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iwatobipen/data_prep.ipynb

Created June 18, 2019 13:23
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data_prep.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Molecule</th>\n",
" <th>Standard Type</th>\n",
" <th>Standard Relation</th>\n",
" <th>Standard Value</th>\n",
" <th>Standard Units</th>\n",
" <th>pChEMBL Value</th>\n",
" <th>Comment</th>\n",
" <th>Compound Key</th>\n",
" <th>Assay</th>\n",
" <th>Assay Description</th>\n",
" <th>...</th>\n",
" <th>Published Relation</th>\n",
" <th>Published Value</th>\n",
" <th>Published Units</th>\n",
" <th>Canonical Smiles</th>\n",
" <th>Data Validity Comment</th>\n",
" <th>Document Journal</th>\n",
" <th>Document Year</th>\n",
" <th>SRC ID</th>\n",
" <th>UO Units</th>\n",
" <th>Potential Duplicate</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>CHEMBL1983006</td>\n",
" <td>Ki</td>\n",
" <td>&gt;</td>\n",
" <td>1584.89</td>\n",
" <td>nM</td>\n",
" <td>NaN</td>\n",
" <td>inactive</td>\n",
" <td>SID103904900</td>\n",
" <td>CHEMBL1963742</td>\n",
" <td>PUBCHEM_BIOASSAY: Navigating the Kinome. (Clas...</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>COc1cc(C(=O)O)c(Cl)cc1NC(=O)Nc2cnc(cn2)C#N</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>7</td>\n",
" <td>UO_0000065</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>CHEMBL2007559</td>\n",
" <td>Ki</td>\n",
" <td>&gt;</td>\n",
" <td>5011.87</td>\n",
" <td>nM</td>\n",
" <td>NaN</td>\n",
" <td>inactive</td>\n",
" <td>SID103905005</td>\n",
" <td>CHEMBL1963742</td>\n",
" <td>PUBCHEM_BIOASSAY: Navigating the Kinome. (Clas...</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>CCCNC(=O)c1ccc(Nc2nc(NCC(F)(F)F)c3sccc3n2)cc1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>7</td>\n",
" <td>UO_0000065</td>\n",
" <td>False</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2 rows × 43 columns</p>\n",
"</div>"
],
"text/plain": [
" Molecule Standard Type Standard Relation Standard Value \\\n",
"0 CHEMBL1983006 Ki > 1584.89 \n",
"1 CHEMBL2007559 Ki > 5011.87 \n",
"\n",
" Standard Units pChEMBL Value Comment Compound Key Assay \\\n",
"0 nM NaN inactive SID103904900 CHEMBL1963742 \n",
"1 nM NaN inactive SID103905005 CHEMBL1963742 \n",
"\n",
" Assay Description ... \\\n",
"0 PUBCHEM_BIOASSAY: Navigating the Kinome. (Clas... ... \n",
"1 PUBCHEM_BIOASSAY: Navigating the Kinome. (Clas... ... \n",
"\n",
" Published Relation Published Value Published Units \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"\n",
" Canonical Smiles Data Validity Comment \\\n",
"0 COc1cc(C(=O)O)c(Cl)cc1NC(=O)Nc2cnc(cn2)C#N NaN \n",
"1 CCCNC(=O)c1ccc(Nc2nc(NCC(F)(F)F)c3sccc3n2)cc1 NaN \n",
"\n",
" Document Journal Document Year SRC ID UO Units Potential Duplicate \n",
"0 NaN NaN 7 UO_0000065 False \n",
"1 NaN NaN 7 UO_0000065 False \n",
"\n",
"[2 rows x 43 columns]"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from rdkit import Chem\n",
"df = pd.read_csv('CHEMBL25-chembl_activity-JAK3.tsv', header=0, sep='\\t')\n",
"df.head(2)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from rdkit.Chem import PandasTools"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
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" <th>Class</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>CHEMBL1983006</td>\n",
" <td>Ki</td>\n",
" <td>></td>\n",
" <td>1584.89</td>\n",
" <td>nM</td>\n",
" <td>NaN</td>\n",
" <td>inactive</td>\n",
" <td>SID103904900</td>\n",
" <td>CHEMBL1963742</td>\n",
" <td>PUBCHEM_BIOASSAY: Navigating the Kinome. (Class of assay: other) Panel member name: JAK3</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td><img 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\" alt=\"Mol\"/></td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>CHEMBL2007559</td>\n",
" <td>Ki</td>\n",
" <td>></td>\n",
" <td>5011.87</td>\n",
" <td>nM</td>\n",
" <td>NaN</td>\n",
" <td>inactive</td>\n",
" <td>SID103905005</td>\n",
" <td>CHEMBL1963742</td>\n",
