{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "#import sys\n", "#!{sys.executable} -m pip install scikit-learn" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['beneficiary', 'provider', 'inpatient', 'outpatient']\n" ] } ], "source": [ "from sqlalchemy import create_engine\n", "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "sns.set()\n", "\n", "#connect to the database\n", "engine = create_engine('postgresql://postgres:pharezpic@123@localhost:5432/healthcare_insurance')\n", "\n", "print(engine.table_names())" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "beneficiary = pd.read_sql('beneficiary', engine)\n", "provider = pd.read_sql('SELECT * FROM provider', engine)\n", "inpatient = pd.read_sql('SELECT * FROM inpatient', engine)\n", "outpatient = pd.read_sql('SELECT * FROM outpatient', engine)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AdmissionDtAttendingPhysicianBeneIDClaimEndDtClaimIDClaimStartDtClmAdmitDiagnosisCodeClmDiagnosisCode_1ClmDiagnosisCode_10ClmDiagnosisCode_2...ClmProcedureCode_4ClmProcedureCode_5ClmProcedureCode_6DeductibleAmtPaidDiagnosisGroupCodeDischargeDtInscClaimAmtReimbursedOperatingPhysicianOtherPhysicianProviderID
02009-04-12PHY390922BENE110012009-04-18CLM466142009-04-1278661970None4019...NoneNoneNone1068.02012009-04-1826000NoneNonePRV55912
12009-08-31PHY318495BENE110012009-09-02CLM660482009-08-3161866186None2948...NoneNoneNone1068.07502009-09-025000PHY318495NonePRV55907
22009-09-17PHY372395BENE110012009-09-20CLM683582009-09-172959029623None30390...NoneNoneNone1068.08832009-09-205000NonePHY324689PRV56046
32009-02-14PHY369659BENE110112009-02-22CLM384122009-02-1443143491None2762...NoneNoneNone1068.0672009-02-225000PHY392961PHY349768PRV52405
42009-08-13PHY379376BENE110142009-08-30CLM636892009-08-137832142None3051...NoneNoneNone1068.09752009-08-3010000PHY398258NonePRV56614
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5 rows × 30 columns

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" ], "text/plain": [ " AdmissionDt AttendingPhysician BeneID ClaimEndDt ClaimID \\\n", "0 2009-04-12 PHY390922 BENE11001 2009-04-18 CLM46614 \n", "1 2009-08-31 PHY318495 BENE11001 2009-09-02 CLM66048 \n", "2 2009-09-17 PHY372395 BENE11001 2009-09-20 CLM68358 \n", "3 2009-02-14 PHY369659 BENE11011 2009-02-22 CLM38412 \n", "4 2009-08-13 PHY379376 BENE11014 2009-08-30 CLM63689 \n", "\n", " ClaimStartDt ClmAdmitDiagnosisCode ClmDiagnosisCode_1 ClmDiagnosisCode_10 \\\n", "0 2009-04-12 7866 1970 None \n", "1 2009-08-31 6186 6186 None \n", "2 2009-09-17 29590 29623 None \n", "3 2009-02-14 431 43491 None \n", "4 2009-08-13 78321 42 None \n", "\n", " ClmDiagnosisCode_2 ... ClmProcedureCode_4 ClmProcedureCode_5 \\\n", "0 4019 ... None None \n", "1 2948 ... None None \n", "2 30390 ... None None \n", "3 2762 ... None None \n", "4 3051 ... None None \n", "\n", " ClmProcedureCode_6 DeductibleAmtPaid DiagnosisGroupCode DischargeDt \\\n", "0 None 1068.0 201 2009-04-18 \n", "1 None 1068.0 750 2009-09-02 \n", "2 None 1068.0 883 2009-09-20 \n", "3 None 1068.0 67 2009-02-22 \n", "4 None 1068.0 975 2009-08-30 \n", "\n", " InscClaimAmtReimbursed OperatingPhysician OtherPhysician ProviderID \n", "0 26000 None None PRV55912 \n", "1 5000 PHY318495 None PRV55907 \n", "2 5000 None PHY324689 PRV56046 \n", "3 5000 PHY392961 PHY349768 PRV52405 \n", "4 10000 PHY398258 None PRV56614 \n", "\n", "[5 rows x 30 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inpatient.head()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AttendingPhysicianBeneIDClaimEndDtClaimIDClaimStartDtClmAdmitDiagnosisCodeClmDiagnosisCode_1ClmDiagnosisCode_10ClmDiagnosisCode_2ClmDiagnosisCode_3...ClmProcedureCode_2ClmProcedureCode_3ClmProcedureCode_4ClmProcedureCode_5ClmProcedureCode_6DeductibleAmtPaidInscClaimAmtReimbursedOperatingPhysicianOtherPhysicianProviderID
0PHY326117BENE110022009-10-11CLM6243492009-10-115640978943NoneV5866V1272...NoneNoneNoneNoneNone030NoneNonePRV56011
1PHY362868BENE110032009-02-12CLM1899472009-02-12793806115NoneNoneNone...NoneNoneNoneNoneNone080NoneNonePRV57610
2PHY328821BENE110032009-06-27CLM4380212009-06-272723NoneNoneNone...NoneNoneNoneNoneNone010NoneNonePRV57595
3PHY334319BENE110042009-01-06CLM1218012009-01-0671988NoneNoneNone...NoneNoneNoneNoneNone040NoneNonePRV56011
4PHY403831BENE110042009-01-22CLM1509982009-01-227194782382None3000072887...NoneNoneNoneNoneNone0200NoneNonePRV56011
\n", "

5 rows × 27 columns

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" ], "text/plain": [ " AttendingPhysician BeneID ClaimEndDt ClaimID ClaimStartDt \\\n", "0 PHY326117 BENE11002 2009-10-11 CLM624349 2009-10-11 \n", "1 PHY362868 BENE11003 2009-02-12 CLM189947 2009-02-12 \n", "2 PHY328821 BENE11003 2009-06-27 CLM438021 2009-06-27 \n", "3 PHY334319 BENE11004 2009-01-06 CLM121801 2009-01-06 \n", "4 PHY403831 BENE11004 2009-01-22 CLM150998 2009-01-22 \n", "\n", " ClmAdmitDiagnosisCode ClmDiagnosisCode_1 ClmDiagnosisCode_10 \\\n", "0 56409 78943 None \n", "1 79380 6115 None \n", "2 2723 None \n", "3 71988 None \n", "4 71947 82382 None \n", "\n", " ClmDiagnosisCode_2 ClmDiagnosisCode_3 ... ClmProcedureCode_2 \\\n", "0 V5866 V1272 ... None \n", "1 None None ... None \n", "2 None None ... None \n", "3 None None ... None \n", "4 30000 72887 ... None \n", "\n", " ClmProcedureCode_3 ClmProcedureCode_4 ClmProcedureCode_5 ClmProcedureCode_6 \\\n", "0 None None None None \n", "1 None None None None \n", "2 None None None None \n", "3 None None None None \n", "4 None None None None \n", "\n", " DeductibleAmtPaid InscClaimAmtReimbursed OperatingPhysician OtherPhysician \\\n", "0 0 30 None None \n", "1 0 80 None None \n", "2 0 10 None None \n", "3 0 40 None None \n", "4 0 200 None None \n", "\n", " ProviderID \n", "0 PRV56011 \n", "1 PRV57610 \n", "2 PRV57595 \n", "3 PRV56011 \n", "4 PRV56011 \n", "\n", "[5 rows x 27 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient.head()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ProviderIDPotentialFraud
0PRV51001No
1PRV51003Yes
2PRV51004No
3PRV51005Yes
4PRV51007No
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" ], "text/plain": [ " ProviderID PotentialFraud\n", "0 PRV51001 No\n", "1 PRV51003 Yes\n", "2 PRV51004 No\n", "3 PRV51005 Yes\n", "4 PRV51007 No" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "provider.head()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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BeneIDDOBDODGenderRaceRenalDiseaseIndicatorStateCountyNoOfMonths_PartACovNoOfMonths_PartBCov...ChronicCond_DepressionChronicCond_DiabetesChronicCond_IschemicHeartChronicCond_OsteoporasisChronicCond_rheumatoidarthritisChronicCond_strokeIPAnnualReimbursementAmtIPAnnualDeductibleAmtOPAnnualReimbursementAmtOPAnnualDeductibleAmt
0BENE110011943-01-01NaT110392301212...1112113600032046070
1BENE110021936-09-01NaT210392801212...222222003050
2BENE110031936-08-01NaT110525901212...221222009040
3BENE110041922-07-01NaT110392701212...211112001810760
4BENE110051935-09-01NaT110246801212...2122220017901200
\n", "

5 rows × 25 columns

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" ], "text/plain": [ " BeneID DOB DOD Gender Race RenalDiseaseIndicator State \\\n", "0 BENE11001 1943-01-01 NaT 1 1 0 39 \n", "1 BENE11002 1936-09-01 NaT 2 1 0 39 \n", "2 BENE11003 1936-08-01 NaT 1 1 0 52 \n", "3 BENE11004 1922-07-01 NaT 1 1 0 39 \n", "4 BENE11005 1935-09-01 NaT 1 1 0 24 \n", "\n", " County NoOfMonths_PartACov NoOfMonths_PartBCov ... \\\n", "0 230 12 12 ... \n", "1 280 12 12 ... \n", "2 590 12 12 ... \n", "3 270 12 12 ... \n", "4 680 12 12 ... \n", "\n", " ChronicCond_Depression ChronicCond_Diabetes ChronicCond_IschemicHeart \\\n", "0 1 1 1 \n", "1 2 2 2 \n", "2 2 2 1 \n", "3 2 1 1 \n", "4 2 1 2 \n", "\n", " ChronicCond_Osteoporasis ChronicCond_rheumatoidarthritis \\\n", "0 2 1 \n", "1 2 2 \n", "2 2 2 \n", "3 1 1 \n", "4 2 2 \n", "\n", " ChronicCond_stroke IPAnnualReimbursementAmt IPAnnualDeductibleAmt \\\n", "0 1 36000 3204 \n", "1 2 0 0 \n", "2 2 0 0 \n", "3 2 0 0 \n", "4 2 0 0 \n", "\n", " OPAnnualReimbursementAmt OPAnnualDeductibleAmt \n", "0 60 70 \n", "1 30 50 \n", "2 90 40 \n", "3 1810 760 \n", "4 1790 1200 \n", "\n", "[5 rows x 25 columns]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "beneficiary.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exploratory Data Analysis (Graphical and Statistic) - Beneficiary" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "BeneID object\n", "DOB datetime64[ns]\n", "DOD datetime64[ns]\n", "Gender int64\n", "Race int64\n", "RenalDiseaseIndicator object\n", "State int64\n", "County int64\n", "NoOfMonths_PartACov int64\n", "NoOfMonths_PartBCov int64\n", "ChronicCond_Alzheimer int64\n", "ChronicCond_Heartfailure int64\n", "ChronicCond_KidneyDisease int64\n", "ChronicCond_Cancer int64\n", "ChronicCond_ObstrPulmonary int64\n", "ChronicCond_Depression int64\n", "ChronicCond_Diabetes int64\n", "ChronicCond_IschemicHeart int64\n", "ChronicCond_Osteoporasis int64\n", "ChronicCond_rheumatoidarthritis int64\n", "ChronicCond_stroke int64\n", "IPAnnualReimbursementAmt int64\n", "IPAnnualDeductibleAmt int64\n", "OPAnnualReimbursementAmt int64\n", "OPAnnualDeductibleAmt int64\n", "dtype: object" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "beneficiary.dtypes" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "BeneID 0\n", "DOB 0\n", "DOD 137135\n", "Gender 0\n", "Race 0\n", "RenalDiseaseIndicator 0\n", "State 0\n", "County 0\n", "NoOfMonths_PartACov 0\n", "NoOfMonths_PartBCov 0\n", "ChronicCond_Alzheimer 0\n", "ChronicCond_Heartfailure 0\n", "ChronicCond_KidneyDisease 0\n", "ChronicCond_Cancer 0\n", "ChronicCond_ObstrPulmonary 0\n", "ChronicCond_Depression 0\n", "ChronicCond_Diabetes 0\n", "ChronicCond_IschemicHeart 0\n", "ChronicCond_Osteoporasis 0\n", "ChronicCond_rheumatoidarthritis 0\n", "ChronicCond_stroke 0\n", "IPAnnualReimbursementAmt 0\n", "IPAnnualDeductibleAmt 0\n", "OPAnnualReimbursementAmt 0\n", "OPAnnualDeductibleAmt 0\n", "dtype: int64" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "beneficiary.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 138556 entries, 0 to 138555\n", "Data columns (total 25 columns):\n", "BeneID 138556 non-null object\n", "DOB 138556 non-null datetime64[ns]\n", "DOD 1421 non-null datetime64[ns]\n", "Gender 138556 non-null int64\n", "Race 138556 non-null int64\n", "RenalDiseaseIndicator 138556 non-null object\n", "State 138556 non-null int64\n", "County 138556 non-null int64\n", "NoOfMonths_PartACov 138556 non-null int64\n", "NoOfMonths_PartBCov 138556 non-null int64\n", "ChronicCond_Alzheimer 138556 non-null int64\n", "ChronicCond_Heartfailure 138556 non-null int64\n", "ChronicCond_KidneyDisease 138556 non-null int64\n", "ChronicCond_Cancer 138556 non-null int64\n", "ChronicCond_ObstrPulmonary 138556 non-null int64\n", "ChronicCond_Depression 138556 non-null int64\n", "ChronicCond_Diabetes 138556 non-null int64\n", "ChronicCond_IschemicHeart 138556 non-null int64\n", "ChronicCond_Osteoporasis 138556 non-null int64\n", "ChronicCond_rheumatoidarthritis 138556 non-null int64\n", "ChronicCond_stroke 138556 non-null int64\n", "IPAnnualReimbursementAmt 138556 non-null int64\n", "IPAnnualDeductibleAmt 138556 non-null int64\n", "OPAnnualReimbursementAmt 138556 non-null int64\n", "OPAnnualDeductibleAmt 138556 non-null int64\n", "dtypes: datetime64[ns](2), int64(21), object(2)\n", "memory usage: 26.4+ MB\n" ] } ], "source": [ "beneficiary.info()" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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GenderRaceStateCountyNoOfMonths_PartACovNoOfMonths_PartBCovChronicCond_AlzheimerChronicCond_HeartfailureChronicCond_KidneyDiseaseChronicCond_Cancer...ChronicCond_DepressionChronicCond_DiabetesChronicCond_IschemicHeartChronicCond_OsteoporasisChronicCond_rheumatoidarthritisChronicCond_strokeIPAnnualReimbursementAmtIPAnnualDeductibleAmtOPAnnualReimbursementAmtOPAnnualDeductibleAmt
count138556.000000138556.000000138556.000000138556.000000138556.000000138556.000000138556.000000138556.000000138556.000000138556.000000...138556.000000138556.000000138556.000000138556.000000138556.000000138556.000000138556.000000138556.000000138556.000000138556.000000
mean1.5709321.25451125.666734374.42474511.90772711.9101451.6678171.5063221.6876431.880041...1.6444761.3981421.3241431.7253171.7431801.9209423660.346502399.8472961298.219348377.718258
std0.4949450.71700715.223443266.2775811.0323320.9368930.4709980.4999620.4634560.324914...0.4786740.4895170.4680560.4463560.4368810.2698319568.621827956.1752022493.901134645.530187
min1.0000001.0000001.0000000.0000000.0000000.0000001.0000001.0000001.0000001.000000...1.0000001.0000001.0000001.0000001.0000001.000000-8000.0000000.000000-70.0000000.000000
25%1.0000001.00000011.000000141.00000012.00000012.0000001.0000001.0000001.0000002.000000...1.0000001.0000001.0000001.0000001.0000002.0000000.0000000.000000170.00000040.000000
50%2.0000001.00000025.000000340.00000012.00000012.0000002.0000002.0000002.0000002.000000...2.0000001.0000001.0000002.0000002.0000002.0000000.0000000.000000570.000000170.000000
75%2.0000001.00000039.000000570.00000012.00000012.0000002.0000002.0000002.0000002.000000...2.0000002.0000002.0000002.0000002.0000002.0000002280.0000001068.0000001500.000000460.000000
max2.0000005.00000054.000000999.00000012.00000012.0000002.0000002.0000002.0000002.000000...2.0000002.0000002.0000002.0000002.0000002.000000161470.00000038272.000000102960.00000013840.000000
\n", "

8 rows × 21 columns

\n", "
" ], "text/plain": [ " Gender Race State County \\\n", "count 138556.000000 138556.000000 138556.000000 138556.000000 \n", "mean 1.570932 1.254511 25.666734 374.424745 \n", "std 0.494945 0.717007 15.223443 266.277581 \n", "min 1.000000 1.000000 1.000000 0.000000 \n", "25% 1.000000 1.000000 11.000000 141.000000 \n", "50% 2.000000 1.000000 25.000000 340.000000 \n", "75% 2.000000 1.000000 39.000000 570.000000 \n", "max 2.000000 5.000000 54.000000 999.000000 \n", "\n", " NoOfMonths_PartACov NoOfMonths_PartBCov ChronicCond_Alzheimer \\\n", "count 138556.000000 138556.000000 138556.000000 \n", "mean 11.907727 11.910145 1.667817 \n", "std 1.032332 0.936893 0.470998 \n", "min 0.000000 0.000000 1.000000 \n", "25% 12.000000 12.000000 1.000000 \n", "50% 12.000000 12.000000 2.000000 \n", "75% 12.000000 12.000000 2.000000 \n", "max 12.000000 12.000000 2.000000 \n", "\n", " ChronicCond_Heartfailure ChronicCond_KidneyDisease \\\n", "count 138556.000000 138556.000000 \n", "mean 1.506322 1.687643 \n", "std 0.499962 0.463456 \n", "min 1.000000 1.000000 \n", "25% 1.000000 1.000000 \n", "50% 2.000000 2.000000 \n", "75% 2.000000 2.000000 \n", "max 2.000000 2.000000 \n", "\n", " ChronicCond_Cancer ... ChronicCond_Depression ChronicCond_Diabetes \\\n", "count 138556.000000 ... 138556.000000 138556.000000 \n", "mean 1.880041 ... 1.644476 1.398142 \n", "std 0.324914 ... 0.478674 0.489517 \n", "min 1.000000 ... 1.000000 1.000000 \n", "25% 2.000000 ... 1.000000 1.000000 \n", "50% 2.000000 ... 2.000000 1.000000 \n", "75% 2.000000 ... 2.000000 2.000000 \n", "max 2.000000 ... 2.000000 2.000000 \n", "\n", " ChronicCond_IschemicHeart ChronicCond_Osteoporasis \\\n", "count 138556.000000 138556.000000 \n", "mean 1.324143 1.725317 \n", "std 0.468056 0.446356 \n", "min 1.000000 1.000000 \n", "25% 1.000000 1.000000 \n", "50% 1.000000 2.000000 \n", "75% 2.000000 2.000000 \n", "max 2.000000 2.000000 \n", "\n", " ChronicCond_rheumatoidarthritis ChronicCond_stroke \\\n", "count 138556.000000 138556.000000 \n", "mean 1.743180 1.920942 \n", "std 0.436881 0.269831 \n", "min 1.000000 1.000000 \n", "25% 1.000000 2.000000 \n", "50% 2.000000 2.000000 \n", "75% 2.000000 2.000000 \n", "max 2.000000 2.000000 \n", "\n", " IPAnnualReimbursementAmt IPAnnualDeductibleAmt \\\n", "count 138556.000000 138556.000000 \n", "mean 3660.346502 399.847296 \n", "std 9568.621827 956.175202 \n", "min -8000.000000 0.000000 \n", "25% 0.000000 0.000000 \n", "50% 0.000000 0.000000 \n", "75% 2280.000000 1068.000000 \n", "max 161470.000000 38272.000000 \n", "\n", " OPAnnualReimbursementAmt OPAnnualDeductibleAmt \n", "count 138556.000000 138556.000000 \n", "mean 1298.219348 377.718258 \n", "std 2493.901134 645.530187 \n", "min -70.000000 0.000000 \n", "25% 170.000000 40.000000 \n", "50% 570.000000 170.000000 \n", "75% 1500.000000 460.000000 \n", "max 102960.000000 13840.000000 \n", "\n", "[8 rows x 21 columns]" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "beneficiary.describe()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "#convert int datatype of category attribute to category\n", "\n", "beneficiary['Gender'] = beneficiary['Gender'].astype('category')\n", "beneficiary['Race'] = beneficiary['Race'].astype('category')\n", "beneficiary['RenalDiseaseIndicator'] = beneficiary['RenalDiseaseIndicator'].astype('category')\n", "beneficiary['State'] = beneficiary['State'].astype('category')\n", "beneficiary['County'] = beneficiary['County'].astype('category')\n", "beneficiary['NoOfMonths_PartACov'] = beneficiary['NoOfMonths_PartACov'].astype('category')\n", "beneficiary['NoOfMonths_PartBCov'] = beneficiary['NoOfMonths_PartBCov'].astype('category')\n", "beneficiary['ChronicCond_Alzheimer'] = beneficiary['ChronicCond_Alzheimer'].astype('category')\n", "beneficiary['ChronicCond_Heartfailure'] = beneficiary['ChronicCond_Heartfailure'].astype('category')\n", "beneficiary['ChronicCond_KidneyDisease'] = beneficiary['ChronicCond_KidneyDisease'].astype('category')\n", "beneficiary['ChronicCond_Cancer'] = beneficiary['ChronicCond_Cancer'].astype('category')\n", "beneficiary['ChronicCond_ObstrPulmonary'] = beneficiary['ChronicCond_ObstrPulmonary'].astype('category')\n", "beneficiary['ChronicCond_Depression'] = beneficiary['ChronicCond_Depression'].astype('category')\n", "beneficiary['ChronicCond_Diabetes'] = beneficiary['ChronicCond_Diabetes'].astype('category')\n", "beneficiary['ChronicCond_IschemicHeart'] = beneficiary['ChronicCond_IschemicHeart'].astype('category')\n", "beneficiary['ChronicCond_Osteoporasis'] = beneficiary['ChronicCond_Osteoporasis'].astype('category')\n", "beneficiary['ChronicCond_rheumatoidarthritis'] = beneficiary['ChronicCond_rheumatoidarthritis'].astype('category')\n", "beneficiary['ChronicCond_stroke'] = beneficiary['ChronicCond_stroke'].astype('category')\n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 138556 entries, 0 to 138555\n", "Data columns (total 25 columns):\n", "BeneID 138556 non-null object\n", "DOB 138556 non-null datetime64[ns]\n", "DOD 1421 non-null datetime64[ns]\n", "Gender 138556 non-null category\n", "Race 138556 non-null category\n", "RenalDiseaseIndicator 138556 non-null category\n", "State 138556 non-null category\n", "County 138556 non-null category\n", "NoOfMonths_PartACov 138556 non-null category\n", "NoOfMonths_PartBCov 138556 non-null category\n", "ChronicCond_Alzheimer 138556 non-null category\n", "ChronicCond_Heartfailure 138556 non-null category\n", "ChronicCond_KidneyDisease 138556 non-null category\n", "ChronicCond_Cancer 138556 non-null category\n", "ChronicCond_ObstrPulmonary 138556 non-null category\n", "ChronicCond_Depression 138556 non-null category\n", "ChronicCond_Diabetes 138556 non-null category\n", "ChronicCond_IschemicHeart 138556 non-null category\n", "ChronicCond_Osteoporasis 138556 non-null category\n", "ChronicCond_rheumatoidarthritis 138556 non-null category\n", "ChronicCond_stroke 138556 non-null category\n", "IPAnnualReimbursementAmt 138556 non-null int64\n", "IPAnnualDeductibleAmt 138556 non-null int64\n", "OPAnnualReimbursementAmt 138556 non-null int64\n", "OPAnnualDeductibleAmt 138556 non-null int64\n", "dtypes: category(18), datetime64[ns](2), int64(4), object(1)\n", "memory usage: 9.9+ MB\n" ] } ], "source": [ "beneficiary.info()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize = (15,8))\n", "sns.countplot(x='Gender', data=beneficiary)\n" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2009.0 1421\n", "Name: Death_year, dtype: int64\n" ] } ], "source": [ "from datetime import date\n", "today = date.today()\n", "current_year = today.year\n", "\n", "beneficiary['Birth_year'] = beneficiary['DOB'].dt.year\n", "beneficiary['Death_year'] = beneficiary['DOD'].dt.year\n", "\n", "beneficiary['Age'] = current_year - beneficiary['Birth_year']\n", "print(beneficiary.Death_year.value_counts())\n", "\n", "beneficiary['Age'] = np.where(beneficiary['Age'] > 95, np.nan, beneficiary['Age'])\n", "beneficiary.Age.describe()\n", "\n", "\n", "for i in beneficiary.DOD:\n", " if i == np.nan:\n", " beneficiary['isAlive'] = 0\n", " else:\n", " beneficiary['isAlive'] = 1" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "beneficiary = beneficiary.dropna(subset=['Age'])\n", "beneficiary = beneficiary.drop(['DOD', 'Death_year', 'DOB'], axis=1)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(107795, 26)" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "beneficiary.shape" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 107795.000000\n", "mean 81.794267\n", "std 10.824806\n", "min 39.000000\n", "25% 79.000000\n", "50% 84.000000\n", "75% 89.000000\n", "max 95.000000\n", "Name: Age, dtype: float64" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#age distribition\n", "plt.figure(figsize = (15,8))\n", "beneficiary.Age.plot(kind='hist', bins=15)\n", "\n", "beneficiary.Age.describe()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Interpretation: older people tend to use health care insurance more\n" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize = (15,8))\n", "sns.countplot(x='Race', data=beneficiary)" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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vqy64idf6o/0u7vzz73FLPgsAR8gFF5x72EsAgCPrQCJxjPEt1X+bc75ujPHEbfiM6sSeaceq4zcy3jZ+cs5eH+mcY3vO2Zdrr72+48dPfdvTi19yAG6da655z2EvAQBOW2eccewmN80Oaifx66oLxxhvqu5T3aNd1F24Z879qquqd1X3HGOcOef80Dbnqm3OO7Z5V44xzqrOra6trtzm/cEprwUAAMBH4UDuSZxzfsmc85PnnI+o/lH1s3POb6reP8b4vG3aN1SvmXN+sLqiXVhWPaF6zfb41dvztuNXbPPX+Bjj86v3zzn3fakpAAAAN+7A/wTGKS6pXjLGOK/6zeoF2/hTq5eNMS5td1/h12/jz64uG2O8pfrT7fyqF1Y/to1/oF1wAgAA8FE6duLE6X1f3gF4YPW2o3JP4sXPfMXNTwRgufy5l7gnEQBuwp57Ej+xevtfOX57LwgAAIDTl0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwCISAQAAWEQiAAAAi0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwCISAQAAWEQiAAAAi0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwCISAQAAWEQiAAAAi0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwCISAQAAWEQiAAAAi0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwCISAQAAWEQiAAAAi0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwCISAQAAWEQiAAAAi0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwCISAQAAWEQiAAAAi0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwCISAQAAWEQiAAAAi0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwCISAQAAWEQiAAAAi0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwCISAQAAWM46yBcfY/zj6mu3pz8/53zmGOMx1fOqu1U/Nee8dJv7iOql1XnV66unzDlvGGPcv3p59bHVrC6Zc14/xrhX9YrqQdU11dfOOd95kJ8HAADgju7AdhK3GPzS6tOrR1SfOcb4+uonqq+oHlY9aozxuO2Ul1dPm3M+pDpWPWkbf3H14jnnQ6s3Vs/exp9TXTHnfFj1kur5B/VZAAAA7iwO8nLTq6u/P+f8iznnB6vfrR5S/d6c821zzhvaheHXjDEeUN1tzvmG7dzLtvGzqy+sXrV3fHv8Ze12EqteWT1umw8AAMCtdGCXm84533Ly8Rjjk9pddvrCdvF40tXVx1cXfYTx+1bXbUG5d7y952yXpV5XXVBdtZ/1nX/+PW7hJwLgqLjggnMPewkAcGQd6D2JVWOMv179fPWM6oZ2u4knHauOt9vRPLGP8bbxk3P2Orbn2M269trrO3781Jc+vfglB+DWueaa9xz2EgDgtHXGGcductPsQL/ddIzxedXrqu+ac76surK6cM+U+7Xb+ftI4++q7jnGOHMbv7AP7xS+Y5vXGOOs6tzq2oP5JAAAAHcOB/nFNZ9Q/V/VxXPOf70N/+ru0HjwFn4XV6+Zc/5h9f4tKqu+YRv/YHVF9XXb+BOq12yPX709bzt+xTYfAACAW+kgLzd9enXX6nljjJNjP1o9sfrp7dir+/CX0lxSvWSMcV71m9ULtvGnVi8bY1xa/VH19dv4s6vLxhhvqf50Ox8AAICPwrETJ07v+/IOwAOrtx2VexIvfuYrbn4iAMvlz73EPYkAcBP23JP4idXb/8rx23tBAAAAnL5EIgAAAItIBAAAYBGJAAAALCIRAACARSQCAACwiEQAAAAWkQgAAMAiEgEAAFhEIgAAAItIBAAAYBGJAAAALCIRAACARSQCAACwiEQAAAAWkQgAAMAiEgEAAFhEIgAAAMtZh70AAOD0de97ntNZ59zlsJcBcKTc8Bcf6N1/9heHvYxbTSQCAB/RWefcpd947rcc9jIAjpTPfOZLq6MbiS43BQAAYBGJAAAALCIRAACARSQCAACwiEQAAAAWkQgAAMAiEgEAAFhEIgAAAItIBAAAYBGJAAAALCIRAACARSQCAACwiEQAAAAWkQgAAMAiEgEAAFhEIgAAAItIBAAAYBGJAAAALCIRAACARSQCAACwiEQAAAAWkQgAAMAiEgEAAFhEIgAAAItIBAAAYBGJAAAALCIRAACARSQCAACwiEQAAAAWkQgAAMAiEgEAAFhEIgAAAItIBAAAYBGJAAAALCIRAACARSQCAACwiEQAAAAWkQgAAMAiEgEAAFhEIgAAAItIBAAAYBGJAAAALCIRAACARSQCAACwiEQAAAAWkQgAAMAiEgEAAFhEIgAAAItIBAAAYBGJAAAALCIRAACARSQCAACwiEQAAAAWkQgAAMAiEgEAAFhEIgAAAItIBAAAYBGJAAAALCIRAACARSQCAACwnHXYC/hojDEuri6tzq5+eM75okNeEgAAwJF2ZHcSxxgfV31/9fnVI6onjzEefrirAgAAONqO8k7iY6pfnHP+SdUY41XVV1ffdzPnnVl1xhnHDnZ1t5H73vvuh70EgCPnqPwz/qg457zzD3sJAEfO6fzvoj1rO/PGjh/lSLyounrP86urz9rHeRdW3fuIxNcLvvsrD3sJAEfO+eff47CXcIfyKU/5wcNeAsCRc0T+XXRh9QenDh7lSDyjOrHn+bHq+D7O+/XqC9pF5YcOYF0AAACnszPbBeKv39jBoxyJV7aLvZPuV121j/M+UP3ygawIAADgaPgrO4gnHeVIfG31PWOMC6r3Vl9VPflwlwQAAHC0HdlvN51zvqN6VvVL1Zuqy+ecv3a4qwIAADjajp04ceLmZwEAAHCncGR3EgEAALjtiUQAAAAWkQgAAMAiEgEAAFhEIgAAAMtR/juJwCEYY1xcXVqdXf3wnPNFh7wkAO5kxhjnVf+levyc8+2HvBy4w7GTCOzbGOPjqu+vPr96RPXkMcbDD3dVANyZjDE+u/rl6iGHvRa4oxKJwC3xmOoX55x/Mud8b/Wq6qsPeU0A3Lk8qfq26qrDXgjcUbncFLglLqqu3vP86uqzDmktANwJzTm/pWqMcdhLgTssO4nALXFGdWLP82PV8UNaCwAAB0AkArfEldWFe57fL5f7AADcobjcFLglXlt9zxjjguq91VdVTz7cJQEAcFuykwjs25zzHdWzql+q3lRdPuf8tcNdFQAAt6VjJ06cuPlZAAAA3CnYSQQAAGARiQAAACwiEQAAgEUkAgAAsIhEAAAAFn8nEYDTxhjjRPXb1YeqE9XHVNdV3zrnfOMBvN/3VPedcz5tjPF/Vw+o/mw7fHb189U/mXO+Z4zxyOq75pxffVuv45YaYzyw+u055z1u4Xk/V71qznnZGONN1aPnnH96K97/y6rPnnP+o1t6LgCnP5EIwOnmi+ecf3zyyRjj6dULq8+9Hd77GXPOV23ve3b1gury6su3SD30QLytzDkf8VGc/qjqPrfVWgA4vYhEAE5bY4yzqvtXf7Jn7FnVV7W7ZeLt1VPnnFdtO4G/Un3eds5rqyfPOY+PMf5h9RXV3aq7V0+fc/7MTb33nPODY4zvrN45xnhodb/qX8w5P3mM8fnV86oz2+14/tM550+PMc6pfrD6ou3Yb1XfPue8bozx+OofVudUH1u9bM757DHGPaqfrD6pOl79RvV3t3V/eXXpds6fb+v+lVN+Ro+uvr/6r9Unt9sB/btzzv88xrioell1UfWH2/uePO9EdcGc84/HGN9dfWN1Q/V71RO3xz+yrev86j3VxdW9qqdUZ44x/mzO+awxxrOrr9/O+f+qp80537n9b/In1UOrH5lzvvCmfuYAnB7ckwjA6eaXxhhvHmNc1S44qr6paozxhOpTqs/adsJeXb10z7n/XfXo6lOrx1VfNMZ4QPWYdpdWfmr1rOr79rOQOef7tjV8yimHvrd63pzzM6tvrv7GNv5d7ULpM+ecn1ZdVf2zMcax6u9X3zjnfGT1OdV3jzHuW/3t6tzt8zxqe50HjTE+qfqB6m/OOT+9enL1b8YYd7+RpX529b9t835yO6/qRdUb5px/vfr2drH2l4wx/la7KPzcOecnV2+rntbu5/enc87PnXM+pPr1dvH3q9WPVj+1BeI3bXMftf18f7u6bM9bvHvO+XCBCHB02EkE4HTzxdvu1me0i8BfmnO+azv2+OqzqjeOMWq3W/cxe879d3PO49V1Y4zfr+4z5/ylLS4vGWM8uF2g3ZJ7+U6028Xb6/+oXrTt9L223Q7hyfXdq/qSbX3nVO+ac57Y5j5+jHFx9bDqWLtdzV+ufmDbdfuP1Q/POX9/jPHU6sLqddtr1W6n8cF9+L7Jk/5wzvmm7fFvtou+2sXx06u21/zFG/l8j6n+zznnu7d533nywBjjv44x/uftPR/dbqf2VI+rfnLO+d7t+fOrZ227qlVX3Mg5AJzG7CQCcFqac/5m9b9Ul21f1FK7KPzBOecjtp23R7a7vPSk9+15fKI6tsXmr1TnVb/Q7nLQY/tZwxjjY9oF3VtOWduPtdtd/I/VY6s3jzHuuq3vO/as77Oqr952/36r+ox2EfeM6oPVsTnn29pF2D/d1vjaLSjPrF538rW21/ucdjt1p/orn/tGHtdul/NUN2zzTn7me40xHjjG+Nbqx9sF8uXVK7vxn9uZe89v97vFWXvmXn8j5wBwGhOJAJy25pyvrH6t+qFt6D9U3zLGOG97/n3V/34zL/OF1RvnnM+r/lP1le3C5iaNMe5W/XD1mjnn20859l+qT59zXtbuMtB7tbtn8T9UTxtjnDPGOKN6Sbv4+6R2AXjpnPPftduVu0u7+/q+td0lor8w5/wH22t8RvW66ku3+yEbY/zN6s3t7qvcr3+/ra8xxv2rL76ROa+t/oc9P9Pvqb6zXfxeNuf88WpWJ8O1dmF59p73+OY9l8F+e/X6OecHbsE6ATiNuNwUgNPd09rt1D223f2HH1e9YfvilT/qw5dWfiSvrL5qjPG77f7P0Z+r7jPGOPdG5v6vY4xL213WeVa7gPqOG5n3zOr5Y4zntNtF+94559vHGP+k+uftdg3PrN7U7l7E67f3fesY4wPV/1v9TrsdxH/VLhp/Z4zx59tnesGc891jjCdX/3q7p/GG6m/NOa/f7mXcj2+rfnL77Fdu6/lL5pyvHmM8vPrP22Wtb6meVH1a9S/HGP9Tu13BX+nD92b+YnX5GOOF28/nE6pf28L496tL9rk+AE5Dx06cOHHzswAAALhTcLkpAAAAi0gEAABgEYkAAAAsIhEAAIBFJAIAALCIRAAAABaRCAAAwPL/A+0o+zz7nLRsAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "beneficiary['RenalDiseaseIndicator'] = np.where(beneficiary['RenalDiseaseIndicator'] == 'Y', 1, beneficiary['RenalDiseaseIndicator'])\n", "plt.figure(figsize = (15,8))\n", "sns.countplot(x='RenalDiseaseIndicator', data=beneficiary)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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BeneIDGenderRaceRenalDiseaseIndicatorStateCountyNoOfMonths_PartACovNoOfMonths_PartBCovChronicCond_AlzheimerChronicCond_Heartfailure...ChronicCond_strokeIPAnnualReimbursementAmtIPAnnualDeductibleAmtOPAnnualReimbursementAmtOPAnnualDeductibleAmtBirth_yearAgeisAliveTotalAnnualReimbursableAmtTotalAnnualDeductibleAmt
0BENE1100111039230121212...13600032046070194379.01360603274
1BENE1100221039280121222...2003050193686.013050
2BENE1100311052590121212...2009040193686.019040
4BENE1100511024680121222...20017901200193587.0117901200
5BENE1100621023810121222...2005000197646.015000
..................................................................
138550BENE1591922102130121222...200420100193785.01420100
138551BENE15919411039140121212...200430460193983.01430460
138552BENE15919521049530121212...200880100193884.01880100
138554BENE15919711016560121211...200265010193092.01265010
138555BENE1591982102120121211...20054701870195270.0154701870
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107795 rows × 28 columns

