{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "b64c1504", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PatientIdAppointmentIDGenderScheduledDayAppointmentDayAgeNeighbourhoodScholarshipHipertensionDiabetesAlcoholismHandcapSMS_receivedNo-show
02.987250e+135642903F2016-04-29T18:38:08Z2016-04-29T00:00:00Z62JARDIM DA PENHA010000No
15.589978e+145642503M2016-04-29T16:08:27Z2016-04-29T00:00:00Z56JARDIM DA PENHA000000No
24.262962e+125642549F2016-04-29T16:19:04Z2016-04-29T00:00:00Z62MATA DA PRAIA000000No
38.679512e+115642828F2016-04-29T17:29:31Z2016-04-29T00:00:00Z8PONTAL DE CAMBURI000000No
48.841186e+125642494F2016-04-29T16:07:23Z2016-04-29T00:00:00Z56JARDIM DA PENHA011000No
.............................................
1105222.572134e+125651768F2016-05-03T09:15:35Z2016-06-07T00:00:00Z56MARIA ORTIZ000001No
1105233.596266e+125650093F2016-05-03T07:27:33Z2016-06-07T00:00:00Z51MARIA ORTIZ000001No
1105241.557663e+135630692F2016-04-27T16:03:52Z2016-06-07T00:00:00Z21MARIA ORTIZ000001No
1105259.213493e+135630323F2016-04-27T15:09:23Z2016-06-07T00:00:00Z38MARIA ORTIZ000001No
1105263.775115e+145629448F2016-04-27T13:30:56Z2016-06-07T00:00:00Z54MARIA ORTIZ000001No
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110527 rows × 14 columns

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" ], "text/plain": [ " PatientId AppointmentID Gender ScheduledDay \\\n", "0 2.987250e+13 5642903 F 2016-04-29T18:38:08Z \n", "1 5.589978e+14 5642503 M 2016-04-29T16:08:27Z \n", "2 4.262962e+12 5642549 F 2016-04-29T16:19:04Z \n", "3 8.679512e+11 5642828 F 2016-04-29T17:29:31Z \n", "4 8.841186e+12 5642494 F 2016-04-29T16:07:23Z \n", "... ... ... ... ... \n", "110522 2.572134e+12 5651768 F 2016-05-03T09:15:35Z \n", "110523 3.596266e+12 5650093 F 2016-05-03T07:27:33Z \n", "110524 1.557663e+13 5630692 F 2016-04-27T16:03:52Z \n", "110525 9.213493e+13 5630323 F 2016-04-27T15:09:23Z \n", "110526 3.775115e+14 5629448 F 2016-04-27T13:30:56Z \n", "\n", " AppointmentDay Age Neighbourhood Scholarship \\\n", "0 2016-04-29T00:00:00Z 62 JARDIM DA PENHA 0 \n", "1 2016-04-29T00:00:00Z 56 JARDIM DA PENHA 0 \n", "2 2016-04-29T00:00:00Z 62 MATA DA PRAIA 0 \n", "3 2016-04-29T00:00:00Z 8 PONTAL DE CAMBURI 0 \n", "4 2016-04-29T00:00:00Z 56 JARDIM DA PENHA 0 \n", "... ... ... ... ... \n", "110522 2016-06-07T00:00:00Z 56 MARIA ORTIZ 0 \n", "110523 2016-06-07T00:00:00Z 51 MARIA ORTIZ 0 \n", "110524 2016-06-07T00:00:00Z 21 MARIA ORTIZ 0 \n", "110525 2016-06-07T00:00:00Z 38 MARIA ORTIZ 0 \n", "110526 2016-06-07T00:00:00Z 54 MARIA ORTIZ 0 \n", "\n", " Hipertension Diabetes Alcoholism Handcap SMS_received No-show \n", "0 1 0 0 0 0 No \n", "1 0 0 0 0 0 No \n", "2 0 0 0 0 0 No \n", "3 0 0 0 0 0 No \n", "4 1 1 0 0 0 No \n", "... ... ... ... ... ... ... \n", "110522 0 0 0 0 1 No \n", "110523 0 0 0 0 1 No \n", "110524 0 0 0 0 1 No \n", "110525 0 0 0 0 1 No \n", "110526 0 0 0 0 1 No \n", "\n", "[110527 rows x 14 columns]" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# loading the data\n", "import pandas as pd\n", "data= pd.read_csv(r\"data/KaggleV2-May-2016.csv\")\n", "data" ] }, { "cell_type": "code", "execution_count": 2, "id": "27c0b011", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(110527, 14)" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#no of rows & col\n", "data.shape" ] }, { "cell_type": "code", "execution_count": 3, "id": "583cf3a2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "PatientId 0\n", "AppointmentID 0\n", "Gender 0\n", "ScheduledDay 0\n", "AppointmentDay 0\n", "Age 0\n", "Neighbourhood 0\n", "Scholarship 0\n", "Hipertension 0\n", "Diabetes 0\n", "Alcoholism 0\n", "Handcap 0\n", "SMS_received 0\n", "No-show 0\n", "dtype: int64" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#sum of null values\n", "data.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 4, "id": "7a36e3ab", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "np.int64(0)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# checking if there are any duplicates\n", "data.duplicated().sum()" ] }, { "cell_type": "code", "execution_count": 5, "id": "98d56db9", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PatientIdAppointmentIDAgeScholarshipHipertensionDiabetesAlcoholismHandcapSMS_received
count1.105270e+051.105270e+05110527.000000110527.000000110527.000000110527.000000110527.000000110527.000000110527.000000
mean1.474963e+145.675305e+0637.0888740.0982660.1972460.0718650.0304000.0222480.321026
std2.560949e+147.129575e+0423.1102050.2976750.3979210.2582650.1716860.1615430.466873
min3.921784e+045.030230e+06-1.0000000.0000000.0000000.0000000.0000000.0000000.000000
25%4.172614e+125.640286e+0618.0000000.0000000.0000000.0000000.0000000.0000000.000000
50%3.173184e+135.680573e+0637.0000000.0000000.0000000.0000000.0000000.0000000.000000
75%9.439172e+135.725524e+0655.0000000.0000000.0000000.0000000.0000000.0000001.000000
max9.999816e+145.790484e+06115.0000001.0000001.0000001.0000001.0000004.0000001.000000
\n", "
