text analysis (1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "import string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.corpus import stopwords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('finale.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>year</th>\n",
       "      <th>Form No : (Sample Year/01)</th>\n",
       "      <th>Lable</th>\n",
       "      <th>Q.1 The content was as described in publicity materials</th>\n",
       "      <th>Q.2 The workshop was applicable to my job</th>\n",
       "      <th>Q.3 I'll recommend this workshop to other conservators.</th>\n",
       "      <th>Q.4 The program was well paced within the allotted time</th>\n",
       "      <th>Q.5 The instructor was a good communicator</th>\n",
       "      <th>Q.6 The material was presented in an organized manner</th>\n",
       "      <th>...</th>\n",
       "      <th>Q.19 Please indicate your top area of specialization using the list below</th>\n",
       "      <th>Q.20 I'd be able to do y work better if I knew more about</th>\n",
       "      <th>Q.21 Topic 1 : Please describe the first of top two topics you would like to learn more about in the next 12 months</th>\n",
       "      <th>Q.22 Topic 1: Preferred Level</th>\n",
       "      <th>Q.23 Topic 1 : Preferred duration of program(days)</th>\n",
       "      <th>Q.24 Topic 1: Preferred Format</th>\n",
       "      <th>Q.25 Topic 2 : Please describe the first of top two topics you would like to learn more about in the next 12 months</th>\n",
       "      <th>Q.26 Topic 2 : Preferred duration of program(days)</th>\n",
       "      <th>Q.27 Topic 2: Preferred Level</th>\n",
       "      <th>Q.28 Topic 2: Preferred Format</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017_01</td>\n",
       "      <td>2017</td>\n",
       "      <td>1</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>R tool</td>\n",
       "      <td>Artificial Intelligence</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "      <td>IOT and knowledge about Ardunio Uno (Programming)</td>\n",
       "      <td>14</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017_02</td>\n",
       "      <td>2017</td>\n",
       "      <td>2</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Deep learning using python</td>\n",
       "      <td>NLP- Discussion of all processing units.</td>\n",
       "      <td>2.0</td>\n",
       "      <td>14</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Application of NLP process(sentimental analysi...</td>\n",
       "      <td>14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017_03</td>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Conservation education</td>\n",
       "      <td>Application of R to business analytics</td>\n",
       "      <td>Business analytics with R for managers</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Business Analytics:Overview/ Handson various t...</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017_04</td>\n",
       "      <td>2017</td>\n",
       "      <td>4</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>Conservation administration</td>\n",
       "      <td>Data analytics and Visualization</td>\n",
       "      <td>Data Visualization using R language</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Visual analytics</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017_05</td>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Architecture</td>\n",
       "      <td>Big data analytics in practical aspects</td>\n",
       "      <td>Machine learning</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Recommender system</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2017_06</td>\n",
       "      <td>2017</td>\n",
       "      <td>6</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Book And Paper</td>\n",
       "      <td>Application of soft computing in software engi...</td>\n",
       "      <td>MATLAb</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>IOT</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2017_07</td>\n",
       "      <td>2017</td>\n",
       "      <td>7</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Book And Paper</td>\n",
       "      <td>NaN</td>\n",
       "      <td>network</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>MANET SECURITY</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017_08</td>\n",
       "      <td>2017</td>\n",
       "      <td>8</td>\n",
       "      <td>Positive</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>Conservation education</td>\n",
       "      <td>Data Analytics and R language</td>\n",
       "      <td>R Language</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Machine Learning</td>\n",
       "      <td>7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2017_09</td>\n",
       "      <td>2017</td>\n",
       "      <td>9</td>\n",
       "      <td>Negative</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Objects</td>\n",
       "      <td>NaN</td>\n",
       "      <td>genetic algorithm</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Statistical technique</td>\n",
       "      <td>15</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2017_10</td>\n",
       "      <td>2017</td>\n",
       "      <td>10</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Architecture</td>\n",
       "      <td>Real Application that can be used for researac...</td>\n",
       "      <td>formal Method</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Software Engineering</td>\n",
       "      <td>14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2017_11</td>\n",
       "      <td>2017</td>\n",
       "      <td>11</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Architecture</td>\n",
       "      <td>Algorithmic details and applications</td>\n",
       "      <td>Formal methods</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Software Engineering</td>\n",
       "      <td>14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2017_12</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Architecture</td>\n",
       "      <td>The proper use of mathematical functions used ...</td>\n",
       "      <td>Formal methods</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Optimisataion</td>\n",
       "      <td>5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2017_13</td>\n",
       "      <td>2017</td>\n",