\n", "
" ], "text/plain": [ " BeneID Gender Race RenalDiseaseIndicator State County \\\n", "0 BENE11001 1 1 0 39 230 \n", "1 BENE11002 2 1 0 39 280 \n", "2 BENE11003 1 1 0 52 590 \n", "4 BENE11005 1 1 0 24 680 \n", "5 BENE11006 2 1 0 23 810 \n", "... ... ... ... ... ... ... \n", "138550 BENE159192 2 1 0 21 30 \n", "138551 BENE159194 1 1 0 39 140 \n", "138552 BENE159195 2 1 0 49 530 \n", "138554 BENE159197 1 1 0 16 560 \n", "138555 BENE159198 2 1 0 21 20 \n", "\n", " NoOfMonths_PartACov NoOfMonths_PartBCov ChronicCond_Alzheimer \\\n", "0 12 12 1 \n", "1 12 12 2 \n", "2 12 12 1 \n", "4 12 12 2 \n", "5 12 12 2 \n", "... ... ... ... \n", "138550 12 12 2 \n", "138551 12 12 1 \n", "138552 12 12 1 \n", "138554 12 12 1 \n", "138555 12 12 1 \n", "\n", " ChronicCond_Heartfailure ... ChronicCond_stroke \\\n", "0 2 ... 1 \n", "1 2 ... 2 \n", "2 2 ... 2 \n", "4 2 ... 2 \n", "5 2 ... 2 \n", "... ... ... ... \n", "138550 2 ... 2 \n", "138551 2 ... 2 \n", "138552 2 ... 2 \n", "138554 1 ... 2 \n", "138555 1 ... 2 \n", "\n", " IPAnnualReimbursementAmt IPAnnualDeductibleAmt \\\n", "0 36000 3204 \n", "1 0 0 \n", "2 0 0 \n", "4 0 0 \n", "5 0 0 \n", "... ... ... \n", "138550 0 0 \n", "138551 0 0 \n", "138552 0 0 \n", "138554 0 0 \n", "138555 0 0 \n", "\n", " OPAnnualReimbursementAmt OPAnnualDeductibleAmt Birth_year Age \\\n", "0 60 70 1943 79.0 \n", "1 30 50 1936 86.0 \n", "2 90 40 1936 86.0 \n", "4 1790 1200 1935 87.0 \n", "5 500 0 1976 46.0 \n", "... ... ... ... ... \n", "138550 420 100 1937 85.0 \n", "138551 430 460 1939 83.0 \n", "138552 880 100 1938 84.0 \n", "138554 2650 10 1930 92.0 \n", "138555 5470 1870 1952 70.0 \n", "\n", " isAlive TotalAnnualReimbursableAmt TotalAnnualDeductibleAmt \n", "0 1 36060 3274 \n", "1 1 30 50 \n", "2 1 90 40 \n", "4 1 1790 1200 \n", "5 1 500 0 \n", "... ... ... ... \n", "138550 1 420 100 \n", "138551 1 430 460 \n", "138552 1 880 100 \n", "138554 1 2650 10 \n", "138555 1 5470 1870 \n", "\n", "[107795 rows x 28 columns]" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bene_deductible_reimburse_amt = beneficiary[['BeneID','IPAnnualReimbursementAmt', 'IPAnnualDeductibleAmt', 'OPAnnualReimbursementAmt', 'OPAnnualDeductibleAmt']]\n", "bene_deductible_reimburse_amt\n", "\n", "\n", "reimburse_amt = ['IPAnnualReimbursementAmt', 'OPAnnualReimbursementAmt']\n", "beneficiary['TotalAnnualReimbursableAmt'] = beneficiary[reimburse_amt].sum(axis=1)\n", "\n", "deductible_amt = ['IPAnnualDeductibleAmt', 'OPAnnualDeductibleAmt']\n", "beneficiary['TotalAnnualDeductibleAmt'] = beneficiary[deductible_amt].sum(axis=1)\n", "beneficiary" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 107795.000000\n", "mean 385.257479\n", "std 935.156802\n", "min 0.000000\n", "25% 0.000000\n", "50% 0.000000\n", "75% 1068.000000\n", "max 37204.000000\n", "Name: IPAnnualDeductibleAmt, dtype: float64" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "beneficiary['IPAnnualDeductibleAmt'].describe()" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 107795.000000\n", "mean 370.021040\n", "std 634.097043\n", "min 0.000000\n", "25% 40.000000\n", "50% 160.000000\n", "75% 450.000000\n", "max 13840.000000\n", "Name: OPAnnualDeductibleAmt, dtype: float64" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "beneficiary['OPAnnualDeductibleAmt'].describe()" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 107795.000000\n", "mean 3544.674614\n", "std 9421.171480\n", "min -8000.000000\n", "25% 0.000000\n", "50% 0.000000\n", "75% 1000.000000\n", "max 155600.000000\n", "Name: IPAnnualReimbursementAmt, dtype: float64" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "beneficiary['IPAnnualReimbursementAmt'].describe()" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 107795.000000\n", "mean 1271.757967\n", "std 2425.755640\n", "min -60.000000\n", "25% 170.000000\n", "50% 560.000000\n", "75% 1480.000000\n", "max 102960.000000\n", "Name: OPAnnualReimbursementAmt, dtype: float64" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "beneficiary['OPAnnualReimbursementAmt'].describe()" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['BeneID', 'Gender', 'Race', 'RenalDiseaseIndicator', 'State', 'County',\n", " 'NoOfMonths_PartACov', 'NoOfMonths_PartBCov', 'ChronicCond_Alzheimer',\n", " 'ChronicCond_Heartfailure', 'ChronicCond_KidneyDisease',\n", " 'ChronicCond_Cancer', 'ChronicCond_ObstrPulmonary',\n", " 'ChronicCond_Depression', 'ChronicCond_Diabetes',\n", " 'ChronicCond_IschemicHeart', 'ChronicCond_Osteoporasis',\n", " 'ChronicCond_rheumatoidarthritis', 'ChronicCond_stroke',\n", " 'IPAnnualReimbursementAmt', 'IPAnnualDeductibleAmt',\n", " 'OPAnnualReimbursementAmt', 'OPAnnualDeductibleAmt', 'Birth_year',\n", " 'Age', 'isAlive', 'TotalAnnualReimbursableAmt',\n", " 'TotalAnnualDeductibleAmt'],\n", " dtype='object')" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "beneficiary.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exploratory Data Analysis (Graphical and Statistic) - Inpatient" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(40474, 30)\n" ] }, { "data": { "text/plain": [ "AdmissionDt object\n", "AttendingPhysician object\n", "BeneID object\n", "ClaimEndDt object\n", "ClaimID object\n", "ClaimStartDt object\n", "ClmAdmitDiagnosisCode object\n", "ClmDiagnosisCode_1 object\n", "ClmDiagnosisCode_10 object\n", "ClmDiagnosisCode_2 object\n", "ClmDiagnosisCode_3 object\n", "ClmDiagnosisCode_4 object\n", "ClmDiagnosisCode_5 object\n", "ClmDiagnosisCode_6 object\n", "ClmDiagnosisCode_7 object\n", "ClmDiagnosisCode_8 object\n", "ClmDiagnosisCode_9 object\n", "ClmProcedureCode_1 object\n", "ClmProcedureCode_2 object\n", "ClmProcedureCode_3 object\n", "ClmProcedureCode_4 object\n", "ClmProcedureCode_5 object\n", "ClmProcedureCode_6 object\n", "DeductibleAmtPaid float64\n", "DiagnosisGroupCode object\n", "DischargeDt object\n", "InscClaimAmtReimbursed int64\n", "OperatingPhysician object\n", "OtherPhysician object\n", "ProviderID object\n", "dtype: object" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print(inpatient.shape)\n", "inpatient.dtypes" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "AdmissionDt 0\n", "AttendingPhysician 112\n", "BeneID 0\n", "ClaimEndDt 0\n", "ClaimID 0\n", "ClaimStartDt 0\n", "ClmAdmitDiagnosisCode 0\n", "ClmDiagnosisCode_1 0\n", "ClmDiagnosisCode_10 36547\n", "ClmDiagnosisCode_2 226\n", "ClmDiagnosisCode_3 676\n", "ClmDiagnosisCode_4 1534\n", "ClmDiagnosisCode_5 2894\n", "ClmDiagnosisCode_6 4838\n", "ClmDiagnosisCode_7 7258\n", "ClmDiagnosisCode_8 9942\n", "ClmDiagnosisCode_9 13497\n", "ClmProcedureCode_1 17326\n", "ClmProcedureCode_2 35020\n", "ClmProcedureCode_3 39509\n", "ClmProcedureCode_4 40358\n", "ClmProcedureCode_5 40465\n", "ClmProcedureCode_6 40474\n", "DeductibleAmtPaid 899\n", "DiagnosisGroupCode 0\n", "DischargeDt 0\n", "InscClaimAmtReimbursed 0\n", "OperatingPhysician 16644\n", "OtherPhysician 35784\n", "ProviderID 0\n", "dtype: int64" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inpatient.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 40474 entries, 0 to 40473\n", "Data columns (total 30 columns):\n", "AdmissionDt 40474 non-null object\n", "AttendingPhysician 40362 non-null object\n", "BeneID 40474 non-null object\n", "ClaimEndDt 40474 non-null object\n", "ClaimID 40474 non-null object\n", "ClaimStartDt 40474 non-null object\n", "ClmAdmitDiagnosisCode 40474 non-null object\n", "ClmDiagnosisCode_1 40474 non-null object\n", "ClmDiagnosisCode_10 3927 non-null object\n", "ClmDiagnosisCode_2 40248 non-null object\n", "ClmDiagnosisCode_3 39798 non-null object\n", "ClmDiagnosisCode_4 38940 non-null object\n", "ClmDiagnosisCode_5 37580 non-null object\n", "ClmDiagnosisCode_6 35636 non-null object\n", "ClmDiagnosisCode_7 33216 non-null object\n", "ClmDiagnosisCode_8 30532 non-null object\n", "ClmDiagnosisCode_9 26977 non-null object\n", "ClmProcedureCode_1 23148 non-null object\n", "ClmProcedureCode_2 5454 non-null object\n", "ClmProcedureCode_3 965 non-null object\n", "ClmProcedureCode_4 116 non-null object\n", "ClmProcedureCode_5 9 non-null object\n", "ClmProcedureCode_6 0 non-null object\n", "DeductibleAmtPaid 39575 non-null float64\n", "DiagnosisGroupCode 40474 non-null object\n", "DischargeDt 40474 non-null object\n", "InscClaimAmtReimbursed 40474 non-null int64\n", "OperatingPhysician 23830 non-null object\n", "OtherPhysician 4690 non-null object\n", "ProviderID 40474 non-null object\n", "dtypes: float64(1), int64(1), object(28)\n", "memory usage: 9.3+ MB\n" ] } ], "source": [ "inpatient.info()" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "AdmissionDt datetime64[ns]\n", "AttendingPhysician object\n", "BeneID object\n", "ClaimEndDt datetime64[ns]\n", "ClaimID object\n", "ClaimStartDt datetime64[ns]\n", "ClmAdmitDiagnosisCode object\n", "ClmDiagnosisCode_1 object\n", "ClmDiagnosisCode_10 object\n", "ClmDiagnosisCode_2 object\n", "ClmDiagnosisCode_3 object\n", "ClmDiagnosisCode_4 object\n", "ClmDiagnosisCode_5 object\n", "ClmDiagnosisCode_6 object\n", "ClmDiagnosisCode_7 object\n", "ClmDiagnosisCode_8 object\n", "ClmDiagnosisCode_9 object\n", "ClmProcedureCode_1 object\n", "ClmProcedureCode_2 object\n", "ClmProcedureCode_3 object\n", "ClmProcedureCode_4 object\n", "ClmProcedureCode_5 object\n", "ClmProcedureCode_6 object\n", "DeductibleAmtPaid float64\n", "DiagnosisGroupCode object\n", "DischargeDt datetime64[ns]\n", "InscClaimAmtReimbursed int64\n", "OperatingPhysician object\n", "OtherPhysician object\n", "ProviderID object\n", "dtype: object" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#convert all date to datetime\n", "inpatient['AdmissionDt'] = pd.to_datetime(inpatient['AdmissionDt'], infer_datetime_format=True, errors='coerce')\n", "inpatient['ClaimEndDt'] = pd.to_datetime(inpatient['ClaimEndDt'], infer_datetime_format=True, errors='coerce')\n", "inpatient['ClaimStartDt'] = pd.to_datetime(inpatient['ClaimStartDt'], infer_datetime_format=True, errors='coerce')\n", "inpatient['DischargeDt'] = pd.to_datetime(inpatient['DischargeDt'], infer_datetime_format=True, errors='coerce')\n", "\n", "inpatient.dtypes" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " DeductibleAmtPaid InscClaimAmtReimbursed\n", "count 39575.0 40474.000000\n", "mean 1068.0 10087.884074\n", "std 0.0 10303.099402\n", "min 1068.0 0.000000\n", "25% 1068.0 4000.000000\n", "50% 1068.0 7000.000000\n", "75% 1068.0 12000.000000\n", "max 1068.0 125000.000000" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inpatient.describe()" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "#convert int datatype of category attribute to category\n", "\n", "inpatient['ClmAdmitDiagnosisCode'] = inpatient['ClmAdmitDiagnosisCode'].astype('category')\n", "inpatient['ClmDiagnosisCode_1'] = inpatient['ClmDiagnosisCode_1'].astype('category')\n", "inpatient['ClmDiagnosisCode_10'] = inpatient['ClmDiagnosisCode_10'].astype('category')\n", "inpatient['ClmDiagnosisCode_2'] = inpatient['ClmDiagnosisCode_2'].astype('category')\n", "inpatient['ClmDiagnosisCode_3'] = inpatient['ClmDiagnosisCode_3'].astype('category')\n", "inpatient['ClmDiagnosisCode_4'] = inpatient['ClmDiagnosisCode_4'].astype('category')\n", "inpatient['ClmDiagnosisCode_5'] = inpatient['ClmDiagnosisCode_5'].astype('category')\n", "inpatient['ClmDiagnosisCode_6'] = inpatient['ClmDiagnosisCode_2'].astype('category')\n", "inpatient['ClmDiagnosisCode_7'] = inpatient['ClmDiagnosisCode_7'].astype('category')\n", "inpatient['ClmDiagnosisCode_8'] = inpatient['ClmDiagnosisCode_8'].astype('category')\n", "inpatient['ClmDiagnosisCode_9'] = inpatient['ClmDiagnosisCode_9'].astype('category')\n", "inpatient['ClmProcedureCode_1'] = inpatient['ClmProcedureCode_1'].astype('category')\n", "inpatient['ClmProcedureCode_2'] = inpatient['ClmProcedureCode_2'].astype('category')\n", "inpatient['ClmProcedureCode_3'] = inpatient['ClmProcedureCode_3'].astype('category')\n", "inpatient['ClmProcedureCode_4'] = inpatient['ClmProcedureCode_4'].astype('category')\n", "inpatient['ClmProcedureCode_5'] = inpatient['ClmProcedureCode_5'].astype('category')\n", "inpatient['ClmProcedureCode_6'] = inpatient['ClmProcedureCode_6'].astype('category')\n" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "#durastion of stay in the hospital\n", "inpatient['duration_of_stay'] = inpatient['DischargeDt'] - inpatient['AdmissionDt']\n", "inpatient['duration_of_stay'] = inpatient['duration_of_stay'] / np.timedelta64(1, 'D')" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Average Amount Reinbursed by Duration of Stay')" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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I5557BoAFC+bx/PPPEArlc+BADjfccCMjR57Mgw/eR//+AznrrHNLvU4iIiIiInI4la0eZYLBIO3atWP1agvLWsELL7zKSy+9wa5du/jiiymsXLmcSZMmMn78Gzz++DPs2rWzzPbC4TD33383d911H6+++g6dO3dlypRP+ctfbsE0e3LzzX877Jj09AxeeulN7rxzLA88cA/h8E8rge7Zs4f//vcpHn30KV566U2OP34ozz77JAC2bfPFF58xatRpjBp1Op9++jG2bRccu27dWp588jluu+1OHn74fi677EpeffUdVq1ayZo1q/nrX2+lefPMEhNH13X58ssv6NPnWAA++OAdbr/9bsaPf4Pbb7+LF154tsj+lb1OIiIiIiJ1nWYeSzH82KrNDlYPg/fee5u9e/dw9dVXABAK5dOyZSuys7MZOnQ4GRkZAJxyyqlEo9FSW1q3bg2ZmZl062YCcM011wOUeF/jIeeccx4AXbt2o0mTJmzcuKHgteXLl7Jjx3ZuuMGbUXScKA0bNgJgxoxpNGvWnE6dOuO6Lj6fjxkzpnHSSacAMHjwEAKBAK1atS7YD7zS3QMH9lO/fv3DYhkz5lIAIpEwHTp04rbb7gTg7rsf4Pvvp/HNN1+ybNkS8vLyihw3f/68Sl0nEREREZG6TsnjUSYSibBp00b69x/E6aefwW9+czkABw4cwO/38/HHHwJuwf5+v79IUuS6LoZhFMz4+f0B4KdHQeTk5JCbe7DMGPx+f8HPjuMSCAQK/R6lb9/j+Oc//wNAKBQqSNwmT57Ijh3bufDCcwE4eDCHjz/+sCB5LNxO4T7KUviex8Kuu+73DBgwkP79BzJw4GDGjr2ryOve4y9Kv04iIiIiIlKUylaPIo7jMG7cc/TqdSxnn/0LPv98Mrm5udi2zR133My3337FoEGDmTFjGjk5OYRCIaZO/abg+MaNG7N+/Vpc12X69KkAtG/fgb1797B+/ToA3njjFT766AP8/kCpydT//jcF8Eo/c3MP0q5d+4LXevXqw7JlS8jK2gjAyy+/yNNPP86PP2YzZ85sXnvtHd5//xPef/8Txo9/g3nzZhcszFOeiiZ4+/btY9OmjVx99TUMHTqcadO+w3GcIvuUdZ1ERERERORwmnms4Xbv3lVQmuk4Ubp1M7nvvgdp2LAha9as4g9/GIPjRBky5ATOPPMcDMPg17++hN/9bjQNGjSgZcufSm+vueZ6brvtRpo2bUbfvv3Yt28vqamp3H33/fz97/di2xHatGnL3XffTyQSJifnAA88cDdnn31ekZhyc/O46qpL8fn83Hvvg0VmDJs1a87tt9/DPffcgeNEycxsyT333M+kSZ8wbNgJZGa2KNj3mGPaMmLEiUycOIGUlJRyr0XTps1o2bIVf/7zH3nyydIfq9GoUSPOOec8rrjiIgKBAAMGDCY/P79I6Wq3bmap10lERERERA5nuK5b/l5VZJrmvcBFsV8nWZZ1m2maLwEjgEO1kWMty5pgmuapwGNAOvCOZVl3xdroB7wINASmAtdYlmWbptkeeB1oAVjAZZZl5VQgrI7A+uzsHByn6Llv376RVq06VP2EpUYIBHzYtlP+jkcRvTc9mZkN2LXrQLLDkATR+NZuGt/aS2NbuyVqfF0nSnjx5wS7DMbXIDPu7UvZfD6DZs3qA3QCNlT4uEQFFEsGTwf6A/2AgaZp/goYBJxoWVa/2J8JpmmmA+OB84CewGDTNM+MNfU6cL1lWd3xbs77fWz7M8AzlmX1AOYCdyfqXEREREREJH7CCycRnv0u+d+8QCInsyS+EnnP4zbgZsuywpZlRYAVQPvYn/GmaS42TXOsaZo+4HhgtWVZ6y3LsvESxl+bptkBSLcsa2aszZdj24PAicD7hbcn8FxERERERCQOoj9uIjz/Y4wGmUS3r8JePSPZIUkFJeyeR8uylh362TTNbnjlqyOBk4E/AfuAT4GrgRy8ZPOQbUBboE0p25sD+2OJZuHtFRabpi1i504fgYDWEKoNats4+nw+MjMbJDuMGkHXoXbT+NZuGt/aS2Nbu8VzfN2ozZaJL+FLq0e7q//J9vf+SXj2u7QcMBJ/+uGfz6VmSfiCOaZp9gYmAbdalmUBvyr02pPAaLwZxMLz1Qbg4M2MVmQ7se0VVtI9j47j1Lp75eqi2njPo+M4up8E3VdT22l8azeNb+2lsa3d4j2+ofkTCW9fR9qp1/Fjrg//kEsJTbiPrZ+9QtqI0XHrR8pW6J7Hyh2XgFgKmKY5HPgKuN2yrFdM0zzWNM0LCu1iABFgM1B4uctWwNYytu8EGpmmeehhgK1j20VEREREpAY6VK4a6Hw8wc6DAfA370Cw18+ILP+G6K4NyQ1QypXIBXPaAR8Bl1qW9XZsswE8bppmk9h9i38AJgCzvEPMrrGE8FJgimVZG4H8WBIKcEVsewSYBlwc2z4amJKocxERERERkapzHZv8b1/ESMkgdfjlRV5LHXw+RnoD8qe/guvUruqx2iaRM4+3AGnAY6ZpLjRNcyFwAvAwMANYDiy0LOsty7LygTHAB7HtK/lpMZzLgP+YprkSqA/8X2z7n4A/mKa5HO9eyrsSeC4iIiIiIlJF4YWTcXZvJHXEaHzpDYu8ZqRkkDr0Nzi71hNZ+V2SIpSKSOSCOX8B/lLKy8+UsP9XwHElbF+Etxpr8e0b8RbfqbVGjBjE9Olz49bewYM5/Pe/T7Nw4Tz8/gANGjTg+utvxDR7MH/+XMaPf56nnnq+1ONffPG/9OjRkxEjTqpUv1dffQXNmjXnX//6T6WOy8nJ4cEH7+Phhx8BvOvRtWt3AFzXJSfnAEOGDOPmm2/H7/eX2s6YMZfy8stvVqjPilyHRIr3mIuIiIgkWzT78HLV4gJdh+FfOZXQnPcJdBp4WIIpNUPCF8yRmsFxHG655S8MGDCIl156k0AgwPz5c7nllht4/fV3K9TG7353TaX7XbNmNSkpQdasWcWOHdtp2bJVhY89cGA/q1dbRbYVTgIPHszhiisuZvbsmQwbNrz44SUeIyIiIiLVx3Vs8r97ESO1Hqkjrih1P8MwSB1xBbnv30N49nuknXR1NUYpFaXksRSRVTOIWFMT0nbQPJFg99KTneLmz5/La6+9RFpaGhs2rKdLl67ce++DhMMh7rvvTrKzswH47W9/z4gRJ7F6tcW//vUQoVA+DRs24p57HiArayM7dmzn6qv/iM/nVSsPGDCI//f/7sEpVlu+YME8nn/+GUKhfA4cyOGGG25k5MiTefDB++jffyD9+w/kjjtuoUOHDqxfv47u3XvQp09fpkz5lAMH9vPQQ4/QsWMnACZPnsigQUPYv38fn3zyUUECOm7cc+zYsZ1Nm7LYu3cPo0f/lnnz5rB8+VK6du3O2LEP8fjj/2b37l3cccctBbOPhe3du7fgHAGmTPmU9957C9d16d69Bzfd9DdSU1MLZvMq0ifAvn17uemmP7N790569erDTTf9jZSUlCKzgpMnf8KCBfO48877uPDCc+nVqw+rV1v85z/P8OijDx82Jps3b+KRRx5m//59pKamceONt9K9ew+2bdvK/fffTV5eHr1796nwe0JERETkaHCoXDXttOvxpZX9yA9/k2MIHns6kcVTCJon4m/VrZqilIqqXQ/Dq8WWLl3MjTfexhtvvM+OHduZNesHpk79llat2jB+/OvcccfdLFq0EICxY+9mzJjf8eqr7/Czn53Oe++9zapVFt26dS9IHA8ZNmwETZo0LbLtgw/e4fbb72b8+De4/fa7eOGFZw+LZ+3a1Vx22ZW8/PJbLFmyiO3bt/Hccy9x6qk/Z+LEDwGwbZsvvviMUaNOY9So0/n004+xbbugjXXr1vLkk89x22138vDD93PZZVfy6qvvsGrVStasWc1f/3orzZtnFkkcx4y5lMsvv4hzzjmVhx4ay1/+ciu9e/dh3bq1fPLJRzz77Hhee+1tmjRpyltvvXZY3OX1CbBt21ZuvPFWXnnlbXJzc/noow/KHZ+hQ0/grbc+ZMGCuSWOyYMP3suf/nQD48e/wW233cm99/4/AP7zn39x1lnn8vLLb3LssYdVbYuIiIgctYqUq3YaVKFjUgeeh1GvKfkzXsV1ogmOsO6yNy+t0nGaeSxFsPvwSs0OJlqnTl1o0aIlAB06dOLAgf306dOX5557mt27dzJs2AjGjLmavXv3kp29m+HDRwLwq19dCMDbb79OSkpqhfq6++4H+P77aXzzzZcsW7aEvLy8w/Zp2rQZ3bv3ACAzswUDB3r1661atWbBAu+pKTNmTKNZs+Z06tQZ13Xx+XzMmDGNk046BYDBg4cQCARo1ap1wX4AzZtncuDAfurXP/zZM4dKUN955w0mT/6UkSO9+y8XLJjL5s2b+OMfr8IwIBKJFMRXWHl9Ahx33ADatWsPwOmnn8GkSZ9w0UWXlHnNevXyZg1LGpPc3FxWrFjOQw/dX7B/Xl4e+/btZcGCedx334Oxvs7kH/94oMx+RERERI4GBaurllOuWpwRTCN12CXkf/k0kWVfkXLs6QmMsu6KrJoOxw2t9HFKHo8SKSkpBT8bhoHrurRr154333yfmTN/YMaMqbz99us8//wrGIZRsG8oFGL37l306NGLCRPex3XdIq8/99zTDB48pEhf1133ewYM8MpTBw4czNixhy9kGwwGi/xe0oI1kydPZMeO7Vx44bmAd4/ixx9/WJA8BgKBMo8vy8UXX8asWT/w9NNPcMsttxONOowadSp//eutBAI+9u/PIRo9/NuqivRZeLvjuEWOOXT9Cs+gAqSmeol5aWOSkpJa5N7LnTt3xMptDRzHBbxx9fkqdx1EREREaqLwwkk42RUrVy0u0GkQ/rZ9CM39kECX4/FlNE5QlHWTk7sXZ8faKh2rstWj2AcfvMO4cc8xatSp3Hzz7ezZswfXdcnMbMHs2TMB+PzzyYwb9xzHHdefJk2aMn788wVJ1axZPzB58sSC+xMB9u/fx6ZNG7n66msYOnQ406Z9d9g9kRXx44/ZzJkzm9dee4f33/+E99//hPHj32DevNls2bK5Qm34/f4SE8BDrr/+RiZN+pg1a1bTv/9Apk79lj17fsR1XR599GHefbdqC+UsXryQ7du34zgOn302iUGDvMV+GzduzPr1a3Fdl+nTS74ftrQxadu2HZ9/PhmAOXNmct11fwBg0KDjC7Z/993XhMOhKsUsIiIiUlN45aoTCXQZUuFy1cIMwyBt+OUQtQnNfLv8A6RS7HVzALdKx2rm8Sh2xhlnc999dzJ69MX4/X6uu+4GGjRowD33PMAjjzzMM8/8H40aNebuu+/HMAz+8Y/HePLJRxk9+mICgQCNGjXm3/9+gqZNm7Fhw3oAGjZsxDnnnMcVV1xEIBBgwIDB5Ofnl1i6WpbPPpvMsGEnkJnZomDbMce0ZcSIE5k4cUKRmdTSNG3ajJYtW/HnP/+RJ5987rDXO3fuwhlnnM1TT/2Hxx9/hquu+j033HANruvStWt3Lr98TKViPqRTp848/PD9ZGfvZuDAQZxzznkAXHPN9dx22400bdqMvn37sW/f3sOOLW1M7r337/z73w/x5puvEggEuf/+hzAMg5tuuo0HHriHiRMn0KNHTzIy6lUpZhEREZGaoEi56vDLq9yOr1ErUvqdTXj+x9g9TiLQpmcco6zbImtnEWjSpkrHGq5btazzKNYRWJ+dnVNQLnjI9u0badWqQ1KCkvgJBHzYduVnS2syvTc9mZkN2LXrQLLDkATR+NZuGt/aS2Nbu1V2fEPzPyY8dwJpp/2ZYKeBR9S3a4c5+N6dGP4gGRfcj+HXvNeRcg7s4uBbt5J+4pW0HvkLgE7Ahooer7JVERERERE5YkXLVY8scQQwAimkDb8MZ+9Wwks+j0OEElk7G4BA+35VOl7Jo4iIiIiIHJF4lasWF2jfj0CH/oTnf4yTkx23dusqe+0sfC264KvftPydS6DksZg6WMYrNZzekyIiIlLThRd4q6umjriy0qurlif1hMvAhdD3VVsMUTzRvVtxsrMIdhlS/s6lUPJYSCCQwsGD+/VhXWoM13U5eHA/gUD5CwyJiIiIJEM0OytWrjo0LuWqxdLrDcQAACAASURBVPkaNCdlwC+wN8zDzloc9/brCnvNLMAg0OX4Krehu04LadIkkz17dpGTc/gqmnL08Pl8VXq8SE0VCKTQpElmssMQEREROUxBuWpaPe/xGgmS0vcM7FXTyf/+deq1+TtGDfhi3XWiGEfJM7pd18VeOwt/mx5H9NxMJY+F+P0Bmjdvneww5Ahp1TcRERGR6uGVq2aRdtqfMdLqJ6wfwx8gdcRo8ib9i/CiyaQO/GXC+iqP69iEZn9AZNn/yDjndvwtuyYtlopysrNw9m0nte8ZR9SOylZFRERERKTSEl2uWlzgmF4EOh9PeOGnOPt3Jry/kjg52eR+8g8ii6eA4xJe8kVS4qgse+0sMPwEOw06onaUPIqIiIiISKVUV7lqcanDLgFfgPwZr1f7OiX2xoUc/OAenB83k/azawn2/hn2hnk4ufuqNY7Kcl2HyNpZ+Nv2PuLZYSWPIiIiIiJSKeEFn+JkZ5E68sqElqsW56vXhNSBvyK6aTH2xvnV0qfr2OTPfIe8zx/HV78Z9c6/j2CXIaT0OgWcKBFrarXEUVXOjrW4OdkEuw494raUPIqIiIiISIVFd28kPP8TAl2HEuyY+HLV4oJ9TsXXtC2hGW/gRkIJ7atwmWqw1ygyzrsLX6NWAPgat8bfpieRFd/i1uDFGiNrZ4E/SKBD/yNuS8mjiIiIiIhUiOvY5H8XK1c9ofrKVQszfH5SR4zGPfgj4QUTE9ZP0TLVP5E2YvRhq7wGe43CzckmuqlmPkLEdaLY62YTaH8cRkr6Eben5FFERERERCrEK1fdVO3lqsUFWnUn0H0E4cWfEd27Na5te2WqbxcqUx1LsJRnIwY69sfIaEx4+ddxjSFeotss3Lz9BLoMiUt7Sh5FRERERKRcyS5XLS51yEUQSCU0/bW4LZ7j5GSTO/FhIos/K1Sm2rLU/Q1fgGCPE4luWoKzf1dcYogne81MCKYRaH9cXNpT8igiIiIiImVyo8kvVy3Ol96Q1OMvJLp1hfcoiiNkb1zglanu2VJqmWpJgj1OAgMiK7894hjiyY3aRNbPJdBxQIXOoyKUPIqIiIiISJnCCz6JlauOSWq5anHBHifjy+xEaObbuOG8KrXxU5nqE/jqNy+zTLUkvvrNCLTvR2TlVNyoXaUYEiG6eQmEcwnGqWQVlDyKiIiIiEgZors3El7wKYGuwwh2HJDscIowfD7Shl+Bm7uP0NwJlT7eObC7WJnqnWWWqZYm2GsUbv4B7PVzK31sokTWzoLUevjb9o5bm0oeRURERESkRG40Uqhc9bJkh1Mif4vOBHueTGTZl0SzN1X4OHvjAg5+eK9XpnpqxctUS4yhbW+Mhi2IrPimSsfHm2uHsDcsINhpMIYvELd2lTyKiIiIiEiJ9sz4sEaWqxaXOvgCjNR6hKa/iuuW/czFEstUO1e8TLUkhuEjpefJRLdZRH/cckRtxYO9cRHYIQJd41eyCkoeRURERESkBNHdG9k744MaWa5anJFWn9QhFxHdsRp71YxS9ytapvqzKpepliRgjgR/gMiK5D+2w147CyOjMf5WZlzbVfIoIiIiIiJFuK5L/nfj8Kc3qLHlqsUFug/H17IroVnv4ubnHPb64WWqV8RtFVIAX1oDAp0GE1n1PW4kP27tVpYbzsXetIhA58EYvvime0oeRURERESkCCc7Cyc7iyYnXlyjy1ULMwwfaSOuxA0dJDTng4LtbtQm/4e34lqmWpqUXqMgkkdkzcyEtF8R9ob5ELUJdh0a97bjd/ekiIiIiIjUCnbWIgAyug8mVLUnYCSFv1k7gr1PJbL0fwTNkRjpDcn76hmcnesI9voZqUMvjutsY3G+ll3xNW1HZPk3BHuchGEYCeurNJE1MzEaZOLL7Bz3tpU8ioiIiIhIEXbWInyZnQjUbwJ5B5IdTqWkDvoV9rrZ5H3zPG7+AXAc0k69jmDnwQnv2zAMgr1OITT9VZxd6/C36JLwPgtz8vYT3bKclOPOSkjiqrJVEREREREp4OTtx9m5jkD7fskOpUqMlHRSh/4Gd992fA2aU++CsdWSOB4S7DoMgmmEl1f/wjn2+rngOgS6xHeV1UM08ygiIiIiIgWim5YALoEOxyU7lCoLdBlCRsNMfM3aY/iD1dq3kZJOsNsJRKxpuEMvqdZ7Ru21s/A1boOvaduEtK+ZRxERERERKWBnLcTIaIyvWYdkh1JlhmHgb9Gl2hPHQ4K9ToFohMiq6dXWp5PzI9Ftqwh0HZKwey2VPIqIiIiICOCtTGpvWkqgfd+kLPZSW/ibtsPfshvhFd/guk619Gmvmw24BBNUsgpKHkVEREREJCa6fRVE8vAfpfc71iTBXqfg7ttBdMuKaukvsnYWvuYd8TVqlbA+lDyKiIiIiAgQe0SHL0DgmF7JDuWoF+g8GCOtAZFqWDjH2bcDZ9f6hM46gpJHERERERGJsbMW4W/TAyOYluxQjnqGP0jQHIm9cQHOwT0J7SuydhYAgS7HJ7QfJY8iIiIiIoKzbzvuvu1H7SM6aqJgz5PBdYms/C6h/dhrZ+Nv1R1f/WYJ7UfJo4iIiIiIeCWrQKD90fuIjprG17AF/nZ9iKz8DteJJqSP6I+bcfZsTvisIyh5FBERERERvOTR16QNvoaZyQ6lVknpOQr34B7sjQsT0r69dhYYBoHOSh5FRERERCTB3HAe0a2WSlYTwN/+OIx6TROycI7rukTWzMTfphe+9IZxb784JY8iIiIiInWcvXkpuFH8KlmNO8PnI9jzZKJbluHs2x7Xtp1d63EP7CLYdWhc2y2NkkcRERERkTrOzloEqfXwt+ya7FBqpWCPE8HwE17xbVzbjaydBT4/gY4D4tpuaZQ8ioiIiIjUYa7rEM1aRKDtsRg+f7LDqZV8GY0JdBpAxJqGa4fj0qbrOthrZxFo1xcjtV5c2iyPkkcRERERkTrM2bUeN/8AgQ4qWU2kYK9REDqIvW5OXNqLbl+Nm7uXQJchcWmvIpQ8ioiIiIjUYXbWIm+1zrbHJjuUWs3fuge+xq0Jx2nhHHvNTAikEOjQPy7tVYSSRxERERGROszeuAh/y24YafWTHUqtZhgGwZ6n4OxcS3T3xiNqy3Vs7PVzCXTojxFMjVOE5VPyKCIiIiJSRzkH9+Bkb9Qqq9Uk2H04+FOILP/miNqJblnulRpXY8kqKHkUEREREamz7KxFAHq+YzUxUusR7DqEyJofcMN5VW4nsnYWpKQTaFe9pcZKHkVERERE6qho1iKM+s3wNWmT7FDqjGCvUWCHiKyeUaXjXTuMvX4+gY6DMPzBOEdXNiWPIiIiIiJ1kGuHsbcsI9C+H4ZhJDucOsOf2QlfZiciy7/Bdd1KH29vWgKRPIJdq7dkFZQ8ioiIiIjUSdGtK8EO6xEdSZDS8xScPVuIbl9V6WPttbMw0hrgb9MzAZGVTcmjiIiIiEgdZGctgkAK/tY9kh1KnRPoOgRSMiq9cI4bycfeuJBA58EYPn+CoiudkkcRERERkTrGdV3srIUEjumNEUhJdjh1jhFIJdh9OPb6OTh5+yt8nL1xAUTDBLoOTWB0pVPyKCIiIiJSxzh7tuDmZOsRHUkU7HUKOFEi1tQKHxNZMxOjXlP8LbsmMLLSKXkUEREREaljfnpEh5LHZPE3boO/TU8iK77FdZxy93fzc4huXkqgy/EYRnLSOCWPIiIiIiJ1TDRrEb5mHfDVa5LsUOq0YK9TcA/sJrp5Sbn7RjbMAydKsEtySlZByaOIiIiISJ3i5ucQ3bFaq6zWAIGOAzDSGxFe/nW5+9prZ2E0bImveYdqiKxkSh5FREREROoQe9NicF0C7fslO5Q6z/AFCPY4kWjWYpwDu0vdz8ndS3TrCoJdhyT1mZxKHkVERERE6hA7azFGekN8mR2THYoAwZ4ngwGRFd+Wuo+9bo6X8HcZUm1xlUTJo4iIiIhIHeE6UexNi/G365u0RVekKF/9ZgTa9yNiTcWN2iXuE1k7C1/TdvibHFPN0RWld4yIiIiISB0R3bEGwrlaZbWGCfY6BTdvP/aGeYe95hzYjbNjTdJnHUHJo4iIiIhInRHNWgQ+P4G2fZIdihTib9sHo0EmkRIWzomsnQ1AsMvx1R3WYZQ8ioiIiIjUEXbWQvytTYyU9GSHIoUYho9gz1OIbrOI7tlS5DV77Ux8LTrja9giSdH9RMmjiIiIiEgd4OzfibNnq0pWa6igOQJ8ASLLvynYFt27FSc7i2ANKFkFJY8iIiIiInWCnbUIQI/oqKF86Q0JdB5MZNUM3EgIAHvtbMAg0Dn5Jaug5FFEREREpE6wsxZhNGqFr1HLZIcipQj2GgWRPCJrZ+K6Lvaamfhbm/jqNUl2aICSRxERERGRWs+N5BPdulIlqzWcv2VXfE3bEln+NU52Fs6+7QS6Dk12WAWUPIqIiIiI1HL2lmXg2AQ6qGS1JjMMg2CvUTi7NxKa9Q4YfgKdBiY7rAJKHkVEREREarlo1iIIpuNv1S3ZoUg5gl2HQTCN6Jbl+Nv2xpfWINkhFVDyKCIiIiJSi7mug521mEC7Phi+QLLDkXIYKeleAgk1ZpXVQ/TuERERERGpxZzdWbi5e7XK6lEkpd/Z4LoEOg1KdihFJDR5NE3zXuCi2K+TLMu6zTTNU4HHgHTgHcuy7ort2w94EWgITAWusSzLNk2zPfA60AKwgMssy8oxTbMx8AbQGdgFXGRZ1vZEno+IiIiIyNHGzloIGPjbHZvsUKSCfA2ak3bimGSHcZiEla3GksTTgf5AP2CgaZqXAOOB84CewGDTNM+MHfI6cL1lWd0BA/h9bPszwDOWZfUA5gJ3x7b/HZhmWVZP4AXgiUSdi4iIiIjI0crOWoSvRWd86Q2THYoc5RJ5z+M24GbLssKWZUWAFUB3YLVlWesty7LxEsZfm6bZAUi3LGtm7NiXY9uDwInA+4W3x34+G2/mEeAt4MzY/iIiIiIiAji5e3F2rdcjOiQuEla2alnWskM/m6bZDa989Um8pPKQbUBboE0p25sD+2OJZuHtFD4mVt66H8gEtlYkvmbN6lfyjORokplZc1alkvjS2NZuGt+SuU4Uw+dPdhhHTONbe2lsa679C2dzEMjsN5zUKo6TxlcOSfiCOaZp9gYmAbcCNt7s4yEG4ODNgLoV2E5s+6F9CjMKvVau7OwcHKd401IbZGY2YNeuA8kOQxJAY1u7aXxL5ubncPCDe/A1a0f6yb/HSDs6v/zU+NZeGtuaLW/ZLIx6TdlnNMWowjhpfGsnn8+o0mRaQh/VYZrmcOAr4HbLsl4BNgOtC+3SCm+msLTtO4FGpmke+rq1NT/NLG6J7YdpmgGgAZCdmDMRERFJjtDcCbi5e4huXsbBD+4humNNskMSkaOEG41gb1lGoH1fDKP4vItI5SVywZx2wEfApZZlvR3bPMt7yewaSwgvBaZYlrURyI8lmwBXxLZHgGnAxbHto4EpsZ8nx34n9vq02P4iIiK1QnT3RiIrvibYaxQZv7wLfH5yJz5MePHnuK6qZ0SkbNFtFkTy9YgOiZtElq3eAqQBj5mmeWjbf4ExwAex1ybz02I4lwEvmKbZEJgP/F9s+5+AV0zTvAvIAi6Jbb8beNk0zWXA3tjxIiIitYLruoRmvI6RWp/UQedjpNaj3vn3kf/dOEIz3yK6fRVpJ/0WI7VeskMVkRrKzloE/iD+Y3omOxSpJYw6+M1lR2C97nmsvVSbX3tpbGs3jW9RkdXfk//N86SeeBUpPU4q2O66LpElXxCa9S5G/aakn3Yd/uYdkxdoBWl8ay+Nbc3kui4H374NX+PWZJx5U5Xb0fjWToXueewEbKjwcYkKSERERKrGDecRmvkOvsxOBM2RRV4zDIOUvj8n4xd3gBMl9+O/E17+tcpYRaQIZ9823AO7CHRQyarEj5JHERGRGiY0/2PcvP2kDb8Cwyj5v2p/y65kXDAWf5uehKa/Sv43z+FG8qs5UhGpqaIbFwHo+Y4SV0oeRUREapDonq1ElvyPYI+R+Ft0LnNfX1oD0s+4kZTBF2CvnUXuhLFEf9xcTZGKSE1mZy3C17QdvvrNkh2K1CJKHkVERGoI13UJff8GBFNJGXxhhY4xDB+p/c8l/ezbcEMHyZ1wP5FV0xMcqYjUZG7oINHtqzTrKHGn5FFERKSGsNfPJbplGamDzseX3rBSxwba9CTjgvvxt+hM/rcvkv/deFw7nKBIRaQmszcvBddR8ihxp+RRRESkBnDtEKEf3sLXtB3BXqdUqQ1fRmPSz76NlP7nErGmkvvRAzh7t8c5UpHaI7z8a8LLvkp2GHFnZy3CSK2Pr0WXZIcitYySRxERkRogvOBT3IM/kjr8cgyfv8rtGD4fqYMvIP3Mm3AP7uHghPuIrJ0dx0hFaofoznWEpr9G6Ps3cPZuS3Y4ceM6DtGsxfjbHYvh00d9iS+9o0RERJLM2beD8KIpBLoOI9DajEubgXZ9ybhgLL6mbcn/6hnyZ7yGG43Epe26JLp7I3lfPoNzYFeyQ5E4ch2b/GkvYWQ0gkAKodnvJzukuHF2rsUN5egRHZIQSh5FRESSLP+HN8EfIHXIRXFt11e/GRnn3k6w7xlEln1F7sSHlARVgrN/F3lTHsVeN5vcSY/g5O5NdkgSJ5ElX+BkbyJ1+BWkHHcm9oZ5RHesSXZYcWFnLQLDR6Btn2SHIrWQkkcREZEksjcuJJq1iNQB5+Gr1yTu7Ru+AGlDf0Pa6X/G2bedgx/ci71hQdz7qW2c/APkTnkU14mSdvLvcHP3kjfpEdz8nGSHJkfI2b+L0NyPCHToT7DTQFKOPQMjvRGhWe/ium6ywztidtYi/K26Y6TWS3YoUgspeRQREUkS1w6T/8Ob+Bq3JtjntIT2Few4kHrnj8XXMJO8L54gf+Y7uI6d0D6PVq4dIu+zx3FzdpP+878Q7D6C9NNvwNm3ndzPHsON5Cc7RKki13XJn/4K+HykDr8CACOYSsrAXxLdvoroxoVJjvDIODnZOD9u0iqrkjBKHkVERJIkvORz3P07ST3hMgx/IOH9+Rq2IOMXdxLsNYrI4inkffovnIN7Et7v0cR1ouR9+SzOznWkjbqGQKvuAATa9ibt1Gtxdm0g7/Mn9BiUo5S9dibRzUtJHXwBvvpNC7YHe5yIr1ErQrPfw3WiSYzwyNhZiwDwd1DyKImh5FFERCQJnJxswvM/IdBxYLXem2QEUkgbMZq0UdcQ3b2R3A/u8Z4JJ7iuS2j6q0SzFpI6/DKCnQYVeT3YcSBpJ11NdOsK8r96VjO3Rxk3P4fQ92/iy+xMsNfPirxm+PykHP9rnL1biayanqQIj5ydtQijYQt8jVonOxSppZQ8ioiIJEFo5tuAS+qwS5LSf7DrUDLOvxcjvRF5kx8lsmFeUuKoScLzJxJZ+R0p/c4hpfepJe4T7D6c1OGXY29cQP6343Bdp5qjlKoKzXoHN3SQtBOvKvERFoGOA/C17Ep47gRcO5SECI+Ma4eIbllOoP1xGIaR7HCkllLyKCIiUs3sLcux180hpf85+Bo0T1oc/sZtyPjV3RiNWhBZ9FnS4qgJwiu/IzxvAoFuw0kZfEGZ+6b0PpWUwRdgr/mB0IzXa8UiK7WdvXUFEWsaKX3PwN+sXYn7GIZB6pCLcHP3El7yRTVHeOSiW1ZANKL7HSWhlDyKiIhUI9exCc14HaNBJil9z0x2OBiBVFJ6nER0x2qie7YmO5yksLMWEpr2Cv62fUg76aoKzdqk9DuHYN8ziSz/mvCcD6ohSqkq1w6TP+0V79/cwPPK3DfQqjuBDv0JL5yMk3+gmiKMDztrIQTT8MfpWbEiJVHyKCIiUo0iS7/E2buVtBMuxQikJDscAALdhoPhJ2JNTXYo1S66cx15Xz6Dr1l70k+9DsNXsYWLDs1SBXucTHjhp4QWTk5wpFJV4YWTcPdtJ23klRiB1HL3Tzn+QrDzCc+fWA3RxYfruthZiwkc0xvDH0x2OFKLKXkUERGpJk7uXkLzPsLfri/+9v2SHU4BX0YjAh37Y6+agRuNJDucauPs207eZ//BSG9E+hk3YqSkV+p4wzBIHTGaQJchhGe/S3j5NwmKVKoqumcL4YWfEug6rMILU/mbHEPQHElk+dc4+3cmOML4cH7chHvwR5WsSsIpeRQREakmoVnvQtT2Zh1r2IIWwR4n4uYfwN64INmhVAsndx+5kx8FIOOsm/FlNKpSO4bPR9opv8ff/jhC018lsmZmPMOUI+C6DqFpr0AwrdILU6UM/BUYfkJzPkxQdPFlx55P6W/fN8mRSG2n5FFERKQa2NtXY6/+npS+Z+Br1CrZ4RzGf0wfjPrNiKz4LtmhJJwbziPvs8dw8/aRfsZfj3g8DF+A9FOvw9+6O/nfvFDwQV6SK7JyKtHtq0gb+ht86Q0rdayvXhNSjj3dey7krg2JCTCO7E2L8WV2wpfRONmhSC2n5FFERCTBXMchNOM1jHpNSel/brLDKZHh8xE0RxLdsgxn/65kh5MwrmOT9+XTONmbSD/1T/hbdIlLu0YghfSf/xVf8/bkffkU9tYVcWlXqsbJ3Uto1jv4W/cg0H1EldpI6XcWRmp9QrPfrdEr6jp5+3F2rFXJqlQLJY8iIiIJFln5LU52FqnDfoMRLH/BjmQJmiMBg8iqackOJSFc1yX/u5eIbl5K6sgrCcT5vlMjJZ2MM2/G17AFeZ8/QXTnuri2LxUX+v5NiEZIGzmmyiXiRkoGKQN+QXTLcqKbl8Y5wviJbloCuHF/P4uURMmjiIhIAjn5BwjN+QB/m54EOg1Odjhl8tVvhr/dsUSsabhONNnhxF14zgfYq2eQMvBXpPQ4KSF9GGn1ST/rVoy0BuROeZToj5sT0o+Uzs5aiL1uNin9f4Gv8ZGVJAd7nYLRIDM2++jEKcL4srMWYmQ0xte8fbJDkTpAyaOIiEgChWd/AOE8Uk+4vMYtklOSYI8TcQ/uIbp5SbJDiavwsq8IL/yUYI+TSBnwi4T25avXhIyzb8XwB8mb/MhRs2JnbeBG8smf/hq+Jm1IOe6sI27P8AdJHXwBTvYm7NU/xCHC+HIdG3vTUgLt+2IY+lgviad3mYiISIJEd60nsvI7gn1Ow9/0mGSHUyGBDv0w0hsSWVl7nvkYWT+P0IzX8bfvR+qI0dWSxPsatiD97FshapM76V84B/ckvE+B0NwJuDnZpI68CsNfsWd2lifQ5Xh8zTsSmvshrh2OS5vxEt2+GiJ5+HW/o1QTJY8iIiIJ4LoO+TNew0hvQOrA85IdToUZvgDB7iOwNy7Eyd2b7HCOmL19FflfP4uvRSfST70Ww+evtr79TY4h/aybcfNzyJv0b5z8A9XWd3UJL/0fm1+8hejuDckOheiuDUSWfkGw58kEWnWLW7uG4SN1yEW4OdlEln8Vt3bjwd64EHwBAsf0TnYoUkcoeRQREUkAe9UMnJ3rSB1yMUZKRrLDqZRgjxPBdYismp7sUI5IdM8W8j5/AqN+c9LPuBEjUP2LFfkzO5H+87/iHNhF3uRHccN51R5DorhOlPDCSYR3rCf3478TXv510lYldZ0o+dNewkhrSOrxv457+4FjeuFv24fQgk9xQwfj3n5VOHn7sdfNwd+mB0YwLdnhSB2h5FFERCTO3NBBQrPexdeyK4Fuw5IdTqX5GrXC39oksnJqjV0kpDzOwT3kTX4Uw+f3VkBNa5C0WAJtepB+2nU42ZvI+/xxXDuUtFjiKbp5CW7uXpqfdQ3+Nj0JTX+V/K+fS0qCHFn6P5zdG0kdfhlGar2E9JE65CII5RJeOCkh7VeGk7uXvE//gZt/gJR+5yQ7HKlDlDyKiIjEWWjeR7j5OaQNv+KoXcQi2OMk3P07iW6zkh1KpbnhXPKmPIYbziX9zJvwNcxMdkgE2vcjbdQfiG5bRd7/nsaN2skO6YhFVk7FSG9Ig76nkH7GjaQMvgB73SxyJ4yt1lVmnQO7Cc39EH/74xK6orG/WXsC3YYRXvoFTk52wvopj3NwD7mf/APnwG7Sz7yJQJseSYtF6p6j8380ERGRGir64yYiy74i2OsU/M07JDucKgt0GgQpGURWfpfsUCrFjUbI++JJnD1bST/tevzNOyY7pALBLkNIHXkl0U2Lyf/meVzn6JzVBW/my964kGD3ERj+gHdfYP9zST/7NtxwHrkT7q+WsmfXdcmf8RpgkFYNiyGlDjofXG9hnmRwDuwmd+JDuLl7ST/rFgJteiYlDqm7lDyKiIjEieu6hGa8jpGS4X3IPIoZgRSC3YZhr5+Lm5+T7HAqxHUd8r99kejWFaSd9FsCbfskO6TDpPQ8mdQhF2Ovm01o+stJu0fwSEVWfQ+uQ9AcWWR7oE1PMi4Yi79lF/K/fZH878YltEzXXjeHaNYiUgefj69+s4T1c4ivQXOCfU7FXjWD6I+bEt5fYc7+neR+8jBuKIeMs28l0Kp7tfYvAkoeRURE4ub/s3fncVLUd/7HX1Xd1ccw3AwgIgznF+QQARFFQQPedxI1ibkTzbVudrO5djf5Zc3u/nY32U2yZk1+uxpNNhpjItHECxAPQLlBTpmv3Ifc9zEz3dVd9fujBx0NzPTA9PRMz/v5ePCY7m9XV70n5Uz6M98rs3ER2V2W2IQP4yTKix3nrHnDroBsBn9D69vf7lRSC58gs3ERsQm34w2dVOw4pxW74DpiF96EXzWX1KIn2lwBGYYhvp1LpPdQ3C7n/NnrblkXktd/I/c92teofvofCQ7vav4cqROk5j+K26MSb8RVzX7+04mPuRFiSVKLft9i1wwO78r1OPq1lN34LSI9B7XYtUXqU/EoIiLSDEK/ltTC3+L26I9nJhc7TrOIdD8Pt2IA/ro5rb7ASa+agb96Jt6Iac2yOXyhxcZ/EG/EVPxVM0i/8Uyx4zRJdvdbhEd24w2bctpjHNclftGH9TIGQQAAIABJREFUSF73NcLqI5x46j78jYuaNUdq0e9zc4snfwbHbbmPtE6inNiYG8luX0Vm57qCXy978G2qn/kXCLKU3fTtVjUUW9ofFY8iIlJUuQ9G/8rW+++hZtZPSa14nszOKkK/ba1ImV7+J8Lqw7lFclrwg2yhecOmEBzaQbBvU7GjnJa/YSGphb8lOmA88Us+VvB5b83BcRzil95FdMilpJf+oVXsk5gvv2oueEmiA8c3emz0vFGUffA+It3Oo/aln1P72v8SZv2zzpDZ/RZ+1at4o64uytzi2MhpOB26kVr0u4L+YSW7fys1z/4rOC7Jm/6WSLfzCnYtkXxEix1ARETapzCTJv3GM6RXPo/jJSkbdAHVOzaQ2bIsd4Dj4HbrS6RiEJFeg3B7DsTtck6rXL00OLyL9OqZRIdeRqTX4GLHaVbeoItJLXgcv2pOqxwql92/ldpXHyLSeyiJK+9pU4W747gkJn2c41uWk141k+QHvlDsSI0K09VkNi3BGzop730z3fJuJG/6FqnFT+KvmkF27yaS076M26nnmWXI+qTm/hKnvDvxcbed0TnOlhONER9/G7VzfpH732PQhGa/RnbfZqqf/3ecaJyyG7+J27l3s19DpKlUPIqISIvL7FxH7bxfEh7ZQ3TIJOKXfIRe5/Vh375jBLXHCPZuIrt3E9m9G/E3LcavejX3Ri9JpOfAd/65PQfhJju1WO4wDAirjxAc2094fH/u67H9ZHZZiMQKsjl5sTmxJN6gCfgbFhGf+FGcWLLYkd4RhgG1r/8aJ5YkefVf4kRjxY7UZE6sDM9cjr/2ZYKL78Dt0LXYkRrkb1gI2XSDQ1ZPxXGjJCZ+hEjvodS++hAn/vA9Eld8Hq9yXJMzpFc+T3B4J8lrv4bj5VfAFkJ0yCTc1TNJLXmSaOVYnEjzfazO7tlA9fP/gZPoQNkN32oV282IgIpHERFpQWHtcWoXPkHmrXk4nXqSvP4bRPuOeM8xbqIjbr8LiPa7IPeeMCA4sjtXUO7ZSHbvptwm3XWb1zsdK+qKyUG5grJHf5yId2b5goCw+tA7RWFwfD/hsQMEJwvF4wcgyL7nPU6yU64HZMLtuGWdz+i6rZ03bAq+nYe/aTGxJhYNhZR563WCPRtITPlcm16gKDbyKvy1s/HXzm71f4Dwq+bidj8P9wyHinqVY4l88D5qXvoZtbN+SnbUNcQvvh3Hze8jaXB4F+nlzxAddDHRfqPPKENzcVyX+ITbqZnxY/x1rxIbOa1ZzpvZWUXNjB/jlHXJ9Ti2wCqyIvlS8SgiIgUXhiGZDQtILXicMFVNbMyNxMbenFdPkeO4RLr0IdKlD97Qy3Lny6TI7ttS10O5kezu9WROLsbhRnC793+3h7LXYJyOFTiOQxhkCU8crFccHnjP4/D4QQjfXxx2xunYg0jFANyBF+GUd8ft2AOnYw/c8u55D91ry9yeg3C7nou/bk6rKR7D1AlSi36H22sw0Va8smo+3E49iVaOI/3mK8QuvAnHSxQ70ill928l2L+F+KUfP6t5pW6nCspu/jtSC5/AXz2T7N6NJKd+qdEiKQxDauf9EqIx4pd87Iyv35wi540mco4hvfyPuaG8Z9kzn9mxlpqZ/4nbsTvJG7+FW9almZKKNI/TFo/GmEeA084AttZ+tiCJRESkpARH91I771dk316L23MQycmfPutFH5xonOg5Bs4x717nxCGyeze+U1D6di7+2tm54xMdIRojPHEQ3rO4hYPToQtueY/cvMpBF+eKwo49cMt74JR3a5NDIZub4zh4wyaTWvA42QPbiXQv/qIdqaVPEaaOk5z09VY5D7apYqOuIbN5Kf5brxEb0Tw9WM3Nt3MhEsUbcslZn8uJeCQmfZzIOUOpnfMw1dO/R+LKexrsTczYeWR3WeKTP9NqevkdxyF+8Z1UP/190qteOKv9XTPbVlLz4k9xO/cmecM3W3RIvki+Gup5XFP3dRLQD3gMyAB3Aq13yTUREWkVwiBDetVM0sv+CK5LfNIn8IZfWbAFTdwOXXEHjIcB4+uunyU4uKNu7uQmCDLv9hh2rMg97tCtWecplTJvyCRSi36f29/v0ruKmiV7YBv+my/hDb+yKCttFoLbazBuz4GkV7+IN/wDrW7hnzCTxl+/gOiA8TjxDs12Xm/gBCLd+lEz+wFqZvwoNyph/G04buQ9xwU1R6ld9ASR3kPxzOXNdv3mEOk5kOjAi0ivmoF3/gfOqLfQ37Kc2tkP4HbrS9n132jTw7CltJ32/zGttf8BYIy5DZhsra2ue/4g8ErLxBMRkbYou3cTtXMfITi4nWjlOOKTPt7iC4E4boRIj/654uL8K1v02qXISZQTHTAOf/184hNuL1qPbBiGpF5/FCdefla9PK2N4zjERl1L7Us/I7NtBV7l2GJHeo/M5qWQrm7yQjn5cLv0puzW75Ka/yjpFc+S3bOBxNQvvqcISy34Dfgp4pd/ulX2NMcv+jCZzctJL3uaxOWfbtJ7/U2LqX3pv3Er+lN23d80a3Eu0tzy+enrBdTfbCsEehQmjoiItGVhuoba1x+l+ul/JEwdJ3H1vSSvvrfVryAp+fGGTYHUiXe3UymCzPr5ZHe/RWzCh0uudyY6YBxOeXf81TOLHeXP+Da3yFWk3lDx5uREYyQmf5bEFXeT3beJ6un/h8zbbwKQ2b6azIaFxMbcQKRrn4Jc/2y5nXvhDb8Cv2ouweFdeb/PXz+f2pd+TqTXoFyPowpHaeXyGaszG5hhjPkN4ACfBP5U0FQiItLm+FuWk3r9UcITh/BGfID4RR9uVds6yNmL9BmG07ECv2ou3uCzn/fWVGG6mtSiJ3ArBra6oYvNwXEjxEZeRWrhb8nu20KkorLYkQAIjuwhu3MdsYs+VPBeP2/oJNweldTOfoCa539I7MKb8dfPx+3cm9iFNxb02mcrNu4W/PWvk1r8JMmr7230eL9qLrVzHyHSZxjJa77aahdKEqkvn98A9wLPArcBtwJPAN8oZCgREWk7ghOHqJn1U2pn3Y8TL6Ps1u+QmPQJFY4lyHFcvGGTye5cR3BkT4tfP7X0acKaYyQu+0SrHLrYHLxhk8FLkG5FvY++nQeO885qx4UW6XYuZbf9H6KDJpJe/kfCY/uIT/7MGW/B01LcZCdio68js2UZ2d3rGzw2/ebL1M59mEjfESSv/WsVjtJmNPqb11qbAaYD/w/4IPCctTYodDAREWndwjAgvfYlTvzub8lsX0Vswu2UffAfiPQcVOxoUkDe0MvAcXMrb7ag7MHt+Gtn4w2bQqRiQIteuyU5sTI8M5nMxsUExw8WOw5hkMV/6zUi513QosPPHS9B4sp7SFxxN/HLPplbXbkNiI2+BifZidTi3xOGp960IL16JqnX/pdIvwtIXv2XWtFZ2pRGi0djzA3AfOABoAJ40xhzS6GDiYhI65U9uJ3qP/4zqdd/TaTnIDrc/s/Ex9yQ90bf0na5HboS7XcBvp1HGGRa5JonF8khliQ+4cMtcs1iio28Cgje2WqmmLLbVxFWH871iLYwx3Hwhk4idv4HWvzaZ8rxEsTG3Up291tkt674s9dTK54jteBxopXjSF51rwpHaXPyGfPxf4CLgcPW2l3AZcD3C5pKRERapTCTJrX4Saqn/wPh0b0krryH5PVfx+3Us9jRpAV5w6YQ1hwls21li1wvs3Fhbn+/i0pvkZxTcTtVEK0cR3rdq4R+bVGz+FVzcZKdG9x/Ud7LGzYZp3PvXO9jkAXq/gCy7I+kF/+e6KCJJKZ9WdsESZuUT/EYqSsaAbDWriC34qqIiLQjmbff5MST3yW94lmiQy6h7I7/izfkUhzHKXY0aWGR80bhlHXBryr80NUwXUNq4RO4PSoLsk1EaxUbfS2kq/Hta0XLEFQfJrNtJZ65TKMKmsBxo8QnfJjg8E78t14jDEPSS6aTXvYU0aGXkbjynj/bx1KkrcjnN0G1MaYfdQWjMeZyoLh/BhMRkRYRVB8ms2U5mc3LyL69FqdTL5I3fJPouecXO5oUkeNG8MzlpFc8S3D8IG55t4JdK7X8j4TVh0lefS+OW5qL5JxKpNdg3J6DSK+ZhXf+B4ryvftvvQZhUJIr2xZatHIcbq/BpJc+RXBwB/6aF/GGXUH88k+W7GJP0j7kUzx+C5gFnGOMWQAMAT5U0FQiIlI0wdG9ZDYvw9+yjGDPRiDE6dyL2PjbiI2+TnN0BADPTCb9xjP4b80jPrYwSyFkD72Nv/pFPDO5XS7EFBt9DbWzf0Zm2xt4leNa9NphGOJXzSNyjsHt3LtFr10KHMchfvEd1Pzp/+YKxxHTiF96l0ZqSJvXaPForV1gjJkIXAJEgIXW2v0FTyYiIi0iDEOCg9vJbF5GZssygoM7AHC79yc2/laileNxu/bRhx55D7dTBZFzR+BXzSV24U3N3pvyziI5XpxYO1gk51SileNwyrvjr5rZ4sVjdpclPLoHb5zWSDxT0d5DiY25EaKxup8R/Q6Vtq/R4tEYUwYMs9a+YIz5IvBvxpj7rLXbCh9PREQKIQwDsns2ktmyjMzmZYTH9gEOkd5DiF/yUaKVY3E7VhQ7prRy3rAp1L70M7Jvv0m078hmPXdm02KyO9cRn/QJ3GSnZj13W+G4EWIjrya18HGy+za36BYlftUciCWJDhjfYtcsRe1hdWBpX/IZtvoIsMkYkwG+Cfwv8CBwTSGDiYhI8wqzGbI71+UKxi3LCWuOghslcu75RC+8kWj/C9vth3Q5M9HKC3Hi5fhVc5q1eAz9WlILf4vbvT/e8Cub7bxtkTdsMqllT5FePZPkB77YItcMUyfIbF6KZy7XMHUReY98iseB1to7jTHfB35prf2+MWZJoYOJiMjZC/0Ume2rcovebFsB6RqIxon2u4Bo5Vii/S7AiSWLHVPaKCfiER06CX/tbIKao832x4f08j8RnjhEctpX2tUiOafixJJ4w6bgr5lNMOF23PLuBb+mv2EhZP12tbqtiOQnn+LRq/t6DfA3xpgIUPqbLImItFFh7XEy21bk5jDuWANZHydejjdgPNHKcUTOPV+9CdJsvGGT8VfPJLP+dWKjrzvr82UP7yS9aibRoZcR6TW4GRK2fbGR0/DXzMJf+xLxi+8o+PX8qrm43fsT6dG/4NcSkbYln+JxgTHmTSADzAdeAmYXNJWIiOQt9GsJjuwhu2c9mS3Lye6sgjDA6dANb/gVRCvHEuk9VPuKSUFEup6L22sw/ro5eKOuPatFQXKL5DwGXqxFiqS2wu1YQXTAeNLrXiE29mYcL1Gwa2X3byE4sJX4pE8U7Boi0nblUzz+E/AYsNpaGxhj/h14obCxRESkvjDrExzdR3BkN+GR3QRH9hDUfQ2rD79znNulD7ELric6YBxuj0qt7ictIjZsCrVzfkF2z3qivYee8Xkym5eSfXst8Uvv0vzb94mNuobMpiX4dh6xkVcV7Dp+1VyIeHiDJxbsGiLSduVTPL5krR128om19rkC5hERabfCICA8vr9eYXiySNxDeHw/hOE7xzrJTridehHpOwq3S6/c4+7naT82KYrowAkw/7HcwjlnWDyGforUgsdxu52Hd/4Hmjlh2xfpNTi36fzqWXjnTy3IXNAwk8bfsIDogPE48Q7Nfn4RafvyKR63GmMuJbe/Y1DoQCIipSwMQ8Lqw/UKw92EdQVicHQvBJl3D/YSuJ17E+k5CHfIpbide+F27o3buZc+2Emr4nhxvMET8d+aT3jJx87ov8/0G88QnjhIYuoXNcT6NGKjrqF29gNktr6BN6D5933MbF4K6RotlCMip5VP8TgceA3wjTEpwAFCa63Gk4iI5CHMZvDXvYJvXyM4shsyqXdfjERxO/XC7XIO0f5jcN4pEHvjJDtp2Km0Gd6wK/DXvYq/cRGxJvYcBkd2k141g+iQS89q2Gupi1aOxenYA3/1zIIUj37VHJxOvYicY5r93CJSGvIpHi8veAoRkRIUhiGZrctJLfod4ZE9uL0G4w2bXK8HsTdOh27tfisCKQ1uj/643fvhV81pUvEYhiG18x+DiKdFchrhuBFiI64itfBxsns3Eek5sNnOHRzZTXaXJTbhw/qjlYicVj7F4+k2FNranEFEREpJdt+W3Ae8XRa3Sx8S1/41kfNG60OZlCzHcfCGTSH1+q/J7t9CpEdlXu/LbF1Odvtq4pd8FLesS2FDlgBv2GRSy54ivXoWyalfbLbz+nYeOC7e0Mua7ZwiUnryKR6n13scA84BlgITCpJIRKQNC44fILVkOpn183ESHYlf9km8YVM0h0vaBW/wRFILf4tfNZfIZZWNHh9mUqTm/wa3a1+8EdMKH7AEOLEk3rAp+GteJLj4dtzy0/2NP39hkMG3rxHtd4EKeBFpUKPFo7V2QP3nxpgrgLsKFUhEpC0K0zWkVz5PetUMICQ25gZiY27AiZUVO5pIi3HiHYgOvAh//QLiF9+J48UbPD694jnC4wdI3PS3+gNLE8RGXoW/ZhbpNbNJTLzzrM+X2baKsOYI3rDJzZBOREpZkyfaWGtfBZp/lraISBsUBlnS617lxBPfIv3GM0Qrx9Hhjn8lPuF2FY7SLnnDpoBfQ2bzkgaPC47uJb3yeaKDJxLVAi1N4nbsQXTARfhVrxKma876fH7VXJyyLkTOG90M6USklDXa82iMGVvvqQOMB5IFSyQi0kZktq8mtfAJgkM7iPQaQvyarxLpOajYsUSKKtJ7KG7n3vhVcxucP1c7/zFwo8QvPvues/YoNvoaMpsW47/1GrGRV53xeYITh8huX0nsghvU+ysijWrqnMcQ2Ad8qTBxRERav+zBHaQW/pbsjjU4HStITPtKblNtLYYj8u7COYueIHtoJ5Guff7smMzWN8huW0l84p24HboWIWXbF+k5CLfXYNKrZ+GdP/WMV23233oNwhDPaHF9EWlck+c8ioi0V0H1EdJLn8K3c8BLEp/4EbwRU3EiXrGjibQq0aGTSC1+Et/OJTLxI+95LcykqZ3/G9yuffDOosdMIDbqGmpnP0Bm6xtntO9jGAb4dh6RPsNxO/cqQEIRKTX5DFvtAHwHuArwgeeBf7PWpgucTUSkVQgzadKrZpBe+TxkfLwR04iPvQUnUV7saCKtkpvsRLTyQjJvvU540Yfe8weW9MrnCY/tI3Hjt3DcfAZAyelEK8fhdKzAXz3zjIrH7C5LeHQv3rhbC5BOREpRPr+1f0ZuYZ1v1n29G7gfaL7NhUREWqEwDMhsWEhq8ZOEJw4SrRxLfMIduF16FzuaSKvnDZtCZvPSXK/YwNzuXsHRfaRXPEd04ASifYYXOWHb57gusZHTSC14nOzeTUR6DmzS+/2qORArIzpgfIESikipyad4vNBa+87yW8aYV4CVhYskIlJ8mV2W1MLfEuzbjNujP4kr7yHaZ1ixY4m0GZFzR+CUd88tnFNXPKYW/AYcl/j7hrLKmfPMZFJLnya9eibJqfkvSRGmTpDZvDS3D200VsCEIlJK8pldfcgY063e83LgcIHyiIgUVXBkNzWzfkrNM/9CWH2ExBV3U3bb91Q4ijSR47p4ZjLZHWsJju2jesMyMlvfIDb2Ftzybo2fQPLixJJ4w6eQ2bSE4PiBvN/nr18A2Qye0d6OIpK/0/Y8GmPur3voA8uMMX8AssDNwJstkE1EpMUExw+SXvUC/tqXIRIlNv6DxEZfgxNteJNzETk9z1xGetnTpNe+zP7tb+B2OYfYqKuLHavkxEZMw189i/SaF0nk0asbhiG+nYPbo5JIj/4tkFBESkVDw1ZP/vlqXt2/kx5vygWMMZ2A+cCN1totxphHgMuAE3WH3GetfcoYMw34Ebk9JJ+w1n6n7v1jgIeATsBc4IvW2owxph/wKNATsMBd1trjTckmIu1bmPXJbH0D384ju30NOLkhYLHxt+GWdSl2PJE2zy3vTuS8UfirXgAgef03cCJaJKe5uR17EB0wHn/dnNxiXrGGt+MO9m8lOLCd+GWfbKGEIlIqTvsb3Fp739me3BhzMfAgMLRe83hgsrV2V73jksDDwBRgO/CcMeY6a+0L5ArEz1trFxpjfkFuwZ6fk1vI52fW2t8aY74LfBf41tlmFpHSlz2wHd/OxV8/H1IncDp0I3bhjXjmctxOPYsdT6SkeMOmkN2+ig7DLsHtO6LYcUpWbPS1ZDYtxrfzGu3d9avmQCSGN3hiC6UTkVKRz1YddwL3Ae+ZoGCtzecT1t3AV4Bf152rDOgHPGyMORd4qu7cE4D11trNdcc9CtxujHkTSFprF9ad75fAfcaYh4DJwK312ueg4lFETiNMncDfsBDfziPYvwXcKNHKsXjm8tzCHme4wbaINCzafwzxiXfSY+I1HKwudprSFek5kEivIaTXvIg3Ytppf6eFmRT+hoVEB16EEytr4ZQi0tblM3bkB8C9wMamntxa+3kAY8zJpt7Ay8CXgSPAs8DngOPArnpv3QX0Bfqcpr0HcNRam3lfu4jIO8IwILuzCr9qLpktSyGbwe12HvFL78IbfIn2aRRpAY4bITb6OiIdOkL1sWLHKWne6GuoffG/yGxdjnea7Tcym5aCX4M3TAvliEjT5VM8brHW/qk5Lmat3QTcdvK5MeanwCeBJ4Gw3qEOEJBbDTafdura89a9uz40lrKKio7FjiAFks+99Y/s5fjKVzm26mUyR/bhJjrQacw0Ol4wlVjvATiO0wJJ5UzoZ7e06f4WVth9MtuX/I5w3WwqJlx5ymN2vvAaXrc+9B41rll/F+reljbdXzkpn+LxV8aYHwIzyK28CoC1dm5TL2aMGQUMtdZOr2ty6s65Azin3qG9gZ0NtO8FOhtjItbabN0xO5uS5cCB4wTB++tPKQUVFR3Zt09/3S5FDd3bMJMms2V5bvGbt98EQiLnjiAx7kNEK8cSRmMcBdivdbVaK/3sljbd35YRGT6N1ILfsHvtCiI9B73nteDwbmq3ryM24Q72N+PvQt3b0qb7W5pc1zmjzrR8iscrgeuBa+u1hcDoJl8tVyz+xBjzMrmhqvcAvwIWAcYYMxjYDHwMeNhau9UYU2uMmWStfR34BPCCtdY3xswD7gR+Q6738oUzyCMibVx2/1b8qrn4GxZAuhqnvDuxcbfgDZ2E27Gi2PFERFqUZy4ntfQp0qtmkpz25fe85tu54ETwhl5apHQi0tblUzyOBc611tae7cWstauMMf8CvA54wHRr7eMAxphPA9OBBPA8uaGsAHcBD9Zt+bEcOLn/5JfJ9Yp+B9gGfPRs84lI2xDWHsffsCC3+M2BbRCJEq0cX7f4zXAcR4vfiEj75MSSeMOn4K+eRXBsP27HHgCEQQb/rdeI9r9AWxGJyBnLp3jcnedxp2Wtraz3+Gfkttl4/zEvARecon0ludVY39++FbjibHKJSNsRhiHVm1ZSs2gGmS3LIcjg9qgkPukTeIMn4sQ7FDuiiEirEBt5Ff7qWaTXziYx8SMAZLatJKw5qoVyROSs5FMUvg2sNMbMBlInG621f1mwVCIi75Ne8iS7VzwH8Q5451+Z62Xs3q/YsUREWh23vDvRgRfhr5tDfOwtOLEkftVcnA5difQdVex4ItKG5VM8buQMtukQEWkuqTeeIb3iOTpeeBXh2DtwIl6xI4mItGqxUdeQ2bgI384jOvAisttXERtzI44bKXY0EWnDGi0erbX3tUQQEZFTSa95kfSS6UQHX0KP6+5h//4TxY4kItLqRXoOJNJ7KOk1swjTNRCGeObyYscSkTbutMWjMeY1a+1lxphj/Plei6G1tlPB04lIu+ZXzSU1/zGileNIXPF5LYQjItIE3qirqX3xv0i/8QyRc8/H7dSz2JFEpI1rqOfx9rqvI1siiIhIff7GRdTOfYRI35Ekpn5RQ61ERJoo2n8sTscKwmP78IwWyhGRs3faP+Nba3fVfd0KXATcDewDLq1rExEpiMzWN6h9+X+I9B5C8up7NcdRROQMOK5LfNytuN37E60cW+w4IlICGh0DZoz5NvAl4A4gCXzPGPPdQgcTkfYp8/ab1Mx+ALdHP5LX/jVONF7sSCIibZY3dBIdPnQfTjRW7CgiUgLymUD0EeB64IS19gAwEfhYQVOJSLuU3bOBmpn/idupN2XX/Q1OLFnsSCIiIiJSJ5/i0bfW1t/f8TDgFy6SiLRH2f1bqX7hP3A6dCF5w9dxEuXFjiQiIiIi9eSzz+N2Y8wNQGiMiQNfBzTnUUSaTfbQTmqe/3ecWBllN3wTt6xLsSOJiIiIyPvkUzz+BfBrYDRwAlgI3FXIUCLSfgRH91Lz3A/AcSi74Ru45d2LHUlERERETqHRYavW2p3W2qlAJ6CrtfYyYFfBk4lIyQuOH6T6uR8QZn2SN3wTt3PvYkcSERERkdM4bc+jMSYGfAo4aK2dbq2trmu/CfgxMLhlIopIKQpqjlLz3A8Ia49TduO3iHTrW+xIIiIiItKAhoat/g8wAuhkjOkKPAn8Crga+LcWyCYiJSpMnaDm+R8SHD9I8vq/IVIxoNiRRERERKQRDRWPlwPDgQrgCeBr5BbKGWGt3dQC2USkBIXpGqpf+BHBoV0kr/0roueYYkcSERERkTw0VDwes9amgbeNMUOB+621/9RCuUSkBIWZNDWz7ifYt5nEVV8h2ndksSOJiIiISJ4aWjAnrPf4gApHETkbYTZDzewHyO6sInHF5/EqxxU7koiIiIg0Qb7FY02hg4hI6QqDLLWv/DfZbSuJX/4pvCGXFjuSiIiIiDRRQ8NWBxpj/nSKxwBYa28uXCwRKRVhGFA79xEym5YQn/gRYsOvKHYkERERETkDDRWPX633eHqhg4hI6QnDkNT8x8i89RqxcbcSG31tsSOJiIiIyBk6bfForf1VSwYRkdKTXjIdf+1LeKOvJTb2lmLHEREREZGz0NCcRxGlIiYWAAAgAElEQVSRM5Z641nSK57FG34F8YvvxHGcYkcSERERkbOg4lFEml16zYuklzxJdPAlxC/7pApHERERkRLQaPFojPmzT33GmK6FiSMibZ1fNZfU/MeIVo4lccXncRz9jUpERESkFOTzqW7ZKdrmNXcQEWn7/I2LqZ33CJG+I0lM/RKOGyl2JBERERFpJqddMMcY8xJwEVBmjDla76UIsKTQwUSkdQuzGYKD28nu3UR232aCfZsJDu0k0nsIyavvxYl4xY4oIiIiIs2ooa06bgO6AQ8Dn6nXngF2FTKUiLQuYRAQHNlFUFcoZvdtJjiwHYIMAE6iI27FAGKDLiY28iqcaLzIiUVERESkuTW0VcdR4CjwAWNMDOgAnJz/2AU4WPh4ItLSwjAkPL4/VyTu3USwbzPZ/VvBr80d4CWI9KjEG3kVkZ4DiFQMxCnvrkVxREREREpcQz2PABhjvgD8BIjxbvEYkhu+KiJtXFBzlGDfJrJ7N78z/DSsPZZ70Y3idu+HN2QSkZ4DcCsG4nbprUVwRERERNqhRotH4JvAJGvt8kKHEZHCCtM1ZPdvIbt3c65g3LeZ8PiB3IuOg9vlXCL9xrzTo+h264sTyefXhIiIiIiUunw+Fe5W4SjS9vmbl1L7yv9AJg2A07GCSM9BREZOw60YSKRHfxwvUeSUIiIiItJa5VM8zjLGfAn4E1BzstFaqzmPIm1AGIb4q2eRWvhb3J4DiY+7lUjFAJxEebGjiYiIiEgbkk/x+G0gDjxQr01zHkXagDAISC14DH/tS0QHjCdx5T040VixY4mIiIhIG9Ro8WitTbZEEBFpXqGfoualn5PdtgJv9HXEL75dC92IiIiIyBnLZ7XVD56q3Vr7h+aPIyLNIag+TM2MnxAc2Ep80ieIjZha7EgiIiIi0sblM2z13nqPY8BoYA6g4lGkFcoefJuaGT8irD1O8pqvEu03ptiRRERERKQE5DNs9cr6z40x5wP/UKhAInLmMm+/Sc2LP8WJxim7+W+J9KgsdiQRERERKRFNngBlrX0TGFaALCJyFvy3XqPm+f/A7dCdslu/q8JRRERERJpVU+c8OsB4IFOwRCLSJGEYkl72NOnlfyRy7giSV30FJ1ZW7FgiIiIiUmKaOucxBPYBnypMHBFpijCboXbuw2TWzyc69HISkz+F4+bzYy0iIiIi0jR5z3k0xkQBx1rrFzyViDQqTJ2g5sX/IrtzHbHxHyR24U04jlPsWCIiIiJSovIZttoT+CUwFYgaY+YAH7fW7ixwNhE5jeDYPmpe+DHB0T0krrwHb8ilxY4kIiIiIiUunwVz/gtYBPQCegLzgJ8XMpSInF5232aqn/5HgurDJK//ugpHEREREWkR+UyOGmqtvaPe8+8ZY9YWKpCInF5myxvUvPxznGQnym78NpGufYodSURERETaiXx6Hj1jTOLkE2NMGbmFc0SkBaXXvEjNrPtxu55L2S3fVeEoIiIiIi0qn57H3wKzjTGPkCsaPws8WdBUIvKOMAhILfwt/ppZRPtfSGLqF3Gi8WLHEhEREZF2Jp/VVv/RGLMDuBaIkFs85xcFziUiQJhJUfvyf5PZshxv5FXEJ34Ux81nwICIiIiISPPKa0M4a+0jxpgn6jUlgerCRBIRgKD6CDUz/5Ng32bil3yM2Kirix1JRERERNqxfLbq+BrwT8DJcXIOueGrkQLmEmnXsod3UvPCjwmrj5C4+l68yrHFjiQiIiIi7Vw+PY9/DUwENhY4i4gAmZ1V1My6HycSpeymbxPpObDYkURERERE8ioe11trVxU8iUg7F4YhmfXzqZ37MG6nXiSv/WvcThXFjiUiIiIiAuRXPP5X3XzHWYB/stFa+78FSyXSzmQPvk1q4eNkd6whcs4wklffixPvUOxYIiIiIiLvyKd4vBs4Dyir1xYCKh5FzlJQc5T00qfwq14FL0l84kfxRkzFieS1lpWIiIiISIvJ5xNqX2vtyIInEWlHwqyPv+ZFUsufgUwK7/wPEB93G06ivNjRREREREROKZ/icasxpo+1dmfB04iUuDAMyWxZRmrhE4TH9hE5bzTxiR8h0rVPsaOJiIiIiDQon+IxANYYY5YAqZON1tqbC5ZKpARl928hteBxsrssbtdzSVz/daJ91akvIiIiIm1DPsXj9Lp/9YUFyCJSkoITh0gtmU7mrddxEuXEL/sk3rApOK62ShURERGRtqPR4tFa+6v6z40xE8nt/agFc0QaEGZSpFfNIL3ieQgyeKOvJT72JpxYWeNvFhERERFpZfJa0tEY4wK3kysaxwKPFzKUSFsWhgGZDQtJLX6S8MRBopXjiE+8E7dTz2JHExERERE5Yw0Wj8aYLsAXgK8AHYAIcL61dkMLZBNpc7J7NlC74DcEezfh9uhP4sp7iPYZVuxYIiIiIiJn7bTFozHmAeBjwDzga8AzQJUKR5E/FxzbT2rR78hsWoxT1oXElM8RHToJx3GLHU1EREREpFk01PP4GeBp4JfAbGttYIzRQjki9YTpGtIrniO9egbgEht7M7ELrsfxEsWOJiIiIiLSrBoqHs8DPgf8HEgaYx4DvBZJJdLKhUGA/9Y80kv+QFhzhOjgS4hP+DBuefdiRxMRERERKYjTFo/W2gPAD4wxPwSuA74InGOMeQX4N2vtjBbKKNKqZHauI7XgcYID23B7DSZ5zV8S6Tmo2LFERERERAoqn606QuB54HljTD9yReQjwDkFzibSqoTpGmrnPkxm0xKc8u4kpn6J6MAJOI5T7GgiIiIiIgWX11YdJ1lrtwF/Z4z5XoHyiLRKwbH91Mz4CcHhncTGf5DY6GtxorFixxIRERERaTFNKh5Pstb6zR1EpLXK7tlAzaz7CbM+yeu+RrTvyGJHEhERERFpcWdUPIq0F/7GRdS++iBOWVfKbvw2ka59ih1JRERERKQoVDyKnEIYhqTf+BPppU8R6TWExNX34iY7FTuWiIiIiEjRNFo8GmNGAPcC3eq3W2vvKFQokWIKsz61cx4ms2EB0cGXkJjyWZyIdqkRERERkfYtn57H3wEzgdUFziJSdEHNUWpn/ZTsnvXExt9G7MKbtZqqiIiIiAj5FY/V1tqvFTyJSJFlD+2kZsaPCasPkZj6JbxBFxc7koiIiIhIq+HmccwcY8z1xphIwdOIFElmx1qq//iPkElRduO3VTiKiIiIiLxPPj2Pu4FngdAYA+AAobVWxaSUhPSbr5B6/de4XfqQvParuB0rih1JRERERKTVyad4vBuYCGxs6smNMZ2A+cCN1totxphpwI+AJPCEtfY7dceNAR4COgFzgS9aazPGmH7Ao0BPwAJ3WWuPG2O6AI8BA4F9wB3W2t1NzSftWxgEpBY9gb96JpHzRpGc+mWcWLLYsUREREREWqV8hq3us9YuttYeqP+vsTcZYy4GXgOG1j1PAg8DtwDDgYuMMdfVHf4o8BfW2qHkejbvrmv/GfAza+0wYCnw3br2fwLmWWuHAw8C/5nH9yHyjtCvpWbW/firZ+KNmErymr9S4SgiIiIi0oB8eh4XGmN+D/wBSJ1stNb+oZH33Q18Bfh13fMJwHpr7WYAY8yjwO3GmDeBpLV2Yd1xvwTuM8Y8BEwGbq3XPgf4FnBD3WsAjwMPGGM8a62fx/cj7Vxw/AA1M39CcHAH8Us/TmzktGJHEhERERFp9fIpHsfVfb2nXltIrpg8LWvt5wHq5kkC9AF21TtkF9C3gfYewFFrbeZ97e85V93w1qNABbAzj+8HgO7dy/M9VNqgioqOp2xP7dzA7j/9K2G6lt53/B1lg8e2cDI5W6e7t1IadH9Lm+5v6dK9LW26v3JSo8WjtfbKZrqWS67oPMkBgia0U9d+8pj6nHqv5eXAgeMEwftPL6WgoqIj+/Yd+7N2f/NSal/+H5xkR5I3/z0nOvflxCmOk9brdPdWSoPub2nT/S1durelTfe3NLmuc0adaactHo0xP7HW/pUx5hn+vIjDWntzE6+1Azin3vPe5HoKT9e+F+hsjIlYa7N1x5zsWXy77rgdxpgo0BFodB6mtE9hGJJe+RzpxU/i9hxI8uqv4pZ1LnYsEREREZE2paEFc16q+/okMP0U/5pqEWCMMYPr9oz8GPCCtXYrUGuMmVR33Cfq2n1gHnBnXfsngRfqHj9f95y61+dpvqOcSpjNUDvnYdKLnyQ66GLKbvy2CkcRERERkTNw2p5Ha+0zdV9/Vb/dGOMAg5t6IWttrTHm0+QKzwS5AvDJupfvAh6s29pjOXB/XfuXgV8ZY74DbAM+Wtf+XeCXxpi1wOG694u8R1h7nJoXf0p2lyU29hZi427Fcd4/4llERERERPLhhGHD8/6MMV8Afgh0qNe8z1rbu5DBCqgS2Kw5j6WroqIje9avp3rmjwmPHSAx5bN4Qy4tdixpBpp3Udp0f0ub7m/p0r0tbbq/panenMcBwJZ835fPaqvfBq4C/h74DnAT7656KtLq1Gxdw4k//gDHcUne+C2ivYcUO5KIiIiISJvX0JzHkw5aaxcBK4Be1tp/BqYUNpZI04XZDOk1L7LrN9/HTXam7NbvqnAUEREREWkm+fQ8+saYrsB6YALwIhApaCqRJgj9Wvx1c0ivnkl44iDJgRcQufwenHiHxt8sIiIiIiJ5yad4/B/gWXLDVVcYY24DqgqaSiQPQe0x/DWzSa+dDakTRM4xxCZ/mt4XXsr+/ceLHU9EREREpKQ0Wjxaax82xjxhrT1hjLkEGA/MLHw0kVMLju0nvWoGftVcyKaJVo4ldsH1RHrlFgHWiqoiIiIiIs3vtMWjMeZr73te/+mXgR8VKJPIKWUP7iC94jkyGxcBDtEhl+SKxq59ih1NRERERKTkNdTzOKqB17THhbSYzO71pFc8S3bbSojG8UZeRWzU1bjl3YsdTURERESk3Tht8Wit/cz724wxcWttqrCRRCAMA7LbVpFe8RzZPetx4uXExt1GbMRUnER5seOJiIiIiLQ7DQ1bjQEPAk9ba5+qa55ujNkH3G2tzbREQGlfwiBDZuNi0iueJzi0A6e8O/FL78Izk3G8eLHjiYiIiIi0Ww0NW/0+0Al4vV7bF4AHgH8AvlO4WNLehJkUftVc0qtmEB4/gNv1XBJX3E108MU4bj6LAouIiIiISCE19Kn8RuAia23NyQZr7dvGmE8CC1DxKM0grD1Oeu1L+GtnE9YeI9JrCLFJnyDSbzSO4xY7noiIiIiI1GmoeEzXLxxPstYeNcZo3qOcleD4QdKrZ+KvexUyKSL9LiA25gaivYcWO5qIiIiIiJxCQ8Vj1hjT0Vp7rH6jMaYj4BU2lpSq7KG3Sa+cQWbDfAhDooMuJjbmeiLdzit2NBERERERaUBDxePjwEPGmM9aa08AGGM6AA8B01sinJSGMMiS2bYCf81ssjvXQSSGN/xKYqOvwe1YUex4IiIiIiKSh4aKx58A/w/YbYxZC7jAcOAxcovpiDQoqD2GXzUH/81XCI8fwOnQjdhFH8YbNhk32anY8UREREREpAka2ucxAO4xxvwzMA4IgEXW2l0tFU7apuy+LaTXziazcSFkM0T6DMe75GNE+4/BcSPFjiciIiIiImeg0T0QrLVbga0tkEXasDCbIbN5Cek1swn2boRoHM9Mxjt/KpFu5xY7noiIiIiInCVtoCdnJThxCH/dK/jrXiWsOYrTuRfxSz6GN3QSTrxDseOJiIiIiEgzUfEoTRaGIdndb+GvfYnM5mUQBkT6jSY2YiqRviO1P6OIiIiISAlS8Sh5CzMp/A0L8dfOJjiwHWJleCOnERsxFbdTz2LHExERERGRAlLxKI0Kju4l/ebL+HYepE7gdutL/PJP4w2+BMeLFzueiIiIiIi0ABWPckphGJDdsZb02tlkt60CxyE6YBzeiGlEeg/FcZxiRxQRERERkRak4lHeI0zX4L/1Gum1LxEe2Y2T7ETswhvxhl+JW96t2PFERERERKRIVDzKOzLbV1M792HCE4dwew4ifuU9RAdehBPxih1NRERERESKTMWjEKZrSC18Ar/qVdwufUjc/GWivYcUO5aIiIiIiLQiKh7buczOKmrnPER47ADe6GuJj/8gTjRW7FgiIiIiItLKqHhsp8JMmtTiJ/HXzMLp1JPkzX9LtPfQYscSEREREZFWSsVjO5Tdu5HaVx4kOLIb7/ypxC++Q1tuiIiIiIhIg1Q8tiNh1ie97I+kVz6HU9aV5A3fJHru+cWOJSIiIiIibYCKx3Yiu38rta8+SHBwB565nPglH8WJlRU7loiIiIiItBEqHktcGGRIr3iO9LI/4STKSV7zV0T7jyl2LBERERERaWNUPJaw7KG3qX31IYJ9m4kOmkhi0sdxEuXFjiUiIiIiIm2QiscSFAYB/pqZpJZMx4kmSEz7Mt7ACcWOJSIiIiIibZiKxxITHNlD7asPkd2znmj/C4lf/mncss7FjiUiIiIiIm2ciscSEYYB/puvkFr0BLgRElfcTXTIpTiOU+xoIiIiIiJSAlQ8loDg+AFq5/yC7NtvEuk7ksTkz+KWdyt2LBERERERKSEqHtuwMAzJvPUatfN/A2FA/LJP4Q2/Qr2NIiIiIiLS7FQ8tlFB9WFq5z5CdttKIucYElM+h9upZ7FjiYiIiIhIiVLx2IyCI7tJLX2azI7VOBEPvDhONA7RGE40juO9+/idr14cJxqD973+zjFePPdaNJY71o3ib1xE7Wv/C5k08Us+ijfyKhzHLfa3LyIiIiIiJUzFYzMIThwiveyP+HYuRKJEB07AcVzCTIrQT0E2TejXEtYcIcykwU8RZlKQSUEYNu1iTgTCLG7PgSSvuBu3yzmF+aZERERERETqUfF4FsLa46RWPIu/9iUIA7zzryR24U24ZV3ye38YQpCpV0ym3y046x7nXktD5t1jnPLueMOm4LiRAn+HIiIiIiIiOSoez0CYriG9ZhbplTPAryU65FLi427F7VTRpPM4jgMRDyIeDuUFSisiIiIiInL2VDw2QZj18d98hfQbzxDWHiNaOZbY+A8R6XZusaOJiIiIiIgUlIrHPIRBlsz6+aSWPU14/ACRPsOJT/gwkZ6Dih1NRERERESkRah4bEAYhmQ2LyW99A8Eh3fhVgwgMfmzRPuOKHY0ERERERGRFqXi8RTCMCT79lpSS6YT7NuM26UPiav+gmjluNw8RRERERERkXZGxeP7ZPduJLX4SbI71+GUdycx5XNEh0zCcbWPooiIiIiItF8qHutkD+4gvWQ6ma1v4CQ6Er/0LrzhV+BEvGJHExERERERKbp2XzwGR/eRWvYUmfULwEsQG/9BYqOuxvESxY4mIiIiIiLSarTb4jGoOUrtkqfxq14Fx8UbfS3xMTfgJLTfooiIiIiIyPu12+Kx5pl/IXNoN96wycTG3oLboWuxI4mIiIiIiLRa7bZ4jPQdSfyqv8Tt3LvYUURERERERFq9dls8Ji69iyAIix1DRERERESkTdD+EyIiIiIiItIoFY8iIiIiIiLSKBWPIiIiIiIi0igVjyIiIiIiItIoFY8iIiIiIiLSKBWPIiIiIiIi0igVjyIiIiIiItIoFY8iIiIiIiLSKBWPIiIiIiIi0igVjyIiIiIiItIoFY8iIiIiIiLSKBWPIiIiIiIi0igVjyIiIiIiItIoFY8iIiIiIiLSKBWPIiIiIiIi0igVjyIiIiIiItIoFY8iIiIiIiLSKBWPIiIiIiIi0igVjyIiIiIiItIoFY8iIiIiIiLSqGgxLmqMeQXoCfh1TV8ABgHfATzgJ9baB+qOnQb8CEgCT1hrv1PXPgZ4COgEzAW+aK3NtOT3ISIiIiIi0l60eM+jMcYBhgIXWGvHWGvHADuAfwYuA8YA9xhjzjfGJIGHgVuA4cBFxpjr6k71KPAX1tqhgAPc3cLfioiIiIiISLtRjJ5HU/d1ljGmO/AgcAx42Vp7EMAY8yTwYWAOsN5au7mu/VHgdmPMm0DSWruw7ly/BO4Dft5i34WIiIiIiEg7UozisSvwEnAvuSGqrwJPALvqHbMLmAD0OUV73wba89a9e3kTY0tbUlHRsdgRpEB0b0ub7m9p0/0tXbq3pU33V05q8eLRWrsAWHDyuTHmF+TmNP5TvcMcICA3rDZsQnveDhw4ThCEjR8obU5FRUf27TtW7BhSALq3pU33t7Tp/pYu3dvSpvtbmlzXOaPOtGLMebzMGDO1XpMDbAHOqdfWG9hJbi5kU9pFRERERESkAIqxVUcX4IfGmIQxpiPwKeDjwFRjTIUxpgz4EDADWAQYY8xgY0wE+BjwgrV2K1BrjJlUd85PAC+0+HciIiIiIiLSTrR48WitfRZ4DngDWAY8bK19Hfh74BVgBfAba+1ia20t8GlgOvAmUAU8WXequ4AfG2OqgHLg/pb8PkRERERERNoTJwzb3by/SmCz5jyWLo3NL126t6VN97e06f6WLt3b0qb7W5rqzXkcQG4KYX7vK1QgERERERERKR0qHkVERERERKRRKh5FRERERESkUSoeRUREREREpFEqHkVERERERKRRKh5FRERERESkUSoeRUREREREpFEqHkVERERERKRRKh5FREREROT/t3fnMXZWZRzHv9MFlE1qLWERJQZ4XJGIImIRaossiqgUEYwiqICKRoMQlRJsEzUKIgRRVMqSKIsiYBRoWIqIG4KIFdHHDSJIQwggS8Ha0vGP9x0ZJh3OzHSGl3vm+/ln7nbufd4+OZ353XPee6Uiw6MkSZIkqcjwKEmSJEkqMjxKkiRJkooMj5IkSZKkIsOjJEmSJKnI8ChJkiRJKjI8SpIkSZKKDI+SJEmSpCLDoyRJkiSpyPAoSZIkSSoyPEqSJEmSigyPkiRJkqQiw6MkSZIkqcjwKEmSJEkqMjxKkiRJkooMj5IkSZKkIsOjJEmSJKnI8ChJkiRJKjI8SpIkSZKKDI+SJEmSpCLDoyRJkiSpyPAoSZIkSSoyPEqSJEmSigyPkiRJkqQiw6MkSZIkqcjwKEmSJEkqMjxKkiRJkooMj5IkSZKkIsOjJEmSJKnI8ChJkiRJKjI8SpIkSZKKDI+SJEmSpCLDoyRJkiSpyPAoSZIkSSoyPEqSJEmSigyPkiRJkqQiw6MkSZIkqcjwKEmSJEkqMjxKkiRJkooMj5IkSZKkIsOjJEmSJKnI8ChJkiRJKjI8SpIkSZKKDI+SJEmSpCLDoyRJkiSpyPAoSZIkSSoyPEqSJEmSigyPkiRJkqSiaV0X0JUzf3QbDz68susyNAGmrzeVVf99ousyNAHsbd3sb93sb73sbd3sb51mbLI+xx++y6jHufIoSZIkSSqatCuPR+3/Stas6e+6DE2AWbM25r77Hum6DE0Ae1s3+1s3+1sve1s3+1unKVP6xjZunOuQJEmSJFXI8ChJkiRJKjI8SpIkSZKKDI+SJEmSpCLDoyRJkiSpyPAoSZIkSSoyPEqSJEmSigyPkiRJkqQiw6MkSZIkqcjwKEmSJEkqMjxKkiRJkooMj5IkSZKkIsOjJEmSJKloWtcFrIuIOARYAEwHTs3MMzouSZIkSZKq1LMrjxGxFfAFYDawI3BERLy826okSZIkqU49Gx6BecDSzHwgM1cAFwPzO65JkiRJkqrUy9tWtwSWD7q+HNh5pINnztxo3AvSs8esWRt3XYImiL2tm/2tm/2tl72tm/3VgF4Oj1OA/kHX+4A1Ixg3FeDBB1ewZk1/6bHqQTNnbsT99z/adRmaAPa2bva3bva3Xva2bva3TlOm9DFjxobQZqOR6uXweDew26DrmwP3jGDcFsDAP5Yq5cpyvext3exv3exvvext3exv1bYA/j7SB/dyeLwG+HxEzAJWAAcAR4xg3E00oXM58MTElSdJkiRJz0pTaYLjTaMZ1Nff37tbN9uv6vgcsB5wVmZ+peOSJEmSJKlKPR0eJUmSJEnPjF7+qg5JkiRJ0jPE8ChJkiRJKjI8SpIkSZKKDI+SJEmSpCLDoyRJkiSpyPAoSZIkSSoyPEqSJEmSiqZ1XcAzLSIOARYA04FTM/OMjkvSOImI64DNgFXtTUdm5o0dlqRxEBGbAL8E3paZd0bEPOAU4LnARZm5oNMCNWZr6e05wGxgRfuQhZl5aWcFaswi4kTg3e3VyzPzOOduHYbprXO3EhGxCJgP9AOLM/MU5249hunvqOZvX39//8RX+iwREVsBPwd2AlbS/NFycGbe3mlhWmcR0QfcDbw4M1d3XY/GR0S8HvgO8FJge+BeIIHdgbuAy2neBLqysyI1JkN724bHPwBvyczl3VanddH+obkQmEPzB8oS4Czgyzh3e9owvf06sAjnbs+LiN2BLwB70Cyy3A68A/gxzt2eN0x/9wYuZhTzd7JtW50HLM3MBzJzBc0/1vyOa9L4iPbnVRHx+4g4utNqNF4+DHwMuKe9vjPw18y8o32T4LvAgV0Vp3XylN5GxAbAi4CzI2JZRCyMiMn2O6oWy4FjMvO/mbkK+BPNmz/O3d63tt6+COduFTLzemBOO0c3o9mhuCnO3SoM09/HGeX8nWyTe0ua//gGLAde2FEtGl8zgGuBdwJzgaMiYs9uS9K6yswPZeYNg25yDldiLb3dHFgKHA7sAuwGfLCL2rRuMvOPmflrgIjYjmaL4xqcuz1vmN4uwblbjcxcFRELaValrsXfu1VZS3+nM8r5O9nOeZxCs81iQB/NLzT1uMz8FfCrgesRsRjYF7i6s6I0EZzDlcrMf9C8+QNARJwOvJ9ma6t6UES8gmaL27HAaprVxwHO3R42uLeZmTh3q5KZJ0bEl2m2q26Pv3erMqS/czNzVPN3sq083g1sMej65jy5HU49LCJmR8TcQTf18eQH56gezuFKRcSrIuKAQTc5h3tYRLyR5l3tz2TmeTh3qzG0t87dekTESyNiR4DMfAy4hOb8OOduBYbp74ayZbAAAAUZSURBVEGjnb+TbeXxGuDzETGL5hOFDgCO6LYkjZNNgUURsSvNEvyhwFHdlqQJcCMQEbEtcAdwCHB2tyVpnPQBp0bEUuBRmv+bz+u2JI1FRGwNXAYclJlL25uduxUYprfO3Xq8BFgYEbNpVhv3B74FnOTcrcLa+ns9o5y/k2rlMTP/BRwPXAfcCpyfmb/ptiqNh8z8Cc0Wmt8BvwXObreyqiKZ+R/gA8APafbr/5nmg6/U4zJzGfAl4Bc0vb01My/otiqN0aeB5wCnRMStEXErzbz9AM7dXre23u6Kc7cKmXkFT/1b6peZeSHO3SoM099FjHL+Tqqv6pAkSZIkjc2kWnmUJEmSJI2N4VGSJEmSVGR4lCRJkiQVGR4lSZIkSUWGR0mSJElSkeFRklSliJgfET8dx+e7KiJe0F6+IiJePl7PPcLX3zEi/h4Rv42IbcYw/q0RsWgCSpMkTRLTui5AkqQesefAhczct4PXfztwXWZ+aIzjXwc8fxzrkSRNMn7PoySpGu3K2nuB+4G/AlsBdwK3ZebJ7WPOHbgeEXcCNwI7AJ8DVrU/1wM2A87LzBMi4hyaL8q+DdgXuAGYn5k3R8QRwCeAJ4B7gaMz8y/t6zwMvArYGlgGvD8zHy0cwwnAwcBq4C/A0cBc4KvAVOCqzHzv04x/F7AAWNPWdCywEvhRO/7bwBeBbwLbATOBR4BDgMfbY9w6Mx+KiD4ggQMz8/dPV7ckqX5uW5UkVSEi9gcOAHYEdgWeN8Kht2Xmy4DLgGOAQzPztcAuwGcj4gWZeVj72DmZedeg13wzcFx7+6uB84HL2tAFsBOwN/AyYBvgwMIxHAbsA7wuM3egCXLnZub3gDOBi54uOLZOAj7aHsMJwB6ZeeOg8ce3r/HvzHxDZm4P3EQTev8JLKUJ4ABzgPsNjpIkMDxKkuoxD7gkMx/JzNXA2SMcdwNAZvYD+wE7RcSJwClAH7Dh04zdmyaQ3dc+x7k0q53btPcvycyVmbkK+APlbaP7AOdk5or2+mnA3IhYb4THAnAhcGlEnAXMAL4y9AGZeTFwbkR8PCJOA/YANmrvPgP4cHv5SJoVSkmSDI+SpKr0Dbq8uv3ZP+T2oUHsUYCI2BD4HfAa4Baa7Z6rhowdamr7/ENrmN5efnzQ7UPrGMnzTaH5fILSuP9rVxZnAzfTbLX92dDHRMRHgMXAYzSrpRcMeo1rgA0iYi7wJuD7I31tSVLdDI+SpFpcCRwYEZtGxBTgfe3t9wGvBYiILYHdhxm/HbAJsCAzf0yzGrc+TaCD5vzB6UPGLAHeExGz2uc/jOZ8y7+N8RiWAIe3QRaacyl/lpkrRzI4Iqa153FukJlnAh8FdoiI9WnC9ED9e9Fsh11Mc07jfrTH2a7AfgM4Czg/M/8zxmORJFXG8ChJqkJmXkGzVfVmmg/Beai963Rgi4hI4Byac/rWZhnwE+DPEfEnmkB1O7Bte/8PgOsj4pWDXvNq4GvA0oj4I3Ao8LbMXDPGw1hMs/L3m7aG1/Dk+YdF7XbdTwLnR8Qtbc2Ht+FzKbBXRJwOnAwcGRHLaLbt3jLoOAHOo/mQn2+N8TgkSRXy01YlSdJTRMR7aD44aJ+ua5EkPXv4PY+SJD2DIuIGYONh7t4tMx8pjJ9Ds9q5Ntdl5qfWsb6fArOA/dfleSRJ9XHlUZIkSZJU5DmPkiRJkqQiw6MkSZIkqcjwKEmSJEkqMjxKkiRJkooMj5IkSZKkov8Bdvv5WpkwOjAAAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# average amount reinbursed based on duration of stay in the hospital\n", "fig, ax = plt.subplots(figsize = (15,8))\n", "inpatient.groupby('duration_of_stay').mean().plot(kind='line', ax=ax)\n", "ax.set_ylabel('Claim Amount Reimbursed')\n", "ax.set_title('Average Amount Reinbursed by Duration of Stay')" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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IP_claim_durationduration_of_stay
404646.06.0
404652.02.0
404662.02.0
404677.07.0
404682.02.0
404694.04.0
404703.03.0
404714.04.0
404721.01.0
404738.08.0
\n", "
" ], "text/plain": [ " IP_claim_duration duration_of_stay\n", "40464 6.0 6.0\n", "40465 2.0 2.0\n", "40466 2.0 2.0\n", "40467 7.0 7.0\n", "40468 2.0 2.0\n", "40469 4.0 4.0\n", "40470 3.0 3.0\n", "40471 4.0 4.0\n", "40472 1.0 1.0\n", "40473 8.0 8.0" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inpatient['IP_claim_duration'] = inpatient['ClaimEndDt'] - inpatient['ClaimStartDt']\n", "inpatient['IP_claim_duration'] = inpatient['IP_claim_duration'] / np.timedelta64(1, 'D')\n", "inpatient[['IP_claim_duration', 'duration_of_stay']].tail(10)" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Average Amount Reinbursed per Month')" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# average amount reinbursed per month\n", "fig, ax = plt.subplots(figsize = (15,8))\n", "inpatient.resample('m', on='ClaimEndDt')['InscClaimAmtReimbursed'].mean().plot(kind='line', ax=ax)\n", "ax.set_ylabel('Claim Amount Reimbursed')\n", "ax.set_title('Average Amount Reinbursed per Month')" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "duration_of_stay\n", "0.0 392100\n", "1.0 3080800\n", "2.0 3690300\n", "3.0 5037300\n", "4.0 4366400\n", "5.0 4066300\n", "6.0 3366300\n", "7.0 2952500\n", "8.0 2379000\n", "9.0 1572000\n", "10.0 1555000\n", "11.0 1437900\n", "12.0 1279000\n", "13.0 992400\n", "14.0 1099000\n", "15.0 955000\n", "16.0 991000\n", "17.0 503000\n", "18.0 1015000\n", "19.0 450000\n", "20.0 215000\n", "21.0 401000\n", "22.0 641000\n", "23.0 208000\n", "24.0 149000\n", "25.0 86000\n", "26.0 132000\n", "27.0 215000\n", "28.0 85000\n", "29.0 93000\n", "30.0 186000\n", "31.0 188000\n", "32.0 158000\n", "33.0 244000\n", "34.0 136000\n", "35.0 1422000\n", "Name: InscClaimAmtReimbursed, dtype: int64" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inpatients who had access to 3 doctors\n", "more_than_one_doctor = inpatient[inpatient['OperatingPhysician'].notnull() & inpatient['OtherPhysician'].notnull() & inpatient['AttendingPhysician'].notnull()]\n", "more_than_one_doctor.groupby('duration_of_stay')['InscClaimAmtReimbursed'].sum()" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "inpatient['Surgery'] = np.where(inpatient['OperatingPhysician'].notnull(), 1, 0)\n", "plt.figure(figsize = (15,8))\n", "sns.boxplot(x='Surgery', y='InscClaimAmtReimbursed', data=inpatient)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize = (15,8))\n", "sns.countplot(x='Surgery', data=inpatient)" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AdmissionDtAttendingPhysicianBeneIDClaimEndDtClaimIDClaimStartDtClmAdmitDiagnosisCodeClmDiagnosisCode_1ClmDiagnosisCode_10ClmDiagnosisCode_2...DiagnosisGroupCodeDischargeDtInscClaimAmtReimbursedOperatingPhysicianOtherPhysicianProviderIDduration_of_stayIP_claim_durationSurgeryFollow_up
02009-04-12PHY390922BENE110012009-04-18CLM466142009-04-1278661970NaN4019...2012009-04-1826000NoneNonePRV559126.06.000
12009-08-31PHY318495BENE110012009-09-02CLM660482009-08-3161866186NaN2948...7502009-09-025000PHY318495NonePRV559072.02.010
22009-09-17PHY372395BENE110012009-09-20CLM683582009-09-172959029623NaN30390...8832009-09-205000NonePHY324689PRV560463.03.001
32009-02-14PHY369659BENE110112009-02-22CLM384122009-02-1443143491NaN2762...672009-02-225000PHY392961PHY349768PRV524058.08.011
42009-08-13PHY379376BENE110142009-08-30CLM636892009-08-137832142NaN3051...9752009-08-3010000PHY398258NonePRV5661417.017.010
..................................................................
404692009-09-28PHY345332BENE1591672009-10-02CLM698862009-09-282859285141482762...8122009-10-027000PHY319565NonePRV536714.04.010
404702009-11-03PHY342806BENE1591752009-11-06CLM745042009-11-037990242823NaN4148...2282009-11-064000PHY365497NonePRV549813.03.010
404712009-11-18PHY423220BENE1591772009-11-22CLM764852009-11-18786054280NaN3963...3022009-11-223000PHY332752NonePRV565884.04.010
404722009-12-17PHY353156BENE1591772009-12-18CLM799492009-12-1778027802NaN5859...3092009-12-185000NoneNonePRV565751.01.000
404732009-09-28PHY431177BENE1591882009-10-06CLM699482009-09-2815361540NaN27800...3402009-10-0615000PHY352941NonePRV547658.08.010
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40474 rows × 34 columns