" ], "text/plain": [ " PatientId AppointmentID Age Scholarship \\\n", "count 1.105270e+05 1.105270e+05 110527.000000 110527.000000 \n", "mean 1.474963e+14 5.675305e+06 37.088874 0.098266 \n", "std 2.560949e+14 7.129575e+04 23.110205 0.297675 \n", "min 3.921784e+04 5.030230e+06 -1.000000 0.000000 \n", "25% 4.172614e+12 5.640286e+06 18.000000 0.000000 \n", "50% 3.173184e+13 5.680573e+06 37.000000 0.000000 \n", "75% 9.439172e+13 5.725524e+06 55.000000 0.000000 \n", "max 9.999816e+14 5.790484e+06 115.000000 1.000000 \n", "\n", " Hipertension Diabetes Alcoholism Handcap \\\n", "count 110527.000000 110527.000000 110527.000000 110527.000000 \n", "mean 0.197246 0.071865 0.030400 0.022248 \n", "std 0.397921 0.258265 0.171686 0.161543 \n", "min 0.000000 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000000 0.000000 0.000000 \n", "50% 0.000000 0.000000 0.000000 0.000000 \n", "75% 0.000000 0.000000 0.000000 0.000000 \n", "max 1.000000 1.000000 1.000000 4.000000 \n", "\n", " SMS_received \n", "count 110527.000000 \n", "mean 0.321026 \n", "std 0.466873 \n", "min 0.000000 \n", "25% 0.000000 \n", "50% 0.000000 \n", "75% 1.000000 \n", "max 1.000000 " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#statistical view of the data\n", "data.describe()" ] }, { "cell_type": "code", "execution_count": 6, "id": "67358f4f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\n", "['F', 'M']\n", "Length: 2, dtype: str" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#checking if there are unusual values\n", "data[\"Gender\"].unique()" ] }, { "cell_type": "code", "execution_count": 7, "id": "c6d7340f", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PatientIdAppointmentIDGenderScheduledDayAppointmentDayAgeNeighbourhoodScholarshipHipertensionDiabetesAlcoholismHandcapSMS_receivedNo-show
998324.659432e+145775010F2016-06-06T08:58:13Z2016-06-06T00:00:00Z-1ROMÃO000000No
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" ], "text/plain": [ " PatientId AppointmentID Gender ScheduledDay \\\n", "99832 4.659432e+14 5775010 F 2016-06-06T08:58:13Z \n", "\n", " AppointmentDay Age Neighbourhood Scholarship Hipertension \\\n", "99832 2016-06-06T00:00:00Z -1 ROMÃO 0 0 \n", "\n", " Diabetes Alcoholism Handcap SMS_received No-show \n", "99832 0 0 0 0 No " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#checking if there are unusual values\n", "data[data[\"Age\"]<0]" ] }, { "cell_type": "code", "execution_count": 8, "id": "da85772d", "metadata": {}, "outputs": [], "source": [ "#deleting the odd raw\n", "data.drop(data[data[\"Age\"] < 0].index, inplace=True)" ] }, { "cell_type": "code", "execution_count": 9, "id": "a8016c22", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PatientIdAppointmentIDGenderScheduledDayAppointmentDayAgeNeighbourhoodScholarshipHipertensionDiabetesAlcoholismHandcapSMS_receivedNo-show
580149.762948e+145651757F2016-05-03T09:14:53Z2016-05-03T00:00:00Z102CONQUISTA000000No
639123.196321e+135700278F2016-05-16T09:17:44Z2016-05-19T00:00:00Z115ANDORINHAS000010Yes
639153.196321e+135700279F2016-05-16T09:17:44Z2016-05-19T00:00:00Z115ANDORINHAS000010Yes
681273.196321e+135562812F2016-04-08T14:29:17Z2016-05-16T00:00:00Z115ANDORINHAS000010Yes
762843.196321e+135744037F2016-05-30T09:44:51Z2016-05-30T00:00:00Z115ANDORINHAS000010No
792709.739430e+125747809M2016-05-30T16:21:56Z2016-05-31T00:00:00Z100TABUAZEIRO000010No
792729.739430e+125747808M2016-05-30T16:21:56Z2016-05-31T00:00:00Z100TABUAZEIRO000010No
903722.342836e+115751563F2016-05-31T10:19:49Z2016-06-02T00:00:00Z102MARIA ORTIZ000000No
920845.578313e+135670914F2016-05-06T14:55:36Z2016-06-03T00:00:00Z100ANTÔNIO HONÓRIO000001No
976667.482346e+145717451F2016-05-19T07:57:56Z2016-06-03T00:00:00Z115SÃO JOSÉ010001No
1085063.939642e+115721152F2016-05-19T15:32:09Z2016-06-01T00:00:00Z100MARUÍPE000000No
\n", "
" ], "text/plain": [ " PatientId AppointmentID Gender ScheduledDay \\\n", "58014 9.762948e+14 5651757 F 2016-05-03T09:14:53Z \n", "63912 3.196321e+13 5700278 F 2016-05-16T09:17:44Z \n", "63915 3.196321e+13 5700279 F 2016-05-16T09:17:44Z \n", "68127 3.196321e+13 5562812 F 2016-04-08T14:29:17Z \n", "76284 3.196321e+13 5744037 F 2016-05-30T09:44:51Z \n", "79270 9.739430e+12 5747809 M 2016-05-30T16:21:56Z \n", "79272 9.739430e+12 5747808 M 2016-05-30T16:21:56Z \n", "90372 2.342836e+11 5751563 F 2016-05-31T10:19:49Z \n", "92084 5.578313e+13 5670914 F 2016-05-06T14:55:36Z \n", "97666 7.482346e+14 5717451 F 2016-05-19T07:57:56Z \n", "108506 3.939642e+11 5721152 F 2016-05-19T15:32:09Z \n", "\n", " AppointmentDay Age Neighbourhood Scholarship Hipertension \\\n", "58014 2016-05-03T00:00:00Z 102 CONQUISTA 0 0 \n", "63912 2016-05-19T00:00:00Z 115 ANDORINHAS 0 0 \n", "63915 2016-05-19T00:00:00Z 115 ANDORINHAS 0 0 \n", "68127 2016-05-16T00:00:00Z 115 ANDORINHAS 0 0 \n", "76284 2016-05-30T00:00:00Z 115 ANDORINHAS 0 0 \n", "79270 2016-05-31T00:00:00Z 100 TABUAZEIRO 0 0 \n", "79272 2016-05-31T00:00:00Z 100 TABUAZEIRO 0 0 \n", "90372 2016-06-02T00:00:00Z 102 MARIA ORTIZ 0 0 \n", "92084 2016-06-03T00:00:00Z 100 ANTÔNIO HONÓRIO 0 0 \n", "97666 2016-06-03T00:00:00Z 115 SÃO JOSÉ 0 1 \n", "108506 2016-06-01T00:00:00Z 100 MARUÍPE 0 0 \n", "\n", " Diabetes Alcoholism Handcap SMS_received No-show \n", "58014 0 0 0 0 No \n", "63912 0 0 1 0 Yes \n", "63915 0 0 1 0 Yes \n", "68127 0 0 1 0 Yes \n", "76284 0 0 1 0 No \n", "79270 0 0 1 0 No \n", "79272 0 0 1 0 No \n", "90372 0 0 0 0 No \n", "92084 0 0 0 1 No \n", "97666 0 0 0 1 No \n", "108506 0 0 0 0 No " ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# seeing if there are odd entries\n", "data[(data[\"Age\"] >= 100) & (data[\"Age\"] <= 10000000)]" ] }, { "cell_type": "code", "execution_count": 10, "id": "aaa3eee6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Index: 110526 entries, 0 to 110526\n", "Data columns (total 14 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 PatientId 110526 non-null float64\n", " 1 AppointmentID 110526 non-null int64 \n", " 2 Gender 110526 non-null str \n", " 3 ScheduledDay 110526 non-null str \n", " 4 AppointmentDay 110526 non-null str \n", " 5 Age 110526 non-null int64 \n", " 6 Neighbourhood 110526 non-null str \n", " 7 Scholarship 110526 non-null int64 \n", " 8 Hipertension 110526 non-null int64 \n", " 9 Diabetes 110526 non-null int64 \n", " 10 Alcoholism 110526 non-null int64 \n", " 11 Handcap 110526 non-null int64 \n", " 12 SMS_received 110526 non-null int64 \n", " 13 No-show 110526 non-null str \n", "dtypes: float64(1), int64(8), str(5)\n", "memory usage: 12.6 MB\n" ] } ], "source": [ "# summary of the data's structure\n", "data.info()" ] }, { "cell_type": "code", "execution_count": 11, "id": "522c9c10", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['PatientId',\n", " 'AppointmentID',\n", " 'Gender',\n", " 'ScheduledDay',\n", " 'AppointmentDay',\n", " 'Age',\n", " 'Neighbourhood',\n", " 'Scholarship',\n", " 'Hipertension',\n", " 'Diabetes',\n", " 'Alcoholism',\n", " 'Handcap',\n", " 'SMS_received',\n", " 'No-show']" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#seeing the col names\n", "list(data.columns)" ] }, { "cell_type": "code", "execution_count": 12, "id": "61c362c6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['PatientId',\n", " 'AppointmentID',\n", " 'Gender',\n", " 'ScheduledDay',\n", " 'AppointmentDay',\n", " 'Age',\n", " 'Neighbourhood',\n", " 'Scholarship',\n", " 'Hypertension',\n", " 'Diabetes',\n", " 'Alcoholism',\n", " 'Handicap',\n", " 'SMS_received',\n", " 'No_show']" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#renaming cols\n", "data.rename(columns={\"Handcap\": \"Handicap\",\"Hipertension\":\"Hypertension\",\"No-show\":\"No_show\"}, inplace=True)\n", "list(data.columns)" ] }, { "cell_type": "code", "execution_count": 13, "id": "b4f07d28", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PatientIdAppointmentIDGenderAgeNeighbourhoodScholarshipHypertensionDiabetesAlcoholismHandicapSMS_receivedNo_showScheduled_DateScheduled_TimeAppointment_Date
02.987250e+135642903F62JARDIM DA PENHA010000No2016-04-2918:38:082016-04-29
15.589978e+145642503M56JARDIM DA PENHA000000No2016-04-2916:08:272016-04-29
24.262962e+125642549F62MATA DA PRAIA000000No2016-04-2916:19:042016-04-29
38.679512e+115642828F8PONTAL DE CAMBURI000000No2016-04-2917:29:312016-04-29
48.841186e+125642494F56JARDIM DA PENHA011000No2016-04-2916:07:232016-04-29
................................................
1105222.572134e+125651768F56MARIA ORTIZ000001No2016-05-0309:15:352016-06-07
1105233.596266e+125650093F51MARIA ORTIZ000001No2016-05-0307:27:332016-06-07
1105241.557663e+135630692F21MARIA ORTIZ000001No2016-04-2716:03:522016-06-07
1105259.213493e+135630323F38MARIA ORTIZ000001No2016-04-2715:09:232016-06-07
1105263.775115e+145629448F54MARIA ORTIZ000001No2016-04-2713:30:562016-06-07
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110526 rows × 15 columns

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" ], "text/plain": [ " PatientId AppointmentID Gender Age Neighbourhood \\\n", "0 2.987250e+13 5642903 F 62 JARDIM DA PENHA \n", "1 5.589978e+14 5642503 M 56 JARDIM DA PENHA \n", "2 4.262962e+12 5642549 F 62 MATA DA PRAIA \n", "3 8.679512e+11 5642828 F 8 PONTAL DE CAMBURI \n", "4 8.841186e+12 5642494 F 56 JARDIM DA PENHA \n", "... ... ... ... ... ... \n", "110522 2.572134e+12 5651768 F 56 MARIA ORTIZ \n", "110523 3.596266e+12 5650093 F 51 MARIA ORTIZ \n", "110524 1.557663e+13 5630692 F 21 MARIA ORTIZ \n", "110525 9.213493e+13 5630323 F 38 MARIA ORTIZ \n", "110526 3.775115e+14 5629448 F 54 MARIA ORTIZ \n", "\n", " Scholarship Hypertension Diabetes Alcoholism Handicap \\\n", "0 0 1 0 0 0 \n", "1 0 0 0 0 0 \n", "2 0 0 0 0 0 \n", "3 0 0 0 0 0 \n", "4 0 1 1 0 0 \n", "... ... ... ... ... ... \n", "110522 0 0 0 0 0 \n", "110523 0 0 0 0 0 \n", "110524 0 0 0 0 0 \n", "110525 0 0 0 0 0 \n", "110526 0 0 0 0 0 \n", "\n", " SMS_received No_show Scheduled_Date Scheduled_Time Appointment_Date \n", "0 0 No 2016-04-29 18:38:08 2016-04-29 \n", "1 0 No 2016-04-29 16:08:27 2016-04-29 \n", "2 0 No 2016-04-29 16:19:04 2016-04-29 \n", "3 0 No 2016-04-29 17:29:31 2016-04-29 \n", "4 0 No 2016-04-29 16:07:23 2016-04-29 \n", "... ... ... ... ... ... \n", "110522 1 No 2016-05-03 09:15:35 2016-06-07 \n", "110523 1 No 2016-05-03 07:27:33 2016-06-07 \n", "110524 1 No 2016-04-27 16:03:52 2016-06-07 \n", "110525 1 No 2016-04-27 15:09:23 2016-06-07 \n", "110526 1 No 2016-04-27 13:30:56 2016-06-07 \n", "\n", "[110526 rows x 15 columns]" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#splitting cols and dropping unnecessary ones\n", "data['ScheduledDay'] = pd.to_datetime(data['ScheduledDay'])\n", "data['AppointmentDay'] = pd.to_datetime(data['AppointmentDay'])\n", "data['Scheduled_Date'] = data['ScheduledDay'].dt.date\n", "data['Scheduled_Time'] = data['ScheduledDay'].dt.time\n", "data['Appointment_Date'] = data['AppointmentDay'].dt.date\n", "data['Appointment_Time'] = data['AppointmentDay'].dt.time\n", "data\n", "import datetime\n", "(data[\"Appointment_Time\"] == datetime.time(0, 0, 0)).sum()\n", "data.drop([\"ScheduledDay\", \"AppointmentDay\",\"Appointment_Time\"], axis=1, inplace=True)\n", "data" ] }, { "cell_type": "code", "execution_count": 14, "id": "2eade9ee", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "np.int64(5)" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#checking for odd scheduling entries\n", "(data[\"Scheduled_Date\"] > data[\"Appointment_Date\"]).sum()" ] }, { "cell_type": "code", "execution_count": 15, "id": "fc9bc4f5", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PatientIdAppointmentIDGenderAgeNeighbourhoodScholarshipHypertensionDiabetesAlcoholismHandicapSMS_receivedNo_showScheduled_DateScheduled_TimeAppointment_Date
270337.839273e+125679978M38RESISTÊNCIA000010Yes2016-05-1010:51:532016-05-09
552267.896294e+125715660F19SANTO ANTÔNIO000010Yes2016-05-1814:50:412016-05-17
641752.425226e+135664962F22CONSOLAÇÃO000000Yes2016-05-0513:43:582016-05-04
715339.982316e+145686628F81SANTO ANTÔNIO000000Yes2016-05-1113:49:202016-05-05
723623.787482e+125655637M7TABUAZEIRO000000Yes2016-05-0406:50:572016-05-03