" <td>PUBCHEM_BIOASSAY: Navigating the Kinome. (Class of assay: other) Panel member name: JAK3</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>CCCNC(=O)c1ccc(Nc2nc(NCC(F)(F)F)c3sccc3n2)cc1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>7</td>\n",
" <td>UO_0000065</td>\n",
" <td>False</td>\n",
" <td><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2 rows × 45 columns</p>\n",
"</div>"
],
"text/plain": [
" Molecule Standard Type Standard Relation Standard Value \\\n",
"0 CHEMBL1983006 Ki > 1584.89 \n",
"1 CHEMBL2007559 Ki > 5011.87 \n",
"\n",
" Standard Units pChEMBL Value Comment Compound Key Assay \\\n",
"0 nM NaN inactive SID103904900 CHEMBL1963742 \n",
"1 nM NaN inactive SID103905005 CHEMBL1963742 \n",
"\n",
" Assay Description ... Published Units \\\n",
"0 PUBCHEM_BIOASSAY: Navigating the Kinome. (Clas... ... NaN \n",
"1 PUBCHEM_BIOASSAY: Navigating the Kinome. (Clas... ... NaN \n",
"\n",
" Canonical Smiles Data Validity Comment \\\n",
"0 COc1cc(C(=O)O)c(Cl)cc1NC(=O)Nc2cnc(cn2)C#N NaN \n",
"1 CCCNC(=O)c1ccc(Nc2nc(NCC(F)(F)F)c3sccc3n2)cc1 NaN \n",
"\n",
" Document Journal Document Year SRC ID UO Units Potential Duplicate \\\n",
"0 NaN NaN 7 UO_0000065 False \n",
"1 NaN NaN 7 UO_0000065 False \n",
"\n",
" ROMol Class \n",
"0 <img src=\"data:image/png;base64,iVBORw0KGgoAAA... 0 \n",
"1 <img src=\"data:image/png;base64,iVBORw0KGgoAAA... 0 \n",
"\n",
"[2 rows x 45 columns]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"PandasTools.AddMoleculeColumnToFrame(df, smilesCol=\"Canonical Smiles\")\n",
"df['Class'] = np.where(df.Comment =='inactive', 0, 1)\n",
"df.head(2)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"PandasTools.WriteSDF(df, 'CHEMBL25-chembl_activity-JAK3.sdf', properties=df.columns)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Molecule', 'Standard Type', 'Standard Relation', 'Standard Value',\n",
" 'Standard Units', 'pChEMBL Value', 'Comment', 'Compound Key', 'Assay',\n",
" 'Assay Description', 'BAO Format', 'Target', 'Target Pref. Name',\n",
" 'Target Organism', 'Target Type', 'Document', 'Source', 'Max Phase',\n",
" '#Ro5 Violations', 'Molecular Weight', 'Ligand Efficiency BEI',\n",
" 'Ligand Efficiency LE', 'Ligand Efficiency LLE',\n",
" 'Ligand Efficiency SEI', 'ALogP', 'Assay Organism',\n",
" 'Assay Tissue ChEMBL ID', 'Assay Tissue Name', 'Assay Cell Type',\n",
" 'Assay Subcellular Fraction', 'Organism Tax ID', 'BAO Format ID',\n",
" 'Published Type', 'Published Relation', 'Published Value',\n",
" 'Published Units', 'Canonical Smiles', 'Data Validity Comment',\n",
" 'Document Journal', 'Document Year', 'SRC ID', 'UO Units',\n",
" 'Potential Duplicate', 'ROMol', 'Class'],\n",
" dtype='object')"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.columns"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 CHEMBL1983006\n",
"1 CHEMBL2007559\n",
"2 CHEMBL1992363\n",
"3 CHEMBL234085\n",
"4 CHEMBL1994830\n",
"5 CHEMBL2005631\n",
"6 CHEMBL1966175\n",
"7 CHEMBL1969664\n",
"8 CHEMBL2004438\n",
"9 CHEMBL1992581\n",
"10 CHEMBL260092\n",
"11 CHEMBL554\n",
"12 CHEMBL215152\n",
"13 CHEMBL1970083\n",
"14 CHEMBL1976240\n",
"15 CHEMBL1987009\n",
"16 CHEMBL2000801\n",
"17 CHEMBL2007002\n",
"18 CHEMBL1987007\n",
"19 CHEMBL2007151\n",
"20 CHEMBL1682545\n",
"21 CHEMBL1975903\n",
"22 CHEMBL482967\n",
"23 CHEMBL583144\n",
"24 CHEMBL1982660\n",
"25 CHEMBL1971947\n",
"26 CHEMBL412142\n",
"27 CHEMBL1992231\n",
"28 CHEMBL2002723\n",
"29 CHEMBL1983393\n",
" ... \n",
"870 CHEMBL24828\n",
"871 CHEMBL306380\n",
"872 CHEMBL491473\n",
"873 CHEMBL296586\n",
"874 CHEMBL1976040\n",
"875 CHEMBL38380\n",
"876 CHEMBL522892\n",
"877 CHEMBL574738\n",
"878 CHEMBL1983268\n",
"879 CHEMBL1870106\n",
"880 CHEMBL1973720\n",
"881 CHEMBL191003\n",
"882 CHEMBL1975128\n",
"883 CHEMBL1940137\n",
"884 CHEMBL1986943\n",
"885 CHEMBL10\n",
"886 CHEMBL483158\n",
"887 CHEMBL1978166\n",
"888 CHEMBL404367\n",
"889 CHEMBL316264\n",
"890 CHEMBL1986603\n",
"891 CHEMBL474432\n",
"892 CHEMBL1972584\n",
"893 CHEMBL941\n",
"894 CHEMBL1421\n",
"895 CHEMBL189963\n",
"896 CHEMBL261849\n",
"897 CHEMBL296468\n",
"898 CHEMBL1825138\n",
"899 CHEMBL939\n",
