pd.to_numeric(df['matron_id'])\n",
"df['sire_id'] = pd.to_numeric(df['sire_id'])\n",
"df['birth_time'] = pd.to_numeric(df['birth_time'])\n",
"df = df.sort_index()\n",
"df = df.drop(['is_gestating', 'is_ready', 'cooldown_index', 'next_action_at', 'siring_with_id'], axis=1)\n",
"df = df[df.genes!='0'] # remove rows with no genes\n",
"df = df[1:] # remove origin kitty\n",
"df_genetics = df\n",
"df_genetics"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:49:06.835748Z",
"start_time": "2017-12-09T01:49:06.812605Z"
}
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Collect training data"
]
},
{
"cell_type": "code",
"execution_count": 518,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:53:55.043121Z",
"start_time": "2017-12-09T01:53:55.034712Z"
}
},
"outputs": [],
"source": [
"def genestr_to_bits(x):\n",
" \"\"\"Gene data is a uint256 string, but I think the genes are it's bytes so lets convert to a byte array\"\"\"\n",
" bits = bin(int(x))[2:]\n",
" bitarray = [1 if b=='1' else 0 for b in bits]\n",
" bitarray = (256-len(bitarray))*[0] + bitarray # pad\n",
" return bitarray"
]
},
{
"cell_type": "code",
"execution_count": 519,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:53:55.810819Z",
"start_time": "2017-12-09T01:53:55.747036Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"335"
]
},
"execution_count": 519,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lens = np.array([len(b) for b in df_genetics.genes.apply(lambda x:bin(int(x)))])\n",
"np.unique(lens)\n",
"(lens==242).sum()"
]
},
{
"cell_type": "code",
"execution_count": 520,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:53:55.992235Z",
"start_time": "2017-12-09T01:53:55.987586Z"
}
},
"outputs": [],
"source": [
"pad = 256-lens"
]
},
{
"cell_type": "code",
"execution_count": 521,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:54:08.262218Z",
"start_time": "2017-12-09T01:53:56.180148Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/wassname/.pyenv/versions/3.5.3/envs/jupyter3/lib/python3.5/site-packages/pandas/core/computation/expressions.py:183: UserWarning: evaluating in Python space because the '*' operator is not supported by numexpr for the bool dtype, use '&' instead\n",
" unsupported[op_str]))\n"
]
},
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" <td>1511467189</td>\n",
" <td>1046</td>\n",
" <td>1087</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>399.712992</td>\n",
" <td>2017-12-05 09:53:38</td>\n",
" <td>3012</td>\n",
" <td>0.856569</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3012</th>\n",
" <td>1511467189</td>\n",
" <td>1046</td>\n",
" <td>1087</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>4.096416</td>\n",
" <td>2017-11-24 10:23:41</td>\n",
" <td>3012</td>\n",
" <td>0.009984</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3013</th>\n",
" <td>1511467349</td>\n",
" <td>1088</td>\n",
" <td>1019</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>231.375440</td>\n",
" <td>2017-12-05 00:18:59</td>\n",
" <td>3013</td>\n",
" <td>0.499733</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3017</th>\n",
" <td>1511467461</td>\n",
" <td>1078</td>\n",
" <td>1056</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>195.708110</td>\n",
" <td>2017-12-08 02:05:55</td>\n",
" <td>3017</td>\n",
" <td>0.430394</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3018</th>\n",
" <td>1511467461</td>\n",
" <td>1043</td>\n",
" <td>3003</td>\n",
" <td>2</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>7.777746</td>\n",
" <td>2017-11-24 09:43:28</td>\n",
" <td>3018</td>\n",
" <td>0.019250</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3018</th>\n",
" <td>1511467461</td>\n",
" <td>1043</td>\n",
" <td>3003</td>\n",
" <td>2</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>3.529732</td>\n",
" <td>2017-11-25 03:49:18</td>\n",
" <td>3018</td>\n",
" <td>0.007695</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3020</th>\n",
" <td>1511467461</td>\n",
" <td>1087</td>\n",
" <td>3006</td>\n",
" <td>2</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>124.010446</td>\n",
" <td>2017-12-05 03:36:28</td>\n",
" <td>3020</td>\n",
" <td>0.268801</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3020</th>\n",
" <td>1511467461</td>\n",
" <td>1087</td>\n",
" <td>3006</td>\n",
" <td>2</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>82.108207</td>\n",
" <td>2017-12-05 02:59:27</td>\n",
" <td>3020</td>\n",
" <td>0.177975</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3020</th>\n",
" <td>1511467461</td>\n",
" <td>1087</td>\n",
" <td>3006</td>\n",
" <td>2</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>8.249211</td>\n",
" <td>2017-11-24 11:04:56</td>\n",
" <td>3020</td>\n",
" <td>0.019992</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3021</th>\n",
" <td>1511467461</td>\n",
" <td>1093</td>\n",
" <td>3008</td>\n",
" <td>2</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>5.974832</td>\n",
" <td>2017-11-25 13:08:18</td>\n",
" <td>3021</td>\n",
" <td>0.012687</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3022</th>\n",
" <td>1511467549</td>\n",
" <td>1062</td>\n",
" <td>1005</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>46.714600</td>\n",
" <td>2017-12-02 13:53:03</td>\n",
" <td>3022</td>\n",
" <td>0.100000</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3024</th>\n",
" <td>1511467642</td>\n",
" <td>1077</td>\n",
" <td>1002</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>598.399623</td>\n",
" <td>2017-12-06 01:31:35</td>\n",
" <td>3024</td>\n",
" <td>1.297431</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3029</th>\n",
" <td>1511467718</td>\n",
" <td>1053</td>\n",
" <td>1010</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>551.445594</td>\n",
" <td>2017-12-04 05:27:15</td>\n",
" <td>3029</td>\n",
" <td>1.200295</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3029</th>\n",
" <td>1511467718</td>\n",
" <td>1053</td>\n",
" <td>1010</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>25.891600</td>\n",
" <td>2017-12-02 00:18:55</td>\n",
" <td>3029</td>\n",
" <td>0.056251</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3029</th>\n",
" <td>1511467718</td>\n",
" <td>1053</td>\n",
" <td>1010</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>18.916080</td>\n",
" <td>2017-11-29 07:21:59</td>\n",
" <td>3029</td>\n",
" <td>0.040000</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3030</th>\n",
" <td>1511467718</td>\n",
" <td>1036</td>\n",
" <td>1047</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>4.121639</td>\n",
" <td>2017-11-24 11:28:35</td>\n",
" <td>3030</td>\n",