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" ], "text/plain": [ " PatientId AppointmentID Gender Age Neighbourhood Scholarship \\\n", "27033 7.839273e+12 5679978 M 38 RESISTÊNCIA 0 \n", "55226 7.896294e+12 5715660 F 19 SANTO ANTÔNIO 0 \n", "64175 2.425226e+13 5664962 F 22 CONSOLAÇÃO 0 \n", "71533 9.982316e+14 5686628 F 81 SANTO ANTÔNIO 0 \n", "72362 3.787482e+12 5655637 M 7 TABUAZEIRO 0 \n", "\n", " Hypertension Diabetes Alcoholism Handicap SMS_received No_show \\\n", "27033 0 0 0 1 0 Yes \n", "55226 0 0 0 1 0 Yes \n", "64175 0 0 0 0 0 Yes \n", "71533 0 0 0 0 0 Yes \n", "72362 0 0 0 0 0 Yes \n", "\n", " Scheduled_Date Scheduled_Time Appointment_Date \n", "27033 2016-05-10 10:51:53 2016-05-09 \n", "55226 2016-05-18 14:50:41 2016-05-17 \n", "64175 2016-05-05 13:43:58 2016-05-04 \n", "71533 2016-05-11 13:49:20 2016-05-05 \n", "72362 2016-05-04 06:50:57 2016-05-03 " ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#checking for odd scheduling entries\n", "data[data[\"Scheduled_Date\"] > data[\"Appointment_Date\"]]" ] }, { "cell_type": "markdown", "id": "56caa188", "metadata": {}, "source": [ "it could be that they made an appointment before but had an emergency they had to come before the appointment,\n", "but it doesn't make sense since none of them showed up" ] }, { "cell_type": "code", "execution_count": 16, "id": "74038c8e", "metadata": {}, "outputs": [], "source": [ "#dropping odd entries\n", "data.drop(data[data[\"Scheduled_Date\"] > data[\"Appointment_Date\"]].index, inplace=True)" ] }, { "cell_type": "code", "execution_count": 17, "id": "67a900b7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([0, 1, 2, 3, 4])" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#checking handicap values\n", "data[\"Handicap\"].unique()" ] }, { "cell_type": "code", "execution_count": 18, "id": "fa2d6fa1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Handicap\n", "0 108282\n", "1 2040\n", "2 183\n", "3 13\n", "4 3\n", "Name: count, dtype: int64" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# seeing if the count of numbers more than 1 are large enough to count it as number of handicaps in one person\n", "data[\"Handicap\"].value_counts()" ] }, { "cell_type": "markdown", "id": "ee585e5a", "metadata": {}, "source": [ "since in the original dataset \"Handcap : True or False\" , and it didn't mention numbers of handicaps then it is best to have it binary like the rest" ] }, { "cell_type": "code", "execution_count": 19, "id": "b32c3ae0", "metadata": {}, "outputs": [], "source": [ "# resetting the handicap values to 0 and 1 \n", "data[\"Handicap\"] = data[\"Handicap\"].apply(lambda x: 1 if x > 0 else 0)" ] }, { "cell_type": "code", "execution_count": 20, "id": "2ec2560c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Handicap\n", "0 108282\n", "1 2239\n", "Name: count, dtype: int64" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#checking if it worked\n", "data[\"Handicap\"].value_counts()" ] }, { "cell_type": "markdown", "id": "9bb9e8cd", "metadata": {}, "source": [ "-------------------" ] }, { "cell_type": "markdown", "id": "f258a279", "metadata": {}, "source": [ "#### **Problem Statement**\n", "- This analysis aims to understand the key factors that influence whether patients miss their medical appointments." ] }, { "cell_type": "code", "execution_count": 21, "id": "2b63d2d1", "metadata": {}, "outputs": [], "source": [ "# Libraries:\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import seaborn as sns" ] }, { "cell_type": "markdown", "id": "242204f2", "metadata": {}, "source": [ "1. Is there a specific gender that shows up more, and what's the no-show rate for each gender?\n" ] }, { "cell_type": "code", "execution_count": 22, "id": "e7573b83", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Females showed up: 57245 out of 71836\n", "Males showed up: 30962 out of 38685\n" ] } ], "source": [ "# Comparing the number of females and males who showed up for their appointments\n", "females_showedUp = data[(data[\"Gender\"]==\"F\") & (data[\"No_show\"]==\"No\")].shape[0]\n", "males_showedUp = data[(data[\"Gender\"]==\"M\") & (data[\"No_show\"]==\"No\")].shape[0]\n", "\n", "Total_Females = data[data[\"Gender\"]==\"F\"].shape[0]\n", "Total_Males = data[data[\"Gender\"]==\"M\"].shape[0]\n", "\n", "print(f\"Females showed up: {females_showedUp} out of {Total_Females}\")\n", "print(f\"Males showed up: {males_showedUp} out of {Total_Males}\")" ] }, { "cell_type": "code", "execution_count": 23, "id": "77a6888c", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#pie chart on Total Appointments by Gender\n", "gender_counts = data[\"Gender\"].value_counts()\n", "\n", "plt.figure(figsize=(6, 6))\n", "plt.pie(gender_counts, labels=gender_counts.index, autopct='%1.1f%%')\n", "plt.title(\"Total Appointments by Gender\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 24, "id": "bf0336ca", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#pie charts comparing the distribution of appointment attendance (No-show vs Show) by gender\n", "fig, axes = plt.subplots(1, 2, figsize=(10, 5))\n", "\n", "# Female pie\n", "female_data = data[data[\"Gender\"] == \"F\"][\"No_show\"].value_counts()\n", "axes[0].pie(female_data, labels=female_data.index, autopct='%1.1f%%')\n", "axes[0].set_title(\"Females\")\n", "\n", "# Male pie\n", "male_data = data[data[\"Gender\"] == \"M\"][\"No_show\"].value_counts()\n", "axes[1].pie(male_data, labels=male_data.index, autopct='%1.1f%%')\n", "axes[1].set_title(\"Males\")\n", "\n", "plt.suptitle(\"No-show Rate by Gender\")\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "d4f45970", "metadata": {}, "source": [ "Out of the appointments in the dataset, females account for 71,839 appointments and males for 38,687 — meaning females make up a larger share of total appointments. However, when comparing no-show rates within each gender group, females had a 20.3% no-show rate compared to 20.0% for