"Name: Molecule, Length: 900, dtype: object"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.Molecule"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"result = pd.read_csv('../svc_rf_gp_output/optuna_svc_rf.csv', header=1)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
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" <td>TrialState.COMPLETE</td>\n",
" <td>0.238889</td>\n",
" <td>2019-06-18 22:03:30.888691</td>\n",
" <td>2019-06-18 22:03:32.526781</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>3.875849e+04</td>\n",
" <td>6.267289e-03</td>\n",
" <td>0.761111</td>\n",
" <td>0.238889</td>\n",
" <td>0.997222</td>\n",
" <td>0.002778</td>\n",
" <td>7838bed6-a6e3-4ef9-9d4e-3b467af0281f</td>\n",
" <td>0.231930</td>\n",
" <td>46</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>35</td>\n",
" <td>35</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.244444</td>\n",
" <td>2019-06-18 22:03:14.052246</td>\n",
" <td>2019-06-18 22:03:14.307057</td>\n",
" <td>RandomForest</td>\n",
" <td>23.386241</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.755556</td>\n",
" <td>0.244444</td>\n",
" <td>0.969444</td>\n",
" <td>0.030556</td>\n",
" <td>5b4410bb-15c7-43e0-9dee-580e3fc50a1a</td>\n",
" <td>0.208318</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.244444</td>\n",
" <td>2019-06-18 22:02:25.751972</td>\n",
" <td>2019-06-18 22:02:25.967720</td>\n",
" <td>RandomForest</td>\n",
" <td>10.384591</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.755556</td>\n",
" <td>0.244444</td>\n",
" <td>0.868056</td>\n",
" <td>0.131944</td>\n",
" <td>3f0324c4-8edf-4ae4-bc12-08f0bdcda640</td>\n",
" <td>0.208328</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>14</td>\n",
" <td>14</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.250000</td>\n",
" <td>2019-06-18 22:02:44.712761</td>\n",
" <td>2019-06-18 22:02:44.959307</td>\n",
" <td>RandomForest</td>\n",
" <td>16.872689</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.750000</td>\n",
" <td>0.250000</td>\n",
" <td>0.947222</td>\n",
" <td>0.052778</td>\n",
" <td>3dadcc6c-3850-4992-a41b-db757aea7c77</td>\n",
" <td>0.199994</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>28</td>\n",
" <td>28</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.255556</td>\n",
" <td>2019-06-18 22:03:03.944803</td>\n",
" <td>2019-06-18 22:03:04.195927</td>\n",
" <td>RandomForest</td>\n",
" <td>14.513422</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>0.898611</td>\n",
" <td>0.101389</td>\n",
" <td>be02eac9-0cb7-47c0-bb89-820c6c9bf8f3</td>\n",
" <td>0.199975</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>48</th>\n",
" <td>48</td>\n",
" <td>48</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.255556</td>\n",
" <td>2019-06-18 22:03:34.796357</td>\n",
" <td>2019-06-18 22:03:36.385644</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>5.606199e+07</td>\n",
" <td>4.089875e-03</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>0.997222</td>\n",
" <td>0.002778</td>\n",
" <td>673a9e0f-920c-4b7c-8e83-f3c550477a5b</td>\n",
" <td>0.248616</td>\n",
" <td>48</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>44</td>\n",
" <td>44</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.272222</td>\n",
" <td>2019-06-18 22:03:28.389051</td>\n",
" <td>2019-06-18 22:03:28.641659</td>\n",
" <td>RandomForest</td>\n",
" <td>19.177346</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.727778</td>\n",
" <td>0.272222</td>\n",
" <td>0.958333</td>\n",
" <td>0.041667</td>\n",
" <td>12575390-ee42-4852-8ca3-7ac65cc89180</td>\n",
" <td>0.204171</td>\n",
" <td>44</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.283333</td>\n",
" <td>2019-06-18 22:02:23.489646</td>\n",
" <td>2019-06-18 22:02:23.701520</td>\n",
" <td>RandomForest</td>\n",
" <td>7.494106</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.716667</td>\n",
" <td>0.283333</td>\n",
" <td>0.816667</td>\n",
" <td>0.183333</td>\n",
" <td>c057026c-9d19-494b-ba3b-ac413151db60</td>\n",
" <td>0.198596</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.305556</td>\n",
" <td>2019-06-18 22:02:48.991047</td>\n",
" <td>2019-06-18 22:02:50.344952</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>1.968448e+01</td>\n",