       "      <td>13</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Conservation science</td>\n",
       "      <td>Machine Learning techniques, supervised and un...</td>\n",
       "      <td>Introduction to Machine Learning using Neural ...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Recommended System</td>\n",
       "      <td>5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2017_14</td>\n",
       "      <td>2017</td>\n",
       "      <td>14</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Machine Learning</td>\n",
       "      <td>Machine Learning</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Self Study Material</td>\n",
       "      <td>Statistics</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Self Study Material</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2017_15</td>\n",
       "      <td>2017</td>\n",
       "      <td>15</td>\n",
       "      <td>Negative</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>Natural Science</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neural Network</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "      <td>Fuzzy System</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Self Study Material</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2017_16</td>\n",
       "      <td>2017</td>\n",
       "      <td>16</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Natural Science</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neural Network and Pattern Recognition</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>R Norm Software</td>\n",
       "      <td>7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2017_17</td>\n",
       "      <td>2017</td>\n",
       "      <td>17</td>\n",
       "      <td>Positive</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Sentiment Analysis and Machine Learning</td>\n",
       "      <td>Sentiment Analysis</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14</td>\n",
       "      <td>Self Study Material</td>\n",
       "      <td>Machine Learning</td>\n",
       "      <td>14</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2017_18</td>\n",
       "      <td>2017</td>\n",
       "      <td>18</td>\n",
       "      <td>Positive</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Natural Language Processing and Python</td>\n",
       "      <td>Natural Language Processing with NLTK</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Information Retrieval with R/ Python/ NLTK</td>\n",
       "      <td>14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2017_19</td>\n",
       "      <td>2017</td>\n",
       "      <td>19</td>\n",
       "      <td>Negative</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>R plots and their significance, Prof. have don...</td>\n",
       "      <td>R plots and its significance</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2017_20</td>\n",
       "      <td>2017</td>\n",
       "      <td>20</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Natural Science</td>\n",
       "      <td>Bio-Inspired Optimisations</td>\n",
       "      <td>Honey Bee and swarm optimisation</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Non-linear optimisation tool</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2017_21</td>\n",
       "      <td>2017</td>\n",
       "      <td>21</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>Conservation education</td>\n",
       "      <td>Machine learning and genetic algorithm. Latest...</td>\n",
       "      <td>machine learning</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Genetic algorithm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2017_22</td>\n",
       "      <td>2017</td>\n",
       "      <td>22</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Conservation education</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2017_23</td>\n",
       "      <td>2017</td>\n",
       "      <td>23</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Statistics and neural networks</td>\n",
       "      <td>Statistics</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "      <td>Machine learning techniques</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2017_24</td>\n",
       "      <td>2017</td>\n",
       "      <td>24</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Book And Paper</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Open CV</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2017_25</td>\n",
       "      <td>2017</td>\n",
       "      <td>25</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Electronic Media</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Machine Learning and Internet of Things</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>Self Study Material</td>\n",
       "      <td>Big Data Analysis</td>\n",
       "      <td>10</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Self Study Material</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2017_26</td>\n",
       "      <td>2017</td>\n",
       "      <td>26</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Natural Science</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Advanced Machine Learning</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "      <td>Use of Big Data analytics for industrial appli...</td>\n",
       "      <td>5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2017_27</td>\n",
       "      <td>2017</td>\n",
       "      <td>27</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Data Analytics and Machine learning</td>\n",
       "      <td>Health Care Analysis with performance guarentee</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10</td>\n",
       "      <td>others</td>\n",
       "      <td>Cloud computing for textile</td>\n",
       "      <td>10</td>\n",
       "      <td>3.0</td>\n",
       "      <td>others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2017_28</td>\n",
       "      <td>2017</td>\n",
       "      <td>28</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Genetic Algorithms</td>\n",
       "      <td>Genetic Algorithms</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Natural Language Processing</td>\n",
       "      <td>15</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2017_29</td>\n",
       "      <td>2017</td>\n",
       "      <td>29</td>\n",
       "      <td>Negative</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>Objects</td>\n",