males. This 0.3% difference is negligible, meaning gender is not a significant factor influencing whether a patient shows up to their appointment." ] }, { "cell_type": "markdown", "id": "409ce8ee", "metadata": {}, "source": [ "----------------------" ] }, { "cell_type": "markdown", "id": "33f4a798", "metadata": {}, "source": [ "2. Is there a specific age group that shows up more, and what's its no-show rate?" ] }, { "cell_type": "code", "execution_count": 25, "id": "0b1674eb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Age_Group\n", "0-9 20.7\n", "10-19 25.2\n", "20-29 24.6\n", "30-39 21.5\n", "40-49 19.9\n", "50-59 17.4\n", "60-69 14.7\n", "70-79 15.5\n", "80-89 16.0\n", "90+ 20.1\n", "Name: No_show, dtype: float64\n" ] } ], "source": [ "## Grouping ages into intervals and calculating no-show percentage for each age group\n", "bins = list(range(0, 91, 10)) + [120]\n", "labels = [f\"{i}-{i+9}\" for i in range(0, 90, 10)] + [\"90+\"]\n", "\n", "data[\"Age_Group\"] = pd.cut(data[\"Age\"], bins=bins, labels=labels, right=True)\n", "\n", "data[\"Age_Group\"].value_counts().sort_index()\n", "\n", "noshow_by_age = data.groupby(\"Age_Group\")[\"No_show\"].apply(lambda x: (x == \"Yes\").mean() * 100).round(1)\n", "print(noshow_by_age)" ] }, { "cell_type": "code", "execution_count": 26, "id": "6c94d740", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# column chart showing No-show Rate by Age Group\n", "plt.figure(figsize=(10, 6))\n", "noshow_by_age.plot(kind=\"bar\", color=\"steelblue\")\n", "\n", "plt.title(\"No-show Rate by Age Group\")\n", "plt.xlabel(\"Age Group\")\n", "plt.ylabel(\"No-show Rate (%)\")\n", "plt.xticks(rotation=45)\n", "plt.axhline(y=data[\"No_show\"].eq(\"Yes\").mean()*100, color=\"red\", linestyle=\"--\", label=\"Overall Avg\")\n", "plt.legend()\n", "plt.tight_layout()\n", "plt.show()\n", "\n" ] }, { "cell_type": "markdown", "id": "45373d3a", "metadata": {}, "source": [ "No-show rates decrease as age increases — younger patients (10-29) have the highest no-show rates (~24-25%), while older patients (50-89) have the lowest (~15-17%). This suggests older patients are more reliable in attending their appointments.\n", "\n", "Note: The 100-119 range had too few records (~11) for a reliable rate — small samples are easily skewed by individual patients (one patient alone made up 4 of the 11). These were merged into a \"90+\" category for more stable results.\n" ] }, { "cell_type": "markdown", "id": "5818b193", "metadata": {}, "source": [ "------------------------" ] }, { "cell_type": "markdown", "id": "1766513a", "metadata": {}, "source": [ "3. Does having a specific medical condition make patients more likely to attend (or miss) their appointment?" ] }, { "cell_type": "code", "execution_count": 27, "id": "fb798057", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ConditionNoShow_Rate_With_Condition%NoShow_Rate_Without_Condition%Count_has_conditionCount_no_condition
0Hypertension17.320.92180188720
1Diabetes18.020.47943102578
2Alcoholism20.120.23360107161
3Handicap18.120.22239108282
\n", "
" ], "text/plain": [ " Condition NoShow_Rate_With_Condition% NoShow_Rate_Without_Condition% \\\n", "0 Hypertension 17.3 20.9 \n", "1 Diabetes 18.0 20.4 \n", "2 Alcoholism 20.1 20.2 \n", "3 Handicap 18.1 20.2 \n", "\n", " Count_has_condition Count_no_condition \n", "0 21801 88720 \n", "1 7943 102578 \n", "2 3360 107161 \n", "3 2239 108282 " ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Comparing no-show rate and count between patients with and without different medical conditions.\n", "conditions = [\"Hypertension\", \"Diabetes\", \"Alcoholism\", \"Handicap\"]\n", "\n", "results = []\n", "for condition in conditions:\n", " has_condition = data[data[condition] == 1]\n", " no_condition = data[data[condition] == 0]\n", " \n", " noshow_rate_has_condition = (has_condition[\"No_show\"] == \"Yes\").mean() * 100\n", " noshow_rate_no_condition = (no_condition[\"No_show\"] == \"Yes\").mean() * 100\n", " \n", " results.append({\n", " \"Condition\": condition,\n", " \"NoShow_Rate_With_Condition%\": round(noshow_rate_has_condition, 1),\n", " \"NoShow_Rate_Without_Condition%\": round(noshow_rate_no_condition, 1),\n", " \"Count_has_condition\": has_condition.shape[0],\n", " \"Count_no_condition\": no_condition.shape[0]\n", " })\n", "\n", "condition_summary = pd.DataFrame(results)\n", "condition_summary" ] }, { "cell_type": "code", "execution_count": 28, "id": "dfbcbdb5", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#clustered col chart showing No-show Rate: With vs Without Each Condition\n", "x = np.arange(len(condition_summary))\n", "width = 0.35\n", "\n", "fig, ax = plt.subplots(figsize=(10, 6))\n", "ax.bar(x - width/2, condition_summary[\"NoShow_Rate_With_Condition%\"], width, label=\"Has Condition\", color=\"indianred\")\n", "ax.bar(x + width/2, condition_summary[\"NoShow_Rate_Without_Condition%\"], width, label=\"No Condition\", color=\"steelblue\")\n", "\n", "ax.set_xlabel(\"Medical Condition\")\n", "ax.set_ylabel(\"No-show Rate (%)\")\n", "ax.set_title(\"No-show Rate: With vs Without Each Condition\")\n", "ax.set_xticks(x)\n", "ax.set_xticklabels(condition_summary[\"Condition\"])\n", "ax.axhline(y=data[\"No_show\"].eq(\"Yes\").mean()*100, color=\"gray\", linestyle=\"--\", label=\"Overall Avg\")\n", "ax.legend()\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "7ebb5451", "metadata": {}, "source": [ "Patients with chronic conditions showed better attendance than those without — Hypertension (17.3% vs 20.9% no-show) and Diabetes (18.0% vs 20.4%) had the biggest gaps followed by Handicap(18.1% vs 20.2%), likely due to routine medical follow-ups. Alcoholism showed almost no effect (20.1% vs 