" <td>0.009989</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3031</th>\n",
" <td>1511467718</td>\n",
" <td>1098</td>\n",
" <td>1017</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>937.400000</td>\n",
" <td>2017-12-05 10:11:05</td>\n",
" <td>3031</td>\n",
" <td>2.000000</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3031</th>\n",
" <td>1511467718</td>\n",
" <td>1098</td>\n",
" <td>1017</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>2.289915</td>\n",
" <td>2017-11-26 13:20:38</td>\n",
" <td>3031</td>\n",
" <td>0.005000</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3032</th>\n",
" <td>1511467718</td>\n",
" <td>1054</td>\n",
" <td>1004</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>981.295931</td>\n",
" <td>2017-12-06 06:53:53</td>\n",
" <td>3032</td>\n",
" <td>2.180653</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3032</th>\n",
" <td>1511467718</td>\n",
" <td>1054</td>\n",
" <td>1004</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>314.984033</td>\n",
" <td>2017-12-06 06:13:25</td>\n",
" <td>3032</td>\n",
" <td>0.699963</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3032</th>\n",
" <td>1511467718</td>\n",
" <td>1054</td>\n",
" <td>1004</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>7.705208</td>\n",
" <td>2017-11-28 21:47:07</td>\n",
" <td>3032</td>\n",
" <td>0.016276</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3033</th>\n",
" <td>1511467823</td>\n",
" <td>1039</td>\n",
" <td>1051</td>\n",
" <td>1</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>47.888720</td>\n",
" <td>2017-11-29 16:19:38</td>\n",
" <td>3033</td>\n",
" <td>0.099592</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45592</th>\n",
" <td>1512333116</td>\n",
" <td>16162</td>\n",
" <td>28528</td>\n",
" <td>17</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>15.392169</td>\n",
" <td>2017-12-04 07:42:22</td>\n",
" <td>45592</td>\n",
" <td>0.033041</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45594</th>\n",
" <td>1512333116</td>\n",
" <td>16176</td>\n",
" <td>38530</td>\n",
" <td>17</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>12.723501</td>\n",
" <td>2017-12-08 00:43:11</td>\n",
" <td>45594</td>\n",
" <td>0.027981</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45597</th>\n",
" <td>1512333116</td>\n",
" <td>16262</td>\n",
" <td>5646</td>\n",
" <td>4</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>71.372034</td>\n",
" <td>2017-12-06 06:00:54</td>\n",
" <td>45597</td>\n",
" <td>0.158604</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45597</th>\n",
" <td>1512333116</td>\n",
" <td>16262</td>\n",
" <td>5646</td>\n",
" <td>4</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>23.875589</td>\n",
" <td>2017-12-07 13:46:57</td>\n",
" <td>45597</td>\n",
" <td>0.052506</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45598</th>\n",
" <td>1512333116</td>\n",
" <td>16274</td>\n",
" <td>27366</td>\n",
" <td>17</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>32.143957</td>\n",
" <td>2017-12-04 05:13:35</td>\n",
" <td>45598</td>\n",
" <td>0.069966</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45598</th>\n",
" <td>1512333116</td>\n",
" <td>16274</td>\n",
" <td>27366</td>\n",
" <td>17</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>17.731081</td>\n",
" <td>2017-12-06 14:13:00</td>\n",
" <td>45598</td>\n",
" <td>0.039402</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45599</th>\n",
" <td>1512333116</td>\n",
" <td>16331</td>\n",
" <td>6439</td>\n",
" <td>14</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>26.936386</td>\n",
" <td>2017-12-04 13:25:22</td>\n",
" <td>45599</td>\n",
" <td>0.057391</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45599</th>\n",
" <td>1512333116</td>\n",
" <td>16331</td>\n",
" <td>6439</td>\n",
" <td>14</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>22.709755</td>\n",
" <td>2017-12-05 21:59:24</td>\n",
" <td>45599</td>\n",
" <td>0.048933</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45599</th>\n",
" <td>1512333116</td>\n",
" <td>16331</td>\n",
" <td>6439</td>\n",
" <td>14</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>13.582793</td>\n",
" <td>2017-12-07 06:29:50</td>\n",
" <td>45599</td>\n",
" <td>0.029871</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45600</th>\n",
" <td>1512333116</td>\n",
" <td>16364</td>\n",
" <td>13561</td>\n",
" <td>13</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>26.837560</td>\n",
" <td>2017-12-06 08:07:35</td>\n",
" <td>45600</td>\n",
" <td>0.059639</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45601</th>\n",
" <td>1512333116</td>\n",
" <td>16365</td>\n",
" <td>40842</td>\n",
" <td>6</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>66.577622</td>\n",
" <td>2017-12-04 05:07:14</td>\n",
" <td>45601</td>\n",
" <td>0.144915</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45601</th>\n",
" <td>1512333116</td>\n",
" <td>16365</td>\n",
" <td>40842</td>\n",
" <td>6</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>30.555222</td>\n",
" <td>2017-12-07 02:10:26</td>\n",
" <td>45601</td>\n",
" <td>0.067196</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45602</th>\n",
" <td>1512333116</td>\n",
" <td>16386</td>\n",
" <td>19319</td>\n",
" <td>20</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>111.586185</td>\n",
" <td>2017-12-06 11:31:01</td>\n",
" <td>45602</td>\n",
" <td>0.247969</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45604</th>\n",
" <td>1512333394</td>\n",
" <td>16392</td>\n",
" <td>32070</td>\n",
" <td>16</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>17.635940</td>\n",
" <td>2017-12-08 12:44:17</td>\n",
" <td>45604</td>\n",
" <td>0.038784</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45607</th>\n",
" <td>1512333492</td>\n",
" <td>25943</td>\n",
" <td>13947</td>\n",
" <td>16</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>31.803504</td>\n",
" <td>2017-12-05 00:49:27</td>\n",
" <td>45607</td>\n",
" <td>0.068690</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45609</th>\n",
" <td>1512333564</td>\n",
" <td>16557</td>\n",
" <td>35617</td>\n",
" <td>12</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>42.137717</td>\n",
" <td>2017-12-05 10:21:51</td>\n",
" <td>45609</td>\n",
" <td>0.089903</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45610</th>\n",
" <td>1512333654</td>\n",
" <td>16561</td>\n",
" <td>30199</td>\n",
" <td>21</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>26.655555</td>\n",
" <td>2017-12-05 22:01:17</td>\n",
" <td>45610</td>\n",
" <td>0.057435</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45621</th>\n",
