{ "cells": [ { "cell_type": "markdown", "id": "2bc92346", "metadata": {}, "source": [ "# Filtering\n", "\n", "## Logical Operators\n", "\n", "| Operator | What it does? |\n", "|----------|------------------------------------------------------|\n", "| `AND` | True if both conditions are true | \n", "| `OR` | True if one of two conditions is true |\n", "| `NOT` | Negate a specified condition |\n", "| `IN` | Allows for multiple OR conditions |\n", "| `NOT IN` | Negate multiple AND conditions |\n", "| `EXISTS` | True if a record exists |\n", "| `LIKE` | True if there is a string match using % |\n", "\n", "\n", "## Relational Operators\n", "Assume `a=1` and `b=1`\n", "\n", "| Relational Operators | What it does? |\n", "|----|---------------------------------------------|\n", "| = | True if a has the same value as b |\n", "| <>, != | True if a does not have the same value as b |\n", "| > | True if a is greater than b |\n", "| < | True if a is less than b |\n", "| >= | True if a is greater than or equal to b |\n", "| <= | True if a is less than or equal to b |\n", "\n", "\n", "## Conditional Evaluation \n", "\n", "```SQL\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientGender = 'Male' AND PatientDateOfBirth < '1950-01-01'\n", "ORDER BY PatientDateOfBirth\n", "```" ] }, { "cell_type": "code", "execution_count": 1, "id": "cf9269da", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 PatientIDPatientGenderPatientDateOfBirthPatientRacePatientMaritalStatusPatientLanguagePatientPopulationPercentageBelowPoverty
0DDC0BC57-7A4E-4E02-9282-177750B74FBCMale1921-03-26 14:38:51.803WhiteSingleEnglish18.410000
153B9FFDD-F80B-43BE-93CF-C34A023EE7E9Male1921-08-22 19:17:09.227WhiteDivorcedIcelandic18.170000
2DA6CECFF-DE13-4C4C-919F-64E1A2B76C9DMale1924-06-27 19:37:58.823AsianDivorcedEnglish83.750000
37C788499-7798-484B-A027-9FCDC4C0DADBMale1926-08-13 10:22:16.247WhiteMarriedEnglish11.890000
425B786AF-0F99-478C-9CFA-0EA607E45834Male1926-08-20 00:21:38.870WhiteMarriedEnglish93.600000
54C201C71-CCED-40D1-9642-F9C8C485B854Male1926-09-22 09:17:14.713African AmericanMarriedEnglish10.300000
6A0A976C8-9B30-4492-B8C4-5B25095B9192Male1931-05-26 14:54:15.847AsianSingleEnglish19.520000
71A220558-5996-43E1-AE5D-7B96180FED35Male1937-09-07 22:23:53.143AsianMarriedEnglish15.110000
821792512-2D40-4326-BEA2-A40127EB24FFMale1938-03-24 19:25:53.980WhiteSingleUnknown89.440000
9C5D09468-574F-4802-B56F-DB38F4EB1687Male1939-07-07 19:39:49.753African AmericanMarriedIcelandic10.870000
10FB909FAE-72DD-4F6F-9828-D92183DF185FMale1940-07-15 12:18:41.080WhiteSingleSpanish14.900000
11FFCDECD6-4048-4DCB-B910-1218160005B3Male1941-05-06 14:56:42.687WhiteSingleEnglish14.490000
129BBF3A51-443D-438B-9289-B98B8E0577C0Male1944-11-25 06:12:56.860WhiteMarriedEnglish16.760000
13E483DE6E-D4E6-47FD-905B-22EE86EC7ACEMale1945-11-18 04:14:31.573African AmericanSingleEnglish16.880000
14967987B9-FFEF-4776-85CF-AE05CA81F583Male1947-02-13 10:26:55.520WhiteWidowedEnglish88.660000
15FB2ABB23-C9D0-4D09-8464-49BF0B982F0FMale1947-12-28 02:45:40.547UnknownMarriedIcelandic18.080000
161A40AF35-C6D4-4D46-B475-A15D84E8A9D5Male1949-01-10 15:37:35.543WhiteMarriedEnglish11.250000
\n" ], "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientGender = 'Male' AND PatientDateOfBirth < '1950-01-01'\n", "ORDER BY PatientDateOfBirth\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "3b11d89a", "metadata": {}, "source": [ "## Using Parenthesis\n", "\n", "```SQL\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE (PatientGender = 'Male' OR PatientRace = 'White') AND PatientDateOfBirth < '1950-01-01'\n", "ORDER BY PatientDateOfBirth\n", "```" ] }, { "cell_type": "code", "execution_count": 2, "id": "0219e7a6", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 PatientIDPatientGenderPatientDateOfBirthPatientRacePatientMaritalStatusPatientLanguagePatientPopulationPercentageBelowPoverty
0DDC0BC57-7A4E-4E02-9282-177750B74FBCMale1921-03-26 14:38:51.803WhiteSingleEnglish18.410000
1C8556CC0-32FC-4CA5-A8CD-9CCF38816167Female1921-04-11 11:39:49.197WhiteMarriedEnglish18.200000
253B9FFDD-F80B-43BE-93CF-C34A023EE7E9Male1921-08-22 19:17:09.227WhiteDivorcedIcelandic18.170000
3DA6CECFF-DE13-4C4C-919F-64E1A2B76C9DMale1924-06-27 19:37:58.823AsianDivorcedEnglish83.750000
47C788499-7798-484B-A027-9FCDC4C0DADBMale1926-08-13 10:22:16.247WhiteMarriedEnglish11.890000
525B786AF-0F99-478C-9CFA-0EA607E45834Male1926-08-20 00:21:38.870WhiteMarriedEnglish93.600000
64C201C71-CCED-40D1-9642-F9C8C485B854Male1926-09-22 09:17:14.713African AmericanMarriedEnglish10.300000
781C5B13B-F6B2-4E57-9593-6E7E4C13B2CEFemale1930-05-28 02:59:42.857WhiteMarriedIcelandic19.220000
8A0A976C8-9B30-4492-B8C4-5B25095B9192Male1931-05-26 14:54:15.847AsianSingleEnglish19.520000
9FA157FA5-F488-4884-BF87-E144630D595CFemale1932-11-01 06:19:56.577WhiteSingleEnglish16.320000
10B39DC5AC-E003-4E6A-91B6-FC07625A1285Female1935-11-03 21:07:09.040WhiteMarriedEnglish15.310000
111A220558-5996-43E1-AE5D-7B96180FED35Male1937-09-07 22:23:53.143AsianMarriedEnglish15.110000
1280D356B4-F974-441F-A5F2-F95986D119A2Female1938-03-06 18:24:18.297WhiteSingleEnglish18.880000
1321792512-2D40-4326-BEA2-A40127EB24FFMale1938-03-24 19:25:53.980WhiteSingleUnknown89.440000
14C5D09468-574F-4802-B56F-DB38F4EB1687Male1939-07-07 19:39:49.753African AmericanMarriedIcelandic10.870000
15FB909FAE-72DD-4F6F-9828-D92183DF185FMale1940-07-15 12:18:41.080WhiteSingleSpanish14.900000
16FFCDECD6-4048-4DCB-B910-1218160005B3Male1941-05-06 14:56:42.687WhiteSingleEnglish14.490000
170E0EADE8-5592-4E0B-9F88-D7596E32EE08Female1942-07-13 21:15:37.517WhiteMarriedSpanish18.800000
1866154E24-D3EE-4311-89DB-6195278F9B3CFemale1944-08-26 13:03:24.297WhiteDivorcedEnglish19.490000
199BBF3A51-443D-438B-9289-B98B8E0577C0Male1944-11-25 06:12:56.860WhiteMarriedEnglish16.760000
20E250799D-F6DE-4914-ADB4-B08A6E5029B9Female1945-08-04 19:03:00.757WhiteSingleUnknown12.860000
21E483DE6E-D4E6-47FD-905B-22EE86EC7ACEMale1945-11-18 04:14:31.573African AmericanSingleEnglish16.880000
22967987B9-FFEF-4776-85CF-AE05CA81F583Male1947-02-13 10:26:55.520WhiteWidowedEnglish88.660000
23FB2ABB23-C9D0-4D09-8464-49BF0B982F0FMale1947-12-28 02:45:40.547UnknownMarriedIcelandic18.080000
241A40AF35-C6D4-4D46-B475-A15D84E8A9D5Male1949-01-10 15:37:35.543WhiteMarriedEnglish11.250000