" <td>8.110338e-05</td>\n",
" <td>0.694444</td>\n",
" <td>0.305556</td>\n",
" <td>0.769444</td>\n",
" <td>0.230556</td>\n",
" <td>9a1c0f18-9074-4b93-98ba-d16a42f8b45b</td>\n",
" <td>0.240263</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>26</td>\n",
" <td>26</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.311111</td>\n",
" <td>2019-06-18 22:03:01.480459</td>\n",
" <td>2019-06-18 22:03:01.695358</td>\n",
" <td>RandomForest</td>\n",
" <td>3.628460</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.688889</td>\n",
" <td>0.311111</td>\n",
" <td>0.770833</td>\n",
" <td>0.229167</td>\n",
" <td>54d591eb-0258-48e8-b1a8-bb55a798ad42</td>\n",
" <td>0.229171</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.311111</td>\n",
" <td>2019-06-18 22:02:23.217196</td>\n",
" <td>2019-06-18 22:02:23.480897</td>\n",
" <td>RandomForest</td>\n",
" <td>3.189117</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.688889</td>\n",
" <td>0.311111</td>\n",
" <td>0.768056</td>\n",
" <td>0.231944</td>\n",
" <td>5a05bd35-d912-44cf-a573-c7785c570106</td>\n",
" <td>0.236106</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.311111</td>\n",
" <td>2019-06-18 22:02:25.976975</td>\n",
" <td>2019-06-18 22:02:27.984899</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>8.611775e+06</td>\n",
" <td>1.594400e-01</td>\n",
" <td>0.688889</td>\n",
" <td>0.311111</td>\n",
" <td>0.997222</td>\n",
" <td>0.002778</td>\n",
" <td>3677709d-ddd7-494d-ba85-94774ba10da7</td>\n",
" <td>0.236135</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>38</td>\n",
" <td>38</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.311111</td>\n",
" <td>2019-06-18 22:03:18.210785</td>\n",
" <td>2019-06-18 22:03:18.447247</td>\n",
" <td>RandomForest</td>\n",
" <td>2.612600</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.688889</td>\n",
" <td>0.311111</td>\n",
" <td>0.768056</td>\n",
" <td>0.231944</td>\n",
" <td>603332e9-54e0-4c45-a1a6-0eebaac59689</td>\n",
" <td>0.238922</td>\n",
" <td>38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>30</td>\n",
" <td>30</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.316667</td>\n",
" <td>2019-06-18 22:03:06.210424</td>\n",
" <td>2019-06-18 22:03:06.434670</td>\n",
" <td>RandomForest</td>\n",
" <td>2.636162</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.683333</td>\n",
" <td>0.316667</td>\n",
" <td>0.765278</td>\n",
" <td>0.234722</td>\n",
" <td>5615de2f-65cc-4b9a-a645-ac773d0dfc19</td>\n",
" <td>0.249976</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>42</td>\n",
" <td>42</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:03:24.052467</td>\n",
" <td>2019-06-18 22:03:26.124511</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>4.299862e+04</td>\n",
" <td>1.365733e+02</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.997222</td>\n",
" <td>0.002778</td>\n",
" <td>f8052310-f9df-41f2-9fd3-3370eeedb79b</td>\n",
" <td>0.245819</td>\n",
" <td>42</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:02:23.710633</td>\n",
" <td>2019-06-18 22:02:25.742917</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>3.776908e+02</td>\n",
" <td>7.730571e+00</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.997222</td>\n",
" <td>0.002778</td>\n",
" <td>0f1208d7-81e6-48ab-8bfb-926ff021ebfc</td>\n",
" <td>0.245819</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>9</td>\n",
" <td>9</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:02:34.687704</td>\n",
" <td>2019-06-18 22:02:35.820173</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>3.573428e-05</td>\n",
" <td>2.553051e+06</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>164ef9fb-4f72-445b-88f6-d04db13359b4</td>\n",
" <td>0.255551</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>39</td>\n",
" <td>39</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:03:18.462685</td>\n",
" <td>2019-06-18 22:03:19.588095</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>4.621037e-02</td>\n",
" <td>1.971082e-07</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>ce8ec1f1-5c7b-4c0d-8646-9485cbc0cd2f</td>\n",