" <td>1512333941</td>\n",
" <td>16838</td>\n",
" <td>21772</td>\n",
" <td>20</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>89.230785</td>\n",
" <td>2017-12-04 04:58:55</td>\n",
" <td>45621</td>\n",
" <td>0.188659</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45622</th>\n",
" <td>1512333943</td>\n",
" <td>16881</td>\n",
" <td>22417</td>\n",
" <td>9</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>11.356870</td>\n",
" <td>2017-12-07 19:04:46</td>\n",
" <td>45622</td>\n",
" <td>0.024976</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45624</th>\n",
" <td>1512334078</td>\n",
" <td>16906</td>\n",
" <td>22726</td>\n",
" <td>17</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>38.217005</td>\n",
" <td>2017-12-04 21:52:03</td>\n",
" <td>45624</td>\n",
" <td>0.082567</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45624</th>\n",
" <td>1512334078</td>\n",
" <td>16906</td>\n",
" <td>22726</td>\n",
" <td>17</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>23.142950</td>\n",
" <td>2017-12-04 21:34:21</td>\n",
" <td>45624</td>\n",
" <td>0.050000</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45628</th>\n",
" <td>1512334078</td>\n",
" <td>17048</td>\n",
" <td>11538</td>\n",
" <td>2</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>163.355168</td>\n",
" <td>2017-12-05 16:15:09</td>\n",
" <td>45628</td>\n",
" <td>0.345583</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45629</th>\n",
" <td>1512334078</td>\n",
" <td>17187</td>\n",
" <td>17460</td>\n",
" <td>17</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>32.375588</td>\n",
" <td>2017-12-04 16:55:59</td>\n",
" <td>45629</td>\n",
" <td>0.068417</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45629</th>\n",
" <td>1512334078</td>\n",
" <td>17187</td>\n",
" <td>17460</td>\n",
" <td>17</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>18.923884</td>\n",
" <td>2017-12-04 16:07:52</td>\n",
" <td>45629</td>\n",
" <td>0.039991</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45629</th>\n",
" <td>1512334078</td>\n",
" <td>17187</td>\n",
" <td>17460</td>\n",
" <td>17</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>13.773179</td>\n",
" <td>2017-12-04 05:01:55</td>\n",
" <td>45629</td>\n",
" <td>0.029979</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45630</th>\n",
" <td>1512334078</td>\n",
" <td>17189</td>\n",
" <td>30399</td>\n",
" <td>11</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>30.228184</td>\n",
" <td>2017-12-04 23:06:07</td>\n",
" <td>45630</td>\n",
" <td>0.064918</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45630</th>\n",
" <td>1512334078</td>\n",
" <td>17189</td>\n",
" <td>30399</td>\n",
" <td>11</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>20.756527</td>\n",
" <td>2017-12-04 17:36:33</td>\n",
" <td>45630</td>\n",
" <td>0.044004</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45630</th>\n",
" <td>1512334078</td>\n",
" <td>17189</td>\n",
" <td>30399</td>\n",
" <td>11</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>4.770418</td>\n",
" <td>2017-12-04 17:17:38</td>\n",
" <td>45630</td>\n",
" <td>0.010113</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45631</th>\n",
" <td>1512334078</td>\n",
" <td>17207</td>\n",
" <td>21691</td>\n",
" <td>11</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>13.970090</td>\n",
" <td>2017-12-04 07:33:42</td>\n",
" <td>45631</td>\n",
" <td>0.029988</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45637</th>\n",
" <td>1512334078</td>\n",
" <td>17332</td>\n",
" <td>11538</td>\n",
" <td>2</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>213.853079</td>\n",
" <td>2017-12-06 06:47:25</td>\n",
" <td>45637</td>\n",
" <td>0.475228</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>27727 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" birth_time matron_id sire_id generation \\\n",
"3005 1511466911 1045 1003 1 \n",
"3007 1511466918 1044 1006 1 \n",
"3008 1511466918 1097 1099 1 \n",
"3010 1511467040 1041 1058 1 \n",
"3010 1511467040 1041 1058 1 \n",
"3010 1511467040 1041 1058 1 \n",
"3011 1511467040 1093 1099 1 \n",
"3012 1511467189 1046 1087 1 \n",
"3012 1511467189 1046 1087 1 \n",
"3012 1511467189 1046 1087 1 \n",
"3013 1511467349 1088 1019 1 \n",
"3017 1511467461 1078 1056 1 \n",
"3018 1511467461 1043 3003 2 \n",
"3018 1511467461 1043 3003 2 \n",
"3020 1511467461 1087 3006 2 \n",
"3020 1511467461 1087 3006 2 \n",
"3020 1511467461 1087 3006 2 \n",
"3021 1511467461 1093 3008 2 \n",
"3022 1511467549 1062 1005 1 \n",
"3024 1511467642 1077 1002 1 \n",
"3029 1511467718 1053 1010 1 \n",
"3029 1511467718 1053 1010 1 \n",
"3029 1511467718 1053 1010 1 \n",
"3030 1511467718 1036 1047 1 \n",
"3031 1511467718 1098 1017 1 \n",
"3031 1511467718 1098 1017 1 \n",
"3032 1511467718 1054 1004 1 \n",
"3032 1511467718 1054 1004 1 \n",
"3032 1511467718 1054 1004 1 \n",
"3033 1511467823 1039 1051 1 \n",
"... ... ... ... ... \n",
"45592 1512333116 16162 28528 17 \n",
"45594 1512333116 16176 38530 17 \n",
"45597 1512333116 16262 5646 4 \n",
"45597 1512333116 16262 5646 4 \n",
"45598 1512333116 16274 27366 17 \n",
"45598 1512333116 16274 27366 17 \n",
"45599 1512333116 16331 6439 14 \n",
"45599 1512333116 16331 6439 14 \n",
"45599 1512333116 16331 6439 14 \n",
"45600 1512333116 16364 13561 13 \n",
"45601 1512333116 16365 40842 6 \n",
"45601 1512333116 16365 40842 6 \n",
"45602 1512333116 16386 19319 20 \n",
"45604 1512333394 16392 32070 16 \n",
"45607 1512333492 25943 13947 16 \n",
"45609 1512333564 16557 35617 12 \n",
"45610 1512333654 16561 30199 21 \n",
"45621 1512333941 16838 21772 20 \n",
"45622 1512333943 16881 22417 9 \n",
"45624 1512334078 16906 22726 17 \n",
"45624 1512334078 16906 22726 17 \n",
"45628 1512334078 17048 11538 2 \n",
"45629 1512334078 17187 17460 17 \n",
"45629 1512334078 17187 17460 17 \n",
"45629 1512334078 17187 17460 17 \n",
"45630 1512334078 17189 30399 11 \n",
"45630 1512334078 17189 30399 11 \n",
"45630 1512334078 17189 30399 11 \n",
"45631 1512334078 17207 21691 11 \n",
"45637 1512334078 17332 11538 2 \n",
"\n",
" genes sold_price_usd \\\n",
"3005 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 75.475318 \n",
"3007 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 101.317700 \n",
"3008 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 5.555534 \n",
"3010 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 23.645100 \n",
"3010 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 9.974763 \n",
"3010 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 4.200592 \n",
"3011 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 6.281243 \n",
