Create and Insert into DataBase

CreateDB.ipynb

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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlalchemy as db\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating Database and Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "engine = db.create_engine('sqlite:///test.sqlite') #Create test.sqlite automatically\n",
    "connection = engine.connect()\n",
    "metadata = db.MetaData()\n",
    "\n",
    "emp = db.Table('emp', metadata,\n",
    "              db.Column('Id', db.Integer()),\n",
    "              db.Column('name', db.String(255), nullable=False),\n",
    "              db.Column('salary', db.Float(), default=100.0),\n",
    "              db.Column('active', db.Boolean(), default=True)\n",
    "              )\n",
    "\n",
    "metadata.create_all(engine) #Creates the table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Inserting Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Inserting record one by one\n",
    "query = db.insert(emp).values(Id=1, name='naveen', salary=60000.00, active=True) \n",
    "ResultProxy = connection.execute(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Inserting many records at ones\n",
    "query = db.insert(emp) \n",
    "values_list = [{'Id':'2', 'name':'ram', 'salary':80000, 'active':False},\n",
    "               {'Id':'3', 'name':'ramesh', 'salary':70000, 'active':True}]\n",
    "ResultProxy = connection.execute(query,values_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>name</th>\n",
       "      <th>salary</th>\n",
       "      <th>active</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>vinay</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>satvik</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>naveen</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>rahul</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   Id    name   salary  active\n",
       "0   1   vinay  60000.0    True\n",
       "1   1  satvik  60000.0    True\n",
       "2   1  naveen  60000.0    True\n",
       "3   2   rahul  80000.0   False"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = connection.execute(db.select([emp])).fetchall()\n",
    "df = pd.DataFrame(results)\n",
    "df.columns = results[0].keys()\n",
    "df.head(4)"
   ]
  }
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