\n" ], "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE (PatientGender = 'Male' OR PatientRace = 'White') AND PatientDateOfBirth < '1950-01-01'\n", "ORDER BY PatientDateOfBirth\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "eb31101c", "metadata": {}, "source": [ "## Using the `NOT` Operator\n", "\n", "```SQL\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE NOT (PatientGender = 'Male' OR PatientRace = 'White') AND PatientDateOfBirth < '1950-01-01'\n", "ORDER BY PatientDateOfBirth\n", "```" ] }, { "cell_type": "code", "execution_count": 3, "id": "290f3cac", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 PatientIDPatientGenderPatientDateOfBirthPatientRacePatientMaritalStatusPatientLanguagePatientPopulationPercentageBelowPoverty
00BC491C5-5A45-4067-BD11-A78BEA00D3BEFemale1921-04-18 01:56:01.807UnknownMarriedEnglish18.050000
1EA9B67E2-15F0-450B-A8A6-14F6E4AE3D12Female1930-04-08 20:59:31.057AsianSeparatedIcelandic98.400000
22A5251B1-0945-47FA-A65C-7A6381562591Female1942-01-07 16:45:33.060UnknownMarriedSpanish18.050000
3CC9CDA72-B37A-4F8F-AFE4-B08F56A183BEFemale1942-04-14 14:01:01.130AsianMarriedSpanish14.150000
46623F5D6-D581-4268-9F9B-21612FBBF7B5Female1943-02-17 15:36:13.787AsianSingleSpanish14.490000
598F593D2-8894-49BB-93B9-5A0E2CF85E2EFemale1944-07-15 19:04:11.487African AmericanMarriedEnglish9.100000
67A7332AD-88B1-4848-9356-E5260E477C59Female1944-12-01 06:30:01.543UnknownMarriedEnglish19.460000
\n" ], "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE NOT (PatientGender = 'Male' OR PatientRace = 'White') AND PatientDateOfBirth < '1950-01-01'\n", "ORDER BY PatientDateOfBirth\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "8cde68de", "metadata": {}, "source": [ "## Inequality condition\n", "\n", "```SQL\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE (PatientGender = 'Male' AND PatientRace <> 'White') AND PatientDateOfBirth < '1950-01-01'\n", "ORDER BY PatientDateOfBirth\n", "```" ] }, { "cell_type": "code", "execution_count": 4, "id": "f284311e", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 PatientIDPatientGenderPatientDateOfBirthPatientRacePatientMaritalStatusPatientLanguagePatientPopulationPercentageBelowPoverty
0DA6CECFF-DE13-4C4C-919F-64E1A2B76C9DMale1924-06-27 19:37:58.823AsianDivorcedEnglish83.750000
14C201C71-CCED-40D1-9642-F9C8C485B854Male1926-09-22 09:17:14.713African AmericanMarriedEnglish10.300000
2A0A976C8-9B30-4492-B8C4-5B25095B9192Male1931-05-26 14:54:15.847AsianSingleEnglish19.520000
31A220558-5996-43E1-AE5D-7B96180FED35Male1937-09-07 22:23:53.143AsianMarriedEnglish15.110000
4C5D09468-574F-4802-B56F-DB38F4EB1687Male1939-07-07 19:39:49.753African AmericanMarriedIcelandic10.870000
5E483DE6E-D4E6-47FD-905B-22EE86EC7ACEMale1945-11-18 04:14:31.573African AmericanSingleEnglish16.880000
6FB2ABB23-C9D0-4D09-8464-49BF0B982F0FMale1947-12-28 02:45:40.547UnknownMarriedIcelandic18.080000
\n" ], "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE (PatientGender = 'Male' AND PatientRace <> 'White') AND PatientDateOfBirth < '1950-01-01'\n", "ORDER BY PatientDateOfBirth\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "4aaac1c6", "metadata": {}, "source": [ "## Range using `BETWEEN` condition\n", "\n", "```SQL\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientDateOfBirth BETWEEN '1920-01-01' AND '1965-01-01'\n", "ORDER BY PatientDateOfBirth\n", "```" ] }, { "cell_type": "code", "execution_count": 5, "id": "36e10ff0", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { 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 PatientIDPatientGenderPatientDateOfBirthPatientRacePatientMaritalStatusPatientLanguagePatientPopulationPercentageBelowPoverty
0DDC0BC57-7A4E-4E02-9282-177750B74FBCMale1921-03-26 14:38:51.803WhiteSingleEnglish18.410000
1C8556CC0-32FC-4CA5-A8CD-9CCF38816167Female1921-04-11 11:39:49.197WhiteMarriedEnglish18.200000
20BC491C5-5A45-4067-BD11-A78BEA00D3BEFemale1921-04-18 01:56:01.807UnknownMarriedEnglish18.050000
353B9FFDD-F80B-43BE-93CF-C34A023EE7E9Male1921-08-22 19:17:09.227WhiteDivorcedIcelandic18.170000
4DA6CECFF-DE13-4C4C-919F-64E1A2B76C9DMale1924-06-27 19:37:58.823AsianDivorcedEnglish83.750000
57C788499-7798-484B-A027-9FCDC4C0DADBMale1926-08-13 10:22:16.247WhiteMarriedEnglish11.890000
625B786AF-0F99-478C-9CFA-0EA607E45834Male1926-08-20 00:21:38.870WhiteMarriedEnglish93.600000
74C201C71-CCED-40D1-9642-F9C8C485B854Male1926-09-22 09:17:14.713African AmericanMarriedEnglish10.300000
8EA9B67E2-15F0-450B-A8A6-14F6E4AE3D12Female1930-04-08 20:59:31.057AsianSeparatedIcelandic98.400000
981C5B13B-F6B2-4E57-9593-6E7E4C13B2CEFemale1930-05-28 02:59:42.857WhiteMarriedIcelandic19.220000
10A0A976C8-9B30-4492-B8C4-5B25095B9192Male1931-05-26 14:54:15.847AsianSingleEnglish19.520000
11FA157FA5-F488-4884-BF87-E144630D595CFemale1932-11-01 06:19:56.577WhiteSingleEnglish16.320000
12B39DC5AC-E003-4E6A-91B6-FC07625A1285Female1935-11-03 21:07:09.040WhiteMarriedEnglish15.310000
131A220558-5996-43E1-AE5D-7B96180FED35Male1937-09-07 22:23:53.143AsianMarriedEnglish15.110000
1480D356B4-F974-441F-A5F2-F95986D119A2Female1938-03-06 18:24:18.297WhiteSingleEnglish18.880000
1521792512-2D40-4326-BEA2-A40127EB24FFMale1938-03-24 19:25:53.980WhiteSingleUnknown89.440000
16C5D09468-574F-4802-B56F-DB38F4EB1687Male1939-07-07 19:39:49.753African AmericanMarriedIcelandic10.870000
17FB909FAE-72DD-4F6F-9828-D92183DF185FMale1940-07-15 12:18:41.080WhiteSingleSpanish14.900000
18FFCDECD6-4048-4DCB-B910-1218160005B3Male1941-05-06 14:56:42.687WhiteSingleEnglish14.490000
192A5251B1-0945-47FA-A65C-7A6381562591Female1942-01-07 16:45:33.060UnknownMarriedSpanish18.050000
20CC9CDA72-B37A-4F8F-AFE4-B08F56A183BEFemale1942-04-14 14:01:01.130AsianMarriedSpanish14.150000
210E0EADE8-5592-4E0B-9F88-D7596E32EE08Female1942-07-13 21:15:37.517WhiteMarriedSpanish18.800000
226623F5D6-D581-4268-9F9B-21612FBBF7B5Female1943-02-17 15:36:13.787AsianSingleSpanish14.490000
2398F593D2-8894-49BB-93B9-5A0E2CF85E2EFemale1944-07-15 19:04:11.487African AmericanMarriedEnglish9.100000
2466154E24-D3EE-4311-89DB-6195278F9B3CFemale1944-08-26 13:03:24.297WhiteDivorcedEnglish19.490000
259BBF3A51-443D-438B-9289-B98B8E0577C0Male1944-11-25 06:12:56.860WhiteMarriedEnglish16.760000
267A7332AD-88B1-4848-9356-E5260E477C59Female1944-12-01 06:30:01.543UnknownMarriedEnglish19.460000
27E250799D-F6DE-4914-ADB4-B08A6E5029B9Female1945-08-04 19:03:00.757WhiteSingleUnknown12.860000
28E483DE6E-D4E6-47FD-905B-22EE86EC7ACEMale1945-11-18 04:14:31.573African AmericanSingleEnglish16.880000
29967987B9-FFEF-4776-85CF-AE05CA81F583Male1947-02-13 10:26:55.520WhiteWidowedEnglish88.660000
30FB2ABB23-C9D0-4D09-8464-49BF0B982F0FMale1947-12-28 02:45:40.547UnknownMarriedIcelandic18.080000
311A40AF35-C6D4-4D46-B475-A15D84E8A9D5Male1949-01-10 15:37:35.543WhiteMarriedEnglish11.250000
32F0B53A2C-98CA-415D-B928-E3FD0E52B22AMale1950-06-20 10:31:18.337African AmericanMarriedEnglish14.870000
33B2EB15FA-5431-4804-9309-4215BDC778C0Male1951-04-13 20:14:02.953WhiteDivorcedEnglish19.410000