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" ], "text/plain": [ " AdmissionDt AttendingPhysician BeneID ClaimEndDt ClaimID \\\n", "0 2009-04-12 PHY390922 BENE11001 2009-04-18 CLM46614 \n", "1 2009-08-31 PHY318495 BENE11001 2009-09-02 CLM66048 \n", "2 2009-09-17 PHY372395 BENE11001 2009-09-20 CLM68358 \n", "3 2009-02-14 PHY369659 BENE11011 2009-02-22 CLM38412 \n", "4 2009-08-13 PHY379376 BENE11014 2009-08-30 CLM63689 \n", "... ... ... ... ... ... \n", "40469 2009-09-28 PHY345332 BENE159167 2009-10-02 CLM69886 \n", "40470 2009-11-03 PHY342806 BENE159175 2009-11-06 CLM74504 \n", "40471 2009-11-18 PHY423220 BENE159177 2009-11-22 CLM76485 \n", "40472 2009-12-17 PHY353156 BENE159177 2009-12-18 CLM79949 \n", "40473 2009-09-28 PHY431177 BENE159188 2009-10-06 CLM69948 \n", "\n", " ClaimStartDt ClmAdmitDiagnosisCode ClmDiagnosisCode_1 \\\n", "0 2009-04-12 7866 1970 \n", "1 2009-08-31 6186 6186 \n", "2 2009-09-17 29590 29623 \n", "3 2009-02-14 431 43491 \n", "4 2009-08-13 78321 42 \n", "... ... ... ... \n", "40469 2009-09-28 2859 2851 \n", "40470 2009-11-03 79902 42823 \n", "40471 2009-11-18 78605 4280 \n", "40472 2009-12-17 7802 7802 \n", "40473 2009-09-28 1536 1540 \n", "\n", " ClmDiagnosisCode_10 ClmDiagnosisCode_2 ... DiagnosisGroupCode \\\n", "0 NaN 4019 ... 201 \n", "1 NaN 2948 ... 750 \n", "2 NaN 30390 ... 883 \n", "3 NaN 2762 ... 67 \n", "4 NaN 3051 ... 975 \n", "... ... ... ... ... \n", "40469 4148 2762 ... 812 \n", "40470 NaN 4148 ... 228 \n", "40471 NaN 3963 ... 302 \n", "40472 NaN 5859 ... 309 \n", "40473 NaN 27800 ... 340 \n", "\n", " DischargeDt InscClaimAmtReimbursed OperatingPhysician OtherPhysician \\\n", "0 2009-04-18 26000 None None \n", "1 2009-09-02 5000 PHY318495 None \n", "2 2009-09-20 5000 None PHY324689 \n", "3 2009-02-22 5000 PHY392961 PHY349768 \n", "4 2009-08-30 10000 PHY398258 None \n", "... ... ... ... ... \n", "40469 2009-10-02 7000 PHY319565 None \n", "40470 2009-11-06 4000 PHY365497 None \n", "40471 2009-11-22 3000 PHY332752 None \n", "40472 2009-12-18 5000 None None \n", "40473 2009-10-06 15000 PHY352941 None \n", "\n", " ProviderID duration_of_stay IP_claim_duration Surgery Follow_up \n", "0 PRV55912 6.0 6.0 0 0 \n", "1 PRV55907 2.0 2.0 1 0 \n", "2 PRV56046 3.0 3.0 0 1 \n", "3 PRV52405 8.0 8.0 1 1 \n", "4 PRV56614 17.0 17.0 1 0 \n", "... ... ... ... ... ... \n", "40469 PRV53671 4.0 4.0 1 0 \n", "40470 PRV54981 3.0 3.0 1 0 \n", "40471 PRV56588 4.0 4.0 1 0 \n", "40472 PRV56575 1.0 1.0 0 0 \n", "40473 PRV54765 8.0 8.0 1 0 \n", "\n", "[40474 rows x 34 columns]" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inpatient['Follow_up'] = np.where(inpatient['OtherPhysician'].notnull(), 1, 0)\n", "inpatient" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "inpatient['Attending'] = np.where(inpatient['AttendingPhysician'].notnull(), 1, 0)" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AdmissionDtAttendingPhysicianBeneIDClaimEndDtClaimIDClaimStartDtClmAdmitDiagnosisCodeClmDiagnosisCode_1ClmDiagnosisCode_10ClmDiagnosisCode_2...InscClaimAmtReimbursedOperatingPhysicianOtherPhysicianProviderIDduration_of_stayIP_claim_durationSurgeryFollow_upAttendingIP_num_claim_diagnosis_code
02009-04-12PHY390922BENE110012009-04-18CLM466142009-04-1278661970NaN4019...26000NoneNonePRV559126.06.000110
12009-08-31PHY318495BENE110012009-09-02CLM660482009-08-3161866186NaN2948...5000PHY318495NonePRV559072.02.01015
22009-09-17PHY372395BENE110012009-09-20CLM683582009-09-172959029623NaN30390...5000NonePHY324689PRV560463.03.00117
32009-02-14PHY369659BENE110112009-02-22CLM384122009-02-1443143491NaN2762...5000PHY392961PHY349768PRV524058.08.011110
42009-08-13PHY379376BENE110142009-08-30CLM636892009-08-137832142NaN3051...10000PHY398258NonePRV5661417.017.010110
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5 rows × 36 columns