" <td>0.255551</td>\n",
" <td>39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>34</td>\n",
" <td>34</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:03:12.023242</td>\n",
" <td>2019-06-18 22:03:14.038953</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>6.201592e+09</td>\n",
" <td>1.045333e+03</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.997222</td>\n",
" <td>0.002778</td>\n",
" <td>c8fcba5c-b520-44d9-b336-f9bba4522be3</td>\n",
" <td>0.245819</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>31</td>\n",
" <td>31</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:03:06.450457</td>\n",
" <td>2019-06-18 22:03:07.576235</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>2.717450e-02</td>\n",
" <td>6.573343e-06</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>0067967a-2675-418a-bdb4-3f29762d438a</td>\n",
" <td>0.255551</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>29</td>\n",
" <td>29</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:03:04.208968</td>\n",
" <td>2019-06-18 22:03:06.197034</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>1.783897e+06</td>\n",
" <td>2.467258e+09</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.997222</td>\n",
" <td>0.002778</td>\n",
" <td>3f633d42-7342-478a-add0-a88ac8b42a9d</td>\n",
" <td>0.245819</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>23</td>\n",
" <td>23</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:02:57.211652</td>\n",
" <td>2019-06-18 22:02:58.356036</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>3.177046e+02</td>\n",
" <td>3.598362e-09</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>f033ddc8-a373-4302-bb67-11feb5001d19</td>\n",
" <td>0.255551</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>21</td>\n",
" <td>21</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:02:53.840331</td>\n",
" <td>2019-06-18 22:02:54.982711</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>1.438888e-10</td>\n",
" <td>1.620458e+05</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>1892cf22-b7fb-45d1-97d1-5ee1cc87daa2</td>\n",
" <td>0.255551</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:02:52.692608</td>\n",
" <td>2019-06-18 22:02:53.828506</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>1.948666e-08</td>\n",
" <td>8.859487e+05</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>3898ae6a-aed8-4d2d-9ab3-60cec5306c2e</td>\n",
" <td>0.255551</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>19</td>\n",
" <td>19</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:02:51.519592</td>\n",
" <td>2019-06-18 22:02:52.679547</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>8.552122e-07</td>\n",
" <td>3.382792e-05</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>db3a56b5-fdf5-45ff-ac0b-e451e62cfe48</td>\n",
" <td>0.255551</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>18</td>\n",
" <td>18</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:02:50.357311</td>\n",
" <td>2019-06-18 22:02:51.508984</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>8.240277e-07</td>\n",
" <td>6.746000e-01</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>995f7df6-586a-4e1b-9805-acc6d580dd0c</td>\n",
" <td>0.255551</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>TrialState.COMPLETE</td>\n",
" <td>0.333333</td>\n",
" <td>2019-06-18 22:03:00.599254</td>\n",
" <td>2019-06-18 22:03:01.465070</td>\n",
" <td>SVC</td>\n",
" <td>NaN</td>\n",
" <td>2.014107e+09</td>\n",
" <td>5.117789e-10</td>\n",
" <td>0.666667</td>\n",
" <td>0.333333</td>\n",
" <td>0.744444</td>\n",
" <td>0.255556</td>\n",
" <td>628ce1b6-a030-44ae-8eba-be75e268dfdb</td>\n",
" <td>0.309717</td>\n",
" <td>25</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 Unnamed: 1 Unnamed: 2 Unnamed: 3 \\\n",
"16 16 16 TrialState.COMPLETE 0.200000 \n",
"0 0 0 TrialState.COMPLETE 0.216667 \n",
"15 15 15 TrialState.COMPLETE 0.216667 \n",
"47 47 47 TrialState.COMPLETE 0.216667 \n",
"45 45 45 TrialState.COMPLETE 0.216667 \n",
"43 43 43 TrialState.COMPLETE 0.216667 \n",