       "      <td>Reliability and Maintenance Analysis and Optim...</td>\n",
       "      <td>Reliability and Maintenance System</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Optimization Techniques</td>\n",
       "      <td>7</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2017_30</td>\n",
       "      <td>2017</td>\n",
       "      <td>30</td>\n",
       "      <td>Positive</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>How to implement some machine learning algorithms</td>\n",
       "      <td>Software defined networking</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "      <td>Deep learning and neural networks</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2017_31</td>\n",
       "      <td>2017</td>\n",
       "      <td>31</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Conservation education</td>\n",
       "      <td>Data Analysis</td>\n",
       "      <td>Data Analysis</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Recommender System</td>\n",
       "      <td>5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2017_32</td>\n",
       "      <td>2017</td>\n",
       "      <td>32</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Controlling my curiosity that forces me to ans...</td>\n",
       "      <td>Support Vector M/C</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "      <td>Social Networks</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2017_33</td>\n",
       "      <td>2017</td>\n",
       "      <td>33</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Book And Paper</td>\n",
       "      <td>Mathematical Modelling</td>\n",
       "      <td>Python</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Image Processing</td>\n",
       "      <td>14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2017_34</td>\n",
       "      <td>2017</td>\n",
       "      <td>34</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Natural Science</td>\n",
       "      <td>RStudio</td>\n",
       "      <td>Genetic Algorithm</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Machine Learning using neural networks.</td>\n",
       "      <td>7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2017_35</td>\n",
       "      <td>2017</td>\n",
       "      <td>35</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Data Analysis using R</td>\n",
       "      <td>Data Analysis using R MATLAB</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Quality Control(Statistical)</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2017_36</td>\n",
       "      <td>2017</td>\n",
       "      <td>36</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Conservation education</td>\n",
       "      <td>Machine Learning</td>\n",
       "      <td>Neural Networks,Deep Learning</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Machine Learning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2018_01</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>Positive</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Electronic Media</td>\n",
       "      <td>Language, syntax and logic</td>\n",
       "      <td>Data mining and machine learning</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Genetic Algorithm</td>\n",
       "      <td>10</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2018_02</td>\n",
       "      <td>2018</td>\n",
       "      <td>2</td>\n",
       "      <td>Negative</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>Electronic Media</td>\n",
       "      <td>machine learning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2018_03</td>\n",
       "      <td>2018</td>\n",
       "      <td>3</td>\n",
       "      <td>Positive</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>technology</td>\n",
       "      <td>Programming</td>\n",
       "      <td>2.0</td>\n",
       "      <td>20</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Painting</td>\n",
       "      <td>20</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2018_04</td>\n",
       "      <td>2018</td>\n",
       "      <td>4</td>\n",
       "      <td>Negative</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Statistical tools</td>\n",
       "      <td>Programming in Statistical tools</td>\n",
       "      <td>2.0</td>\n",
       "      <td>any</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Data mining</td>\n",
       "      <td>any</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2018_05</td>\n",
       "      <td>2018</td>\n",
       "      <td>5</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Natural Science</td>\n",
       "      <td>R and algorithms discussed in course</td>\n",
       "      <td>Python based learning and algorithm generation</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Matlab tools specially analytical / statistica...</td>\n",
       "      <td>5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2018_06</td>\n",
       "      <td>2018</td>\n",
       "      <td>6</td>\n",
       "      <td>Negative</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>Objects</td>\n",
       "      <td>linking of matlab and R</td>\n",
       "      <td>Advance Machine learning based on ANN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Machine learning based on deep neural networks</td>\n",
       "      <td>05-Oct</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2018_07</td>\n",
       "      <td>2018</td>\n",
       "      <td>7</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Machine learning using python</td>\n",
       "      <td>2.0</td>\n",
       "      <td>05-Oct</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2018_08</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>Positive</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>upcoming technologies</td>\n",
       "      <td>data mining</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>animation</td>\n",
       "      <td>7</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2018_09</td>\n",
       "      <td>2018</td>\n",
       "      <td>9</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Big data</td>\n",
       "      <td>1.0</td>\n",
       "      <td>20-30</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2018_10</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Natural Science</td>\n",
       "      <td>Data Visualisation</td>\n",
