reg_linear.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/marioymario/Human_Resourses_attrition/blob/main/reg_linear.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "6df844e0",
      "metadata": {
        "id": "6df844e0"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "from sklearn.linear_model import LinearRegression\n",
        "import csv\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib notebook"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "cc47a1b2",
      "metadata": {
        "id": "cc47a1b2"
      },
      "outputs": [],
      "source": [
        "with open(\"/home/gato/Scripts/py_ex/LearnPython-main/files/cars.csv\", \"r\") as f:\n",
        "    csv_reader = csv.DictReader(f)\n",
        "    cars = list(csv_reader)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "d81190c1",
      "metadata": {
        "id": "d81190c1"
      },
      "outputs": [],
      "source": [
        "horsepower = [int(keys['Horsepower']) for keys in cars]\n",
        "torque = [int(keys['Torque']) for keys in cars]\n",
        "x = np.array(horsepower).reshape(-1,1)\n",
        "y = np.array(torque).reshape(-1,1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "44fa3fa1",
      "metadata": {
        "id": "44fa3fa1"
      },
      "outputs": [],
      "source": [
        "l_r = LinearRegression()\n",
        "l_r.fit(x, y)\n",
        "y_pred = l_r.predict(x)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "525fb1cc",
      "metadata": {
        "id": "525fb1cc",
        "outputId": "59a40cc5-8f7c-4bd2-d910-e00c8b75592e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "('6.03274', '0.98586')"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "##\n",
        "## the interceptor and the slope\n",
        "alpha = str(round(l_r.intercept_[0], 5)) ## el interceptor[0] y cinco decimales\n",
        "beta = str(round(l_r.coef_[0][0], 5))\n",
        "alpha, beta"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "c4d96bdb",
      "metadata": {
        "id": "c4d96bdb",
        "outputId": "07197b94-46ab-4098-9d0a-5734e0514259"
      },
      "outputs": [
        {
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              "    // Request the server to send over a new figure.\n",
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              "    fig.image_mode = msg['mode'];\n",
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              "    for (var key in msg) {\n",
              "        if (!(key in fig.buttons)) {\n",
              "            continue;\n",
              "        }\n",
              "        fig.buttons[key].disabled = !msg[key];\n",
              "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
              "    if (msg['mode'] === 'PAN') {\n",
              "        fig.buttons['Pan'].classList.add('active');\n",
              "        fig.buttons['Zoom'].classList.remove('active');\n",
              "    } else if (msg['mode'] === 'ZOOM') {\n",
              "        fig.buttons['Pan'].classList.remove('active');\n",
              "        fig.buttons['Zoom'].classList.add('active');\n",
              "    } else {\n",
              "        fig.buttons['Pan'].classList.remove('active');\n",
              "        fig.buttons['Zoom'].classList.remove('active');\n",
              "    }\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",
              "            var img = evt.data;\n",
              "            if (img.type !== 'image/png') {\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",
              "                img.type = 'image/png';\n",
              "            }\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",
              "\n",
              "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
              "                img\n",
              "            );\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        } else if (\n",
              "            typeof evt.data === 'string' &&\n",
              "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
              "        ) {\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(\n",
              "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
              "                msg\n",
              "            );\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(\n",
              "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
              "                    e,\n",
              "                    e.stack,\n",
              "                    msg\n",
              "                );\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",
              "    }\n",
              "    if (e.target) {\n",
              "        targ = e.target;\n",
              "    } else if (e.srcElement) {\n",
              "        targ = e.srcElement;\n",
              "    }\n",
              "    if (targ.nodeType === 3) {\n",
              "        // defeat Safari bug\n",
              "        targ = targ.parentNode;\n",
              "    }\n",
              "\n",
              "    // pageX,Y are the mouse positions relative to the document\n",
              "    var boundingRect = targ.getBoundingClientRect();\n",
              "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
              "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
              "        }\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",
              "        this.canvas.focus();\n",
              "        this.canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    var x = canvas_pos.x * this.ratio;\n",
              "    var y = canvas_pos.y * this.ratio;\n",
              "\n",
              "    this.send_message(name, {\n",
              "        x: x,\n",
              "        y: y,\n",
              "        button: event.button,\n",
              "        step: event.step,\n",
              "        guiEvent: simpleKeys(event),\n",
              "    });\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",
              "    // Prevent repeat events\n",
              "    if (name === 'key_press') {\n",
              "        if (event.key === this._key) {\n",
              "            return;\n",
              "        } else {\n",
              "            this._key = event.key;\n",
              "        }\n",
              "    }\n",
              "    if (name === 'key_release') {\n",
              "        this._key = null;\n",
              "    }\n",
              "\n",
              "    var value = '';\n",
              "    if (event.ctrlKey && event.key !== 'Control') {\n",
              "        value += 'ctrl+';\n",
              "    }\n",
              "    else if (event.altKey && event.key !== 'Alt') {\n",
              "        value += 'alt+';\n",
              "    }\n",
              "    else if (event.shiftKey && event.key !== 'Shift') {\n",
              "        value += 'shift+';\n",
              "    }\n",
              "\n",
              "    value += 'k' + event.key;\n",
              "\n",
              "    this._key_event_extra(event, name);\n",
              "\n",
              "    this.send_message(name, { key: value, 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",
              "\n",
              "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
              "// prettier-ignore\n",
              "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
              "\n",
              "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
              "\n",
              "mpl.default_extension = \"png\";/* global mpl */\n",
              "\n",
              "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.binaryType = comm.kernel.ws.binaryType;\n",
              "    ws.readyState = comm.kernel.ws.readyState;\n",