20.2%)." ] }, { "cell_type": "markdown", "id": "0d2d7cca", "metadata": {}, "source": [ "-----------------------" ] }, { "cell_type": "markdown", "id": "36afda4b", "metadata": {}, "source": [ "4. Does receiving an SMS reminder before the appointment affect attendance?" ] }, { "cell_type": "code", "execution_count": 29, "id": "d53716ff", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "No-show count WITH SMS: 9784 (out of 35482 appointments)\n", "No-show count WITHOUT SMS: 12530 (out of 75039 appointments)\n", "No-show rate WITH SMS: 27.6%\n", "No-show rate WITHOUT SMS: 16.7%\n" ] } ], "source": [ "# Comparing no-show counts and rates between patients who received SMS reminders and those who didn't\n", "received_sms = data[data[\"SMS_received\"] == 1]\n", "no_sms = data[data[\"SMS_received\"] == 0]\n", "\n", "noshow_count_sms = (received_sms[\"No_show\"] == \"Yes\").sum()\n", "noshow_count_no_sms = (no_sms[\"No_show\"] == \"Yes\").sum()\n", "\n", "print(f\"No-show count WITH SMS: {noshow_count_sms} (out of {received_sms.shape[0]} appointments)\")\n", "print(f\"No-show count WITHOUT SMS: {noshow_count_no_sms} (out of {no_sms.shape[0]} appointments)\")\n", "\n", "noshow_rate_sms = (received_sms[\"No_show\"] == \"Yes\").mean() * 100\n", "noshow_rate_no_sms = (no_sms[\"No_show\"] == \"Yes\").mean() * 100\n", "print(f\"No-show rate WITH SMS: {noshow_rate_sms:.1f}%\")\n", "print(f\"No-show rate WITHOUT SMS: {noshow_rate_no_sms:.1f}%\")" ] }, { "cell_type": "code", "execution_count": 30, "id": "01660a33", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Bar chart comparing no-show rate percentages: SMS received vs not\n", "categories = [\"Received SMS\", \"No SMS\"]\n", "rates = [noshow_rate_sms, noshow_rate_no_sms]\n", "\n", "plt.figure(figsize=(7, 6))\n", "bars = plt.bar(categories, rates, color=[\"steelblue\", \"indianred\"])\n", "\n", "plt.xlabel(\"SMS Reminder\")\n", "plt.ylabel(\"No-show Rate (%)\")\n", "plt.title(\"No-show Rate: SMS Received vs Not\")\n", "plt.axhline(y=data[\"No_show\"].eq(\"Yes\").mean()*100, color=\"gray\", linestyle=\"--\", label=\"Overall Avg\")\n", "plt.legend()\n", "\n", "for bar in bars:\n", " height = bar.get_height()\n", " plt.text(bar.get_x() + bar.get_width()/2, height + 0.3, f\"{height:.1f}%\", ha=\"center\")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "237fe63e", "metadata": {}, "source": [ "Unexpectedly, patients who received an SMS reminder had a higher no-show rate (27.6%) than those who didn't (16.7%). This likely isn't causal — SMS reminders are probably sent for appointments booked further in advance, and longer waiting times (not the SMS itself) may be the real driver of no-shows. This should be verified against the waiting-time analysis" ] }, { "cell_type": "markdown", "id": "a03c8912", "metadata": {}, "source": [ "-----------------------" ] }, { "cell_type": "markdown", "id": "a522ad4e", "metadata": {}, "source": [ "5. Does waiting time (days between ScheduledDay and AppointmentDay) affect no-show rate " ] }, { "cell_type": "code", "execution_count": 31, "id": "0b987a63", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 110521.000000\n", "mean 10.184345\n", "std 15.255153\n", "min 0.000000\n", "25% 0.000000\n", "50% 4.000000\n", "75% 15.000000\n", "max 179.000000\n", "Name: Waiting_Days, dtype: float64" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Calculating the number of days between scheduling and appointment dates, then summarizing its statistic\n", "data[\"Waiting_Days\"] = (pd.to_datetime(data[\"Appointment_Date\"]) - pd.to_datetime(data[\"Scheduled_Date\"])).dt.days\n", "\n", "data[\"Waiting_Days\"].describe()" ] }, { "cell_type": "code", "execution_count": 32, "id": "46d455a9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Waiting_Group\n", "Same day 4.6\n", "1-7 days 24.1\n", "8-30 days 31.7\n", "31+ days 33.0\n", "Name: No_show, dtype: float64\n" ] } ], "source": [ "# Grouping patients by waiting time intervals and calculating the no-show rate for each waiting period\n", "bins = [-1, 0, 7, 30, 179]\n", "labels = [\"Same day\", \"1-7 days\", \"8-30 days\", \"31+ days\"]\n", "\n", "data[\"Waiting_Group\"] = pd.cut(data[\"Waiting_Days\"], bins=bins, labels=labels)\n", "\n", "data[\"Waiting_Group\"].value_counts().sort_index()\n", "\n", "noshow_by_waiting = data.groupby(\"Waiting_Group\")[\"No_show\"].apply(lambda x: (x == \"Yes\").mean() * 100).round(1)\n", "print(noshow_by_waiting)" ] }, { "cell_type": "code", "execution_count": 33, "id": "f471c031", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# col chart showing No-show Rate by Waiting Time\n", "plt.figure(figsize=(8, 6))\n", "bars = plt.bar(noshow_by_waiting.index, noshow_by_waiting.values, color=\"steelblue\")\n", "\n", "plt.xlabel(\"Waiting Time\")\n", "plt.ylabel(\"No-show Rate (%)\")\n", "plt.title(\"No-show Rate by Waiting Time\")\n", "plt.axhline(y=data[\"No_show\"].eq(\"Yes\").mean()*100, color=\"gray\", linestyle=\"--\", label=\"Overall Avg\")\n", "plt.legend()\n", "\n", "for bar in bars:\n", " height = bar.get_height()\n", " plt.text(bar.get_x() + bar.get_width()/2, height + 0.5, f\"{height:.1f}%\", ha=\"center\")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 34, "id": "19df28aa", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Box plot comparing waiting time differences between patients who received SMS and those who didn't\n", "sns.boxplot(x=\"SMS_received\", y=\"Waiting_Days\", data=data)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "0437a1f3", "metadata": {}, "source": [ "No-show rate rises sharply with waiting time: 4.6% for same-day appointments vs 33.0% for 31+ days — nearly 7x higher. This is the strongest pattern found so far, and it likely explains the earlier counter-intuitive