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" ], "text/plain": [ " AdmissionDt AttendingPhysician BeneID ClaimEndDt ClaimID ClaimStartDt \\\n", "0 2009-04-12 PHY390922 BENE11001 2009-04-18 CLM46614 2009-04-12 \n", "1 2009-08-31 PHY318495 BENE11001 2009-09-02 CLM66048 2009-08-31 \n", "2 2009-09-17 PHY372395 BENE11001 2009-09-20 CLM68358 2009-09-17 \n", "3 2009-02-14 PHY369659 BENE11011 2009-02-22 CLM38412 2009-02-14 \n", "4 2009-08-13 PHY379376 BENE11014 2009-08-30 CLM63689 2009-08-13 \n", "\n", " ClmAdmitDiagnosisCode ClmDiagnosisCode_1 ClmDiagnosisCode_10 \\\n", "0 7866 1970 NaN \n", "1 6186 6186 NaN \n", "2 29590 29623 NaN \n", "3 431 43491 NaN \n", "4 78321 42 NaN \n", "\n", " ClmDiagnosisCode_2 ... InscClaimAmtReimbursed OperatingPhysician \\\n", "0 4019 ... 26000 None \n", "1 2948 ... 5000 PHY318495 \n", "2 30390 ... 5000 None \n", "3 2762 ... 5000 PHY392961 \n", "4 3051 ... 10000 PHY398258 \n", "\n", " OtherPhysician ProviderID duration_of_stay IP_claim_duration Surgery \\\n", "0 None PRV55912 6.0 6.0 0 \n", "1 None PRV55907 2.0 2.0 1 \n", "2 PHY324689 PRV56046 3.0 3.0 0 \n", "3 PHY349768 PRV52405 8.0 8.0 1 \n", "4 None PRV56614 17.0 17.0 1 \n", "\n", " Follow_up Attending IP_num_claim_diagnosis_code \n", "0 0 1 10 \n", "1 0 1 5 \n", "2 1 1 7 \n", "3 1 1 10 \n", "4 0 1 10 \n", "\n", "[5 rows x 36 columns]" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "claims_code = ['ClmAdmitDiagnosisCode', 'ClmDiagnosisCode_1', 'ClmDiagnosisCode_10', 'ClmDiagnosisCode_2', 'ClmDiagnosisCode_3', 'ClmDiagnosisCode_4',\n", " 'ClmDiagnosisCode_5', 'ClmDiagnosisCode_6', 'ClmDiagnosisCode_7', 'ClmDiagnosisCode_8', 'ClmDiagnosisCode_9']\n", "\n", "inpatient['IP_num_claim_diagnosis_code'] = inpatient[claims_code].count(axis=1)\n", "inpatient.head()" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AdmissionDtAttendingPhysicianBeneIDClaimEndDtClaimIDClaimStartDtClmAdmitDiagnosisCodeClmDiagnosisCode_1ClmDiagnosisCode_10ClmDiagnosisCode_2...OperatingPhysicianOtherPhysicianProviderIDduration_of_stayIP_claim_durationSurgeryFollow_upAttendingIP_num_claim_diagnosis_codeIP_num_claim_procedure_code
02009-04-12PHY390922BENE110012009-04-18CLM466142009-04-1278661970NaN4019...NoneNonePRV559126.06.0001101
12009-08-31PHY318495BENE110012009-09-02CLM660482009-08-3161866186NaN2948...PHY318495NonePRV559072.02.010152
22009-09-17PHY372395BENE110012009-09-20CLM683582009-09-172959029623NaN30390...NonePHY324689PRV560463.03.001171
32009-02-14PHY369659BENE110112009-02-22CLM384122009-02-1443143491NaN2762...PHY392961PHY349768PRV524058.08.0111102
42009-08-13PHY379376BENE110142009-08-30CLM636892009-08-137832142NaN3051...PHY398258NonePRV5661417.017.0101102
\n", "