34D8B53AA2-7953-4477-9EA4-68400EBAAC5CMale1951-06-11 20:11:10.003African AmericanUnknownEnglish16.890000
357A025E77-7832-4F53-B9A7-09A3F98AC17EFemale1951-07-12 08:23:45.520AsianSingleEnglish16.690000
3664182B95-EB72-4E2B-BE77-8050B71498CEMale1952-01-18 19:51:12.917African AmericanSeparatedEnglish13.030000
3779A7BA2A-D35A-4CB8-A835-6BAA13B0058CFemale1952-05-03 02:30:21.563WhiteSingleSpanish16.240000
38714823AF-C52C-414C-B53B-C43EACD194C3Male1952-05-08 23:51:50.127WhiteMarriedEnglish13.230000
398AF47463-8534-4203-B210-C2290F6CE689Female1952-06-27 17:29:04.187WhiteDivorcedEnglish11.880000
409C75DF1F-9DA6-4C98-8F5B-E10BDC805ED0Female1952-07-19 13:35:56.833WhiteDivorcedEnglish88.650000
41BC44CE19-9FC5-4AC9-A296-9EBC5E3D03AEFemale1953-06-04 03:16:17.843African AmericanMarriedEnglish15.040000
4269B5D2A0-12FD-46EF-A5FF-B29C4BAFBE49Male1954-05-02 16:38:15.957WhiteMarriedEnglish18.650000
433B11D6B3-A36A-4B69-A437-C29BF425A941Female1954-05-18 10:19:19.110AsianSeparatedEnglish10.800000
449E18822E-7D13-45C7-B50E-F95CFF92BC3EMale1954-10-16 06:45:56.257UnknownSingleEnglish15.240000
45C65A4ADE-112E-49E4-B72A-0DED22C242EDMale1955-04-07 18:55:17.077WhiteMarriedEnglish19.660000
46FE0B9B59-1927-45B7-8556-E079DC1DE30AMale1955-08-23 01:01:22.260WhiteDivorcedEnglish6.480000
477548B6CF-79D9-461D-A0C5-20B861406FACMale1956-11-13 14:08:00.253WhiteMarriedIcelandic14.030000
48F00C64F8-2033-4640-80FE-F1F62CBE26A5Female1957-06-04 18:31:01.177African AmericanSingleEnglish15.720000
49C60FE675-CA52-4C55-A233-F4B27E94987FMale1957-10-30 23:26:15.303AsianMarriedSpanish12.800000
506A57AC0C-57F3-4C19-98A1-51135EFBC4FFFemale1958-07-07 16:00:19.383UnknownMarriedEnglish94.060000
51A7142B71-A144-4D56-BD14-3E966B01DB37Male1960-03-28 13:40:52.270WhiteDivorcedSpanish19.520000
52016A590E-D093-4667-A5DA-D68EA6987D93Male1960-12-06 06:37:05.640WhiteUnknownEnglish15.020000
53EEAFC0B3-B835-4D99-AB33-2F9428E54E5FFemale1961-01-08 15:19:15.490AsianUnknownEnglish18.950000
546D5DCAC1-17FE-4D7C-923B-806EFBA3E6DFMale1961-10-22 02:47:13.170AsianMarriedEnglish13.900000
5549DADA25-F2C2-42BB-8210-D78E6C7B0D48Male1962-04-08 10:18:26.263African AmericanMarriedEnglish19.500000
5665A7FBE0-EA9F-49E9-9824-D8F3AD98DAC0Female1962-11-30 06:28:33.110WhiteSeparatedSpanish17.980000
57B70E5A76-F2BC-41E4-B037-CD4D9ABA0967Male1962-12-15 01:59:01.737WhiteSingleIcelandic13.100000
58C242E3A4-E785-4DF1-A0E4-3B568DC88F2EMale1963-02-23 21:46:28.840AsianSingleSpanish7.590000
59CD2ADB1B-97F7-4EF6-BC5C-3E0EC562A06FFemale1963-04-16 08:54:08.647WhiteSingleIcelandic11.160000
602E26695A-EFB0-4C7F-9318-E3030B154E39Female1963-06-28 05:37:36.843AsianMarriedEnglish14.200000
6136775002-9EC3-4889-AD4F-80DC6855C8D8Female1963-07-16 22:16:48.477AsianSingleSpanish15.560000
622EE42DEF-37CA-4694-827E-FA4EAF882BFCMale1964-04-27 00:41:40.410WhiteMarriedEnglish18.910000
63C2CCB1AB-6633-4CB3-B4E8-157E6FB02376Female1964-05-07 10:20:37.740WhiteSingleSpanish15.980000
648D389A8C-A6D8-4447-9DDE-1A28AB4EC667Female1964-07-10 08:50:13.707AsianMarriedEnglish4.340000
\n" ], "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientDateOfBirth BETWEEN '1920-01-01' AND '1965-01-01'\n", "ORDER BY PatientDateOfBirth\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "c5fe4b41", "metadata": {}, "source": [ "## String Condition\n", "\n", "```SQL\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientID BETWEEN '2A' AND '53'\n", "ORDER BY PatientID\n", "```" ] }, { "cell_type": "code", "execution_count": 6, "id": "ac3ac0dd", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 PatientIDPatientGenderPatientDateOfBirthPatientRacePatientMaritalStatusPatientLanguagePatientPopulationPercentageBelowPoverty
02A5251B1-0945-47FA-A65C-7A6381562591Female1942-01-07 16:45:33.060UnknownMarriedSpanish18.050000
12A8772FE-61DB-483E-B6BF-6C0A74BA9C2AFemale1966-10-14 15:31:48.427AsianSingleEnglish11.150000
22E26695A-EFB0-4C7F-9318-E3030B154E39Female1963-06-28 05:37:36.843AsianMarriedEnglish14.200000
32EE42DEF-37CA-4694-827E-FA4EAF882BFCMale1964-04-27 00:41:40.410WhiteMarriedEnglish18.910000
43231F930-2978-4F50-8234-755449851E7BMale1979-05-26 04:58:10.627WhiteSingleEnglish18.360000
535FE7491-1A1D-48CB-810C-8DC2599AB3DDMale1969-11-02 06:34:34.527WhiteMarriedEnglish4.510000
636775002-9EC3-4889-AD4F-80DC6855C8D8Female1963-07-16 22:16:48.477AsianSingleSpanish15.560000
736E2F89E-777A-4D77-9D95-0D70A8AB416FMale1980-05-30 13:23:50.703African AmericanSeparatedEnglish19.360000
83B11D6B3-A36A-4B69-A437-C29BF425A941Female1954-05-18 10:19:19.110AsianSeparatedEnglish10.800000
93E462A8F-7B90-43A1-A8B6-AD82CB5002C9Female1986-12-20 16:41:34.793WhiteMarriedSpanish18.330000
1049DADA25-F2C2-42BB-8210-D78E6C7B0D48Male1962-04-08 10:18:26.263African AmericanMarriedEnglish19.500000
114C201C71-CCED-40D1-9642-F9C8C485B854Male1926-09-22 09:17:14.713African AmericanMarriedEnglish10.300000
\n" ], "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientID BETWEEN '2A' AND '53'\n", "ORDER BY PatientID\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "c8cc6da3", "metadata": {}, "source": [ "## Membership Condition\n", "\n", "```SQL\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientRace = 'White' OR PatientRace = 'Asian'\n", "ORDER BY PatientDateOfBirth\n", "```" ] }, { "cell_type": "code", "execution_count": 7, "id": "6f0da6f6", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " 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0DDC0BC57-7A4E-4E02-9282-177750B74FBCMale1921-03-26 14:38:51.803WhiteSingleEnglish18.410000
1C8556CC0-32FC-4CA5-A8CD-9CCF38816167Female1921-04-11 11:39:49.197WhiteMarriedEnglish18.200000
253B9FFDD-F80B-43BE-93CF-C34A023EE7E9Male1921-08-22 19:17:09.227WhiteDivorcedIcelandic18.170000
3DA6CECFF-DE13-4C4C-919F-64E1A2B76C9DMale1924-06-27 19:37:58.823AsianDivorcedEnglish83.750000
47C788499-7798-484B-A027-9FCDC4C0DADBMale1926-08-13 10:22:16.247WhiteMarriedEnglish11.890000
525B786AF-0F99-478C-9CFA-0EA607E45834Male1926-08-20 00:21:38.870WhiteMarriedEnglish93.600000
6EA9B67E2-15F0-450B-A8A6-14F6E4AE3D12Female1930-04-08 20:59:31.057AsianSeparatedIcelandic98.400000
781C5B13B-F6B2-4E57-9593-6E7E4C13B2CEFemale1930-05-28 02:59:42.857WhiteMarriedIcelandic19.220000
8A0A976C8-9B30-4492-B8C4-5B25095B9192Male1931-05-26 14:54:15.847AsianSingleEnglish19.520000
9FA157FA5-F488-4884-BF87-E144630D595CFemale1932-11-01 06:19:56.577WhiteSingleEnglish16.320000
10B39DC5AC-E003-4E6A-91B6-FC07625A1285Female1935-11-03 21:07:09.040WhiteMarriedEnglish15.310000
111A220558-5996-43E1-AE5D-7B96180FED35Male1937-09-07 22:23:53.143AsianMarriedEnglish15.110000
1280D356B4-F974-441F-A5F2-F95986D119A2Female1938-03-06 18:24:18.297WhiteSingleEnglish18.880000
