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DanielaLaura/working2.ipynb

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working2.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
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"text": [
"C:\\Users\\Daniela\\Anaconda3.5\\lib\\site-packages\\sklearn\\ensemble\\weight_boosting.py:29: DeprecationWarning: numpy.core.umath_tests is an internal NumPy module and should not be imported. It will be removed in a future NumPy release.\n",
" from numpy.core.umath_tests import inner1d\n"
]
}
],
"source": [
"import pandas as pd\n",
"from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier\n",
"from IPython.display import display\n",
"\n",
"from sklearn import metrics"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"sub = pd.read_csv('tutorial_train_data1.csv', index_col='actor_account_id')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
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" Unnamed: 0 dt_cnt con_cnt log_cnt char_cnt exp_amt \\\n",
"actor_account_id \n",
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},
"execution_count": 3,
"metadata": {},
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],
"source": [
"sub.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"customer1= pd.read_csv(\"00C172F0.csv\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"sub = pd.read_csv('tutorial_train_data1.csv', index_col='actor_account_id')\n",
"train = pd.DataFrame( index=sub.index)\n",
"for actor_account_id in train.index:\n",
" seg = pd.read_csv('traindata/' + actor_account_id + '.csv')\n",
" \n",
" log = seg['logid'].values\n",
" time = seg['time'].values\n",
" \n",
" train.loc[actor_account_id, 'log_cnt'] = len(log)\n",
" train.loc[actor_account_id, 'con_cnt']= seg.loc[seg['logid']== 1003, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'exp_amt'] = seg.loc[seg['logid']== 1016, 'use_value1_num'].sum()\n",
" train.loc[actor_account_id, 'exp_mastery_amt'] = seg.loc[seg['logid']== 1016, 'use_value3_num'].sum()\n",
" train.loc[actor_account_id, 'exhaust_cnt'] = seg.loc[seg['logid']== 1201, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'die_cnt'] = seg.loc[seg['logid']== 1202, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'quest_cnt'] = seg.loc[seg['logid']== 5004, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'party_join_cnt'] = seg.loc[seg['logid']== 1102, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'party_kick_cnt'] = seg.loc[seg['logid']== 1106, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'guild_join_cnt'] = seg.loc[seg['logid']== 6005, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'guild_withdraw_cnt'] = seg.loc[seg['logid']== 6009, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'teleport_cnt'] =seg.loc[seg['logid']== 1010, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'pve_cnt']= seg.loc[seg['logid']== 1208, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'pvp_cnt']= seg.loc[seg['logid']== 1209, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'ducel_end_cnt']= len(set(seg[(seg.logid ==1404) & (seg.logid ==1406)].count()))\n",
" train.loc[actor_account_id, 'spent_money']= seg.loc[seg['logid']== 1010, 'use_value2_num'].sum()\n",
" train.loc[actor_account_id, 'increased_money']= seg.loc[seg['logid']== 1017, 'use_value2_num'].sum()\n",
" train.loc[actor_account_id, 'decreased_money']= seg.loc[seg['logid']== 1018, 'use_value2_num'].sum()\n",
" train.loc[actor_account_id, 'increased_money2']= seg.loc[seg['logid']== 2006, 'use_value2_num'].sum()\n",
" train.loc[actor_account_id, 'increased_money3']= seg.loc[seg['logid']== 2016, 'use_value2_num'].sum()\n",
" train.loc[actor_account_id, 'decreased_money2']= seg.loc[seg['logid']== 2105, 'use_value2_num'].sum()\n",
