{
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"source": [
"## Exercise 4"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For this exercise you are given a database containing information about real estate around\n",
"Uppsala. You are also given a Python module that helps working the database.\n",
"\n",
"- The database (`uppsala.sqlite`) and the code (`db.py` and `homes.py`) are found in the `download` directory.\n",
"- Read the module's [documentation](../../files/db_module_documentation.html)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The module `db.py` will help you produce a HTML file whit your results plotted on a map. This set-up uses OpenStreetMap. \n",
"\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The center is defined as the point:\n",
"\n",
"`latitude: 59.865795990339876`\n",
"\n",
"`longitude: 17.64583576202392`\n",
"\n",
"\n",
"- Open `homes.py` and use it to solve the exercise"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Questions:\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"a) What is the price of the cheapest house around the given center and within 2 kilometers?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"b) Plot the 100 cheapest houses in this area."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"c) Find the most expensive house that has an area larger than 10, and print its price and area."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"d) Print or plot this house."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"----\n",
"
\n",
"Proposed solution
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**a) and b)**\n",
"\n",
"First, we do all imports and set the coordinates of the 'center'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from db import HomeDB\n",
"from db import haversine as get_distance\n",
"from db import plot, sort_by_price\n",
"\n",
"lat = 59.865795990339876\n",
"lng = 17.64583576202392\n",
"radius = 2000 # in m\n",
"\n",
"\n",
"db = HomeDB('../../files/uppsala.sqlite')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We define a help function that gets all houses that are central and returns them sorted by price:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def cheap_central():\n",
" \"\"\" Find the within 2000m from the center and sort by increasing price \"\"\"\n",
" db.connect()\n",
" homes = db.select() # Let's get all homes and then sort and filter them\n",
" db.disconnect()\n",
" # TODO sort homes by price and keep only homes that are close to the center"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's start by picking homes that are central. We create a new list, `selected`, where all central houses will be put. But how do we know if a home is central?\n",
"\n",
"- we get it's location\n",
"- we use the `get_distance()` from `db` to check the distance between the home and the given center"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```py\n",
"selected = []\n",
"for home in homes:\n",
" h_lat, h_lon = home.get_location()\n",
" distance = get_distance(h_lat, h_lon, lat, lng)\n",
" if distance <= 2000:\n",
" selected.append(home)\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next step is to sort the homes by price. The function `sort_by_price()` from `db` is useful here!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```py\n",
"sorted_selected = sort_by_price(selected)\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's put it all together:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def cheap_central():\n",
" \"\"\" Find the within 2000m from the center and sort by increasing price \"\"\"\n",
" db.connect()\n",
" homes = db.select()\n",
" db.disconnect()\n",
" selected = []\n",
" for home in homes:\n",
" h_lat, h_lon = home.get_location()\n",
" distance = get_distance(h_lat, h_lon, lat, lng)\n",
" if distance <= 2000:\n",
" selected.append(home)\n",
" sorted_selected = sort_by_price(selected)\n",
" return sorted_selected"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For a), we just print the first item of the list"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def part_a():\n",
" print('Cheapest house: ' + str(cheap_central()[0].get_price()))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For b), we select the 100 first items and plot them. `outfile` is the name of the resulting html file."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def part_b(outfile):\n",
" num = 100\n",
" central = cheap_central()\n",
" pos = set()\n",
" for home in central[:num]:\n",
" pos.add(home.get_location())\n",
" plot(central[:num],\n",
" output=outfile,\n",
" special=central[0],\n",
" zoom=14,\n",
" latitude=lat,\n",
" longitude=lng,\n",
" radius=radius\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**c) and d)**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We define another help function to find the most expensive houses."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"def expensive():\n",
" \"\"\" Sort houses by price per square meter \"\"\"\n",
" db.connect()\n",
" # use the built in filtering in db.select to get houses with a big enough area\n",
" homes = db.select('area > 10')\n",
" db.disconnect()\n",
" expensive = sort_by_price(homes, reverse=True)\n",
" return expensive"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For c), we get the first item and print it."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def part_c():\n",
" house = expensive()[0]\n",
" print('Most expensive:' + str(house.get_price()) + '. Square meters: ' +str(house.get_area()))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For d), we plot it. Again, `outfile` is the name of the resulting html file."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def part_d(outfile):\n",
" house = expensive()[0]\n",
" plot([house],\n",
" output=outfile,\n",
" special=house,\n",
" zoom=14,\n",
" latitude=lat,\n",
" longitude=lng,\n",
" radius=radius\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Optionally, add a main function to print all answers."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Part a:\n",
"Cheapest house: 330000.0\n",
"\n",
"Part b: printed to selection_b.html\n",
"\n",
"Part c:\n",
"Most expensive:20000000.0. Square meters: 120.0\n",
"\n",
"Part d: printed to selection_d.html\n"
]
}
],
"source": [
"if __name__ == \"__main__\":\n",
" print('Part a:')\n",
" part_a()\n",
" print()\n",
" part_b('selection_b.html')\n",
" print('Part b: printed to selection_b.html')\n",
" print()\n",
" print('Part c:')\n",
" part_c()\n",
" print()\n",
" part_d('selection_d.html')\n",
" print('Part d: printed to selection_d.html')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### `selection_b.html`:"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### `selection_d.html`:"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Bonus exercises**\n",
"\n",
"- Find out what types of houses there are.\n",
"- Plot all houses of type 'Gård'. \n",
"\n",
"- Print a circle of houses, like so:\n",
"\n",
""
]
}
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