1321792512-2D40-4326-BEA2-A40127EB24FFMale1938-03-24 19:25:53.980WhiteSingleUnknown89.440000
14FB909FAE-72DD-4F6F-9828-D92183DF185FMale1940-07-15 12:18:41.080WhiteSingleSpanish14.900000
15FFCDECD6-4048-4DCB-B910-1218160005B3Male1941-05-06 14:56:42.687WhiteSingleEnglish14.490000
16CC9CDA72-B37A-4F8F-AFE4-B08F56A183BEFemale1942-04-14 14:01:01.130AsianMarriedSpanish14.150000
170E0EADE8-5592-4E0B-9F88-D7596E32EE08Female1942-07-13 21:15:37.517WhiteMarriedSpanish18.800000
186623F5D6-D581-4268-9F9B-21612FBBF7B5Female1943-02-17 15:36:13.787AsianSingleSpanish14.490000
1966154E24-D3EE-4311-89DB-6195278F9B3CFemale1944-08-26 13:03:24.297WhiteDivorcedEnglish19.490000
209BBF3A51-443D-438B-9289-B98B8E0577C0Male1944-11-25 06:12:56.860WhiteMarriedEnglish16.760000
21E250799D-F6DE-4914-ADB4-B08A6E5029B9Female1945-08-04 19:03:00.757WhiteSingleUnknown12.860000
22967987B9-FFEF-4776-85CF-AE05CA81F583Male1947-02-13 10:26:55.520WhiteWidowedEnglish88.660000
231A40AF35-C6D4-4D46-B475-A15D84E8A9D5Male1949-01-10 15:37:35.543WhiteMarriedEnglish11.250000
24B2EB15FA-5431-4804-9309-4215BDC778C0Male1951-04-13 20:14:02.953WhiteDivorcedEnglish19.410000
257A025E77-7832-4F53-B9A7-09A3F98AC17EFemale1951-07-12 08:23:45.520AsianSingleEnglish16.690000
2679A7BA2A-D35A-4CB8-A835-6BAA13B0058CFemale1952-05-03 02:30:21.563WhiteSingleSpanish16.240000
27714823AF-C52C-414C-B53B-C43EACD194C3Male1952-05-08 23:51:50.127WhiteMarriedEnglish13.230000
288AF47463-8534-4203-B210-C2290F6CE689Female1952-06-27 17:29:04.187WhiteDivorcedEnglish11.880000
299C75DF1F-9DA6-4C98-8F5B-E10BDC805ED0Female1952-07-19 13:35:56.833WhiteDivorcedEnglish88.650000
3069B5D2A0-12FD-46EF-A5FF-B29C4BAFBE49Male1954-05-02 16:38:15.957WhiteMarriedEnglish18.650000
313B11D6B3-A36A-4B69-A437-C29BF425A941Female1954-05-18 10:19:19.110AsianSeparatedEnglish10.800000
32C65A4ADE-112E-49E4-B72A-0DED22C242EDMale1955-04-07 18:55:17.077WhiteMarriedEnglish19.660000
33FE0B9B59-1927-45B7-8556-E079DC1DE30AMale1955-08-23 01:01:22.260WhiteDivorcedEnglish6.480000
347548B6CF-79D9-461D-A0C5-20B861406FACMale1956-11-13 14:08:00.253WhiteMarriedIcelandic14.030000
35C60FE675-CA52-4C55-A233-F4B27E94987FMale1957-10-30 23:26:15.303AsianMarriedSpanish12.800000
36A7142B71-A144-4D56-BD14-3E966B01DB37Male1960-03-28 13:40:52.270WhiteDivorcedSpanish19.520000
37016A590E-D093-4667-A5DA-D68EA6987D93Male1960-12-06 06:37:05.640WhiteUnknownEnglish15.020000
38EEAFC0B3-B835-4D99-AB33-2F9428E54E5FFemale1961-01-08 15:19:15.490AsianUnknownEnglish18.950000
396D5DCAC1-17FE-4D7C-923B-806EFBA3E6DFMale1961-10-22 02:47:13.170AsianMarriedEnglish13.900000
4065A7FBE0-EA9F-49E9-9824-D8F3AD98DAC0Female1962-11-30 06:28:33.110WhiteSeparatedSpanish17.980000
41B70E5A76-F2BC-41E4-B037-CD4D9ABA0967Male1962-12-15 01:59:01.737WhiteSingleIcelandic13.100000
42C242E3A4-E785-4DF1-A0E4-3B568DC88F2EMale1963-02-23 21:46:28.840AsianSingleSpanish7.590000
43CD2ADB1B-97F7-4EF6-BC5C-3E0EC562A06FFemale1963-04-16 08:54:08.647WhiteSingleIcelandic11.160000
442E26695A-EFB0-4C7F-9318-E3030B154E39Female1963-06-28 05:37:36.843AsianMarriedEnglish14.200000
4536775002-9EC3-4889-AD4F-80DC6855C8D8Female1963-07-16 22:16:48.477AsianSingleSpanish15.560000
462EE42DEF-37CA-4694-827E-FA4EAF882BFCMale1964-04-27 00:41:40.410WhiteMarriedEnglish18.910000
47C2CCB1AB-6633-4CB3-B4E8-157E6FB02376Female1964-05-07 10:20:37.740WhiteSingleSpanish15.980000
488D389A8C-A6D8-4447-9DDE-1A28AB4EC667Female1964-07-10 08:50:13.707AsianMarriedEnglish4.340000
497FD13988-E58A-4A5C-8680-89AC200950FAMale1965-07-12 15:41:20.523WhiteMarriedSpanish12.410000
502A8772FE-61DB-483E-B6BF-6C0A74BA9C2AFemale1966-10-14 15:31:48.427AsianSingleEnglish11.150000
516985D824-3269-4D12-A9DD-B932D640E26EFemale1967-10-27 03:58:29.027WhiteMarriedEnglish12.010000
52DCE5AEB8-6DB9-4106-8AE4-02CCC5C23741Female1967-11-09 08:14:51.143WhiteSingleUnknown16.430000
5303A481F5-B32A-4A91-BD42-43EB78FEBA77Female1968-02-07 23:02:38.017AsianSingleUnknown93.230000
5456A35E74-90BE-44A0-B7BA-7743BB152133Female1968-11-09 15:29:19.557WhiteMarriedEnglish8.810000
5535FE7491-1A1D-48CB-810C-8DC2599AB3DDMale1969-11-02 06:34:34.527WhiteMarriedEnglish4.510000
56DB22A4D9-7E4D-485C-916A-9CD1386507FBFemale1970-07-25 13:04:20.717AsianMarriedEnglish6.670000
57220C8D43-1322-4A9D-B890-D426942A3649Male1971-03-13 18:31:24.877AsianMarriedEnglish16.710000
58B5D31F01-7273-4901-B56F-8139769A11EFFemale1971-04-02 18:56:59.353AsianUnknownUnknown82.080000
59135C831F-7DA5-46C0-959C-EBCBD8810B43Male1971-05-13 04:40:05.623WhiteUnknownSpanish12.380000
601A8791E3-A61C-455A-8DEE-763EB90C9B2CMale1973-08-16 10:58:34.413AsianSingleEnglish13.970000
616D8008ED-D623-4BE4-B93B-335F9797C170Female1978-03-14 13:41:28.337WhiteMarriedIcelandic14.810000
62B3892204-880B-40EF-B3BB-B824B50E99E5Male1978-08-06 08:38:27.330WhiteSingleSpanish16.860000
630681FA35-A794-4684-97BD-00B88370DB41Female1978-10-02 21:46:05.300AsianUnknownSpanish19.160000
646E70D84D-C75F-477C-BC37-9177C3698C66Male1979-01-04 05:45:29.580WhiteMarriedEnglish16.090000
653231F930-2978-4F50-8234-755449851E7BMale1979-05-26 04:58:10.627WhiteSingleEnglish18.360000
66E5478913-6819-4977-BB11-4C8B61175B56Female1980-03-21 13:08:56.867WhiteSingleEnglish12.920000
670A9BA3E4-CF3C-49C4-9774-5EEA2EE7D123Male1980-04-04 07:59:15.820WhiteSingleSpanish14.280000
683E462A8F-7B90-43A1-A8B6-AD82CB5002C9Female1986-12-20 16:41:34.793WhiteMarriedSpanish18.330000
69A50BE9B4-8A0B-4169-B894-F7BD86D7D90BFemale1987-04-18 16:31:16.333AsianDivorcedEnglish14.070000
701311FEE4-2FDC-46E4-83D3-1550A3E51D2CFemale1988-03-28 03:09:22.807WhiteSingleEnglish14.990000
718856096E-E59C-4156-A767-C091AF799C80Female1988-11-25 02:59:36.373WhiteDivorcedEnglish11.080000
\n" ], "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientRace = 'White' OR PatientRace = 'Asian'\n", "ORDER BY PatientDateOfBirth\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "88d8d80f", "metadata": {}, "source": [ "### `IN` condition\n", "```SQL\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientRace IN ('White', 'Asian')\n", "ORDER BY PatientDateOfBirth\n", "```" ] }, { "cell_type": "code", "execution_count": 8, "id": "49e85ba0", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " 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1C8556CC0-32FC-4CA5-A8CD-9CCF38816167Female1921-04-11 11:39:49.197WhiteMarriedEnglish18.200000
253B9FFDD-F80B-43BE-93CF-C34A023EE7E9Male1921-08-22 19:17:09.227WhiteDivorcedIcelandic18.170000
3DA6CECFF-DE13-4C4C-919F-64E1A2B76C9DMale1924-06-27 19:37:58.823AsianDivorcedEnglish83.750000
47C788499-7798-484B-A027-9FCDC4C0DADBMale1926-08-13 10:22:16.247WhiteMarriedEnglish11.890000
525B786AF-0F99-478C-9CFA-0EA607E45834Male1926-08-20 00:21:38.870WhiteMarriedEnglish93.600000