"3012 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 478.842000 \n",
"3012 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 399.712992 \n",
"3012 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 4.096416 \n",
"3013 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 231.375440 \n",
"3017 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 195.708110 \n",
"3018 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 7.777746 \n",
"3018 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 3.529732 \n",
"3020 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 124.010446 \n",
"3020 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 82.108207 \n",
"3020 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 8.249211 \n",
"3021 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 5.974832 \n",
"3022 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 46.714600 \n",
"3024 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 598.399623 \n",
"3029 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 551.445594 \n",
"3029 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 25.891600 \n",
"3029 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 18.916080 \n",
"3030 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 4.121639 \n",
"3031 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 937.400000 \n",
"3031 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 2.289915 \n",
"3032 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 981.295931 \n",
"3032 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 314.984033 \n",
"3032 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 7.705208 \n",
"3033 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 47.888720 \n",
"... ... ... \n",
"45592 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 15.392169 \n",
"45594 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 12.723501 \n",
"45597 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 71.372034 \n",
"45597 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 23.875589 \n",
"45598 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 32.143957 \n",
"45598 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 17.731081 \n",
"45599 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 26.936386 \n",
"45599 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 22.709755 \n",
"45599 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 13.582793 \n",
"45600 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 26.837560 \n",
"45601 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 66.577622 \n",
"45601 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 30.555222 \n",
"45602 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 111.586185 \n",
"45604 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 17.635940 \n",
"45607 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 31.803504 \n",
"45609 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 42.137717 \n",
"45610 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 26.655555 \n",
"45621 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 89.230785 \n",
"45622 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 11.356870 \n",
"45624 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 38.217005 \n",
"45624 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 23.142950 \n",
"45628 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 163.355168 \n",
"45629 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 32.375588 \n",
"45629 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 18.923884 \n",
"45629 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 13.773179 \n",
"45630 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 30.228184 \n",
"45630 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 20.756527 \n",
"45630 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 4.770418 \n",
"45631 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 13.970090 \n",
"45637 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... 213.853079 \n",
"\n",
" date kitty_id price_eth \\\n",
"3005 2017-12-02 05:08:56 3005 0.160056 \n",
"3007 2017-12-03 00:22:07 3007 0.220000 \n",
"3008 2017-11-24 08:25:32 3008 0.013552 \n",
"3010 2017-11-29 07:17:53 3010 0.050000 \n",
"3010 2017-11-30 06:41:14 3010 0.022729 \n",
"3010 2017-11-24 04:15:04 3010 0.009996 \n",
"3011 2017-11-24 06:00:39 3011 0.014819 \n",
"3012 2017-12-04 00:15:11 3012 1.000000 \n",
"3012 2017-12-05 09:53:38 3012 0.856569 \n",
"3012 2017-11-24 10:23:41 3012 0.009984 \n",
"3013 2017-12-05 00:18:59 3013 0.499733 \n",
"3017 2017-12-08 02:05:55 3017 0.430394 \n",
"3018 2017-11-24 09:43:28 3018 0.019250 \n",
"3018 2017-11-25 03:49:18 3018 0.007695 \n",
"3020 2017-12-05 03:36:28 3020 0.268801 \n",
"3020 2017-12-05 02:59:27 3020 0.177975 \n",
"3020 2017-11-24 11:04:56 3020 0.019992 \n",
"3021 2017-11-25 13:08:18 3021 0.012687 \n",
"3022 2017-12-02 13:53:03 3022 0.100000 \n",
"3024 2017-12-06 01:31:35 3024 1.297431 \n",
"3029 2017-12-04 05:27:15 3029 1.200295 \n",
"3029 2017-12-02 00:18:55 3029 0.056251 \n",
"3029 2017-11-29 07:21:59 3029 0.040000 \n",
"3030 2017-11-24 11:28:35 3030 0.009989 \n",
"3031 2017-12-05 10:11:05 3031 2.000000 \n",
"3031 2017-11-26 13:20:38 3031 0.005000 \n",
"3032 2017-12-06 06:53:53 3032 2.180653 \n",
"3032 2017-12-06 06:13:25 3032 0.699963 \n",
"3032 2017-11-28 21:47:07 3032 0.016276 \n",
"3033 2017-11-29 16:19:38 3033 0.099592 \n",
"... ... ... ... \n",
"45592 2017-12-04 07:42:22 45592 0.033041 \n",
"45594 2017-12-08 00:43:11 45594 0.027981 \n",
"45597 2017-12-06 06:00:54 45597 0.158604 \n",
"45597 2017-12-07 13:46:57 45597 0.052506 \n",
"45598 2017-12-04 05:13:35 45598 0.069966 \n",
"45598 2017-12-06 14:13:00 45598 0.039402 \n",
"45599 2017-12-04 13:25:22 45599 0.057391 \n",
"45599 2017-12-05 21:59:24 45599 0.048933 \n",
"45599 2017-12-07 06:29:50 45599 0.029871 \n",
"45600 2017-12-06 08:07:35 45600 0.059639 \n",
"45601 2017-12-04 05:07:14 45601 0.144915 \n",
"45601 2017-12-07 02:10:26 45601 0.067196 \n",
"45602 2017-12-06 11:31:01 45602 0.247969 \n",
"45604 2017-12-08 12:44:17 45604 0.038784 \n",
"45607 2017-12-05 00:49:27 45607 0.068690 \n",
"45609 2017-12-05 10:21:51 45609 0.089903 \n",
"45610 2017-12-05 22:01:17 45610 0.057435 \n",
"45621 2017-12-04 04:58:55 45621 0.188659 \n",
"45622 2017-12-07 19:04:46 45622 0.024976 \n",
"45624 2017-12-04 21:52:03 45624 0.082567 \n",
"45624 2017-12-04 21:34:21 45624 0.050000 \n",
"45628 2017-12-05 16:15:09 45628 0.345583 \n",
"45629 2017-12-04 16:55:59 45629 0.068417 \n",
"45629 2017-12-04 16:07:52 45629 0.039991 \n",
"45629 2017-12-04 05:01:55 45629 0.029979 \n",
"45630 2017-12-04 23:06:07 45630 0.064918 \n",
