Sentiment_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training on 1850 data, testing on 150 data\n",
      "Training complete\n",
      "accuracy: 81.33333333333333 %\n",
      "Most Informative Features\n",
      "             outstanding = True           positi : negati =     16.4 : 1.0\n",
      "               ludicrous = True           negati : positi =     13.5 : 1.0\n",
      "              astounding = True           positi : negati =     13.0 : 1.0\n",
      "                  avoids = True           positi : negati =     13.0 : 1.0\n",
      "                 idiotic = True           negati : positi =     12.3 : 1.0\n",
      "             fascination = True           positi : negati =     11.6 : 1.0\n",
      "               atrocious = True           negati : positi =     11.1 : 1.0\n",
      "                  symbol = True           positi : negati =     10.9 : 1.0\n",
      "                  annual = True           positi : negati =     10.2 : 1.0\n",
      "                  hudson = True           negati : positi =      9.8 : 1.0\n"
     ]
    }
   ],
   "source": [
    "from nltk.classify import NaiveBayesClassifier\n",
    "from nltk.corpus import movie_reviews\n",
    "import pickle\n",
    "import nltk.classify.util\n",
    "import sys\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "def clean(words):\n",
    "    return dict([(word, True) for word in words])\n",
    "\n",
    "\n",
    "negative_ids = movie_reviews.fileids('neg')\n",
    "positive_ids = movie_reviews.fileids('pos')\n",
    "\n",
    "\n",
    "negative_features = [(clean(movie_reviews.words(fileids=[f])), 'negative') for f in negative_ids]\n",
    "positive_features = [(clean(movie_reviews.words(fileids=[f])), 'positive') for f in positive_ids]\n",
    "\n",
    "\n",
    "negative_cutoff = int(len(negative_features) * 95/100)\n",
    "positive_cutoff = int(len(positive_features) * 90/100)\n",
    "\n",
    "train_features = negative_features[:negative_cutoff] + positive_features[:positive_cutoff]\n",
    "test_features = negative_features[negative_cutoff:] + positive_features[positive_cutoff:]\n",
    "\n",
    "print('Training on %d data, testing on %d data' % (len(train_features), len(test_features)))\n",
    "classifier = NaiveBayesClassifier.train(train_features)\n",
    "print('Training complete')\n",
    "print('accuracy:', nltk.classify.util.accuracy(classifier, test_features)*100,'%')\n",
    "classifier.show_most_informative_features()\n",
    "\n",
    "\n",
    "f = open('model', 'wb')\n",
    "pickle.dump(classifier, f)\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "negative\n",
      "positive\n",
      "positive\n",
      "negative\n"
     ]
    }
   ],
   "source": [
    "f = open('model', 'rb')\n",
    "classifier = pickle.load(f)\n",
    "f.close()\n",
    "\n",
    "\n",
    "\n",
    "sentence=\"i don't love you \"\n",
    "features = clean(sentence)\n",
    "print(classifier.classify(features))\n",
    "\n",
    "sentence=\"i love you sweetheart \"\n",
    "features = clean(sentence)\n",
    "print(classifier.classify(features))\n",
    "\n",
    "\n",
    "sentence=\"i am not saying that i don't love you\"\n",
    "features = clean(sentence)\n",
    "print(classifier.classify(features))\n",
    "\n",
    "sentence=\"This size of laptop is very bad\"\n",
    "features = clean(sentence)\n",
    "print(classifier.classify(features))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Vineet negative  Not trustable product\n",
      "\n",
      " Badal positive  just go and purchase its good\n",
      "\n",
      " Vinay negative  Never buy it\n",
      "\n",
      " Sister negative  Go and try this product is best\n",
      "\n",
      " Ankit negative  Don't buy this its bad disgusting\n",
      "\n",
      " DJ positive  Wow marvelous design\n",
      "\n",
      " Brother positive  This is best product ever i have seen it best\n",
      "\n",
      " Dad positive  So when are you buying it's pretty good \n",
      "\n",
      " Mom positive  I want to buy another, love it\n",
      "\n",
      " Vinay positive  If you buy you will like you are in heaven\n",
      "\n",
      " Vineet negative  Don't buy its very worst\n",
