Case and Cast

case.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlalchemy as db"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "engine = db.create_engine('sqlite:///census.sqlite')\n",
    "connection = engine.connect()\n",
    "metadata = db.MetaData()\n",
    "census = db.Table('census', metadata, autoload=True, autoload_with=engine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "female_pop = db.func.sum(db.case([(census.columns.sex == 'F', census.columns.pop2000)],else_=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_pop = db.cast(db.func.sum(census.columns.pop2000), db.Float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "query = db.select([female_pop/total_pop * 100])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "51.09467432293413\n"
     ]
    }
   ],
   "source": [
    "result = connection.execute(query).scalar()\n",
    "print(result)"
   ]
  }
 ],
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