"41 41 41 TrialState.COMPLETE 0.216667 \n",
"40 40 40 TrialState.COMPLETE 0.216667 \n",
"37 37 37 TrialState.COMPLETE 0.216667 \n",
"33 33 33 TrialState.COMPLETE 0.216667 \n",
"32 32 32 TrialState.COMPLETE 0.216667 \n",
"27 27 27 TrialState.COMPLETE 0.216667 \n",
"24 24 24 TrialState.COMPLETE 0.216667 \n",
"22 22 22 TrialState.COMPLETE 0.216667 \n",
"49 49 49 TrialState.COMPLETE 0.216667 \n",
"10 10 10 TrialState.COMPLETE 0.216667 \n",
"6 6 6 TrialState.COMPLETE 0.216667 \n",
"7 7 7 TrialState.COMPLETE 0.216667 \n",
"8 8 8 TrialState.COMPLETE 0.216667 \n",
"12 12 12 TrialState.COMPLETE 0.216667 \n",
"13 13 13 TrialState.COMPLETE 0.216667 \n",
"11 11 11 TrialState.COMPLETE 0.216667 \n",
"36 36 36 TrialState.COMPLETE 0.227778 \n",
"46 46 46 TrialState.COMPLETE 0.238889 \n",
"35 35 35 TrialState.COMPLETE 0.244444 \n",
"4 4 4 TrialState.COMPLETE 0.244444 \n",
"14 14 14 TrialState.COMPLETE 0.250000 \n",
"28 28 28 TrialState.COMPLETE 0.255556 \n",
"48 48 48 TrialState.COMPLETE 0.255556 \n",
"44 44 44 TrialState.COMPLETE 0.272222 \n",
"2 2 2 TrialState.COMPLETE 0.283333 \n",
"17 17 17 TrialState.COMPLETE 0.305556 \n",
"26 26 26 TrialState.COMPLETE 0.311111 \n",
"1 1 1 TrialState.COMPLETE 0.311111 \n",
"5 5 5 TrialState.COMPLETE 0.311111 \n",
"38 38 38 TrialState.COMPLETE 0.311111 \n",
"30 30 30 TrialState.COMPLETE 0.316667 \n",
"42 42 42 TrialState.COMPLETE 0.333333 \n",
"3 3 3 TrialState.COMPLETE 0.333333 \n",
"9 9 9 TrialState.COMPLETE 0.333333 \n",
"39 39 39 TrialState.COMPLETE 0.333333 \n",
"34 34 34 TrialState.COMPLETE 0.333333 \n",
"31 31 31 TrialState.COMPLETE 0.333333 \n",
"29 29 29 TrialState.COMPLETE 0.333333 \n",
"23 23 23 TrialState.COMPLETE 0.333333 \n",
"21 21 21 TrialState.COMPLETE 0.333333 \n",
"20 20 20 TrialState.COMPLETE 0.333333 \n",
"19 19 19 TrialState.COMPLETE 0.333333 \n",
"18 18 18 TrialState.COMPLETE 0.333333 \n",
"25 25 25 TrialState.COMPLETE 0.333333 \n",
"\n",
" Unnamed: 4 Unnamed: 5 classifier \\\n",
"16 2019-06-18 22:02:47.169348 2019-06-18 22:02:48.979594 SVC \n",
"0 2019-06-18 22:02:19.740744 2019-06-18 22:02:23.206707 GP \n",
"15 2019-06-18 22:02:44.971267 2019-06-18 22:02:47.159137 GP \n",
"47 2019-06-18 22:03:32.542369 2019-06-18 22:03:34.780375 GP \n",
"45 2019-06-18 22:03:28.656780 2019-06-18 22:03:30.873618 GP \n",
"43 2019-06-18 22:03:26.139444 2019-06-18 22:03:28.373341 GP \n",
"41 2019-06-18 22:03:21.813688 2019-06-18 22:03:24.037341 GP \n",
"40 2019-06-18 22:03:19.603166 2019-06-18 22:03:21.798719 GP \n",
"37 2019-06-18 22:03:15.989643 2019-06-18 22:03:18.196465 GP \n",
"33 2019-06-18 22:03:09.810656 2019-06-18 22:03:12.010288 GP \n",
"32 2019-06-18 22:03:07.589158 2019-06-18 22:03:09.796816 GP \n",
"27 2019-06-18 22:03:01.709206 2019-06-18 22:03:03.931287 GP \n",
"24 2019-06-18 22:02:58.368511 2019-06-18 22:03:00.586441 GP \n",
"22 2019-06-18 22:02:54.997181 2019-06-18 22:02:57.198490 GP \n",
"49 2019-06-18 22:03:36.401421 2019-06-18 22:03:38.635362 GP \n",
"10 2019-06-18 22:02:35.830986 2019-06-18 22:02:38.048653 GP \n",
"6 2019-06-18 22:02:27.993969 2019-06-18 22:02:30.216894 GP \n",
"7 2019-06-18 22:02:30.226862 2019-06-18 22:02:32.445038 GP \n",
"8 2019-06-18 22:02:32.455555 2019-06-18 22:02:34.677195 GP \n",
"12 2019-06-18 22:02:40.268297 2019-06-18 22:02:42.482124 GP \n",
"13 2019-06-18 22:02:42.493654 2019-06-18 22:02:44.701361 GP \n",
"11 2019-06-18 22:02:38.059341 2019-06-18 22:02:40.258514 GP \n",
"36 2019-06-18 22:03:14.320827 2019-06-18 22:03:15.973941 SVC \n",
"46 2019-06-18 22:03:30.888691 2019-06-18 22:03:32.526781 SVC \n",
"35 2019-06-18 22:03:14.052246 2019-06-18 22:03:14.307057 RandomForest \n",
"4 2019-06-18 22:02:25.751972 2019-06-18 22:02:25.967720 RandomForest \n",
"14 2019-06-18 22:02:44.712761 2019-06-18 22:02:44.959307 RandomForest \n",
"28 2019-06-18 22:03:03.944803 2019-06-18 22:03:04.195927 RandomForest \n",
"48 2019-06-18 22:03:34.796357 2019-06-18 22:03:36.385644 SVC \n",
"44 2019-06-18 22:03:28.389051 2019-06-18 22:03:28.641659 RandomForest \n",
"2 2019-06-18 22:02:23.489646 2019-06-18 22:02:23.701520 RandomForest \n",