      "\n",
      " Vinay positive  You will Enjoy this product awesome\n",
      "\n",
      " Vina positive  value for money\n",
      "\n",
      " Vina negative  Not portable bad for this\n",
      "\n",
      " Vina negative  but this is not for child if you have don't buy this\n",
      "\n",
      " Dad negative  Worst than any other brand\n",
      "\n",
      " Ankit positive  Best Technical support\n",
      "\n",
      " Gullu negative  For student it is bad\n",
      "\n",
      " Gullu positive  good for teachers\n",
      "\n",
      "positive: 10 \n",
      "Negative: 9\n"
     ]
    }
   ],
   "source": [
    "opinion={}\n",
    "\n",
    "f=open('export_chat.txt','r')\n",
    "pos,neg=0,0\n",
    "for line in f:\n",
    "    try:\n",
    "        chat=line.split('-')[1].split(':')[1]\n",
    "        name=line.split('-')[1].split(':')[0]\n",
    "        if opinion.get(name,None) is None:\n",
    "            opinion[name]=[0,0]\n",
    "        res=classifier.classify(clean(chat))\n",
    "        print(name,res,chat)\n",
    "        if res=='positive':\n",
    "            pos+=1\n",
    "            opinion[name][0]+=1\n",
    "        else:\n",
    "            neg+=1\n",
    "            opinion[name][1]+=1\n",
    "    except:\n",
    "        pass\n",
    "print(\"positive: {} \\nNegative: {}\".format(pos,neg))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
       "\n",
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       "    var size = msg['size'];\n",
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       "    };\n",
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       "\n",
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       "    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",
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       "        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",
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       "    var cursor = msg['cursor'];\n",
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       "        break;\n",
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       "        break;\n",
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       "}\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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overridden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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"
    }
   ],
   "source": [
    "neg=abs(neg)\n",
    "labels = ['positive','negative']\n",
    "sizes = [pos,neg]\n",
    "fig1, ax1 = plt.subplots()\n",
    "ax1.pie(sizes ,labels=labels, autopct='%1.1f%%')\n",
    "plt.title('Whatsapp Sentiment Analysis')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "names,positive,negative=[],[],[]\n",
    "for name in opinion:\n",
    "    names.append(name)\n",
    "    positive.append(opinion[name][0])\n",
    "    negative.append(opinion[name][1])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def autolabel(rects):\n",
    "    for rect in rects:\n",
    "        h = rect.get_height()\n",
    "        ax.text(rect.get_x()+rect.get_width()/2., 1.05*h, '%d'%int(h),\n",
    "                ha='center', va='bottom')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overridden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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"
    }
   ],
   "source": [
    "ind = np.arange(len(names))\n",
    "width=0.3\n",
    "max_x=max(max(positive),max(negative))+2\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot()\n",
    "\n",
    "yvals = positive\n",
    "rects1 = ax.bar(ind, yvals, width, color='g')\n",
    "zvals = negative\n",
    "rects2 = ax.bar(ind+width, zvals, width, color='r')\n",
    "\n",
    "ax.set_xlabel('Names')\n",
    "ax.set_ylabel('Sentiment')\n",
    "\n",
    "ax.set_xticks(ind+width)\n",
    "ax.set_yticks(np.arange(0,max_x,1))\n",
    "ax.set_xticklabels( names )\n",
    "ax.legend( (rects1[0], rects2[0]), ('positive', 'negative') )\n",
    "ax.set_title('Whatsapp Chat Sentiment Analysis')\n",
    "\n",
    "\n",
    "autolabel(rects1)\n",
    "autolabel(rects2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}