              "    function updateReadyState(_event) {\n",
              "        if (comm.kernel.ws) {\n",
              "            ws.readyState = comm.kernel.ws.readyState;\n",
              "        } else {\n",
              "            ws.readyState = 3; // Closed state.\n",
              "        }\n",
              "    }\n",
              "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
              "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
              "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
              "        var data = msg['content']['data'];\n",
              "        if (data['blob'] !== undefined) {\n",
              "            data = {\n",
              "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
              "            };\n",
              "        }\n",
              "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
              "        ws.onmessage(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 = document.getElementById(id);\n",
              "    var ws_proxy = comm_websocket_adapter(comm);\n",
              "\n",
              "    function ondownload(figure, _format) {\n",
              "        window.open(figure.canvas.toDataURL());\n",
              "    }\n",
              "\n",
              "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
              "    fig.cell_info[0].output_area.element.on(\n",
              "        'cleared',\n",
              "        { fig: fig },\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
              "    var width = fig.canvas.width / fig.ratio;\n",
              "    fig.cell_info[0].output_area.element.off(\n",
              "        'cleared',\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
              "        '<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 / this.ratio;\n",
              "    var dataURL = this.canvas.toDataURL();\n",
              "    this.cell_info[1]['text/html'] =\n",
              "        '<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 () {\n",
              "        fig.push_to_output();\n",
              "    }, 1000);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var toolbar = document.createElement('div');\n",
              "    toolbar.classList = 'btn-toolbar';\n",
              "    this.root.appendChild(toolbar);\n",
              "\n",
              "    function on_click_closure(name) {\n",
              "        return function (_event) {\n",
              "            return fig.toolbar_button_onclick(name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    function on_mouseover_closure(tooltip) {\n",
              "        return function (event) {\n",
              "            if (!event.currentTarget.disabled) {\n",
              "                return fig.toolbar_button_onmouseover(tooltip);\n",
              "            }\n",
              "        };\n",
              "    }\n",
              "\n",
              "    fig.buttons = {};\n",
              "    var buttonGroup = document.createElement('div');\n",
              "    buttonGroup.classList = 'btn-group';\n",
              "    var button;\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",
              "            /* Instead of a spacer, we start a new button group. */\n",
              "            if (buttonGroup.hasChildNodes()) {\n",
              "                toolbar.appendChild(buttonGroup);\n",
              "            }\n",
              "            buttonGroup = document.createElement('div');\n",
              "            buttonGroup.classList = 'btn-group';\n",
              "            continue;\n",
              "        }\n",
              "\n",
              "        button = fig.buttons[name] = document.createElement('button');\n",
              "        button.classList = 'btn btn-default';\n",
              "        button.href = '#';\n",
              "        button.title = name;\n",
              "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
              "        button.addEventListener('click', on_click_closure(method_name));\n",
              "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
              "        buttonGroup.appendChild(button);\n",
              "    }\n",
              "\n",
              "    if (buttonGroup.hasChildNodes()) {\n",
              "        toolbar.appendChild(buttonGroup);\n",
              "    }\n",
              "\n",
              "    // Add the status bar.\n",
              "    var status_bar = document.createElement('span');\n",
              "    status_bar.classList = 'mpl-message pull-right';\n",
              "    toolbar.appendChild(status_bar);\n",
              "    this.message = status_bar;\n",
              "\n",
              "    // Add the close button to the window.\n",
              "    var buttongrp = document.createElement('div');\n",
              "    buttongrp.classList = 'btn-group inline pull-right';\n",
              "    button = document.createElement('button');\n",
              "    button.classList = 'btn btn-mini btn-primary';\n",
              "    button.href = '#';\n",
              "    button.title = 'Stop Interaction';\n",
              "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
              "    button.addEventListener('click', function (_evt) {\n",
              "        fig.handle_close(fig, {});\n",
              "    });\n",
              "    button.addEventListener(\n",
              "        'mouseover',\n",
              "        on_mouseover_closure('Stop Interaction')\n",
              "    );\n",
              "    buttongrp.appendChild(button);\n",
              "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
              "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
              "    var fig = event.data.fig;\n",
              "    if (event.target !== this) {\n",
              "        // Ignore bubbled events from children.\n",
              "        return;\n",
              "    }\n",
              "    fig.close_ws(fig, {});\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function (el) {\n",
              "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
              "    // this is important to make the div 'focusable\n",
              "    el.setAttribute('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",
              "    } else {\n",
              "        // location in version 2\n",
              "        IPython.keyboard_manager.register_events(el);\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",
              "\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",
              "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(\n",
              "        'matplotlib',\n",
              "        mpl.mpl_figure_comm\n",
              "    );\n",
              "}\n"
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/html": [
              "<img 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\" width=\"640\">"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fedb212aa00>]"
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "fig1, ax1 = plt.subplots()\n",
        "ax1.set_title('interceptor: {} and pendiente: {}'.format(alpha, beta))\n",
        "ax1.scatter(x, y)\n",
        "ax1.plot(x, y_pred, c='r', alpha=0.25)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "c2b97d66",
      "metadata": {
        "id": "c2b97d66"
      },
      "outputs": [],
      "source": [
        ""
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "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": "3.9.7"
    },
    "colab": {
      "name": "tarea_linear_reg.ipynb",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}