"17 2019-06-18 22:02:48.991047 2019-06-18 22:02:50.344952 SVC \n",
"26 2019-06-18 22:03:01.480459 2019-06-18 22:03:01.695358 RandomForest \n",
"1 2019-06-18 22:02:23.217196 2019-06-18 22:02:23.480897 RandomForest \n",
"5 2019-06-18 22:02:25.976975 2019-06-18 22:02:27.984899 SVC \n",
"38 2019-06-18 22:03:18.210785 2019-06-18 22:03:18.447247 RandomForest \n",
"30 2019-06-18 22:03:06.210424 2019-06-18 22:03:06.434670 RandomForest \n",
"42 2019-06-18 22:03:24.052467 2019-06-18 22:03:26.124511 SVC \n",
"3 2019-06-18 22:02:23.710633 2019-06-18 22:02:25.742917 SVC \n",
"9 2019-06-18 22:02:34.687704 2019-06-18 22:02:35.820173 SVC \n",
"39 2019-06-18 22:03:18.462685 2019-06-18 22:03:19.588095 SVC \n",
"34 2019-06-18 22:03:12.023242 2019-06-18 22:03:14.038953 SVC \n",
"31 2019-06-18 22:03:06.450457 2019-06-18 22:03:07.576235 SVC \n",
"29 2019-06-18 22:03:04.208968 2019-06-18 22:03:06.197034 SVC \n",
"23 2019-06-18 22:02:57.211652 2019-06-18 22:02:58.356036 SVC \n",
"21 2019-06-18 22:02:53.840331 2019-06-18 22:02:54.982711 SVC \n",
"20 2019-06-18 22:02:52.692608 2019-06-18 22:02:53.828506 SVC \n",
"19 2019-06-18 22:02:51.519592 2019-06-18 22:02:52.679547 SVC \n",
"18 2019-06-18 22:02:50.357311 2019-06-18 22:02:51.508984 SVC \n",
"25 2019-06-18 22:03:00.599254 2019-06-18 22:03:01.465070 SVC \n",
"\n",
" rf_max_depth svc_c svc_gamma test_arcc test_error \\\n",
"16 NaN 7.221305e+03 1.907887e-02 0.800000 0.200000 \n",
"0 NaN NaN NaN 0.783333 0.216667 \n",
"15 NaN NaN NaN 0.783333 0.216667 \n",
"47 NaN NaN NaN 0.783333 0.216667 \n",
"45 NaN NaN NaN 0.783333 0.216667 \n",
"43 NaN NaN NaN 0.783333 0.216667 \n",
"41 NaN NaN NaN 0.783333 0.216667 \n",
"40 NaN NaN NaN 0.783333 0.216667 \n",
"37 NaN NaN NaN 0.783333 0.216667 \n",
"33 NaN NaN NaN 0.783333 0.216667 \n",
"32 NaN NaN NaN 0.783333 0.216667 \n",
"27 NaN NaN NaN 0.783333 0.216667 \n",
"24 NaN NaN NaN 0.783333 0.216667 \n",
"22 NaN NaN NaN 0.783333 0.216667 \n",
"49 NaN NaN NaN 0.783333 0.216667 \n",
"10 NaN NaN NaN 0.783333 0.216667 \n",
"6 NaN NaN NaN 0.783333 0.216667 \n",
"7 NaN NaN NaN 0.783333 0.216667 \n",
"8 NaN NaN NaN 0.783333 0.216667 \n",
"12 NaN NaN NaN 0.783333 0.216667 \n",
"13 NaN NaN NaN 0.783333 0.216667 \n",
"11 NaN NaN NaN 0.783333 0.216667 \n",
"36 NaN 1.331151e+05 8.807112e-03 0.772222 0.227778 \n",
"46 NaN 3.875849e+04 6.267289e-03 0.761111 0.238889 \n",
"35 23.386241 NaN NaN 0.755556 0.244444 \n",
"4 10.384591 NaN NaN 0.755556 0.244444 \n",
"14 16.872689 NaN NaN 0.750000 0.250000 \n",
"28 14.513422 NaN NaN 0.744444 0.255556 \n",
"48 NaN 5.606199e+07 4.089875e-03 0.744444 0.255556 \n",
"44 19.177346 NaN NaN 0.727778 0.272222 \n",
"2 7.494106 NaN NaN 0.716667 0.283333 \n",
"17 NaN 1.968448e+01 8.110338e-05 0.694444 0.305556 \n",
"26 3.628460 NaN NaN 0.688889 0.311111 \n",
"1 3.189117 NaN NaN 0.688889 0.311111 \n",
"5 NaN 8.611775e+06 1.594400e-01 0.688889 0.311111 \n",
"38 2.612600 NaN NaN 0.688889 0.311111 \n",
"30 2.636162 NaN NaN 0.683333 0.316667 \n",
"42 NaN 4.299862e+04 1.365733e+02 0.666667 0.333333 \n",
"3 NaN 3.776908e+02 7.730571e+00 0.666667 0.333333 \n",
"9 NaN 3.573428e-05 2.553051e+06 0.666667 0.333333 \n",
"39 NaN 4.621037e-02 1.971082e-07 0.666667 0.333333 \n",
"34 NaN 6.201592e+09 1.045333e+03 0.666667 0.333333 \n",
"31 NaN 2.717450e-02 6.573343e-06 0.666667 0.333333 \n",
"29 NaN 1.783897e+06 2.467258e+09 0.666667 0.333333 \n",
"23 NaN 3.177046e+02 3.598362e-09 0.666667 0.333333 \n",
"21 NaN 1.438888e-10 1.620458e+05 0.666667 0.333333 \n",
"20 NaN 1.948666e-08 8.859487e+05 0.666667 0.333333 \n",
"19 NaN 8.552122e-07 3.382792e-05 0.666667 0.333333 \n",
"18 NaN 8.240277e-07 6.746000e-01 0.666667 0.333333 \n",
"25 NaN 2.014107e+09 5.117789e-10 0.666667 0.333333 \n",
"\n",
" train_acc train_error uuid val_acc \\\n",
"16 0.997222 0.002778 9f280919-31cf-40db-921b-85916c35b5e3 0.216632 \n",
"0 0.997222 0.002778 0b3e313e-0f26-444c-877b-c6f548300280 0.249966 \n",
"15 0.997222 0.002778 2b87ae07-02b9-461b-9ec3-2cfd16332122 0.249966 \n",
"47 0.997222 0.002778 38a62ff9-323b-40ee-87b2-9d3ccd5b4a33 0.249966 \n",
"45 0.997222 0.002778 f02eed52-24dd-4a2c-86ef-300d3f73c62e 0.249966 \n",