6EA9B67E2-15F0-450B-A8A6-14F6E4AE3D12Female1930-04-08 20:59:31.057AsianSeparatedIcelandic98.400000
781C5B13B-F6B2-4E57-9593-6E7E4C13B2CEFemale1930-05-28 02:59:42.857WhiteMarriedIcelandic19.220000
8A0A976C8-9B30-4492-B8C4-5B25095B9192Male1931-05-26 14:54:15.847AsianSingleEnglish19.520000
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111A220558-5996-43E1-AE5D-7B96180FED35Male1937-09-07 22:23:53.143AsianMarriedEnglish15.110000
1280D356B4-F974-441F-A5F2-F95986D119A2Female1938-03-06 18:24:18.297WhiteSingleEnglish18.880000
1321792512-2D40-4326-BEA2-A40127EB24FFMale1938-03-24 19:25:53.980WhiteSingleUnknown89.440000
14FB909FAE-72DD-4F6F-9828-D92183DF185FMale1940-07-15 12:18:41.080WhiteSingleSpanish14.900000
15FFCDECD6-4048-4DCB-B910-1218160005B3Male1941-05-06 14:56:42.687WhiteSingleEnglish14.490000
16CC9CDA72-B37A-4F8F-AFE4-B08F56A183BEFemale1942-04-14 14:01:01.130AsianMarriedSpanish14.150000
170E0EADE8-5592-4E0B-9F88-D7596E32EE08Female1942-07-13 21:15:37.517WhiteMarriedSpanish18.800000
186623F5D6-D581-4268-9F9B-21612FBBF7B5Female1943-02-17 15:36:13.787AsianSingleSpanish14.490000
1966154E24-D3EE-4311-89DB-6195278F9B3CFemale1944-08-26 13:03:24.297WhiteDivorcedEnglish19.490000
209BBF3A51-443D-438B-9289-B98B8E0577C0Male1944-11-25 06:12:56.860WhiteMarriedEnglish16.760000
21E250799D-F6DE-4914-ADB4-B08A6E5029B9Female1945-08-04 19:03:00.757WhiteSingleUnknown12.860000
22967987B9-FFEF-4776-85CF-AE05CA81F583Male1947-02-13 10:26:55.520WhiteWidowedEnglish88.660000
231A40AF35-C6D4-4D46-B475-A15D84E8A9D5Male1949-01-10 15:37:35.543WhiteMarriedEnglish11.250000
24B2EB15FA-5431-4804-9309-4215BDC778C0Male1951-04-13 20:14:02.953WhiteDivorcedEnglish19.410000
257A025E77-7832-4F53-B9A7-09A3F98AC17EFemale1951-07-12 08:23:45.520AsianSingleEnglish16.690000
2679A7BA2A-D35A-4CB8-A835-6BAA13B0058CFemale1952-05-03 02:30:21.563WhiteSingleSpanish16.240000
27714823AF-C52C-414C-B53B-C43EACD194C3Male1952-05-08 23:51:50.127WhiteMarriedEnglish13.230000
288AF47463-8534-4203-B210-C2290F6CE689Female1952-06-27 17:29:04.187WhiteDivorcedEnglish11.880000
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701311FEE4-2FDC-46E4-83D3-1550A3E51D2CFemale1988-03-28 03:09:22.807WhiteSingleEnglish14.990000
718856096E-E59C-4156-A767-C091AF799C80Female1988-11-25 02:59:36.373WhiteDivorcedEnglish11.080000
\n" ], "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientRace IN ('White', 'Asian')\n", "ORDER BY PatientDateOfBirth\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "0544b28a", "metadata": {}, "source": [ "### `NOT IN` condition\n", "```SQL\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientRace NOT IN ('White', 'Asian')\n", "ORDER BY PatientDateOfBirth\n", "```" ] }, { "cell_type": "code", "execution_count": 9, "id": "e92bd9d7", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 PatientIDPatientGenderPatientDateOfBirthPatientRacePatientMaritalStatusPatientLanguagePatientPopulationPercentageBelowPoverty
00BC491C5-5A45-4067-BD11-A78BEA00D3BEFemale1921-04-18 01:56:01.807UnknownMarriedEnglish18.050000
14C201C71-CCED-40D1-9642-F9C8C485B854Male1926-09-22 09:17:14.713African AmericanMarriedEnglish10.300000
2C5D09468-574F-4802-B56F-DB38F4EB1687Male1939-07-07 19:39:49.753African AmericanMarriedIcelandic10.870000
32A5251B1-0945-47FA-A65C-7A6381562591Female1942-01-07 16:45:33.060UnknownMarriedSpanish18.050000
498F593D2-8894-49BB-93B9-5A0E2CF85E2EFemale1944-07-15 19:04:11.487African AmericanMarriedEnglish9.100000
57A7332AD-88B1-4848-9356-E5260E477C59Female1944-12-01 06:30:01.543UnknownMarriedEnglish19.460000
6E483DE6E-D4E6-47FD-905B-22EE86EC7ACEMale1945-11-18 04:14:31.573African AmericanSingleEnglish16.880000
7FB2ABB23-C9D0-4D09-8464-49BF0B982F0FMale1947-12-28 02:45:40.547UnknownMarriedIcelandic18.080000
8F0B53A2C-98CA-415D-B928-E3FD0E52B22AMale1950-06-20 10:31:18.337African AmericanMarriedEnglish14.870000
9D8B53AA2-7953-4477-9EA4-68400EBAAC5CMale1951-06-11 20:11:10.003African AmericanUnknownEnglish16.890000
1064182B95-EB72-4E2B-BE77-8050B71498CEMale1952-01-18 19:51:12.917African AmericanSeparatedEnglish13.030000
11BC44CE19-9FC5-4AC9-A296-9EBC5E3D03AEFemale1953-06-04 03:16:17.843African AmericanMarriedEnglish15.040000
129E18822E-7D13-45C7-B50E-F95CFF92BC3EMale1954-10-16 06:45:56.257UnknownSingleEnglish15.240000
13F00C64F8-2033-4640-80FE-F1F62CBE26A5Female1957-06-04 18:31:01.177African AmericanSingleEnglish15.720000
146A57AC0C-57F3-4C19-98A1-51135EFBC4FFFemale1958-07-07 16:00:19.383UnknownMarriedEnglish94.060000
1549DADA25-F2C2-42BB-8210-D78E6C7B0D48Male1962-04-08 10:18:26.263African AmericanMarriedEnglish19.500000
1680AC01B2-BD55-4BE0-A59A-4024104CF4E9Female1965-05-14 15:25:09.740African AmericanMarriedEnglish19.740000
17A19A0B00-4C9A-4206-B1FE-17E6DA3CEB0BFemale1967-07-01 01:44:24.907UnknownMarriedEnglish17.840000
18EA7C2F0F-DA1C-4CE8-9700-4BB1FC7AF3FBMale1969-01-05 00:15:09.627UnknownMarriedEnglish3.300000
19886B5885-1EE2-49F3-98D5-A2F02EB8A9D4Female1970-04-27 09:15:11.080UnknownMarriedEnglish10.350000
20C54B5AAD-98E8-472D-BAA0-638D9F3BD024Female1972-11-13 22:50:43.600African AmericanSingleUnknown94.000000
2169CC25ED-A54A-4BAF-97E3-774BB3C9DED1Female1974-10-13 14:51:28.997UnknownMarriedEnglish17.720000
22DB92CDC6-FA9B-4492-BC2C-0C588AD78956Male1977-06-30 01:46:05.467UnknownSingleIcelandic1.700000
23868E700E-3C56-458F-A477-078D671DCB20Female1978-09-21 15:29:44.770African AmericanMarriedIcelandic5.940000
2436E2F89E-777A-4D77-9D95-0D70A8AB416FMale1980-05-30 13:23:50.703African AmericanSeparatedEnglish19.360000
25672D554B-D6D1-40B2-A6A4-21A4CB6B1AA6Male1983-06-17 04:46:13.753African AmericanSingleIcelandic11.040000
26CC12B481-B516-455B-884F-4CA900B29F2EFemale1985-10-21 07:59:04.777UnknownDivorcedEnglish14.580000
27B7E9FC4C-5182-4A34-954E-CEF5FC07E96DFemale1985-12-11 02:48:16.907UnknownSingleEnglish11.430000
\n" ], "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientRace NOT IN ('White', 'Asian')\n", "ORDER BY PatientDateOfBirth\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "340da73d", "metadata": {}, "source": [ "### Using subqueries\n", "```SQL\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientID IN (SELECT PatientID FROM PatientCorePopulatedTable WHERE PatientDateOfBirth > '1980-01-01')\n", "ORDER BY PatientDateOfBirth\n", "```" ] }, { "cell_type": "code", "execution_count": 10, "id": "ffb38c78", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 PatientIDPatientGenderPatientDateOfBirthPatientRacePatientMaritalStatusPatientLanguagePatientPopulationPercentageBelowPoverty
0E5478913-6819-4977-BB11-4C8B61175B56Female1980-03-21 13:08:56.867WhiteSingleEnglish12.920000