"45630 2017-12-04 17:36:33 45630 0.044004 \n",
"45630 2017-12-04 17:17:38 45630 0.010113 \n",
"45631 2017-12-04 07:33:42 45631 0.029988 \n",
"45637 2017-12-06 06:47:25 45637 0.475228 \n",
"\n",
" sire_genes \\\n",
"3005 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3007 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3008 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3010 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3010 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3010 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3011 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3012 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3012 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3012 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3013 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3017 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3018 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3018 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3020 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3020 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3020 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3021 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3022 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3024 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3029 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3029 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3029 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3030 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3031 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3031 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3032 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3032 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3032 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3033 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"... ... \n",
"45592 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45594 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45597 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45597 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45598 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45598 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45599 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45599 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45599 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45600 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45601 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45601 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45602 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45604 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45607 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45609 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45610 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45621 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45622 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45624 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45624 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45628 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45629 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45629 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45629 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45630 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45630 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45630 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45631 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45637 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"\n",
" matron_genes \n",
"3005 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3007 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3008 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3010 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3010 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3010 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3011 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3012 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3012 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3012 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3013 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3017 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3018 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3018 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3020 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3020 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3020 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3021 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3022 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3024 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3029 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3029 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3029 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3030 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3031 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3031 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3032 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3032 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3032 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"3033 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"... ... \n",
"45592 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45594 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45597 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45597 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45598 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45598 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45599 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45599 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45599 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45600 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45601 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45601 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45602 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45604 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45607 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45609 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45610 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45621 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45622 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45624 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45624 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45628 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45629 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45629 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45629 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45630 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45630 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45630 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45631 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"45637 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