5 rows × 37 columns

\n", "
" ], "text/plain": [ " AdmissionDt AttendingPhysician BeneID ClaimEndDt ClaimID ClaimStartDt \\\n", "0 2009-04-12 PHY390922 BENE11001 2009-04-18 CLM46614 2009-04-12 \n", "1 2009-08-31 PHY318495 BENE11001 2009-09-02 CLM66048 2009-08-31 \n", "2 2009-09-17 PHY372395 BENE11001 2009-09-20 CLM68358 2009-09-17 \n", "3 2009-02-14 PHY369659 BENE11011 2009-02-22 CLM38412 2009-02-14 \n", "4 2009-08-13 PHY379376 BENE11014 2009-08-30 CLM63689 2009-08-13 \n", "\n", " ClmAdmitDiagnosisCode ClmDiagnosisCode_1 ClmDiagnosisCode_10 \\\n", "0 7866 1970 NaN \n", "1 6186 6186 NaN \n", "2 29590 29623 NaN \n", "3 431 43491 NaN \n", "4 78321 42 NaN \n", "\n", " ClmDiagnosisCode_2 ... OperatingPhysician OtherPhysician ProviderID \\\n", "0 4019 ... None None PRV55912 \n", "1 2948 ... PHY318495 None PRV55907 \n", "2 30390 ... None PHY324689 PRV56046 \n", "3 2762 ... PHY392961 PHY349768 PRV52405 \n", "4 3051 ... PHY398258 None PRV56614 \n", "\n", " duration_of_stay IP_claim_duration Surgery Follow_up Attending \\\n", "0 6.0 6.0 0 0 1 \n", "1 2.0 2.0 1 0 1 \n", "2 3.0 3.0 0 1 1 \n", "3 8.0 8.0 1 1 1 \n", "4 17.0 17.0 1 0 1 \n", "\n", " IP_num_claim_diagnosis_code IP_num_claim_procedure_code \n", "0 10 1 \n", "1 5 2 \n", "2 7 1 \n", "3 10 2 \n", "4 10 2 \n", "\n", "[5 rows x 37 columns]" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "claims_proceed_code = ['ClmProcedureCode_1', 'ClmProcedureCode_2', 'ClmProcedureCode_3', 'ClmProcedureCode_4',\n", " 'ClmProcedureCode_5', 'ClmProcedureCode_6', 'DiagnosisGroupCode']\n", "\n", "inpatient['IP_num_claim_procedure_code'] = inpatient[claims_proceed_code].count(axis=1)\n", "inpatient.head()" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "inpatient = inpatient.drop(['ClmAdmitDiagnosisCode', 'ClmDiagnosisCode_1', 'ClmDiagnosisCode_10', 'ClmDiagnosisCode_2', 'ClmDiagnosisCode_3', 'ClmDiagnosisCode_4',\n", " 'ClmDiagnosisCode_5', 'ClmDiagnosisCode_6', 'ClmDiagnosisCode_7', 'ClmDiagnosisCode_8', 'ClmDiagnosisCode_9', 'ClmProcedureCode_1', 'ClmProcedureCode_2',\n", " 'ClmProcedureCode_3', 'ClmProcedureCode_4', 'ClmProcedureCode_5', 'ClmProcedureCode_6', 'DiagnosisGroupCode', 'OperatingPhysician', 'OtherPhysician',\n", " 'AdmissionDt' ,'AttendingPhysician', 'ClaimEndDt',\t'ClaimStartDt',\t'DeductibleAmtPaid', 'DischargeDt'], axis=1)\n" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax =plt.subplots()\n", "\n", "plt.figure(figsize = (15,8))\n", "ax.plot(inpatient['IP_num_claim_procedure_code'], inpatient['InscClaimAmtReimbursed'], marker='o', linestyle='none', markersize=1)\n", "\n", "\n", "sns.stripplot(data=inpatient, x=\"IP_num_claim_procedure_code\", y=\"InscClaimAmtReimbursed\", jitter=0.8, size=2)" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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BeneIDClaimIDInscClaimAmtReimbursedProviderIDduration_of_stayIP_claim_durationSurgeryFollow_upAttendingIP_num_claim_diagnosis_codeIP_num_claim_procedure_code
0BENE11001CLM4661426000PRV559126.06.0001101
1BENE11001CLM660485000PRV559072.02.010152
2BENE11001CLM683585000PRV560463.03.001171
3BENE11011CLM384125000PRV524058.08.0111102
4BENE11014CLM6368910000PRV5661417.017.0101102
....................................
40469BENE159167CLM698867000PRV536714.04.0101112
40470BENE159175CLM745044000PRV549813.03.0101102
40471BENE159177CLM764853000PRV565884.04.0101102
40472BENE159177CLM799495000PRV565751.01.0001101
40473BENE159188CLM6994815000PRV547658.08.0101102
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40474 rows × 11 columns

