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added example of SQLite
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‎Figs/Nursery.png

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‎Notebooks/01_SQLite.ipynb

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"print(cur.fetchall())"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Creating a Table and inserzing Data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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{
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"data": {
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"text/plain": [
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"<sqlite3.Cursor at 0x7fe1fa654180>"
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"<sqlite3.Cursor at 0x7f12fb4210a0>"
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]
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},
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"execution_count": 9,
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Using Pandas"
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"#### Using Pandas to query"
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]
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},
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{
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"os.remove(os.path.join(\"..\",\"SampleDBs\",'sqlite_example.db'))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Another example"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [],
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"source": [
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"conn = sqlite3.connect(os.path.join(\"..\",\"SampleDBs\",\"test.db\"))\n",
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" \n",
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"#Here, you can also supply database name as the special name :memory: to create a database in RAM."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"outputs": [],
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"source": [
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"conn.execute('''CREATE TABLE COMPANY \n",
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" (ID INT PRIMARY KEY NOT NULL,\n",
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" NAME TEXT NOT NULL,\n",
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" AGE INT NOT NULL,\n",
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" ADDRESS CHAR(50),\n",
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" SALARY REAL);''')\n",
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"conn.close()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"outputs": [],
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"source": [
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"conn = sqlite3.connect(os.path.join(\"..\",\"SampleDBs\",\"test.db\"))\n",
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"\n",
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"conn.execute(\"INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) VALUES (1, 'Paul', 32, 'California', 20000.00 )\");\n",
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"conn.execute(\"INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) VALUES (2, 'Allen', 25, 'Texas', 15000.00 )\");\n",
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"conn.execute(\"INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) VALUES (3, 'Teddy', 23, 'Norway', 20000.00 )\");\n",
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"conn.execute(\"INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) VALUES (4, 'Mark', 25, 'Rich-Mond ', 65000.00 )\");\n",
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"\n",
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"conn.commit()\n",
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"conn.close()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"ID = 1\n",
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"NAME = Paul\n",
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"ADDRESS = California\n",
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"SALARY = 20000.0 \n",
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"\n",
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"ID = 2\n",
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"NAME = Allen\n",
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"ADDRESS = Texas\n",
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"SALARY = 15000.0 \n",
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"\n",
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"ID = 3\n",
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"NAME = Teddy\n",
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"ADDRESS = Norway\n",
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"SALARY = 20000.0 \n",
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"\n",
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"ID = 4\n",
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"NAME = Mark\n",
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"ADDRESS = Rich-Mond \n",
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"SALARY = 65000.0 \n",
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"\n"
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]
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}
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],
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"source": [
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"conn = sqlite3.connect(os.path.join(\"..\",\"SampleDBs\",\"test.db\"))\n",
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"\n",
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"cursor = conn.execute(\"SELECT id, name, address, salary from COMPANY\")\n",
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"for row in cursor:\n",
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" print(\"ID = \", row[0])\n",
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" print(\"NAME = \", row[1])\n",
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" print(\"ADDRESS = \", row[2])\n",
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" print(\"SALARY = \", row[3], \"\\n\")\n",
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" \n",
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"conn.close()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [],
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"source": [
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"os.remove(os.path.join(\"..\",\"SampleDBs\",\"test.db\"))"
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]
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},
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"cell_type": "markdown",
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"execution_count": 19,
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"4 Worlds "
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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"version": "3.8.10"
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}
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},
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"nbformat": 4,

‎SampleDBs/nursery_create.sql

100644100755
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