SMS result (Q4): SMS reminders go to longer-wait appointments, which were already more likely to no-show regardless of the SMS itself." ] }, { "cell_type": "markdown", "id": "b2a7327d", "metadata": {}, "source": [ "---------------------------------------" ] }, { "cell_type": "markdown", "id": "798cff2d", "metadata": {}, "source": [ "6. Is there a specific neighbourhood with a higher no-show rate than others?" ] }, { "cell_type": "code", "execution_count": 35, "id": "9949674e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Neighbourhood\n", "ILHAS OCEÂNICAS DE TRINDADE 100.0\n", "SANTOS DUMONT 28.9\n", "SANTA CECÍLIA 27.5\n", "SANTA CLARA 26.5\n", "ITARARÉ 26.3\n", " ... \n", "SOLON BORGES 14.7\n", "MÁRIO CYPRESTE 14.6\n", "AEROPORTO 12.5\n", "ILHA DO BOI 8.6\n", "PARQUE INDUSTRIAL 0.0\n", "Name: No_show, Length: 81, dtype: float64\n" ] } ], "source": [ "# Calculating the percentage of missed appointments for each neighbourhood\n", "noshow_by_neighbourhood = data.groupby(\"Neighbourhood\")[\"No_show\"].apply(lambda x: (x == \"Yes\").mean() * 100).round(1)\n", "\n", "noshow_by_neighbourhood = noshow_by_neighbourhood.sort_values(ascending=False)\n", "\n", "print(noshow_by_neighbourhood)" ] }, { "cell_type": "code", "execution_count": 36, "id": "639f043c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Neighbourhood\n", "PARQUE INDUSTRIAL 1\n", "ILHAS OCEÂNICAS DE TRINDADE 2\n", "AEROPORTO 8\n", "ILHA DO FRADE 10\n", "ILHA DO BOI 35\n", " ... \n", "ITARARÉ 3514\n", "JARDIM DA PENHA 3877\n", "RESISTÊNCIA 4430\n", "MARIA ORTIZ 5805\n", "JARDIM CAMBURI 7717\n", "Name: count, Length: 81, dtype: int64" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#checking no. of appointments in ILHAS OCEÂNICAS DE TRINDADE and PARQUE INDUSTRIAL to validate extreme no-show rates (100% and 0%)\n", "data[\"Neighbourhood\"].value_counts().sort_values() " ] }, { "cell_type": "code", "execution_count": 37, "id": "0d0dc51f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Neighbourhood\n", "SANTOS DUMONT 28.9\n", "SANTA CECÍLIA 27.5\n", "SANTA CLARA 26.5\n", "ITARARÉ 26.3\n", "JESUS DE NAZARETH 24.4\n", "HORTO 24.0\n", "ILHA DO PRÍNCIPE 23.5\n", "CARATOÍRA 23.0\n", "ANDORINHAS 23.0\n", "PRAIA DO SUÁ 22.8\n", "Name: No_show, dtype: float64\n", "Neighbourhood\n", "MORADA DE CAMBURI 16.7\n", "VILA RUBIM 16.6\n", "DO QUADRO 16.5\n", "JARDIM DA PENHA 16.3\n", "SANTA MARTHA 15.8\n", "DO CABRAL 15.7\n", "DE LOURDES 15.4\n", "SOLON BORGES 14.7\n", "MÁRIO CYPRESTE 14.6\n", "ILHA DO BOI 8.6\n", "Name: No_show, dtype: float64\n" ] } ], "source": [ "# Filtering out low-frequency neighbourhoods and calculating no-show rates for reliable comparison across neighbourhoods.\n", "neighbourhood_counts = data[\"Neighbourhood\"].value_counts()\n", "valid_neighbourhoods = neighbourhood_counts[neighbourhood_counts >= 30].index\n", "\n", "filtered_data = data[data[\"Neighbourhood\"].isin(valid_neighbourhoods)]\n", "\n", "noshow_by_neighbourhood = filtered_data.groupby(\"Neighbourhood\")[\"No_show\"].apply(lambda x: (x == \"Yes\").mean() * 100).round(1)\n", "noshow_by_neighbourhood = noshow_by_neighbourhood.sort_values(ascending=False)\n", "\n", "print(noshow_by_neighbourhood.head(10))\n", "print(noshow_by_neighbourhood.tail(10))" ] }, { "cell_type": "code", "execution_count": 38, "id": "daabfbc8", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Bar chart showing No-show Rate: Top 10 vs Bottom 10 Neighbourhoods\n", "top10 = noshow_by_neighbourhood.head(10)\n", "bottom10 = noshow_by_neighbourhood.tail(10)\n", "\n", "combined = pd.concat([top10, bottom10])\n", "\n", "plt.figure(figsize=(8, 8))\n", "colors = [\"indianred\"] * 10 + [\"steelblue\"] * 10\n", "bars = plt.barh(combined.index, combined.values, color=colors)\n", "\n", "plt.xlabel(\"No-show Rate (%)\")\n", "plt.ylabel(\"Neighbourhood\")\n", "plt.title(\"No-show Rate: Top 10 vs Bottom 10 Neighbourhoods\")\n", "plt.axvline(x=data[\"No_show\"].eq(\"Yes\").mean()*100, color=\"gray\", linestyle=\"--\", label=\"Overall Avg\")\n", "plt.legend()\n", "plt.gca().invert_yaxis()\n", "\n", "for bar in bars:\n", " width = bar.get_width()\n", " plt.text(width + 0.3, bar.get_y() + bar.get_height()/2, f\"{width:.1f}%\", va=\"center\")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "58b3d216", "metadata": {}, "source": [ "No-show rates vary by neighbourhood, from 8.6% (Ilha do Boi) to 28.9% (Santos Dumont) — a moderate difference, but smaller than the waiting-time effect. The exact reason isn't clear without more local context." ] }, { "cell_type": "markdown", "id": "48919221", "metadata": {}, "source": [ "-----------------" ] }, { "cell_type": "markdown", "id": "76818839", "metadata": {}, "source": [ "7. Does having multiple medical conditions together result in a different no-show rate than having just one condition?" ] }, { "cell_type": "code", "execution_count": 39, "id": "d1240a12", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Condition_Count\n", "No conditions 20.9\n", "1 condition 17.9\n", "2 conditions 17.9\n", "3 conditions 15.4\n", "4 conditions 30.8\n", "Name: No_show, dtype: float64\n" ] } ], "source": [ "# Calculating no-show rates based on the number of medical conditions each patient has\n", "data[\"Condition_Count\"] = data[\"Hypertension\"] + data[\"Diabetes\"] + data[\"Alcoholism\"] + data[\"Handicap\"]\n", "noshow_by_count = data.groupby(\"Condition_Count\")[\"No_show\"].apply(lambda x: (x == \"Yes\").mean() * 100).round(1)\n", "\n", "noshow_by_count.index = noshow_by_count.index.map({\n", " 0: \"No conditions\",\n", " 1: \"1 condition\",\n", " 2: \"2 conditions\",\n", " 3: \"3 conditions\",\n", " 4: \"4 conditions\"\n", "})\n", "\n", "print(noshow_by_count)" ] }, { "cell_type": "code", "execution_count": 40, "id": "f61d7658", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Count\n", "Condition_Count \n", "0 84111\n", "1 18121\n", "2 7658\n", "3 618\n", "4 13\n" ] } ], "source": [ "# Counting no. of patients according to number of conditions\n", "condition_table = data[\"Condition_Count\"].value_counts().sort_index()\n", "\n", "condition_table = condition_table.rename(\"Count\").to_frame()\n", "print(condition_table)" ] }, { "cell_type": "code", "execution_count": 41, "id": "95bc7ef6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Condition_Count_Grouped\n", "No conditions 20.9\n", "1 condition 17.9\n", "2 conditions 17.9\n", "3+ conditions 15.7\n", "Name: No_show, dtype: float64\n" ] } ], "source": [ "# Merging the small 4-conditions group into 3+ and calculating no-show rates by condition count for more reliable results.