"\n",
"[27727 rows x 11 columns]"
]
},
"execution_count": 521,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# merge and add parent genes\n",
"df = pd.merge(df_genetics, df_sales, how='inner', left_index=True, right_index=True)\n",
"df\n",
"\n",
"# remove rows where we don't have the parent genetics\n",
"mask1 = df['sire_id'].apply(lambda x:int(x) in df_genetics.index)\n",
"mask2 = df['matron_id'].apply(lambda x:int(x) in df_genetics.index)\n",
"df = df[mask1*mask2]\n",
"\n",
"# remove generation 0\n",
"df = df[df['generation']>0]\n",
"len(df)\n",
"\n",
"df['sire_genes']=df['sire_id'].apply(lambda x:df_genetics.loc[x].genes).apply(genestr_to_bits)\n",
"df['matron_genes']=df['matron_id'].apply(lambda x:df_genetics.loc[x].genes).apply(genestr_to_bits)\n",
"df['genes']=df['genes'].apply(genestr_to_bits)\n",
"\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 528,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:54:50.809681Z",
"start_time": "2017-12-09T01:54:49.978090Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"((27727, 256, 2), (27727, 256))"
]
},
"execution_count": 528,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# parent genes\n",
"X = np.array([df['sire_genes'], df['matron_genes']])\n",
"X = np.transpose(X, (1,2,0))\n",
"\n",
"# child genes\n",
"Y = np.stack(df['genes'].values)\n",
"X.shape, Y.shape"
]
},
{
"cell_type": "code",
"execution_count": 529,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:54:50.818108Z",
"start_time": "2017-12-09T01:54:50.811249Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"256"
]
},
"execution_count": 529,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a=df['sire_genes']\n",
"min([len(b) for b in a])"
]
},
{
"cell_type": "code",
"execution_count": 530,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:54:51.392946Z",
"start_time": "2017-12-09T01:54:50.819805Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"((24954, 256, 2), (24954, 256))"
]
},
"execution_count": 530,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# split into test and train, val (& shuffle)\n",
"import sklearn.model_selection\n",
"X_train, X_test, y_train, y_test = sklearn.model_selection.train_test_split(X,Y, random_state=42, test_size=0.1)\n",
"X_train, X_val, y_train, y_val = sklearn.model_selection.train_test_split(X_train,Y_train, random_state=42, test_size=0.1)\n",
"X_train.shape, y_train.shape"
]
},
{
"cell_type": "code",
"execution_count": 581,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T02:19:10.775011Z",
"start_time": "2017-12-09T02:15:26.291075Z"
}
},
"outputs": [
{
"ename": "KeyboardInterrupt",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-581-ffb6e5f5711d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Check for overlap between y and y_train\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0moverlap\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0my_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m>\u001b[0m\u001b[0;36m0\u001b[0m \u001b[0;32min\u001b[0m \u001b[0my_train\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0my\u001b[0m \u001b[0;32min\u001b[0m \u001b[0my_test\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0moverlap\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m<ipython-input-581-ffb6e5f5711d>\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Check for overlap between y and y_train\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0moverlap\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0my_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m>\u001b[0m\u001b[0;36m0\u001b[0m \u001b[0;32min\u001b[0m \u001b[0my_train\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0my\u001b[0m \u001b[0;32min\u001b[0m \u001b[0my_test\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0moverlap\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
]
}
],
"source": [
"# Check for overlap between y and y_train\n",
"overlap = np.array([((y - y_train)==0).all(-1).sum()>0 in y_train for y in y_test])\n",
"overlap.sum()/len(y_test)"
]
},
{
"cell_type": "code",
"execution_count": 585,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T02:23:28.277230Z",
"start_time": "2017-12-09T02:20:44.495483Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 1000/1000 [02:43<00:00, 6.11it/s]\n"
]
}
],
"source": [
"# # NOTE: there is ~50% overlap between test and train :( because of repeated breeding\n",
"# # For now I'll just leave it and try to get an accuracy higher than the overlap\n",
"\n",
"# # check for overlap\n",
"# overlaps = []\n",
"# for y in tqdm(y_test[:1000]):\n",
"# overlaps.append(((y - y_train)==0).all(-1).sum()>0)\n",
"# overlaps = np.array(overlaps)\n",
"# print('overlap fraction', overlaps.sum()/len(overlaps))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T02:24:43.706674Z",
"start_time": "2017-12-09T02:24:43.701528Z"
}
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:07:43.456217Z",
"start_time": "2017-12-09T01:07:43.453853Z"
}
},
"source": [
"# Train"
]
},
{
"cell_type": "code",
"execution_count": 531,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:54:51.396546Z",
"start_time": "2017-12-09T01:54:51.394619Z"
}
},
"outputs": [],
"source": [
"import keras"
]
},
{
"cell_type": "code",
"execution_count": 543,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T01:57:02.963859Z",
"start_time": "2017-12-09T01:57:02.905721Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"_________________________________________________________________\n",
"Layer (type) Output Shape Param # \n",
"=================================================================\n",
"input_40 (InputLayer) (None, 256, 2) 0 \n",
"_________________________________________________________________\n",
"flatten_36 (Flatten) (None, 512) 0 \n",
"_________________________________________________________________\n",
"dense_36 (Dense) (None, 256) 131328 \n",
"_________________________________________________________________\n",