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" ], "text/plain": [ " BeneID ClaimID InscClaimAmtReimbursed ProviderID \\\n", "0 BENE11001 CLM46614 26000 PRV55912 \n", "1 BENE11001 CLM66048 5000 PRV55907 \n", "2 BENE11001 CLM68358 5000 PRV56046 \n", "3 BENE11011 CLM38412 5000 PRV52405 \n", "4 BENE11014 CLM63689 10000 PRV56614 \n", "... ... ... ... ... \n", "40469 BENE159167 CLM69886 7000 PRV53671 \n", "40470 BENE159175 CLM74504 4000 PRV54981 \n", "40471 BENE159177 CLM76485 3000 PRV56588 \n", "40472 BENE159177 CLM79949 5000 PRV56575 \n", "40473 BENE159188 CLM69948 15000 PRV54765 \n", "\n", " duration_of_stay IP_claim_duration Surgery Follow_up Attending \\\n", "0 6.0 6.0 0 0 1 \n", "1 2.0 2.0 1 0 1 \n", "2 3.0 3.0 0 1 1 \n", "3 8.0 8.0 1 1 1 \n", "4 17.0 17.0 1 0 1 \n", "... ... ... ... ... ... \n", "40469 4.0 4.0 1 0 1 \n", "40470 3.0 3.0 1 0 1 \n", "40471 4.0 4.0 1 0 1 \n", "40472 1.0 1.0 0 0 1 \n", "40473 8.0 8.0 1 0 1 \n", "\n", " IP_num_claim_diagnosis_code IP_num_claim_procedure_code \n", "0 10 1 \n", "1 5 2 \n", "2 7 1 \n", "3 10 2 \n", "4 10 2 \n", "... ... ... \n", "40469 11 2 \n", "40470 10 2 \n", "40471 10 2 \n", "40472 10 1 \n", "40473 10 2 \n", "\n", "[40474 rows x 11 columns]" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inpatient" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exploratory Data Analysis (Graphical and Statistic) - Outpatient" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AttendingPhysicianBeneIDClaimEndDtClaimIDClaimStartDtClmAdmitDiagnosisCodeClmDiagnosisCode_1ClmDiagnosisCode_10ClmDiagnosisCode_2ClmDiagnosisCode_3...ClmProcedureCode_2ClmProcedureCode_3ClmProcedureCode_4ClmProcedureCode_5ClmProcedureCode_6DeductibleAmtPaidInscClaimAmtReimbursedOperatingPhysicianOtherPhysicianProviderID
0PHY326117BENE110022009-10-11CLM6243492009-10-115640978943NoneV5866V1272...NoneNoneNoneNoneNone030NoneNonePRV56011
1PHY362868BENE110032009-02-12CLM1899472009-02-12793806115NoneNoneNone...NoneNoneNoneNoneNone080NoneNonePRV57610
2PHY328821BENE110032009-06-27CLM4380212009-06-272723NoneNoneNone...NoneNoneNoneNoneNone010NoneNonePRV57595
3PHY334319BENE110042009-01-06CLM1218012009-01-0671988NoneNoneNone...NoneNoneNoneNoneNone040NoneNonePRV56011
4PHY403831BENE110042009-01-22CLM1509982009-01-227194782382None3000072887...NoneNoneNoneNoneNone0200NoneNonePRV56011
\n", "

5 rows × 27 columns

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" ], "text/plain": [ " AttendingPhysician BeneID ClaimEndDt ClaimID ClaimStartDt \\\n", "0 PHY326117 BENE11002 2009-10-11 CLM624349 2009-10-11 \n", "1 PHY362868 BENE11003 2009-02-12 CLM189947 2009-02-12 \n", "2 PHY328821 BENE11003 2009-06-27 CLM438021 2009-06-27 \n", "3 PHY334319 BENE11004 2009-01-06 CLM121801 2009-01-06 \n", "4 PHY403831 BENE11004 2009-01-22 CLM150998 2009-01-22 \n", "\n", " ClmAdmitDiagnosisCode ClmDiagnosisCode_1 ClmDiagnosisCode_10 \\\n", "0 56409 78943 None \n", "1 79380 6115 None \n", "2 2723 None \n", "3 71988 None \n", "4 71947 82382 None \n", "\n", " ClmDiagnosisCode_2 ClmDiagnosisCode_3 ... ClmProcedureCode_2 \\\n", "0 V5866 V1272 ... None \n", "1 None None ... None \n", "2 None None ... None \n", "3 None None ... None \n", "4 30000 72887 ... None \n", "\n", " ClmProcedureCode_3 ClmProcedureCode_4 ClmProcedureCode_5 ClmProcedureCode_6 \\\n", "0 None None None None \n", "1 None None None None \n", "2 None None None None \n", "3 None None None None \n", "4 None None None None \n", "\n", " DeductibleAmtPaid InscClaimAmtReimbursed OperatingPhysician OtherPhysician \\\n", "0 0 30 None None \n", "1 0 80 None None \n", "2 0 10 None None \n", "3 0 40 None None \n", "4 0 200 None None \n", "\n", " ProviderID \n", "0 PRV56011 \n", "1 PRV57610 \n", "2 PRV57595 \n", "3 PRV56011 \n", "4 PRV56011 \n", "\n", "[5 rows x 27 columns]" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient.head()" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(517737, 27)" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient.shape" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "AttendingPhysician 1396\n", "BeneID 0\n", "ClaimEndDt 0\n", "ClaimID 0\n", "ClaimStartDt 0\n", "ClmAdmitDiagnosisCode 0\n", "ClmDiagnosisCode_1 10453\n", "ClmDiagnosisCode_10 516654\n", "ClmDiagnosisCode_2 195380\n", "ClmDiagnosisCode_3 314480\n", "ClmDiagnosisCode_4 392141\n", "ClmDiagnosisCode_5 443393\n", "ClmDiagnosisCode_6 468981\n", "ClmDiagnosisCode_7 484776\n", "ClmDiagnosisCode_8 494825\n", "ClmDiagnosisCode_9 502899\n", "ClmProcedureCode_1 517575\n", "ClmProcedureCode_2 517701\n", "ClmProcedureCode_3 517733\n", "ClmProcedureCode_4 517735\n", "ClmProcedureCode_5 517737\n", "ClmProcedureCode_6 517737\n", "DeductibleAmtPaid 0\n", "InscClaimAmtReimbursed 0\n", "OperatingPhysician 427120\n", "OtherPhysician 322691\n", "ProviderID 0\n", "dtype: int64" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "AttendingPhysician object\n", "BeneID object\n", "ClaimEndDt object\n", "ClaimID object\n", "ClaimStartDt object\n", "ClmAdmitDiagnosisCode object\n", "ClmDiagnosisCode_1 object\n", "ClmDiagnosisCode_10 object\n", "ClmDiagnosisCode_2 object\n", "ClmDiagnosisCode_3 object\n", "ClmDiagnosisCode_4 object\n", "ClmDiagnosisCode_5 object\n", "ClmDiagnosisCode_6 object\n", "ClmDiagnosisCode_7 object\n", "ClmDiagnosisCode_8 object\n", "ClmDiagnosisCode_9 object\n", "ClmProcedureCode_1 object\n", "ClmProcedureCode_2 object\n", "ClmProcedureCode_3 object\n", "ClmProcedureCode_4 object\n", "ClmProcedureCode_5 object\n", "ClmProcedureCode_6 object\n", "DeductibleAmtPaid int64\n", "InscClaimAmtReimbursed int64\n", "OperatingPhysician object\n", "OtherPhysician object\n", "ProviderID object\n", "dtype: object" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient.dtypes" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 517737 entries, 0 to 517736\n", "Data columns (total 27 columns):\n", "AttendingPhysician 516341 non-null object\n", "BeneID 517737 non-null object\n", "ClaimEndDt 517737 non-null object\n", "ClaimID 517737 non-null object\n", "ClaimStartDt 517737 non-null object\n", "ClmAdmitDiagnosisCode 517737 non-null object\n", "ClmDiagnosisCode_1 507284 non-null object\n", "ClmDiagnosisCode_10 1083 non-null object\n", "ClmDiagnosisCode_2 322357 non-null object\n", "ClmDiagnosisCode_3 203257 non-null object\n", "ClmDiagnosisCode_4 125596 non-null object\n", "ClmDiagnosisCode_5 74344 non-null object\n", "ClmDiagnosisCode_6 48756 non-null object\n", "ClmDiagnosisCode_7 32961 non-null object\n", "ClmDiagnosisCode_8 22912 non-null object\n", "ClmDiagnosisCode_9 14838 non-null object\n", "ClmProcedureCode_1 162 non-null object\n", "ClmProcedureCode_2 36 non-null object\n", "ClmProcedureCode_3 4 non-null object\n", "ClmProcedureCode_4 2 non-null object\n", "ClmProcedureCode_5 0 non-null object\n", "ClmProcedureCode_6 0 non-null object\n", "DeductibleAmtPaid 517737 non-null int64\n", "InscClaimAmtReimbursed 517737 non-null int64\n", "OperatingPhysician 90617 non-null object\n", "OtherPhysician 195046 non-null object\n", "ProviderID 517737 non-null object\n", "dtypes: int64(2), object(25)\n", "memory usage: 106.7+ MB\n" ] } ], "source": [ "outpatient.info()" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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DeductibleAmtPaidInscClaimAmtReimbursed
count517737.000000517737.000000
mean2.779233286.334799
std15.785839694.034343
min0.0000000.000000
25%0.00000040.000000
50%0.00000080.000000
75%0.000000200.000000
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" ], "text/plain": [ " DeductibleAmtPaid InscClaimAmtReimbursed\n", "count 517737.000000 517737.000000\n", "mean 2.779233 286.334799\n", "std 15.785839 694.034343\n", "min 0.000000 0.000000\n", "25% 0.000000 40.000000\n", "50% 0.000000 80.000000\n", "75% 0.000000 200.000000\n", "max 897.000000 102500.000000" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient.describe()" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "AttendingPhysician object\n", "BeneID object\n", "ClaimEndDt datetime64[ns]\n", "ClaimID object\n", "ClaimStartDt datetime64[ns]\n", "ClmAdmitDiagnosisCode object\n", "ClmDiagnosisCode_1 object\n", "ClmDiagnosisCode_10 object\n", "ClmDiagnosisCode_2 object\n", "ClmDiagnosisCode_3 object\n", "ClmDiagnosisCode_4 object\n", "ClmDiagnosisCode_5 object\n", "ClmDiagnosisCode_6 object\n", "ClmDiagnosisCode_7 object\n", "ClmDiagnosisCode_8 object\n", "ClmDiagnosisCode_9 object\n", "ClmProcedureCode_1 object\n", "ClmProcedureCode_2 object\n", "ClmProcedureCode_3 object\n", "ClmProcedureCode_4 object\n", "ClmProcedureCode_5 object\n", "ClmProcedureCode_6 object\n", "DeductibleAmtPaid int64\n", "InscClaimAmtReimbursed int64\n", "OperatingPhysician object\n", "OtherPhysician object\n", "ProviderID object\n", "dtype: object" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#convert all date to datetime\n", "outpatient['ClaimEndDt'] = pd.to_datetime(outpatient['ClaimEndDt'], infer_datetime_format=True, errors='coerce')\n", "outpatient['ClaimStartDt'] = pd.to_datetime(outpatient['ClaimStartDt'], infer_datetime_format=True, errors='coerce')\n", "\n", "\n", "outpatient.dtypes" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [], "source": [ "#convert int datatype of category attribute to category\n", "\n", "outpatient['ClmAdmitDiagnosisCode'] = outpatient['ClmAdmitDiagnosisCode'].astype('category')\n", "outpatient['ClmDiagnosisCode_1'] = outpatient['ClmDiagnosisCode_1'].astype('category')\n", "outpatient['ClmDiagnosisCode_10'] = outpatient['ClmDiagnosisCode_10'].astype('category')\n", "outpatient['ClmDiagnosisCode_2'] = outpatient['ClmDiagnosisCode_2'].astype('category')\n", "outpatient['ClmDiagnosisCode_3'] = outpatient['ClmDiagnosisCode_3'].astype('category')\n", "outpatient['ClmDiagnosisCode_4'] = outpatient['ClmDiagnosisCode_4'].astype('category')\n", "outpatient['ClmDiagnosisCode_5'] = outpatient['ClmDiagnosisCode_5'].astype('category')\n", "outpatient['ClmDiagnosisCode_6'] = outpatient['ClmDiagnosisCode_2'].astype('category')\n", "outpatient['ClmDiagnosisCode_7'] = outpatient['ClmDiagnosisCode_7'].astype('category')\n", "outpatient['ClmDiagnosisCode_8'] = outpatient['ClmDiagnosisCode_8'].astype('category')\n", "outpatient['ClmDiagnosisCode_9'] = outpatient['ClmDiagnosisCode_9'].astype('category')\n", "outpatient['ClmProcedureCode_1'] = outpatient['ClmProcedureCode_1'].astype('category')\n", "outpatient['ClmProcedureCode_2'] = outpatient['ClmProcedureCode_2'].astype('category')\n", "outpatient['ClmProcedureCode_3'] = outpatient['ClmProcedureCode_3'].astype('category')\n", "outpatient['ClmProcedureCode_4'] = outpatient['ClmProcedureCode_4'].astype('category')\n", "outpatient['ClmProcedureCode_5'] = outpatient['ClmProcedureCode_5'].astype('category')\n", "outpatient['ClmProcedureCode_6'] = outpatient['ClmProcedureCode_6'].astype('category')" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.0 453348\n", "20.0 24312\n", "1.0 11960\n", "2.0 4366\n", "14.0 2735\n", "3.0 2597\n", "7.0 2564\n", "4.0 2238\n", "5.0 1511\n", "9.0 1378\n", "6.0 1306\n", "8.0 1189\n", "16.0 1136\n", "10.0 982\n", "15.0 975\n", "11.0 953\n", "13.0 947\n", "12.0 903\n", "17.0 808\n", "18.0 800\n", "19.0 727\n", "23.0 1\n", "21.0 1\n", "Name: OP_claim_duration, dtype: int64" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient['OP_claim_duration'] = outpatient['ClaimEndDt'] - outpatient['ClaimStartDt']\n", "outpatient['OP_claim_duration'] = outpatient['OP_claim_duration'] / np.timedelta64(1, 'D')\n", "outpatient['OP_claim_duration'].value_counts()" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Average Amount Reinbursed per Month')" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# average amount reinbursed per month\n", "fig, ax = plt.subplots(figsize = (15,8))\n", "outpatient.resample('m', on='ClaimEndDt')['InscClaimAmtReimbursed'].mean().plot(kind='line', ax=ax)\n", "ax.set_ylabel('Claim Amount Reimbursed')\n", "ax.set_title('Average Amount Reinbursed per Month')" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 427120\n", "1 90617\n", "Name: OP_Surgery, dtype: int64" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient['OP_Surgery'] = np.where(outpatient['OperatingPhysician'].notnull(), 1, 0)\n", "outpatient.OP_Surgery.value_counts()" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 322691\n", "1 195046\n", "Name: OP_follow_up, dtype: int64" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient['OP_follow_up'] = np.where(outpatient['OtherPhysician'].notnull(), 1, 0)\n", "outpatient.OP_follow_up.value_counts()" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": [ "outpatient['OP_Attending'] = np.where(outpatient['AttendingPhysician'].notnull(), 1, 0)" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AttendingPhysicianBeneIDClaimEndDtClaimIDClaimStartDtClmAdmitDiagnosisCodeClmDiagnosisCode_1ClmDiagnosisCode_10ClmDiagnosisCode_2ClmDiagnosisCode_3...DeductibleAmtPaidInscClaimAmtReimbursedOperatingPhysicianOtherPhysicianProviderIDOP_claim_durationOP_SurgeryOP_follow_upOP_AttendingOP_num_claim_diagnosis_code
0PHY326117BENE110022009-10-11CLM6243492009-10-115640978943NaNV5866V1272...030NoneNonePRV560110.00015
1PHY362868BENE110032009-02-12CLM1899472009-02-12793806115NaNNaNNaN...080NoneNonePRV576100.00012
2PHY328821BENE110032009-06-27CLM4380212009-06-272723NaNNaNNaN...010NoneNonePRV575950.00012
3PHY334319BENE110042009-01-06CLM1218012009-01-0671988NaNNaNNaN...040NoneNonePRV560110.00012
4PHY403831BENE110042009-01-22CLM1509982009-01-227194782382NaN3000072887...0200NoneNonePRV560110.00017
\n", "

5 rows × 32 columns

\n", "
" ], "text/plain": [ " AttendingPhysician BeneID ClaimEndDt ClaimID ClaimStartDt \\\n", "0 PHY326117 BENE11002 2009-10-11 CLM624349 2009-10-11 \n", "1 PHY362868 BENE11003 2009-02-12 CLM189947 2009-02-12 \n", "2 PHY328821 BENE11003 2009-06-27 CLM438021 2009-06-27 \n", "3 PHY334319 BENE11004 2009-01-06 CLM121801 2009-01-06 \n", "4 PHY403831 BENE11004 2009-01-22 CLM150998 2009-01-22 \n", "\n", " ClmAdmitDiagnosisCode ClmDiagnosisCode_1 ClmDiagnosisCode_10 \\\n", "0 56409 78943 NaN \n", "1 79380 6115 NaN \n", "2 2723 NaN \n", "3 71988 NaN \n", "4 71947 82382 NaN \n", "\n", " ClmDiagnosisCode_2 ClmDiagnosisCode_3 ... DeductibleAmtPaid \\\n", "0 V5866 V1272 ... 0 \n", "1 NaN NaN ... 0 \n", "2 NaN NaN ... 0 \n", "3 NaN NaN ... 0 \n", "4 30000 72887 ... 0 \n", "\n", " InscClaimAmtReimbursed OperatingPhysician OtherPhysician ProviderID \\\n", "0 30 None None PRV56011 \n", "1 80 None None PRV57610 \n", "2 10 None None PRV57595 \n", "3 40 None None PRV56011 \n", "4 200 None None PRV56011 \n", "\n", " OP_claim_duration OP_Surgery OP_follow_up OP_Attending \\\n", "0 0.0 0 0 1 \n", "1 0.0 0 0 1 \n", "2 0.0 0 0 1 \n", "3 0.0 0 0 1 \n", "4 0.0 0 0 1 \n", "\n", " OP_num_claim_diagnosis_code \n", "0 5 \n", "1 2 \n", "2 2 \n", "3 2 \n", "4 7 \n", "\n", "[5 rows x 32 columns]" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "claims_code = ['ClmAdmitDiagnosisCode', 'ClmDiagnosisCode_1', 'ClmDiagnosisCode_10', 'ClmDiagnosisCode_2', 'ClmDiagnosisCode_3', 'ClmDiagnosisCode_4',\n", " 'ClmDiagnosisCode_5', 'ClmDiagnosisCode_6', 'ClmDiagnosisCode_7', 'ClmDiagnosisCode_8', 'ClmDiagnosisCode_9']\n", "\n", "outpatient['OP_num_claim_diagnosis_code'] = outpatient[claims_code].count(axis=1)\n", "outpatient.head()" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AttendingPhysicianBeneIDClaimEndDtClaimIDClaimStartDtClmAdmitDiagnosisCodeClmDiagnosisCode_1ClmDiagnosisCode_10ClmDiagnosisCode_2ClmDiagnosisCode_3...InscClaimAmtReimbursedOperatingPhysicianOtherPhysicianProviderIDOP_claim_durationOP_SurgeryOP_follow_upOP_AttendingOP_num_claim_diagnosis_codeOP_num_claim_procedure_code
0PHY326117BENE110022009-10-11CLM6243492009-10-115640978943NaNV5866V1272...30NoneNonePRV560110.000150
1PHY362868BENE110032009-02-12CLM1899472009-02-12793806115NaNNaNNaN...80NoneNonePRV576100.000120
2PHY328821BENE110032009-06-27CLM4380212009-06-272723NaNNaNNaN...10NoneNonePRV575950.000120
3PHY334319BENE110042009-01-06CLM1218012009-01-0671988NaNNaNNaN...40NoneNonePRV560110.000120
4PHY403831BENE110042009-01-22CLM1509982009-01-227194782382NaN3000072887...200NoneNonePRV560110.000170
\n", "

5 rows × 33 columns

\n", "
" ], "text/plain": [ " AttendingPhysician BeneID ClaimEndDt ClaimID ClaimStartDt \\\n", "0 PHY326117 BENE11002 2009-10-11 CLM624349 2009-10-11 \n", "1 PHY362868 BENE11003 2009-02-12 CLM189947 2009-02-12 \n", "2 PHY328821 BENE11003 2009-06-27 CLM438021 2009-06-27 \n", "3 PHY334319 BENE11004 2009-01-06 CLM121801 2009-01-06 \n", "4 PHY403831 BENE11004 2009-01-22 CLM150998 2009-01-22 \n", "\n", " ClmAdmitDiagnosisCode ClmDiagnosisCode_1 ClmDiagnosisCode_10 \\\n", "0 56409 78943 NaN \n", "1 79380 6115 NaN \n", "2 2723 NaN \n", "3 71988 NaN \n", "4 71947 82382 NaN \n", "\n", " ClmDiagnosisCode_2 ClmDiagnosisCode_3 ... InscClaimAmtReimbursed \\\n", "0 V5866 V1272 ... 30 \n", "1 NaN NaN ... 80 \n", "2 NaN NaN ... 10 \n", "3 NaN NaN ... 40 \n", "4 30000 72887 ... 200 \n", "\n", " OperatingPhysician OtherPhysician ProviderID OP_claim_duration OP_Surgery \\\n", "0 None None PRV56011 0.0 0 \n", "1 None None PRV57610 0.0 0 \n", "2 None None PRV57595 0.0 0 \n", "3 None None PRV56011 0.0 0 \n", "4 None None PRV56011 0.0 0 \n", "\n", " OP_follow_up OP_Attending OP_num_claim_diagnosis_code \\\n", "0 0 1 5 \n", "1 0 1 2 \n", "2 0 1 2 \n", "3 0 1 2 \n", "4 0 1 7 \n", "\n", " OP_num_claim_procedure_code \n", "0 0 \n", "1 0 \n", "2 0 \n", "3 0 \n", "4 0 \n", "\n", "[5 rows x 33 columns]" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "claims_proceed_code = ['ClmProcedureCode_1', 'ClmProcedureCode_2', 'ClmProcedureCode_3', 'ClmProcedureCode_4',\n", " 'ClmProcedureCode_5', 'ClmProcedureCode_6']\n", "\n", "outpatient['OP_num_claim_procedure_code'] = outpatient[claims_proceed_code].count(axis=1)\n", "outpatient.head()" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax =plt.subplots()\n", "\n", "plt.figure(figsize = (15,8))\n", "ax.plot(outpatient['OP_num_claim_procedure_code'], outpatient['InscClaimAmtReimbursed'], marker='o', linestyle='none', markersize=1)\n", "\n", "\n", "sns.stripplot(data=outpatient, x=\"OP_num_claim_procedure_code\", y=\"InscClaimAmtReimbursed\", jitter=0.8, size=2)" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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BeneIDClaimIDDeductibleAmtPaidInscClaimAmtReimbursedProviderIDOP_claim_durationOP_SurgeryOP_follow_upOP_AttendingOP_num_claim_diagnosis_codeOP_num_claim_procedure_code
0BENE11002CLM624349030PRV560110.000150
1BENE11003CLM189947080PRV576100.000120
2BENE11003CLM438021010PRV575950.000120
3BENE11004CLM121801040PRV560110.000120
4BENE11004CLM1509980200PRV560110.000170
\n", "
" ], "text/plain": [ " BeneID ClaimID DeductibleAmtPaid InscClaimAmtReimbursed ProviderID \\\n", "0 BENE11002 CLM624349 0 30 PRV56011 \n", "1 BENE11003 CLM189947 0 80 PRV57610 \n", "2 BENE11003 CLM438021 0 10 PRV57595 \n", "3 BENE11004 CLM121801 0 40 PRV56011 \n", "4 BENE11004 CLM150998 0 200 PRV56011 \n", "\n", " OP_claim_duration OP_Surgery OP_follow_up OP_Attending \\\n", "0 0.0 0 0 1 \n", "1 0.0 0 0 1 \n", "2 0.0 0 0 1 \n", "3 0.0 0 0 1 \n", "4 0.0 0 0 1 \n", "\n", " OP_num_claim_diagnosis_code OP_num_claim_procedure_code \n", "0 5 0 \n", "1 2 0 \n", "2 2 0 \n", "3 2 0 \n", "4 7 0 " ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient = outpatient.drop(['ClmAdmitDiagnosisCode', 'ClmDiagnosisCode_1', 'ClmDiagnosisCode_10', 'ClmDiagnosisCode_2', 'ClmDiagnosisCode_3', 'ClmDiagnosisCode_4',\n", " 'ClmDiagnosisCode_5', 'ClmDiagnosisCode_6', 'ClmDiagnosisCode_7', 'ClmDiagnosisCode_8', 'ClmDiagnosisCode_9', 'ClmProcedureCode_1', 'ClmProcedureCode_2',\n", " 'ClmProcedureCode_3', 'ClmProcedureCode_4', 'ClmProcedureCode_5', 'ClmProcedureCode_6', 'OperatingPhysician', 'OtherPhysician',\n", " 'AttendingPhysician', 'ClaimEndDt',\t'ClaimStartDt'], axis=1)\n", "\n", "outpatient.head()" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ProviderIDPotentialFraud
0PRV51001No
1PRV51003Yes
2PRV51004No
3PRV51005Yes
4PRV51007No
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" ], "text/plain": [ " ProviderID PotentialFraud\n", "0 PRV51001 No\n", "1 PRV51003 Yes\n", "2 PRV51004 No\n", "3 PRV51005 Yes\n", "4 PRV51007 No" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "provider.head()" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ProviderIDPotentialFraud
count54105410
unique54102
topPRV54436No
freq14904
\n", "
" ], "text/plain": [ " ProviderID PotentialFraud\n", "count 5410 5410\n", "unique 5410 2\n", "top PRV54436 No\n", "freq 1 4904" ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "provider.describe()" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 5410 entries, 0 to 5409\n", "Data columns (total 2 columns):\n", "ProviderID 5410 non-null object\n", "PotentialFraud 5410 non-null object\n", "dtypes: object(2)\n", "memory usage: 84.7+ KB\n" ] } ], "source": [ "provider.info()" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "ProviderID 0\n", "PotentialFraud 0\n", "dtype: int64" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "provider.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 72, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize = (15,8))\n", "sns.countplot(x='PotentialFraud', data=provider)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## MERGED DATASETS EDA " ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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BeneIDClaimID_OPDeductibleAmtPaidInscClaimAmtReimbursed_OPProviderID_OPOP_claim_durationOP_SurgeryOP_follow_upOP_AttendingOP_num_claim_diagnosis_code...ClaimID_IPInscClaimAmtReimbursed_IPProviderID_IPduration_of_stayIP_claim_durationSurgeryFollow_upAttendingIP_num_claim_diagnosis_codeIP_num_claim_procedure_code
0BENE11011CLM144521050PRV523140.00017...CLM384125000PRV524058.08.0111102
1BENE11011CLM347780050PRV510120.00112...CLM384125000PRV524058.08.0111102
2BENE11011CLM507201080PRV510630.00015...CLM384125000PRV524058.08.0111102
3BENE11014CLM523157060PRV568350.00112...CLM6368910000PRV5661417.017.0101102
4BENE11017CLM1107180100PRV5478615.00012...CLM709508000PRV549866.06.0111102
..................................................................
173577BENE159177CLM5521870100PRV565750.00112...CLM764853000PRV565884.04.0101102
173578BENE159177CLM5521870100PRV565750.00112...CLM799495000PRV565751.01.0001101
173579BENE159188CLM40133605030PRV547652.010110...CLM6994815000PRV547658.08.0101102
173580BENE159188CLM499056010PRV547780.00115...CLM6994815000PRV547658.08.0101102
173581BENE159188CLM6478090500PRV547780.00012...CLM6994815000PRV547658.08.0101102
\n", "