10A9BA3E4-CF3C-49C4-9774-5EEA2EE7D123Male1980-04-04 07:59:15.820WhiteSingleSpanish14.280000
236E2F89E-777A-4D77-9D95-0D70A8AB416FMale1980-05-30 13:23:50.703African AmericanSeparatedEnglish19.360000
3672D554B-D6D1-40B2-A6A4-21A4CB6B1AA6Male1983-06-17 04:46:13.753African AmericanSingleIcelandic11.040000
4CC12B481-B516-455B-884F-4CA900B29F2EFemale1985-10-21 07:59:04.777UnknownDivorcedEnglish14.580000
5B7E9FC4C-5182-4A34-954E-CEF5FC07E96DFemale1985-12-11 02:48:16.907UnknownSingleEnglish11.430000
63E462A8F-7B90-43A1-A8B6-AD82CB5002C9Female1986-12-20 16:41:34.793WhiteMarriedSpanish18.330000
7A50BE9B4-8A0B-4169-B894-F7BD86D7D90BFemale1987-04-18 16:31:16.333AsianDivorcedEnglish14.070000
81311FEE4-2FDC-46E4-83D3-1550A3E51D2CFemale1988-03-28 03:09:22.807WhiteSingleEnglish14.990000
98856096E-E59C-4156-A767-C091AF799C80Female1988-11-25 02:59:36.373WhiteDivorcedEnglish11.080000
\n" ], "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM PatientCorePopulatedTable\n", "WHERE PatientID IN (SELECT PatientID FROM PatientCorePopulatedTable WHERE PatientDateOfBirth > '1980-01-01')\n", "ORDER BY PatientDateOfBirth\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "c539ecc5", "metadata": {}, "source": [ "## Using Wildcards\n", "\n", "```SQL\n", "SELECT *\n", "FROM AdmissionsDiagnosesCorePopulatedTable\n", "WHERE PrimaryDiagnosisCode LIKE 'M%'\n", "ORDER BY PrimaryDiagnosisCode\n", "```" ] }, { "cell_type": "code", "execution_count": 11, "id": "c3e32953", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": 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 PatientIDAdmissionIDPrimaryDiagnosisCodePrimaryDiagnosisDescription
080AC01B2-BD55-4BE0-A59A-4024104CF4E92M01.XDirect infection of joint in infectious and parasitic diseases classified elsewhere
14C201C71-CCED-40D1-9642-F9C8C485B8545M01.X1Direct infection of shoulder joint in infectious and parasitic diseases classified elsewhere
225B786AF-0F99-478C-9CFA-0EA607E458341M01.X5Direct infection of hip in infectious and parasitic diseases classified elsewhere
321792512-2D40-4326-BEA2-A40127EB24FF4M01.X72Direct infection of left ankle and foot in infectious and parasitic diseases classified elsewhere
4DA6CECFF-DE13-4C4C-919F-64E1A2B76C9D2M02.35Reiter's disease, hip
525B786AF-0F99-478C-9CFA-0EA607E458347M02.352Reiter's disease, left hip
66623F5D6-D581-4268-9F9B-21612FBBF7B54M02.352Reiter's disease, left hip
7EA7C2F0F-DA1C-4CE8-9700-4BB1FC7AF3FB1M02.37Reiter's disease, ankle and foot
80681FA35-A794-4684-97BD-00B88370DB412M02.38Reiter's disease, vertebrae
92A8772FE-61DB-483E-B6BF-6C0A74BA9C2A2M05.13Rheumatoid lung disease with rheumatoid arthritis of wrist
10A7142B71-A144-4D56-BD14-3E966B01DB373M05.132Rheumatoid lung disease with rheumatoid arthritis of left wrist
11135C831F-7DA5-46C0-959C-EBCBD8810B435M05.17Rheumatoid lung disease with rheumatoid arthritis of ankle and foot
122A5251B1-0945-47FA-A65C-7A63815625913M05.23Rheumatoid vasculitis with rheumatoid arthritis of wrist
13EEAFC0B3-B835-4D99-AB33-2F9428E54E5F1M05.25Rheumatoid vasculitis with rheumatoid arthritis of hip
14E483DE6E-D4E6-47FD-905B-22EE86EC7ACE3M05.252Rheumatoid vasculitis with rheumatoid arthritis of left hip
157548B6CF-79D9-461D-A0C5-20B861406FAC1M05.261Rheumatoid vasculitis with rheumatoid arthritis of right knee
16C65A4ADE-112E-49E4-B72A-0DED22C242ED1M05.27Rheumatoid vasculitis with rheumatoid arthritis of ankle and foot
17FB2ABB23-C9D0-4D09-8464-49BF0B982F0F1M05.272Rheumatoid vasculitis with rheumatoid arthritis of left ankle and foot
18B39DC5AC-E003-4E6A-91B6-FC07625A12855M05.441Rheumatoid myopathy with rheumatoid arthritis of right hand
197A025E77-7832-4F53-B9A7-09A3F98AC17E1M05.442Rheumatoid myopathy with rheumatoid arthritis of left hand
200E0EADE8-5592-4E0B-9F88-D7596E32EE082M05.49Rheumatoid myopathy with rheumatoid arthritis of multiple sites
2169B5D2A0-12FD-46EF-A5FF-B29C4BAFBE492M05.5Rheumatoid polyneuropathy with rheumatoid arthritis
2280AC01B2-BD55-4BE0-A59A-4024104CF4E95M05.51Rheumatoid polyneuropathy with rheumatoid arthritis of shoulder
237548B6CF-79D9-461D-A0C5-20B861406FAC3M05.511Rheumatoid polyneuropathy with rheumatoid arthritis of right shoulder
2480D356B4-F974-441F-A5F2-F95986D119A26M05.561Rheumatoid polyneuropathy with rheumatoid arthritis of right knee
25EEAFC0B3-B835-4D99-AB33-2F9428E54E5F2M05.59Rheumatoid polyneuropathy with rheumatoid arthritis of multiple sites
26B2EB15FA-5431-4804-9309-4215BDC778C01M05.722Rheumatoid arthritis with rheumatoid factor of left elbow without organ or systems involvement
27FA157FA5-F488-4884-BF87-E144630D595C1M05.732Rheumatoid arthritis with rheumatoid factor of left wrist without organ or systems involvement
2835FE7491-1A1D-48CB-810C-8DC2599AB3DD3M05.741Rheumatoid arthritis with rheumatoid factor of right hand without organ or systems involvement
29967987B9-FFEF-4776-85CF-AE05CA81F5831M05.742Rheumatoid arthritis with rheumatoid factor of left hand without organ or systems involvement
3025B786AF-0F99-478C-9CFA-0EA607E458344M05.75Rheumatoid arthritis with rheumatoid factor of hip without organ or systems involvement
31886B5885-1EE2-49F3-98D5-A2F02EB8A9D41M05.752Rheumatoid arthritis with rheumatoid factor of left hip without organ or systems involvement
32B39DC5AC-E003-4E6A-91B6-FC07625A12851M06.041Rheumatoid arthritis without rheumatoid factor, right hand
33E483DE6E-D4E6-47FD-905B-22EE86EC7ACE4M06.051Rheumatoid arthritis without rheumatoid factor, right hip
3498F593D2-8894-49BB-93B9-5A0E2CF85E2E5M06.2Rheumatoid bursitis
35A19A0B00-4C9A-4206-B1FE-17E6DA3CEB0B3M06.222Rheumatoid bursitis, left elbow
367FD13988-E58A-4A5C-8680-89AC200950FA3M06.25Rheumatoid bursitis, hip
37E250799D-F6DE-4914-ADB4-B08A6E5029B91M06.31Rheumatoid nodule, shoulder
38FA157FA5-F488-4884-BF87-E144630D595C2M06.34Rheumatoid nodule, hand
39DB22A4D9-7E4D-485C-916A-9CD1386507FB1M06.361Rheumatoid nodule, right knee
40C8556CC0-32FC-4CA5-A8CD-9CCF388161673M06.37Rheumatoid nodule, ankle and foot
4135FE7491-1A1D-48CB-810C-8DC2599AB3DD1M10.31Gout due to renal impairment, shoulder
4221792512-2D40-4326-BEA2-A40127EB24FF6M10.322Gout due to renal impairment, left elbow
43CC12B481-B516-455B-884F-4CA900B29F2E1M10.361Gout due to renal impairment, right knee
44868E700E-3C56-458F-A477-078D671DCB201M10.37Gout due to renal impairment, ankle and foot
45CD2ADB1B-97F7-4EF6-BC5C-3E0EC562A06F2M10.38Gout due to renal impairment, vertebrae
46BC44CE19-9FC5-4AC9-A296-9EBC5E3D03AE3M11.05Hydroxyapatite deposition disease, hip
47D8B53AA2-7953-4477-9EA4-68400EBAAC5C5M11.052Hydroxyapatite deposition disease, left hip
4879A7BA2A-D35A-4CB8-A835-6BAA13B0058C1M11.071Hydroxyapatite deposition disease, right ankle and foot