"dense_37 (Dense) (None, 256) 65792 \n",
"=================================================================\n",
"Total params: 197,120\n",
"Trainable params: 197,120\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"# Simple model with two layers\n",
"model = keras.models.Sequential()\n",
"model.add(keras.layers.InputLayer((256,2)))\n",
"model.add(keras.layers.Flatten())\n",
"model.add(keras.layers.Dense(256, activation='elu'))\n",
"model.add(keras.layers.Dense(256, activation='sigmoid'))\n",
"\n",
"model.compile(loss='categorical_crossentropy',\n",
" optimizer=keras.optimizers.Adam(lr=1e-3),\n",
" metrics=['accuracy'])\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 544,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T02:05:14.746685Z",
"start_time": "2017-12-09T01:57:03.763481Z"
},
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/100\n",
"24954/24954 [==============================] - 5s - loss: 508.7665 - acc: 0.0907 \n",
"Epoch 2/100\n",
"24954/24954 [==============================] - 4s - loss: 503.2542 - acc: 0.0828 \n",
"Epoch 3/100\n",
"24954/24954 [==============================] - 4s - loss: 502.2601 - acc: 0.0971 \n",
"Epoch 4/100\n",
"24954/24954 [==============================] - 4s - loss: 501.8326 - acc: 0.0468 \n",
"Epoch 5/100\n",
"24954/24954 [==============================] - 4s - loss: 501.5762 - acc: 0.0706 \n",
"Epoch 6/100\n",
"24954/24954 [==============================] - 4s - loss: 501.3692 - acc: 0.1013 \n",
"Epoch 7/100\n",
"24954/24954 [==============================] - 4s - loss: 501.2114 - acc: 0.1160 \n",
"Epoch 8/100\n",
"24954/24954 [==============================] - 4s - loss: 501.0631 - acc: 0.1080 \n",
"Epoch 9/100\n",
"24954/24954 [==============================] - 4s - loss: 500.9294 - acc: 0.1333 \n",
"Epoch 10/100\n",
"24954/24954 [==============================] - 5s - loss: 500.8025 - acc: 0.1472 \n",
"Epoch 11/100\n",
"24954/24954 [==============================] - 5s - loss: 500.6628 - acc: 0.1409 \n",
"Epoch 12/100\n",
"24954/24954 [==============================] - 5s - loss: 500.5388 - acc: 0.1506 \n",
"Epoch 13/100\n",
"24954/24954 [==============================] - 5s - loss: 500.4203 - acc: 0.1564 \n",
"Epoch 14/100\n",
"24954/24954 [==============================] - 5s - loss: 500.3127 - acc: 0.1752 \n",
"Epoch 15/100\n",
"24954/24954 [==============================] - 5s - loss: 500.2032 - acc: 0.1860 \n",
"Epoch 16/100\n",
"24954/24954 [==============================] - 5s - loss: 500.0808 - acc: 0.1923 \n",
"Epoch 17/100\n",
"24954/24954 [==============================] - 5s - loss: 499.9710 - acc: 0.1900 \n",
"Epoch 18/100\n",
"24954/24954 [==============================] - 5s - loss: 499.8602 - acc: 0.2000 \n",
"Epoch 19/100\n",
"24954/24954 [==============================] - 5s - loss: 499.7545 - acc: 0.1910 \n",
"Epoch 20/100\n",
"24954/24954 [==============================] - 5s - loss: 499.6652 - acc: 0.2022 \n",
"Epoch 21/100\n",
"24954/24954 [==============================] - 4s - loss: 499.5557 - acc: 0.1997 \n",
"Epoch 22/100\n",
"24954/24954 [==============================] - 5s - loss: 499.4768 - acc: 0.2096 \n",
"Epoch 23/100\n",
"24954/24954 [==============================] - 5s - loss: 499.3653 - acc: 0.2014 \n",
"Epoch 24/100\n",
"24954/24954 [==============================] - 4s - loss: 499.2876 - acc: 0.2222 \n",
"Epoch 25/100\n",
"24954/24954 [==============================] - 4s - loss: 499.1896 - acc: 0.2224 \n",
"Epoch 26/100\n",
"24954/24954 [==============================] - 6s - loss: 499.0884 - acc: 0.2323 \n",
"Epoch 27/100\n",
"24954/24954 [==============================] - 5s - loss: 499.0261 - acc: 0.2369 \n",
"Epoch 28/100\n",
"24954/24954 [==============================] - 5s - loss: 498.9483 - acc: 0.2440 \n",
"Epoch 29/100\n",
"24954/24954 [==============================] - 5s - loss: 498.8798 - acc: 0.2555 \n",
"Epoch 30/100\n",
"24954/24954 [==============================] - 5s - loss: 498.7836 - acc: 0.2652 \n",
"Epoch 31/100\n",
"24954/24954 [==============================] - 5s - loss: 498.7234 - acc: 0.2802 \n",
"Epoch 32/100\n",
"24954/24954 [==============================] - 5s - loss: 498.6712 - acc: 0.2870 \n",
"Epoch 33/100\n",
"24954/24954 [==============================] - 5s - loss: 498.6031 - acc: 0.3033 \n",
"Epoch 34/100\n",
"24954/24954 [==============================] - 5s - loss: 498.5419 - acc: 0.3184 \n",
"Epoch 35/100\n",
"24954/24954 [==============================] - ETA: 0s - loss: 498.4404 - acc: 0.322 - 5s - loss: 498.4631 - acc: 0.3229 \n",
"Epoch 36/100\n",
"24954/24954 [==============================] - 5s - loss: 498.4073 - acc: 0.3339 \n",
"Epoch 37/100\n",
"24954/24954 [==============================] - 5s - loss: 498.3550 - acc: 0.3508 \n",
"Epoch 38/100\n",
"24954/24954 [==============================] - 4s - loss: 498.2924 - acc: 0.3740 \n",
"Epoch 39/100\n",
"24954/24954 [==============================] - 4s - loss: 498.2358 - acc: 0.3892 \n",
"Epoch 40/100\n",
"24954/24954 [==============================] - 4s - loss: 498.1778 - acc: 0.4148 \n",
"Epoch 41/100\n",
"24954/24954 [==============================] - 4s - loss: 498.1198 - acc: 0.4259 \n",
"Epoch 42/100\n",
"24954/24954 [==============================] - 4s - loss: 498.0702 - acc: 0.4421 \n",
"Epoch 43/100\n",
"24954/24954 [==============================] - 4s - loss: 498.0349 - acc: 0.4627 \n",
"Epoch 44/100\n",
"24954/24954 [==============================] - 4s - loss: 497.9844 - acc: 0.4617 \n",
"Epoch 45/100\n",
"24954/24954 [==============================] - 4s - loss: 497.9390 - acc: 0.4922 \n",
"Epoch 46/100\n",
"24954/24954 [==============================] - 4s - loss: 497.8961 - acc: 0.5116 \n",
"Epoch 47/100\n",
"24954/24954 [==============================] - 4s - loss: 497.8525 - acc: 0.5299 \n",
"Epoch 48/100\n",
"24954/24954 [==============================] - 4s - loss: 497.8148 - acc: 0.5372 \n",
"Epoch 49/100\n",
"24954/24954 [==============================] - 4s - loss: 497.7646 - acc: 0.5615 \n",
"Epoch 50/100\n",
"24954/24954 [==============================] - 4s - loss: 497.7226 - acc: 0.5784 \n",
"Epoch 51/100\n",
"24954/24954 [==============================] - 4s - loss: 497.6797 - acc: 0.5886 \n",
"Epoch 52/100\n",
"24954/24954 [==============================] - 4s - loss: 497.6548 - acc: 0.5903 \n",
"Epoch 53/100\n",
"24954/24954 [==============================] - 4s - loss: 497.6038 - acc: 0.6122 \n",
"Epoch 54/100\n",
"24954/24954 [==============================] - 4s - loss: 497.5729 - acc: 0.6191 \n",
"Epoch 55/100\n",
"24954/24954 [==============================] - 4s - loss: 497.5331 - acc: 0.6262 \n",