\n", "data[\"Condition_Count_Grouped\"] = data[\"Condition_Count\"].replace({4: 3})\n", "\n", "data[\"Condition_Count_Grouped\"].value_counts().sort_index()\n", "\n", "noshow_by_count_grouped = data.groupby(\"Condition_Count_Grouped\")[\"No_show\"].apply(lambda x: (x == \"Yes\").mean() * 100).round(1)\n", "\n", "noshow_by_count_grouped.index = noshow_by_count_grouped.index.map({\n", " 0: \"No conditions\",\n", " 1: \"1 condition\",\n", " 2: \"2 conditions\",\n", " 3: \"3+ conditions\"\n", "})\n", "\n", "print(noshow_by_count_grouped)" ] }, { "cell_type": "code", "execution_count": 42, "id": "0c1798f6", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Collumn chart showing No-show Rate by Number of Medical Conditions\n", "plt.figure(figsize=(8, 6))\n", "bars = plt.bar(noshow_by_count_grouped.index, noshow_by_count_grouped.values, color=\"steelblue\")\n", "\n", "plt.xlabel(\"Number of Conditions\")\n", "plt.ylabel(\"No-show Rate (%)\")\n", "plt.title(\"No-show Rate by Number of Medical Conditions\")\n", "plt.axhline(y=data[\"No_show\"].eq(\"Yes\").mean()*100, color=\"gray\", linestyle=\"--\", label=\"Overall Avg\")\n", "plt.legend()\n", "\n", "for bar in bars:\n", " height = bar.get_height()\n", " plt.text(bar.get_x() + bar.get_width()/2, height + 0.3, f\"{height:.1f}%\", ha=\"center\")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "0e436a81", "metadata": {}, "source": [ "No-show rate steadily decreases as the number of conditions increases — from 20.9% (none) to 15.7% (3+ conditions). This confirms the earlier finding: patients managing more chronic conditions tend to attend more reliably, likely due to more frequent medical follow-ups." ] }, { "cell_type": "markdown", "id": "73f22723", "metadata": {}, "source": [ "----------------------------" ] }, { "cell_type": "markdown", "id": "abf0d763", "metadata": {}, "source": [ "## Conslusion" ] }, { "cell_type": "markdown", "id": "a82c0da0", "metadata": {}, "source": [ "- **Waiting time** is the strongest factor affecting no-shows; longer delays lead to higher missed appointment rates. \n", "- **Younger patients** are more likely to miss appointments, while older patients attend more consistently. \n", "- Patients with **chronic conditions** tend to show higher commitment to attending. \n", "- **SMS reminders** are associated with higher no-show rates as people who receive SMS tend to have longer waiting times\n", "- **Gender** has minimal impact on attendance behavior. \n", "- Differences across **neighbourhoods** suggest that external factors like access or location may influence attendance. \n", "\n", "**Overall:** Both operational factors (waiting time) and patient characteristics (age and health condition) play a key role in appointment attendance." ] }, { "cell_type": "markdown", "id": "4e5fc3b8", "metadata": {}, "source": [ "-------------" ] }, { "cell_type": "markdown", "id": "d3c7bc69", "metadata": {}, "source": [ "## Recommendations\n", "\n", "Based on the insights above, here are some practical recommendations to help reduce no-show rates:\n", "\n", "1. **Focus on long-wait appointments.** Waiting time had the strongest effect on no-shows (4.6% for same-day vs 33.0% for 31+ days). The clinic should prioritize follow-up reminders — or offer earlier slots — specifically for appointments booked more than 7 days in advance.\n", "\n", "2. **Redesign the SMS reminder strategy.** Since SMS reminders are mainly sent for long-wait appointments (which already have higher no-show risk), a single SMS isn't enough. Consider sending multiple reminders (e.g. one at booking, one a few days before) for appointments with long waiting periods.\n", "\n", "3. **Target younger age groups (10-29).** This group has the highest no-show rate (~24-25%). Reminder messages could be tailored to this age group's habits — e.g. app notifications or WhatsApp instead of SMS, which younger patients may engage with more.\n", "\n", "4. **Investigate high no-show neighbourhoods.** Areas like Santos Dumont and Santa Cecília (~28% no-show) may benefit from a closer look at potential access barriers — transportation, clinic distance, or local outreach — to understand and address the root cause.\n", "\n", "5. **Leverage chronic-condition follow-up systems for all patients.** Patients with chronic conditions showed better attendance, likely due to structured follow-up care. Applying similar reminder/tracking systems to patients without chronic conditions may improve their attendance too.\n", "\n", "6. **Gender-based interventions are not necessary.** Since no-show rates are nearly identical between males and females (20.3% vs 20.0%), resources are better spent on the factors above rather than gender-targeted campaigns." ] } ], "metadata": { "kernelspec": { "display_name": "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": "3.14.6" } }, "nbformat": 4, "nbformat_minor": 5 }