" #train.loc[actor_account_id, 'total_increase_money']= train['increased_money']+ train['increased_money2']+ train['increased_money3']\n",
" #train.loc[actor_account_id, 'total_decrease_money']= train['decreased_money']+train['decreased_money2']\n",
" train.loc[actor_account_id, 'increased_experience']= seg.loc[seg['logid']== 1016, 'use_value1_num'].sum()\n",
" train.loc[actor_account_id, 'total_experience']= seg.loc[seg['logid']== 1016, 'new_value2_num'].sum()\n",
" train.loc[actor_account_id, 'in_item']= seg.loc[seg['logid']== 1022, 'use_value1_num'].count() \n",
" train.loc[actor_account_id, 'decreased_item']= seg.loc[seg['logid']== 1023, 'use_value1_num'].count()\n",
" train.loc[actor_account_id, 'increased_item1']= seg.loc[seg['logid']== 1022, 'new_value2_num'].sum()\n",
" train.loc[actor_account_id, 'decreased_item1']= seg.loc[seg['logid']== 1023, 'new_value2_num'].sum()\n",
" train.loc[actor_account_id, 'del_cnt']= seg.loc[seg['logid']== 1012, 'actor_account_id'].count()\n",
" train.loc[actor_account_id, 'guild_create_cnt']= seg.loc[seg['logid']== 6001, 'actor_account_id'].count() \n",
" #train[actor_account_id, 'guild_destroy_cnt']= seg.loc[seg['logid']== 6002, 'actor_account_id'].count() \n",
" train.loc[actor_account_id, 'min_time'] =time.min()\n",
" train.loc[actor_account_id, 'max_time'] = time.max()\n",
" \n",
" #train.loc[actor_account_id, 'sum'] = x.sum()\n",
" #train.loc[actor_account_id, 'range'] = x.max()-x.min()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
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" <td>2016-04-29 16:54:39.814</td>\n",
" <td>2016-05-08 20:16:30.029</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 31 columns</p>\n",
"</div>"
],
"text/plain": [
" log_cnt con_cnt exp_amt exp_mastery_amt exhaust_cnt \\\n",
"actor_account_id \n",
"003B1E06 37423.0 176.0 77029.0 4229266.0 171.0 \n",
"003D42CD 33900.0 102.0 1797006.0 11180677.0 141.0 \n",
"006093EB 49063.0 237.0 0.0 12847058.0 177.0 \n",
"0067CFF2 4608.0 28.0 0.0 1801082.0 31.0 \n",
"00731F6C 4881.0 21.0 0.0 2862484.0 21.0 \n",
"\n",
" die_cnt quest_cnt party_join_cnt party_kick_cnt \\\n",
"actor_account_id \n",
"003B1E06 114.0 754.0 148.0 0.0 \n",
"003D42CD 84.0 822.0 104.0 0.0 \n",
"006093EB 109.0 831.0 273.0 0.0 \n",
"0067CFF2 27.0 49.0 12.0 0.0 \n",
"00731F6C 11.0 90.0 12.0 0.0 \n",
"\n",
" guild_join_cnt ... \\\n",
"actor_account_id ... \n",
"003B1E06 0.0 ... \n",
"003D42CD 1.0 ... \n",
"006093EB 0.0 ... \n",
"0067CFF2 0.0 ... \n",
"00731F6C 0.0 ... \n",
"\n",
" increased_experience total_experience in_item \\\n",
"actor_account_id \n",
"003B1E06 77029.0 6.408195e+09 4729.0 \n",
"003D42CD 1797006.0 3.432078e+09 3390.0 \n",
"006093EB 0.0 1.147595e+10 6395.0 \n",
"0067CFF2 0.0 6.347596e+08 665.0 \n",
"00731F6C 0.0 9.571554e+08 461.0 \n",
"\n",
" decreased_item increased_item1 decreased_item1 del_cnt \\\n",
"actor_account_id \n",
"003B1E06 2516.0 816621.0 225331.0 3.0 \n",
"003D42CD 2469.0 261674.0 329964.0 3.0 \n",
"006093EB 3467.0 1053594.0 368977.0 0.0 \n",
"0067CFF2 474.0 124022.0 81095.0 0.0 \n",
"00731F6C 257.0 57062.0 13773.0 0.0 \n",
"\n",
" guild_create_cnt min_time \\\n",
"actor_account_id \n",
"003B1E06 0.0 2016-04-01 18:44:53.524 \n",
"003D42CD 0.0 2016-04-04 14:13:54.266 \n",
"006093EB 0.0 2016-04-01 11:09:13.026 \n",
"0067CFF2 0.0 2016-04-01 00:00:39.522 \n",
"00731F6C 0.0 2016-04-29 16:54:39.814 \n",
"\n",
" max_time \n",
"actor_account_id \n",
"003B1E06 2016-05-08 10:49:15.998 \n",
"003D42CD 2016-05-11 03:34:49.201 \n",
"006093EB 2016-05-10 15:35:21.701 \n",
"0067CFF2 2016-05-11 01:03:42.471 \n",
"00731F6C 2016-05-08 20:16:30.029 \n",
"\n",
"[5 rows x 31 columns]"
]
},
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