"Epoch 56/100\n",
"24954/24954 [==============================] - 4s - loss: 497.5200 - acc: 0.6542 \n",
"Epoch 57/100\n",
"24954/24954 [==============================] - 4s - loss: 497.4703 - acc: 0.6478 \n",
"Epoch 58/100\n",
"24954/24954 [==============================] - 5s - loss: 497.4415 - acc: 0.6641 \n",
"Epoch 59/100\n",
"24954/24954 [==============================] - 5s - loss: 497.4102 - acc: 0.6716 \n",
"Epoch 60/100\n",
"24954/24954 [==============================] - 5s - loss: 497.3693 - acc: 0.6777 \n",
"Epoch 61/100\n",
"24954/24954 [==============================] - 5s - loss: 497.3296 - acc: 0.6932 \n",
"Epoch 62/100\n",
"24954/24954 [==============================] - 5s - loss: 497.3165 - acc: 0.7019 \n",
"Epoch 63/100\n",
"24954/24954 [==============================] - 5s - loss: 497.2862 - acc: 0.7270 \n",
"Epoch 64/100\n",
"24954/24954 [==============================] - 5s - loss: 497.2591 - acc: 0.7323 \n",
"Epoch 65/100\n",
"24954/24954 [==============================] - 5s - loss: 497.2193 - acc: 0.7383 \n",
"Epoch 66/100\n",
"24954/24954 [==============================] - 5s - loss: 497.1976 - acc: 0.7318 \n",
"Epoch 67/100\n",
"24954/24954 [==============================] - 5s - loss: 497.1773 - acc: 0.7330 \n",
"Epoch 68/100\n",
"24954/24954 [==============================] - 5s - loss: 497.1554 - acc: 0.7534 \n",
"Epoch 69/100\n",
"24954/24954 [==============================] - 5s - loss: 497.0994 - acc: 0.7620 \n",
"Epoch 70/100\n",
"24954/24954 [==============================] - 5s - loss: 497.1024 - acc: 0.7591 \n",
"Epoch 71/100\n",
"24954/24954 [==============================] - 5s - loss: 497.0706 - acc: 0.7655 \n",
"Epoch 72/100\n",
"24954/24954 [==============================] - 5s - loss: 497.0300 - acc: 0.7703 \n",
"Epoch 73/100\n",
"24954/24954 [==============================] - 5s - loss: 497.0103 - acc: 0.7759 \n",
"Epoch 74/100\n",
"24954/24954 [==============================] - 5s - loss: 496.9908 - acc: 0.7790 \n",
"Epoch 75/100\n",
"24954/24954 [==============================] - 5s - loss: 496.9939 - acc: 0.7741 \n",
"Epoch 76/100\n",
"24954/24954 [==============================] - 5s - loss: 496.9489 - acc: 0.7874 \n",
"Epoch 77/100\n",
"24954/24954 [==============================] - 5s - loss: 496.9348 - acc: 0.7836 \n",
"Epoch 78/100\n",
"24954/24954 [==============================] - 5s - loss: 496.9030 - acc: 0.7872 \n",
"Epoch 79/100\n",
"24954/24954 [==============================] - 5s - loss: 496.8914 - acc: 0.7955 \n",
"Epoch 80/100\n",
"24954/24954 [==============================] - 5s - loss: 496.8739 - acc: 0.7982 \n",
"Epoch 81/100\n",
"24954/24954 [==============================] - 5s - loss: 496.8343 - acc: 0.8059 \n",
"Epoch 82/100\n",
"24954/24954 [==============================] - 5s - loss: 496.8141 - acc: 0.8062 \n",
"Epoch 83/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"24954/24954 [==============================] - 5s - loss: 496.7922 - acc: 0.8149 \n",
"Epoch 84/100\n",
"24954/24954 [==============================] - 4s - loss: 496.7672 - acc: 0.8147 \n",
"Epoch 85/100\n",
"24954/24954 [==============================] - 4s - loss: 496.7608 - acc: 0.8108 \n",
"Epoch 86/100\n",
"24954/24954 [==============================] - 4s - loss: 496.7526 - acc: 0.8283 \n",
"Epoch 87/100\n",
"24954/24954 [==============================] - 4s - loss: 496.7163 - acc: 0.8276 \n",
"Epoch 88/100\n",
"24954/24954 [==============================] - 4s - loss: 496.7204 - acc: 0.8274 \n",
"Epoch 89/100\n",
"24954/24954 [==============================] - 4s - loss: 496.6877 - acc: 0.8336 \n",
"Epoch 90/100\n",
"24954/24954 [==============================] - 4s - loss: 496.6718 - acc: 0.8333 \n",
"Epoch 91/100\n",
"24954/24954 [==============================] - 4s - loss: 496.6418 - acc: 0.8322 \n",
"Epoch 92/100\n",
"24954/24954 [==============================] - 4s - loss: 496.6560 - acc: 0.8411 \n",
"Epoch 93/100\n",
"24954/24954 [==============================] - 5s - loss: 496.6134 - acc: 0.8406 \n",
"Epoch 94/100\n",
"24954/24954 [==============================] - 5s - loss: 496.5966 - acc: 0.8433 \n",
"Epoch 95/100\n",
"24954/24954 [==============================] - 4s - loss: 496.5886 - acc: 0.8423 \n",
"Epoch 96/100\n",
"24954/24954 [==============================] - 4s - loss: 496.5726 - acc: 0.8496 \n",
"Epoch 97/100\n",
"24954/24954 [==============================] - 4s - loss: 496.5361 - acc: 0.8467 \n",
"Epoch 98/100\n",
"24954/24954 [==============================] - 4s - loss: 496.5321 - acc: 0.8535 \n",
"Epoch 99/100\n",
"24954/24954 [==============================] - 4s - loss: 496.5290 - acc: 0.8458 \n",
"Epoch 100/100\n",
"24954/24954 [==============================] - 4s - loss: 496.4984 - acc: 0.8490 \n"
]
}
],
"source": [
"history = model.fit(X_train,y_train, epochs=100)"
]
},
{
"cell_type": "code",
"execution_count": 549,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T02:07:24.353484Z",
"start_time": "2017-12-09T02:07:24.207550Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7febfab5cc50>"
]
},
"execution_count": 549,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<matplotlib.figure.Figure at 0x7febfabc36d8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pd.DataFrame(history.history)['acc'].plot()"
]
},
{
"cell_type": "code",
"execution_count": 552,
"metadata": {
"ExecuteTime": {
"end_time": "2017-12-09T02:08:03.160197Z",
"start_time": "2017-12-09T02:08:02.932726Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2656/2773 [===========================>..] - ETA: 0s"
]
},
{
"data": {
"text/plain": [
"{'acc': 0.8968626036998214, 'loss': 505.5500093082465}"
]
},
"execution_count": 552,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"metrics = model.evaluate(X_test,y_test)\n",
"metrics = dict(zip(model.metrics_names, metrics))\n",
"metrics"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "jupyter3",
"language": "python",
"name": "jupyter3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.3"
},
"toc": {
"colors": {
"hover_highlight": "#DAA520",
"navigate_num": "#000000",
"navigate_text": "#333333",
"running_highlight": "#FF0000",
"selected_highlight": "#FFD700",
"sidebar_border": "#EEEEEE",
"wrapper_background": "#FFFFFF"
},
"moveMenuLeft": true,
"nav_menu": {
"height": "55px",
"width": "254px"
},
"navigate_menu": true,
"number_sections": true,
"sideBar": true,
"threshold": 4,
"toc_cell": false,
"toc_section_display": "block",
"toc_window_display": false,
"widenNotebook": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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