173582 rows × 21 columns

\n", "
" ], "text/plain": [ " BeneID ClaimID_OP DeductibleAmtPaid InscClaimAmtReimbursed_OP \\\n", "0 BENE11011 CLM144521 0 50 \n", "1 BENE11011 CLM347780 0 50 \n", "2 BENE11011 CLM507201 0 80 \n", "3 BENE11014 CLM523157 0 60 \n", "4 BENE11017 CLM110718 0 100 \n", "... ... ... ... ... \n", "173577 BENE159177 CLM552187 0 100 \n", "173578 BENE159177 CLM552187 0 100 \n", "173579 BENE159188 CLM401336 0 5030 \n", "173580 BENE159188 CLM499056 0 10 \n", "173581 BENE159188 CLM647809 0 500 \n", "\n", " ProviderID_OP OP_claim_duration OP_Surgery OP_follow_up \\\n", "0 PRV52314 0.0 0 0 \n", "1 PRV51012 0.0 0 1 \n", "2 PRV51063 0.0 0 0 \n", "3 PRV56835 0.0 0 1 \n", "4 PRV54786 15.0 0 0 \n", "... ... ... ... ... \n", "173577 PRV56575 0.0 0 1 \n", "173578 PRV56575 0.0 0 1 \n", "173579 PRV54765 2.0 1 0 \n", "173580 PRV54778 0.0 0 1 \n", "173581 PRV54778 0.0 0 0 \n", "\n", " OP_Attending OP_num_claim_diagnosis_code ... ClaimID_IP \\\n", "0 1 7 ... CLM38412 \n", "1 1 2 ... CLM38412 \n", "2 1 5 ... CLM38412 \n", "3 1 2 ... CLM63689 \n", "4 1 2 ... CLM70950 \n", "... ... ... ... ... \n", "173577 1 2 ... CLM76485 \n", "173578 1 2 ... CLM79949 \n", "173579 1 10 ... CLM69948 \n", "173580 1 5 ... CLM69948 \n", "173581 1 2 ... CLM69948 \n", "\n", " InscClaimAmtReimbursed_IP ProviderID_IP duration_of_stay \\\n", "0 5000 PRV52405 8.0 \n", "1 5000 PRV52405 8.0 \n", "2 5000 PRV52405 8.0 \n", "3 10000 PRV56614 17.0 \n", "4 8000 PRV54986 6.0 \n", "... ... ... ... \n", "173577 3000 PRV56588 4.0 \n", "173578 5000 PRV56575 1.0 \n", "173579 15000 PRV54765 8.0 \n", "173580 15000 PRV54765 8.0 \n", "173581 15000 PRV54765 8.0 \n", "\n", " IP_claim_duration Surgery Follow_up Attending \\\n", "0 8.0 1 1 1 \n", "1 8.0 1 1 1 \n", "2 8.0 1 1 1 \n", "3 17.0 1 0 1 \n", "4 6.0 1 1 1 \n", "... ... ... ... ... \n", "173577 4.0 1 0 1 \n", "173578 1.0 0 0 1 \n", "173579 8.0 1 0 1 \n", "173580 8.0 1 0 1 \n", "173581 8.0 1 0 1 \n", "\n", " IP_num_claim_diagnosis_code IP_num_claim_procedure_code \n", "0 10 2 \n", "1 10 2 \n", "2 10 2 \n", "3 10 2 \n", "4 10 2 \n", "... ... ... \n", "173577 10 2 \n", "173578 10 1 \n", "173579 10 2 \n", "173580 10 2 \n", "173581 10 2 \n", "\n", "[173582 rows x 21 columns]" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "all_claims = outpatient.merge(inpatient, on='BeneID', suffixes=('_OP', '_IP'))\n", "all_claims" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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BeneIDClaimIDInscClaimAmtReimbursedProviderIDduration_of_stayIP_claim_durationSurgeryFollow_upAttendingIP_num_claim_diagnosis_codeIP_num_claim_procedure_codePotentialFraud
0BENE11001CLM4661426000PRV559126.06.0001101Yes
1BENE17521CLM3472119000PRV5591212.012.0111103Yes
2BENE21718CLM7233617000PRV5591218.018.0101102Yes
3BENE22934CLM7339413000PRV559124.04.011182Yes
4BENE24402CLM329113000PRV559124.04.010122Yes
.......................................
40469BENE156181CLM5701712000PRV557067.07.0111102No
40470BENE156872CLM670455000PRV515727.07.0111102No
40471BENE157414CLM7603614000PRV556888.08.0001101No
40472BENE158281CLM3514310000PRV564850.00.010192No
40473BENE159166CLM389856000PRV518127.07.0101112No
\n", "

40474 rows × 12 columns

\n", "
" ], "text/plain": [ " BeneID ClaimID InscClaimAmtReimbursed ProviderID \\\n", "0 BENE11001 CLM46614 26000 PRV55912 \n", "1 BENE17521 CLM34721 19000 PRV55912 \n", "2 BENE21718 CLM72336 17000 PRV55912 \n", "3 BENE22934 CLM73394 13000 PRV55912 \n", "4 BENE24402 CLM32911 3000 PRV55912 \n", "... ... ... ... ... \n", "40469 BENE156181 CLM57017 12000 PRV55706 \n", "40470 BENE156872 CLM67045 5000 PRV51572 \n", "40471 BENE157414 CLM76036 14000 PRV55688 \n", "40472 BENE158281 CLM35143 10000 PRV56485 \n", "40473 BENE159166 CLM38985 6000 PRV51812 \n", "\n", " duration_of_stay IP_claim_duration Surgery Follow_up Attending \\\n", "0 6.0 6.0 0 0 1 \n", "1 12.0 12.0 1 1 1 \n", "2 18.0 18.0 1 0 1 \n", "3 4.0 4.0 1 1 1 \n", "4 4.0 4.0 1 0 1 \n", "... ... ... ... ... ... \n", "40469 7.0 7.0 1 1 1 \n", "40470 7.0 7.0 1 1 1 \n", "40471 8.0 8.0 0 0 1 \n", "40472 0.0 0.0 1 0 1 \n", "40473 7.0 7.0 1 0 1 \n", "\n", " IP_num_claim_diagnosis_code IP_num_claim_procedure_code PotentialFraud \n", "0 10 1 Yes \n", "1 10 3 Yes \n", "2 10 2 Yes \n", "3 8 2 Yes \n", "4 2 2 Yes \n", "... ... ... ... \n", "40469 10 2 No \n", "40470 10 2 No \n", "40471 10 1 No \n", "40472 9 2 No \n", "40473 11 2 No \n", "\n", "[40474 rows x 12 columns]" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inpatient_provider = inpatient.merge(provider, on='ProviderID')\n", "inpatient_provider" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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BeneIDClaimIDDeductibleAmtPaidInscClaimAmtReimbursedProviderIDOP_claim_durationOP_SurgeryOP_follow_upOP_AttendingOP_num_claim_diagnosis_codeOP_num_claim_procedure_codePotentialFraud
0BENE11002CLM624349030PRV560110.000150Yes
1BENE11004CLM121801040PRV560110.000120Yes
2BENE11004CLM1509980200PRV560110.000170Yes
3BENE11004CLM173224020PRV560110.000120Yes
4BENE11004CLM224741040PRV560110.000160Yes
.......................................
517732BENE154687CLM18435803300PRV543020.010120No
517733BENE157252CLM60318501900PRV577620.000120No
517734BENE157378CLM46077002100PRV5157720.000140No
517735BENE158295CLM306999010PRV530830.000120No
517736BENE158736CLM589654060PRV563770.001160No
\n", "

517737 rows × 12 columns

\n", "
" ], "text/plain": [ " BeneID ClaimID DeductibleAmtPaid InscClaimAmtReimbursed \\\n", "0 BENE11002 CLM624349 0 30 \n", "1 BENE11004 CLM121801 0 40 \n", "2 BENE11004 CLM150998 0 200 \n", "3 BENE11004 CLM173224 0 20 \n", "4 BENE11004 CLM224741 0 40 \n", "... ... ... ... ... \n", "517732 BENE154687 CLM184358 0 3300 \n", "517733 BENE157252 CLM603185 0 1900 \n", "517734 BENE157378 CLM460770 0 2100 \n", "517735 BENE158295 CLM306999 0 10 \n", "517736 BENE158736 CLM589654 0 60 \n", "\n", " ProviderID OP_claim_duration OP_Surgery OP_follow_up OP_Attending \\\n", "0 PRV56011 0.0 0 0 1 \n", "1 PRV56011 0.0 0 0 1 \n", "2 PRV56011 0.0 0 0 1 \n", "3 PRV56011 0.0 0 0 1 \n", "4 PRV56011 0.0 0 0 1 \n", "... ... ... ... ... ... \n", "517732 PRV54302 0.0 1 0 1 \n", "517733 PRV57762 0.0 0 0 1 \n", "517734 PRV51577 20.0 0 0 1 \n", "517735 PRV53083 0.0 0 0 1 \n", "517736 PRV56377 0.0 0 1 1 \n", "\n", " OP_num_claim_diagnosis_code OP_num_claim_procedure_code \\\n", "0 5 0 \n", "1 2 0 \n", "2 7 0 \n", "3 2 0 \n", "4 6 0 \n", "... ... ... \n", "517732 2 0 \n", "517733 2 0 \n", "517734 4 0 \n", "517735 2 0 \n", "517736 6 0 \n", "\n", " PotentialFraud \n", "0 Yes \n", "1 Yes \n", "2 Yes \n", "3 Yes \n", "4 Yes \n", "... ... \n", "517732 No \n", "517733 No \n", "517734 No \n", "517735 No \n", "517736 No \n", "\n", "[517737 rows x 12 columns]" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient_provider = outpatient.merge(provider, on='ProviderID')\n", "outpatient_provider" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "BeneID 0\n", "ClaimID 0\n", "DeductibleAmtPaid 0\n", "InscClaimAmtReimbursed 0\n", "ProviderID 0\n", "OP_claim_duration 0\n", "OP_Surgery 0\n", "OP_follow_up 0\n", "OP_Attending 0\n", "OP_num_claim_diagnosis_code 0\n", "OP_num_claim_procedure_code 0\n", "PotentialFraud 0\n", "dtype: int64" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient_provider.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "No 328343\n", "Yes 189394\n", "Name: PotentialFraud, dtype: int64" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "outpatient_provider.PotentialFraud.value_counts()" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\"_ = pd.plotting.scatter_matrix(outpatient_provider, c='y', figsize=[10,10], s=150, marker='D')\\nplt.show()\"" ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\"\"\"_ = pd.plotting.scatter_matrix(outpatient_provider, c='y', figsize=[10,10], s=150, marker='D')\n", "plt.show()\"\"\"" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#print(inpatient_provider.corr())\n", " \n", "# plotting correlation heatmap\n", "plt.figure(figsize = (17,10))\n", "sns.heatmap(inpatient_provider.corr(), annot=True, annot_kws={\"size\": 9}, linewidths=.5, linecolor='white', center=0, cmap=\"YlGnBu\", yticklabels=False)\n", " " ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1, 'Correlation Map')" ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#print(outpatient_provider.corr())\n", " \n", "# plotting correlation heatmap\n", "plt.figure(figsize = (17,10))\n", "sns.heatmap(outpatient_provider.corr(), annot=True, annot_kws={\"size\": 9}, linewidths=.5, linecolor='white', center=0, cmap=\"YlGnBu\", yticklabels=False)\n", "plt.title('Correlation Map')" ] }, { "cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['BeneID', 'Gender', 'Race', 'RenalDiseaseIndicator', 'State', 'County',\n", " 'NoOfMonths_PartACov', 'NoOfMonths_PartBCov', 'ChronicCond_Alzheimer',\n", " 'ChronicCond_Heartfailure', 'ChronicCond_KidneyDisease',\n", " 'ChronicCond_Cancer', 'ChronicCond_ObstrPulmonary',\n", " 'ChronicCond_Depression', 'ChronicCond_Diabetes',\n", " 'ChronicCond_IschemicHeart', 'ChronicCond_Osteoporasis',\n", " 'ChronicCond_rheumatoidarthritis', 'ChronicCond_stroke',\n", " 'IPAnnualReimbursementAmt', 'IPAnnualDeductibleAmt',\n", " 'OPAnnualReimbursementAmt', 'OPAnnualDeductibleAmt', 'Birth_year',\n", " 'Age', 'isAlive', 'TotalAnnualReimbursableAmt',\n", " 'TotalAnnualDeductibleAmt', 'ClaimID', 'DeductibleAmtPaid',\n", " 'InscClaimAmtReimbursed', 'ProviderID', 'OP_claim_duration',\n", " 'OP_Surgery', 'OP_follow_up', 'OP_Attending',\n", " 'OP_num_claim_diagnosis_code', 'OP_num_claim_procedure_code',\n", " 'PotentialFraud'],\n", " dtype='object')" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bene_provider = beneficiary.merge(outpatient_provider, on='BeneID')\n", "bene_provider.columns" ] }, { "cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 82, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"figure.figsize\"] = (20,10)\n", "bene_provider.groupby(['State'])['PotentialFraud'].value_counts().sort_index(ascending=True).unstack().plot(kind='bar',stacked = True)\n" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 83, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"figure.figsize\"] = (20,10)\n", "bene_provider.groupby(['Gender'])['PotentialFraud'].value_counts().sort_index(ascending=True).unstack().plot(kind='bar')\n" ] }, { "cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 84, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"figure.figsize\"] = (20,10)\n", "bene_provider.groupby(['Race'])['PotentialFraud'].value_counts().sort_index(ascending=True).unstack().plot(kind='bar')\n" ] }, { "cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 85, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"figure.figsize\"] = (20,10)\n", "bene_provider.groupby(['Gender','PotentialFraud'])['OPAnnualReimbursementAmt'].sum().sort_index(ascending=True).unstack().plot(kind='bar')\n" ] }, { "cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 86, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"figure.figsize\"] = (20,10)\n", "bene_provider.groupby(['OP_num_claim_diagnosis_code'])['PotentialFraud'].value_counts().sort_index(ascending=True).unstack().plot(kind='bar',stacked = True)" ] }, { "cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 87, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize = (15,8))\n", "bene_provider.OP_num_claim_diagnosis_code.plot(kind='hist', bins=6)" ] }, { "cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1, 'Correlation Map')" ] }, "execution_count": 88, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#print(outpatient_provider.corr())\n", " \n", "# plotting correlation heatmap\n", "plt.figure(figsize = (17,10))\n", "sns.heatmap(bene_provider.corr(), annot=True, annot_kws={\"size\": 9}, linewidths=.5, linecolor='white', center=0, cmap=\"YlGnBu\", yticklabels=False)\n", "plt.title('Correlation Map')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## MODELLING POTENTIAL FRAUD OUTPATIENT" ] }, { "cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Gender category\n", "Race category\n", "RenalDiseaseIndicator object\n", "State category\n", "County category\n", "ChronicCond_Alzheimer category\n", "ChronicCond_Heartfailure category\n", "ChronicCond_KidneyDisease category\n", "ChronicCond_Cancer category\n", "ChronicCond_ObstrPulmonary category\n", "ChronicCond_Depression category\n", "ChronicCond_Diabetes category\n", "ChronicCond_IschemicHeart category\n", "ChronicCond_Osteoporasis category\n", "ChronicCond_rheumatoidarthritis category\n", "ChronicCond_stroke category\n", "Age float64\n", "isAlive int64\n", "TotalAnnualReimbursableAmt int64\n", "TotalAnnualDeductibleAmt int64\n", "DeductibleAmtPaid int64\n", "InscClaimAmtReimbursed int64\n", "OP_claim_duration float64\n", "OP_Surgery int32\n", "OP_follow_up int32\n", "OP_Attending int32\n", "OP_num_claim_diagnosis_code int64\n", "OP_num_claim_procedure_code int64\n", "dtype: object" ] }, "execution_count": 89, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.model_selection import train_test_split, cross_val_score, GridSearchCV\n", "from sklearn.neighbors import KNeighborsClassifier\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.metrics import roc_curve, roc_auc_score, classification_report, confusion_matrix\n", "from sklearn.preprocessing import Imputer, StandardScaler\n", "from sklearn.pipeline import Pipeline\n", "import numpy as np\n", "from sklearn.ensemble import RandomForestClassifier\n", "\n", "#print(bene_provider.columns)\n", "\n", "features = bene_provider.drop(['BeneID', 'ClaimID', 'ProviderID', 'PotentialFraud', 'NoOfMonths_PartACov', 'NoOfMonths_PartBCov',\n", " 'IPAnnualReimbursementAmt', 'IPAnnualDeductibleAmt','OPAnnualReimbursementAmt', 'OPAnnualDeductibleAmt', 'Birth_year'], axis=1)\n", "target = bene_provider['PotentialFraud']\n", "\n", "# map potential fraud to numerical values\n", "\n", "scale_mapper = {\"No\": 0, \"Yes\":1}\n", "target = target.replace(scale_mapper)\n", "target.shape\n", "features.dtypes\n", "\n" ] }, { "cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [], "source": [ "#standardize faetures\n", "scaler = StandardScaler()\n", "features_std = scaler.fit_transform(features)\n", "\n", "#split dataset\n", "X_train, X_test, y_train, y_test = train_test_split(features_std, target, test_size=0.3, random_state=42, stratify=target)\n" ] }, { "cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'#KNN\\nknn = KNeighborsClassifier(n_neighbors=2)\\n\\nmodel = knn.fit(X_train, y_train)\\n\\ny_pred = model.predict(X_test)\\n\\nknn.score(X_test, y_test)'" ] }, "execution_count": 91, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\"\"\"#KNN\n", "knn = KNeighborsClassifier(n_neighbors=2)\n", "\n", "model = knn.fit(X_train, y_train)\n", "\n", "y_pred = model.predict(X_test)\n", "\n", "knn.score(X_test, y_test)\"\"\"" ] }, { "cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'cv_results = cross_val_score(knn, X_train, y_train, cv=5)\\nprint(np.mean(cv_results))\\nprint(confusion_matrix(y_test, y_pred))\\nprint(classification_report(y_test, y_pred))'" ] }, "execution_count": 92, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\"\"\"cv_results = cross_val_score(knn, X_train, y_train, cv=5)\n", "print(np.mean(cv_results))\n", "print(confusion_matrix(y_test, y_pred))\n", "print(classification_report(y_test, y_pred))\"\"\"" ] }, { "cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.5188223452440865" ] }, "execution_count": 93, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Logistic Regression\n", "logreg = LogisticRegression(random_state=0, solver='saga', class_weight=\"balanced\")\n", "\n", "model_logreg = logreg.fit(X_train, y_train)\n", "\n", "y_pred = model_logreg.predict(X_test)\n", "\n", "logreg.score(X_test, y_test)" ] }, { "cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.5181592763601174\n", "[[39901 35998]\n", " [21368 21953]]\n", " precision recall f1-score support\n", "\n", " 0 0.65 0.53 0.58 75899\n", " 1 0.38 0.51 0.43 43321\n", "\n", " accuracy 0.52 119220\n", " macro avg 0.52 0.52 0.51 119220\n", "weighted avg 0.55 0.52 0.53 119220\n", "\n" ] } ], "source": [ "cv_results_logreg = cross_val_score(logreg, X_train, y_train, cv=5)\n", "print(np.mean(cv_results_logreg))\n", "print(confusion_matrix(y_test, y_pred))\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.700021926432286\n", "[[58461 17438]\n", " [18027 25294]]\n", " precision recall f1-score support\n", "\n", " 0 0.76 0.77 0.77 75899\n", " 1 0.59 0.58 0.59 43321\n", "\n", " accuracy 0.70 119220\n", " macro avg 0.68 0.68 0.68 119220\n", "weighted avg 0.70 0.70 0.70 119220\n", "\n" ] } ], "source": [ "dt = DecisionTreeClassifier(random_state=1, class_weight=\"balanced\", criterion='gini')\n", "model_dt = dt.fit(X_train, y_train)\n", "y_pred = model_dt.predict(X_test)\n", "model_dt.score(X_test, y_test)\n", "\n", "cv_results_dt = cross_val_score(dt, X_train, y_train, cv=5)\n", "print(np.mean(cv_results_dt))\n", "print(confusion_matrix(y_test, y_pred))\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "GridSearchCV(cv=10, error_score='raise-deprecating',\n", " estimator=DecisionTreeClassifier(class_weight='balanced',\n", " criterion='gini', max_depth=None,\n", " max_features=None,\n", " max_leaf_nodes=None,\n", " min_impurity_decrease=0.0,\n", " min_impurity_split=None,\n", " min_samples_leaf=1,\n", " min_samples_split=2,\n", " min_weight_fraction_leaf=0.0,\n", " presort=False, random_state=1,\n", " splitter='best'),\n", " iid='warn', n_jobs=-1,\n", " param_grid={'class_weight': ['balanced'],\n", " 'criterion': ['gini', 'entropy'],\n", " 'max_depth': [3, 4, 5, 6],\n", " 'max_features': [0.2, 0.4, 0.6, 0.8],\n", " 'min_samples_leaf': [0.04, 0.06, 0.08]},\n", " pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n", " scoring='accuracy', verbose=0)" ] }, "execution_count": 96, "metadata": {}, "output_type": "execute_result" } ], "source": [ "params_dt = {\n", " 'max_depth': [3,4,5,6],\n", " 'min_samples_leaf': [0.04, 0.06, 0.08],\n", " 'max_features': [0.2,0.4,0.6,0.8],\n", " 'class_weight': ['balanced'], \n", " 'criterion': ['gini', 'entropy']\n", "}\n", "grid_dt = GridSearchCV(estimator=dt, param_grid=params_dt, scoring='accuracy', cv=10, n_jobs=-1)\n", "grid_dt.fit(X_train, y_train)" ] }, { "cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'class_weight': 'balanced', 'criterion': 'gini', 'max_depth': 5, 'max_features': 0.6, 'min_samples_leaf': 0.06}\n", "0.6423104713905176\n", "DecisionTreeClassifier(class_weight='balanced', criterion='gini', max_depth=5,\n", " max_features=0.6, max_leaf_nodes=None,\n", " min_impurity_decrease=0.0, min_impurity_split=None,\n", " min_samples_leaf=0.06, min_samples_split=2,\n", " min_weight_fraction_leaf=0.0, presort=False,\n", " random_state=1, splitter='best')\n", "[[58242 17657]\n", " [24916 18405]]\n", " precision recall f1-score support\n", "\n", " 0 0.70 0.77 0.73 75899\n", " 1 0.51 0.42 0.46 43321\n", "\n", " accuracy 0.64 119220\n", " macro avg 0.61 0.60 0.60 119220\n", "weighted avg 0.63 0.64 0.63 119220\n", "\n" ] } ], "source": [ "best_hyperparams = grid_dt.best_params_\n", "best_cv_score = grid_dt.best_score_\n", "best_model = grid_dt.best_estimator_\n", "\n", "print(best_hyperparams)\n", "print(best_cv_score)\n", "print(best_model)\n", "\n", "y_pred = best_model.predict(X_test)\n", "print(confusion_matrix(y_test, y_pred))\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\User\\Anaconda3\\lib\\site-packages\\sklearn\\ensemble\\forest.py:245: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n", " \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "0.700021926432286\n", "[[66019 9880]\n", " [24637 18684]]\n", " precision recall f1-score support\n", "\n", " 0 0.73 0.87 0.79 75899\n", " 1 0.65 0.43 0.52 43321\n", "\n", " accuracy 0.71 119220\n", " macro avg 0.69 0.65 0.66 119220\n", "weighted avg 0.70 0.71 0.69 119220\n", "\n" ] } ], "source": [ "rf = RandomForestClassifier(random_state=1, class_weight=\"balanced\", criterion='gini')\n", "model_rf = rf.fit(X_train, y_train)\n", "y_pred = model_rf.predict(X_test)\n", "model_rf.score(X_test, y_test)\n", "\n", "cv_results_rf = cross_val_score(rf, X_train, y_train, cv=5)\n", "print(np.mean(cv_results_dt))\n", "print(confusion_matrix(y_test, y_pred))\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "code", "execution_count": 99, "metadata": {}, "outputs": [], "source": [ "params_rf = {\n", " 'n_estimators': [200,300,400,500],\n", " 'max_depth': [2,4,6,8],\n", " 'min_samples_leaf': [0.1, 0.2, 0.3],\n", " 'max_features': [\"sqrt\", \"log2\"],\n", " 'class_weight': ['balanced'], \n", " 'criterion': ['gini', 'entropy']\n", "}\n", "grid_rf = GridSearchCV(estimator=rf, param_grid=params_rf, scoring='accuracy', cv=5, n_jobs=-1)\n", "grid_rf.fit(X_train, y_train)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "best_hyperparams = grid_rf.best_params_\n", "best_cv_score = grid_rf.best_score_\n", "best_model = grid_rf.best_estimator_\n", "\n", "print(best_hyperparams)\n", "print(best_cv_score)\n", "print(best_model)\n", "\n", "y_pred = best_model.predict(X_test)\n", "print(confusion_matrix(y_test, y_pred))\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "importances_rf = pd.Series(rf.feature_importances_, index = features.columns)\n", "sorted_importance_rf = importances_rf.sort_values()\n", "sorted_importance_rf.plot(kind='barh', color='lightgreen')\n", "plt.show()" ] } ], "metadata": { "interpreter": { "hash": "9d3bae0a0f66551680ef8a166f6b92cc2774d5d7901f027deb7bb883ed06d5ae" }, "kernelspec": { "display_name": "Python 3.7.4 ('base')", "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": "3.7.4" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }