|
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Housing Prices in São Paulo\n",
"\n",
"This notebook gathers information about housing prices and their sizes on the city of São Paulo, Brazil."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Import Libraries\n",
"import pandas as pd\n",
"import requests\n",
"from bs4 import BeautifulSoup\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib\n",
"matplotlib.style.use('ggplot')\n",
"%matplotlib notebook"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This dataset is gathering information from [Imovel Web](http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-1.html), a brazilian online real estate portal. The function belows creates a new URL in each loop iteration."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"def getURL(page_number):\n",
" base_url = \"http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-\"\n",
" end_url = \".html\"\n",
" url = base_url + str(page_number) + end_url\n",
" return url"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def num(s):\n",
" try:\n",
" return int(s)\n",
" except ValueError:\n",
" return float(s)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The function below requests a url, passes the page to [BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/bs4/doc/) that in turn scrapes each data item from a this page. Each new item is added to a [pandas](https://pandas.pydata.org) series that is then appended to a dataset for later use."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def grab_data(url, i):\n",
" try:\n",
" result = requests.get(url)\n",
" page = BeautifulSoup(result.content, \"html5lib\")\n",
" items = page.find_all('li', class_='post')\n",
" for item in items:\n",
" title = item.find(\"a\", class_='dl-aviso-link').get('title')\n",
" price = item.find(\"span\", class_='precio-valor').string.replace(\"R$\",\"\").replace(\".\",\"\").strip()\n",
" size = item.find(\"li\", class_='post-m2totales')\n",
" if size is not None:\n",
" size = size.text.replace(\"total\",\"\").strip()\n",
" #print(size + \" - \" + price + \" - \" + title)\n",
" price = num(str(price))/1000\n",
" size = num(str(size.replace(\"m²\",\"\")))\n",
" df.loc[i] = [size, price]\n",
" i = i + 1\n",
" return i\n",
" except:\n",
" print(\"--> ERROR\")\n",
" return i"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Below is the actual program loop. It will grab data from *n* number of pages using the ```grab_data()``` function. While this is happening, the program prints the current URL that is beign scraped or prints an error message. If an error occurs, the program will continue scraping from the next link."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-1.html\n",
"2 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-2.html\n",
"3 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-3.html\n",
"4 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-4.html\n",
"5 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-5.html\n",
"6 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-6.html\n",
"7 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-7.html\n",
"8 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-8.html\n",
"9 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-9.html\n",
"10 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-10.html\n",
"11 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-11.html\n",
"12 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-12.html\n",
"13 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-13.html\n",
"14 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-14.html\n",
"15 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-15.html\n",
"16 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-16.html\n",
"--> ERROR\n",
"17 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-17.html\n",
"18 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-18.html\n",
"19 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-19.html\n",
"20 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-20.html\n",
"21 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-21.html\n",
"22 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-22.html\n",
"23 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-23.html\n",
"24 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-24.html\n",
"25 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-25.html\n",
"26 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-26.html\n",
"27 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-27.html\n",
"28 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-28.html\n",
"29 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-29.html\n",
"--> ERROR\n",
"30 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-30.html\n",
"31 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-31.html\n",
"32 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-32.html\n",
"33 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-33.html\n",
"34 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-34.html\n",
"35 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-35.html\n",
"36 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-36.html\n",
"37 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-37.html\n",
"38 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-38.html\n",
"39 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-39.html\n",
"40 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-40.html\n",
"41 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-41.html\n",
"42 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-42.html\n",
"43 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-43.html\n",
"44 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-44.html\n",
"45 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-45.html\n",
"--> ERROR\n",
"46 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-46.html\n",
"47 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-47.html\n",
"48 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-48.html\n",
"49 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-49.html\n",
"50 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-50.html\n",
"51 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-51.html\n",
"52 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-52.html\n",
"53 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-53.html\n",
"54 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-54.html\n",
"55 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-55.html\n",
"56 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-56.html\n",
"57 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-57.html\n",
"58 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-58.html\n",
"59 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-59.html\n",
"60 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-60.html\n",
"61 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-61.html\n",
"62 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-62.html\n",
"63 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-63.html\n",
"--> ERROR\n",
"64 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-64.html\n",
"65 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-65.html\n",
"66 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-66.html\n",
"67 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-67.html\n",
"68 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-68.html\n",
"69 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-69.html\n",
"70 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-70.html\n",
"71 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-71.html\n",
"72 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-72.html\n",
"73 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-73.html\n",
"74 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-74.html\n",
"75 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-75.html\n",
"76 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-76.html\n",
"77 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-77.html\n",
"78 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-78.html\n",
"79 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-79.html\n",
"80 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-80.html\n",
"81 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-81.html\n",
"82 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-82.html\n",
"83 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-83.html\n",
"84 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-84.html\n",
"85 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-85.html\n",
"86 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-86.html\n",
"--> ERROR\n",
"87 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-87.html\n",
"88 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-88.html\n",
"--> ERROR\n",
"89 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-89.html\n",
"90 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-90.html\n",
"91 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-91.html\n",
"--> ERROR\n",
"92 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-92.html\n",
"93 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-93.html\n",
"94 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-94.html\n",
"95 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-95.html\n",
"96 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-96.html\n",
"97 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-97.html\n",
"98 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-98.html\n",
"99 - http://www.imovelweb.com.br/imoveis-venda-sao-paulo-sp-pagina-99.html\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>size</th>\n",
" <th>price</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1084</th>\n",
" <td>69.0</td>\n",
" <td>480.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1085</th>\n",
" <td>103.0</td>\n",
" <td>945.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1086</th>\n",
" <td>56.0</td>\n",
" <td>650.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1087</th>\n",
" <td>81.0</td>\n",
" <td>800.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1088</th>\n",
" <td>70.0</td>\n",
" <td>35.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" size price\n",
"1084 69.0 480.0\n",
"1085 103.0 945.0\n",
"1086 56.0 650.0\n",
"1087 81.0 800.0\n",
"1088 70.0 35.0"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.DataFrame([], columns=('size', 'price'))\n",
"i = 0\n",
"for page_number in range(1,100):\n",
" url = getURL(page_number)\n",
" print(str(page_number) + \" - \" + url)\n",
" i = grab_data(url, i)\n",
"df.tail() "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The next snippet creates a plot with the data gathered in the previous step."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
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" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x1123e2390>"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.plot(x=\"size\", y=\"price\", s=2, kind='scatter', xlim=(0, 600), ylim=(0, 3000), style=\"o\")\n",
"plt.xlabel(\"Size (m²)\")\n",
"plt.ylabel(\"Price (1000 of R$)\")"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>size,price</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>100.0,1150.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>102.0,760.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>63.0,519.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>30.0,278.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0\n",
"0 size,price\n",
"1 100.0,1150.0\n",
"2 102.0,760.0\n",
"3 63.0,519.0\n",
"4 30.0,278.2"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filename = 'housing-prices-sao-paulo.txt'\n",
"df.to_csv(filename, index=False, encoding='utf-8')\n",
"saved_data = pd.read_csv(filename, sep=\" \", header = None)\n",
"saved_data.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"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": "3.6.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|