4981C5B13B-F6B2-4E57-9593-6E7E4C13B2CE2M11.072Hydroxyapatite deposition disease, left ankle and foot
5081C5B13B-F6B2-4E57-9593-6E7E4C13B2CE5M12.111Kaschin-Beck disease, right shoulder
51220C8D43-1322-4A9D-B890-D426942A36494M12.161Kaschin-Beck disease, right knee
527A025E77-7832-4F53-B9A7-09A3F98AC17E4M12.162Kaschin-Beck disease, left knee
5381C5B13B-F6B2-4E57-9593-6E7E4C13B2CE4M12.162Kaschin-Beck disease, left knee
54B39DC5AC-E003-4E6A-91B6-FC07625A12853M1A.352Chronic gout due to renal impairment, left hip
55A7142B71-A144-4D56-BD14-3E966B01DB371M24.22Disorder of ligament, elbow
5636775002-9EC3-4889-AD4F-80DC6855C8D82M24.242Disorder of ligament, left hand
57A0A976C8-9B30-4492-B8C4-5B25095B91921M24.251Disorder of ligament, right hip
5836775002-9EC3-4889-AD4F-80DC6855C8D85M24.272Disorder of ligament, left ankle
596985D824-3269-4D12-A9DD-B932D640E26E2M26.6Temporomandibular joint disorders
606D5DCAC1-17FE-4D7C-923B-806EFBA3E6DF3M49.84Spondylopathy in diseases classified elsewhere, thoracic region
61135C831F-7DA5-46C0-959C-EBCBD8810B432M49.87Spondylopathy in diseases classified elsewhere, lumbosacral region
626A57AC0C-57F3-4C19-98A1-51135EFBC4FF3M51Thoracic, thoracolumbar, and lumbosacral intervertebral disc disorders
63220C8D43-1322-4A9D-B890-D426942A36491M63Disorders of muscle in diseases classified elsewhere
6425B786AF-0F99-478C-9CFA-0EA607E458342M63.831Disorders of muscle in diseases classified elsewhere, right forearm
654C201C71-CCED-40D1-9642-F9C8C485B8541M63.832Disorders of muscle in diseases classified elsewhere, left forearm
66CC9CDA72-B37A-4F8F-AFE4-B08F56A183BE2M63.851Disorders of muscle in diseases classified elsewhere, right thigh
67220C8D43-1322-4A9D-B890-D426942A36492M72Fibroblastic disorders
682A5251B1-0945-47FA-A65C-7A63815625914M84Disorder of continuity of bone
690E0EADE8-5592-4E0B-9F88-D7596E32EE083M84.51Pathological fracture in neoplastic disease, shoulder
70E5478913-6819-4977-BB11-4C8B61175B562M84.552Pathological fracture in neoplastic disease, left femur
71A0A976C8-9B30-4492-B8C4-5B25095B91924M90Osteopathies in diseases classified elsewhere
726D5DCAC1-17FE-4D7C-923B-806EFBA3E6DF1M90.51Osteonecrosis in diseases classified elsewhere, shoulder
73967987B9-FFEF-4776-85CF-AE05CA81F5834M90.511Osteonecrosis in diseases classified elsewhere, right shoulder
748AF47463-8534-4203-B210-C2290F6CE6892M90.522Osteonecrosis in diseases classified elsewhere, left upper arm
751A40AF35-C6D4-4D46-B475-A15D84E8A9D55M90.53Osteonecrosis in diseases classified elsewhere, forearm
769E18822E-7D13-45C7-B50E-F95CFF92BC3E2M90.6Osteitis deformans in neoplastic diseases
778856096E-E59C-4156-A767-C091AF799C801M90.6Osteitis deformans in neoplastic diseases
78135C831F-7DA5-46C0-959C-EBCBD8810B434M90.632Osteitis deformans in neoplastic diseases, left forearm
7921792512-2D40-4326-BEA2-A40127EB24FF3M90.642Osteitis deformans in neoplastic diseases, left hand
80C60FE675-CA52-4C55-A233-F4B27E94987F3M90.86Osteopathy in diseases classified elsewhere, lower leg
\n" ], "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM AdmissionsDiagnosesCorePopulatedTable\n", "WHERE PrimaryDiagnosisCode LIKE 'M%'\n", "ORDER BY PrimaryDiagnosisCode\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "da25556f", "metadata": {}, "source": [ "```SQL\n", "SELECT *\n", "FROM AdmissionsDiagnosesCorePopulatedTable\n", "WHERE PrimaryDiagnosisCode LIKE '%4'\n", "ORDER BY PrimaryDiagnosisCode\n", "```" ] }, { "cell_type": "code", "execution_count": 12, "id": "0b106085", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 PatientIDAdmissionIDPrimaryDiagnosisCodePrimaryDiagnosisDescription
0868E700E-3C56-458F-A477-078D671DCB202B33.4Hantavirus (cardio)-pulmonary syndrome [HPS] [HCPS]
166154E24-D3EE-4311-89DB-6195278F9B3C4B97.34Human T-cell lymphotrophic virus, type II [HTLV-II] as the cause of diseases classified elsewhere
2DA6CECFF-DE13-4C4C-919F-64E1A2B76C9D3C71.4Malignant neoplasm of occipital lobe
36E70D84D-C75F-477C-BC37-9177C3698C662D13.4Benign neoplasm of liver
479A7BA2A-D35A-4CB8-A835-6BAA13B0058C3D14Benign neoplasm of middle ear and respiratory system
56D8008ED-D623-4BE4-B93B-335F9797C1703D41.4Neoplasm of uncertain behavior of bladder
635FE7491-1A1D-48CB-810C-8DC2599AB3DD2D48.4Neoplasm of uncertain behavior of peritoneum
725B786AF-0F99-478C-9CFA-0EA607E458345E08.64Diabetes mellitus due to underlying condition with hypoglycemia
8016A590E-D093-4667-A5DA-D68EA6987D932E11.64Type 2 diabetes mellitus with hypoglycemia
9EA9B67E2-15F0-450B-A8A6-14F6E4AE3D121E72.4Disorders of ornithine metabolism
10CC12B481-B516-455B-884F-4CA900B29F2E2E87.4Mixed disorder of acid-base balance
110A9BA3E4-CF3C-49C4-9774-5EEA2EE7D1231F31.4Bipolar disorder, current episode depressed, severe, without psychotic features
1264182B95-EB72-4E2B-BE77-8050B71498CE2F45.4Pain disorders related to psychological factors
1380D356B4-F974-441F-A5F2-F95986D119A21H34Retinal vascular occlusions
1481C5B13B-F6B2-4E57-9593-6E7E4C13B2CE1I25.84Coronary atherosclerosis due to calcified coronary lesion
15220C8D43-1322-4A9D-B890-D426942A36493J14Pneumonia due to Hemophilus influenzae
1680D356B4-F974-441F-A5F2-F95986D119A22K50.014Crohn's disease of small intestine with abscess
17FA157FA5-F488-4884-BF87-E144630D595C2M06.34Rheumatoid nodule, hand
186D5DCAC1-17FE-4D7C-923B-806EFBA3E6DF3M49.84Spondylopathy in diseases classified elsewhere, thoracic region
192A5251B1-0945-47FA-A65C-7A63815625914M84Disorder of continuity of bone
20F0B53A2C-98CA-415D-B928-E3FD0E52B22A3N18.4Chronic kidney disease, stage 4 (severe)
2153B9FFDD-F80B-43BE-93CF-C34A023EE7E92Q60.4Renal hypoplasia, bilateral
223B11D6B3-A36A-4B69-A437-C29BF425A9412T82.4Mechanical complication of vascular dialysis catheter
\n" ], "text/plain": [ "" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM AdmissionsDiagnosesCorePopulatedTable\n", "WHERE PrimaryDiagnosisCode LIKE '%4'\n", "ORDER BY PrimaryDiagnosisCode\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "d95ea2c3", "metadata": {}, "source": [ "```SQL\n", "SELECT *\n", "FROM AdmissionsDiagnosesCorePopulatedTable\n", "WHERE PrimaryDiagnosisCode LIKE '%5.%'\n", "ORDER BY PrimaryDiagnosisCode\n", "```" ] }, { "cell_type": "code", "execution_count": 13, "id": "8b572a60", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 PatientIDAdmissionIDPrimaryDiagnosisCodePrimaryDiagnosisDescription
0967987B9-FFEF-4776-85CF-AE05CA81F5832B95.1Streptococcus, group B, as the cause of diseases classified elsewhere
1DDC0BC57-7A4E-4E02-9282-177750B74FBC2B95.62Methicillin resistant Staphylococcus aureus infection as the cause of diseases classified elsewhere
2DDC0BC57-7A4E-4E02-9282-177750B74FBC3C05.1Malignant neoplasm of soft palate