"43 0.997222 0.002778 3092efb3-0cf5-408c-a1d9-51d513a5cb89 0.249966 \n",
"41 0.997222 0.002778 383621d0-e98f-48a1-8912-501a6d733680 0.249966 \n",
"40 0.997222 0.002778 473e29a4-cb94-47c5-8500-65474b5690e9 0.249966 \n",
"37 0.997222 0.002778 9c97801f-0e50-4719-9437-aca5c5724243 0.249966 \n",
"33 0.997222 0.002778 11263e94-e411-403c-8605-a711e3b7ab7c 0.249966 \n",
"32 0.997222 0.002778 bcd8293b-c780-44f8-806f-93ab085ef38d 0.249966 \n",
"27 0.997222 0.002778 3a6a2d46-c138-45e4-9973-c44d6db565bb 0.249966 \n",
"24 0.997222 0.002778 7d08cb32-3915-4806-81eb-3cabcca63aa6 0.249966 \n",
"22 0.997222 0.002778 fefcda86-fcd5-4e5e-99de-cce1729a32ad 0.249966 \n",
"49 0.997222 0.002778 b4962aa7-3d16-4aa9-afa8-40467df000e3 0.249966 \n",
"10 0.997222 0.002778 799ee9bb-22c3-4e62-b190-be73f7532b4f 0.249966 \n",
"6 0.997222 0.002778 2e498977-dd3b-40ed-bb15-cbcf4a4416b5 0.249966 \n",
"7 0.997222 0.002778 5213a44d-4282-4fd5-89e3-78cd679971ec 0.249966 \n",
"8 0.997222 0.002778 fa638e71-2f25-4e1e-abed-439a1e4f37de 0.249966 \n",
"12 0.997222 0.002778 1f91a5f7-9018-4953-bb70-d9e2e9bf6776 0.249966 \n",
"13 0.997222 0.002778 508c6672-9679-4e82-901b-d40752d0f15a 0.249966 \n",
"11 0.997222 0.002778 951f5d98-2101-4a88-b2c4-1cb057b6f568 0.249966 \n",
"36 0.997222 0.002778 b657627c-f239-476c-ba08-2f6e4d6f0aac 0.224975 \n",
"46 0.997222 0.002778 7838bed6-a6e3-4ef9-9d4e-3b467af0281f 0.231930 \n",
"35 0.969444 0.030556 5b4410bb-15c7-43e0-9dee-580e3fc50a1a 0.208318 \n",
"4 0.868056 0.131944 3f0324c4-8edf-4ae4-bc12-08f0bdcda640 0.208328 \n",
"14 0.947222 0.052778 3dadcc6c-3850-4992-a41b-db757aea7c77 0.199994 \n",
"28 0.898611 0.101389 be02eac9-0cb7-47c0-bb89-820c6c9bf8f3 0.199975 \n",
"48 0.997222 0.002778 673a9e0f-920c-4b7c-8e83-f3c550477a5b 0.248616 \n",
"44 0.958333 0.041667 12575390-ee42-4852-8ca3-7ac65cc89180 0.204171 \n",
"2 0.816667 0.183333 c057026c-9d19-494b-ba3b-ac413151db60 0.198596 \n",
"17 0.769444 0.230556 9a1c0f18-9074-4b93-98ba-d16a42f8b45b 0.240263 \n",
"26 0.770833 0.229167 54d591eb-0258-48e8-b1a8-bb55a798ad42 0.229171 \n",
"1 0.768056 0.231944 5a05bd35-d912-44cf-a573-c7785c570106 0.236106 \n",
"5 0.997222 0.002778 3677709d-ddd7-494d-ba85-94774ba10da7 0.236135 \n",
"38 0.768056 0.231944 603332e9-54e0-4c45-a1a6-0eebaac59689 0.238922 \n",
"30 0.765278 0.234722 5615de2f-65cc-4b9a-a645-ac773d0dfc19 0.249976 \n",
"42 0.997222 0.002778 f8052310-f9df-41f2-9fd3-3370eeedb79b 0.245819 \n",
"3 0.997222 0.002778 0f1208d7-81e6-48ab-8bfb-926ff021ebfc 0.245819 \n",
"9 0.744444 0.255556 164ef9fb-4f72-445b-88f6-d04db13359b4 0.255551 \n",
"39 0.744444 0.255556 ce8ec1f1-5c7b-4c0d-8646-9485cbc0cd2f 0.255551 \n",
"34 0.997222 0.002778 c8fcba5c-b520-44d9-b336-f9bba4522be3 0.245819 \n",
"31 0.744444 0.255556 0067967a-2675-418a-bdb4-3f29762d438a 0.255551 \n",
"29 0.997222 0.002778 3f633d42-7342-478a-add0-a88ac8b42a9d 0.245819 \n",
"23 0.744444 0.255556 f033ddc8-a373-4302-bb67-11feb5001d19 0.255551 \n",
"21 0.744444 0.255556 1892cf22-b7fb-45d1-97d1-5ee1cc87daa2 0.255551 \n",
"20 0.744444 0.255556 3898ae6a-aed8-4d2d-9ab3-60cec5306c2e 0.255551 \n",
"19 0.744444 0.255556 db3a56b5-fdf5-45ff-ac0b-e451e62cfe48 0.255551 \n",
"18 0.744444 0.255556 995f7df6-586a-4e1b-9805-acc6d580dd0c 0.255551 \n",
"25 0.744444 0.255556 628ce1b6-a030-44ae-8eba-be75e268dfdb 0.309717 \n",
"\n",
" _number \n",
"16 16 \n",
"0 0 \n",
"15 15 \n",
"47 47 \n",
"45 45 \n",
"43 43 \n",
"41 41 \n",
"40 40 \n",
"37 37 \n",
"33 33 \n",
"32 32 \n",
"27 27 \n",
"24 24 \n",
"22 22 \n",
"49 49 \n",
"10 10 \n",
"6 6 \n",
"7 7 \n",
"8 8 \n",
"12 12 \n",
"13 13 \n",
"11 11 \n",
"36 36 \n",
"46 46 \n",
"35 35 \n",
"4 4 \n",
"14 14 \n",
"28 28 \n",
"48 48 \n",
"44 44 \n",
"2 2 \n",
"17 17 \n",
"26 26 \n",
"1 1 \n",
"5 5 \n",
"38 38 \n",
"30 30 \n",
"42 42 \n",
"3 3 \n",
"9 9 \n",
"39 39 \n",
"34 34 \n",
"31 31 \n",
"29 29 \n",
"23 23 \n",
"21 21 \n",
"20 20 \n",
"19 19 \n",
"18 18 \n",
"25 25 "
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"result.sort_values('test_arcc', ascending=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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