31A8791E3-A61C-455A-8DEE-763EB90C9B2C3C15.8Malignant neoplasm of overlapping sites of esophagus
40BC491C5-5A45-4067-BD11-A78BEA00D3BE1C75.1Malignant neoplasm of pituitary gland
5FE0B9B59-1927-45B7-8556-E079DC1DE30A3C75.3Malignant neoplasm of pineal gland
669B5D2A0-12FD-46EF-A5FF-B29C4BAFBE493D15.0Benign neoplasm of thymus
7C65A4ADE-112E-49E4-B72A-0DED22C242ED3D35.2Benign neoplasm of pituitary gland
87FD13988-E58A-4A5C-8680-89AC200950FA1D35.5Benign neoplasm of carotid body
98AF47463-8534-4203-B210-C2290F6CE6895D55.2Anemia due to disorders of glycolytic enzymes
107548B6CF-79D9-461D-A0C5-20B861406FAC2E75.01Sandhoff disease
110BC491C5-5A45-4067-BD11-A78BEA00D3BE2F25.0Schizoaffective disorder, bipolar type
1264182B95-EB72-4E2B-BE77-8050B71498CE2F45.4Pain disorders related to psychological factors
13A19A0B00-4C9A-4206-B1FE-17E6DA3CEB0B2F45.41Pain disorder exclusively related to psychological factors
142A5251B1-0945-47FA-A65C-7A63815625916F95.1Chronic motor or vocal tic disorder
15DB92CDC6-FA9B-4492-BC2C-0C588AD789561H75.01Mastoiditis in infectious and parasitic diseases classified elsewhere, right ear
16B2EB15FA-5431-4804-9309-4215BDC778C02H75.03Mastoiditis in infectious and parasitic diseases classified elsewhere, bilateral
17C54B5AAD-98E8-472D-BAA0-638D9F3BD0242I15.2Hypertension secondary to endocrine disorders
18135C831F-7DA5-46C0-959C-EBCBD8810B433I25.10Atherosclerotic heart disease of native coronary artery without angina pectoris
19CC9CDA72-B37A-4F8F-AFE4-B08F56A183BE1I25.110Atherosclerotic heart disease of native coronary artery with unstable angina pectoris
2053B9FFDD-F80B-43BE-93CF-C34A023EE7E94I25.711Atherosclerosis of autologous vein coronary artery bypass graft(s) with angina pectoris with documented spasm
2169B5D2A0-12FD-46EF-A5FF-B29C4BAFBE495I25.75Atherosclerosis of native coronary artery of transplanted heart with angina pectoris
22016A590E-D093-4667-A5DA-D68EA6987D933I25.812Atherosclerosis of bypass graft of coronary artery of transplanted heart without angina pectoris
236985D824-3269-4D12-A9DD-B932D640E26E1I25.82Chronic total occlusion of coronary artery
2481C5B13B-F6B2-4E57-9593-6E7E4C13B2CE1I25.84Coronary atherosclerosis due to calcified coronary lesion
252A8772FE-61DB-483E-B6BF-6C0A74BA9C2A2M05.13Rheumatoid lung disease with rheumatoid arthritis of wrist
26A7142B71-A144-4D56-BD14-3E966B01DB373M05.132Rheumatoid lung disease with rheumatoid arthritis of left wrist
27135C831F-7DA5-46C0-959C-EBCBD8810B435M05.17Rheumatoid lung disease with rheumatoid arthritis of ankle and foot
282A5251B1-0945-47FA-A65C-7A63815625913M05.23Rheumatoid vasculitis with rheumatoid arthritis of wrist
29EEAFC0B3-B835-4D99-AB33-2F9428E54E5F1M05.25Rheumatoid vasculitis with rheumatoid arthritis of hip
30E483DE6E-D4E6-47FD-905B-22EE86EC7ACE3M05.252Rheumatoid vasculitis with rheumatoid arthritis of left hip
317548B6CF-79D9-461D-A0C5-20B861406FAC1M05.261Rheumatoid vasculitis with rheumatoid arthritis of right knee
32C65A4ADE-112E-49E4-B72A-0DED22C242ED1M05.27Rheumatoid vasculitis with rheumatoid arthritis of ankle and foot
33FB2ABB23-C9D0-4D09-8464-49BF0B982F0F1M05.272Rheumatoid vasculitis with rheumatoid arthritis of left ankle and foot
34B39DC5AC-E003-4E6A-91B6-FC07625A12855M05.441Rheumatoid myopathy with rheumatoid arthritis of right hand
357A025E77-7832-4F53-B9A7-09A3F98AC17E1M05.442Rheumatoid myopathy with rheumatoid arthritis of left hand
360E0EADE8-5592-4E0B-9F88-D7596E32EE082M05.49Rheumatoid myopathy with rheumatoid arthritis of multiple sites
3769B5D2A0-12FD-46EF-A5FF-B29C4BAFBE492M05.5Rheumatoid polyneuropathy with rheumatoid arthritis
3880AC01B2-BD55-4BE0-A59A-4024104CF4E95M05.51Rheumatoid polyneuropathy with rheumatoid arthritis of shoulder
397548B6CF-79D9-461D-A0C5-20B861406FAC3M05.511Rheumatoid polyneuropathy with rheumatoid arthritis of right shoulder
4080D356B4-F974-441F-A5F2-F95986D119A26M05.561Rheumatoid polyneuropathy with rheumatoid arthritis of right knee
41EEAFC0B3-B835-4D99-AB33-2F9428E54E5F2M05.59Rheumatoid polyneuropathy with rheumatoid arthritis of multiple sites
42B2EB15FA-5431-4804-9309-4215BDC778C01M05.722Rheumatoid arthritis with rheumatoid factor of left elbow without organ or systems involvement
43FA157FA5-F488-4884-BF87-E144630D595C1M05.732Rheumatoid arthritis with rheumatoid factor of left wrist without organ or systems involvement
4435FE7491-1A1D-48CB-810C-8DC2599AB3DD3M05.741Rheumatoid arthritis with rheumatoid factor of right hand without organ or systems involvement
45967987B9-FFEF-4776-85CF-AE05CA81F5831M05.742Rheumatoid arthritis with rheumatoid factor of left hand without organ or systems involvement
4625B786AF-0F99-478C-9CFA-0EA607E458344M05.75Rheumatoid arthritis with rheumatoid factor of hip without organ or systems involvement
47886B5885-1EE2-49F3-98D5-A2F02EB8A9D41M05.752Rheumatoid arthritis with rheumatoid factor of left hip without organ or systems involvement
48C5D09468-574F-4802-B56F-DB38F4EB16871N25.1Nephrogenic diabetes insipidus
4965A7FBE0-EA9F-49E9-9824-D8F3AD98DAC02S35.415Laceration of left renal vein
50C8556CC0-32FC-4CA5-A8CD-9CCF388161672Z95.810Presence of automatic (implantable) cardiac defibrillator
\n" ], "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('100_patients.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM AdmissionsDiagnosesCorePopulatedTable\n", "WHERE PrimaryDiagnosisCode LIKE '%5.%'\n", "ORDER BY PrimaryDiagnosisCode\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] }, { "cell_type": "markdown", "id": "2a175776", "metadata": {}, "source": [ "## Checking for NULL\n", "\n", "```SQL\n", "SELECT *\n", "FROM Cars\n", "WHERE color_id IS NULL\n", "```" ] }, { "cell_type": "code", "execution_count": 14, "id": "84e55b8b", "metadata": { "tags": [ "hide-input", "output_scroll" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 car_idmake_model_idcolor_idavailable
\n" ], "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import sqlite3\n", "import pandas as pd\n", "\n", "conn = sqlite3.connect('cars.db')\n", "\n", "sql_statement = \"\"\"\n", "SELECT *\n", "FROM Cars\n", "WHERE color_id IS NULL\n", "\"\"\"\n", "df = pd.read_sql_query(sql_statement, conn)\n", "df.style.set_table_attributes('style=\"font-size: 12px\"')" ] } ], "metadata": { "jupytext": { "formats": "md:myst", "text_representation": { "extension": ".md", "format_name": "myst" } }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.7" }, "source_map": [ 11, 50, 65, 76, 91, 102, 117, 128, 143, 154, 169, 180, 195, 206, 221, 232, 247, 257, 272, 282, 297, 308, 323, 332, 347, 356, 371, 381 ] }, "nbformat": 4, "nbformat_minor": 5 }