       "      <td>Data Collection</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "      <td>Data Processing</td>\n",
       "      <td>15</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2018_11</td>\n",
       "      <td>2018</td>\n",
       "      <td>11</td>\n",
       "      <td>Positive</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Conservation education</td>\n",
       "      <td>Machine learning and recommendation system</td>\n",
       "      <td>Recommendation System</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>NaN</td>\n",
       "      <td>R</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Self Study Material</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2018_12</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Book And Paper</td>\n",
       "      <td>MI</td>\n",
       "      <td>Deep Learning</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "      <td>MI and Data Mining</td>\n",
       "      <td>5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2018_13</td>\n",
       "      <td>2018</td>\n",
       "      <td>13</td>\n",
       "      <td>Negative</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>Interpretation of results produced by R for a ...</td>\n",
       "      <td>understanding statistical techniques for Data ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Web based follow-up with industry experts for ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2018_14</td>\n",
       "      <td>2018</td>\n",
       "      <td>14</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Others</td>\n",
       "      <td>working on HADOOP/spark</td>\n",
       "      <td>Big Data - HADOOP/SPARK</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Big data - Python</td>\n",
       "      <td>7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2018_15</td>\n",
       "      <td>2018</td>\n",
       "      <td>15</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Conservation science</td>\n",
       "      <td>The recents advancements in supervised, unsupe...</td>\n",
       "      <td>Recommender System</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>MAchine learning using neural networks</td>\n",
       "      <td>5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2018_16</td>\n",
       "      <td>2018</td>\n",
       "      <td>16</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Electronic Media</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2018_17</td>\n",
       "      <td>2018</td>\n",
       "      <td>17</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Architecture</td>\n",
       "      <td>Data mining Techniques</td>\n",
       "      <td>Big data Analytics Techniques</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Tools used to explore Big Data</td>\n",
       "      <td>4</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2018_18</td>\n",
       "      <td>2018</td>\n",
       "      <td>18</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Architecture</td>\n",
       "      <td>image processing techniques</td>\n",
       "      <td>image processing with feature extraction</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Tools used to implement features in images and...</td>\n",
       "      <td>10</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2018_19</td>\n",
       "      <td>2018</td>\n",
       "      <td>19</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Natural Science</td>\n",
       "      <td>the concept of ontology</td>\n",
       "      <td>ontology matching algorithms</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Match selection</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>55 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         ID  year  Form No : (Sample Year/01)     Lable  \\\n",
       "0   2017_01  2017                           1  Positive   \n",
       "1   2017_02  2017                           2  Positive   \n",
       "2   2017_03  2017                           3  Positive   \n",
       "3   2017_04  2017                           4  Positive   \n",
       "4   2017_05  2017                           5  Positive   \n",
       "5   2017_06  2017                           6  Positive   \n",
       "6   2017_07  2017                           7  Positive   \n",
       "7   2017_08  2017                           8  Positive   \n",
       "8   2017_09  2017                           9  Negative   \n",
       "9   2017_10  2017                          10  Positive   \n",
       "10  2017_11  2017                          11  Positive   \n",
       "11  2017_12  2017                          12  Positive   \n",
       "12  2017_13  2017                          13  Positive   \n",
       "13  2017_14  2017                          14  Positive   \n",
       "14  2017_15  2017                          15  Negative   \n",
       "15  2017_16  2017                          16  Positive   \n",
       "16  2017_17  2017                          17  Positive   \n",
       "17  2017_18  2017                          18  Positive   \n",
       "18  2017_19  2017                          19  Negative   \n",
       "19  2017_20  2017                          20  Positive   \n",
       "20  2017_21  2017                          21  Positive   \n",
       "21  2017_22  2017                          22  Positive   \n",
       "22  2017_23  2017                          23  Positive   \n",
       "23  2017_24  2017                          24  Positive   \n",
       "24  2017_25  2017                          25  Positive   \n",
       "25  2017_26  2017                          26  Positive   \n",
       "26  2017_27  2017                          27  Positive   \n",
       "27  2017_28  2017                          28  Positive   \n",
       "28  2017_29  2017                          29  Negative   \n",
       "29  2017_30  2017                          30  Positive   \n",
       "30  2017_31  2017                          31  Positive   \n",
       "31  2017_32  2017                          32  Negative   \n",
       "32  2017_33  2017                          33  Positive   \n",
       "33  2017_34  2017                          34  Positive   \n",
       "34  2017_35  2017                          35  Positive   \n",
       "35  2017_36  2017                          36  Positive   \n",
       "36  2018_01  2018                           1  Positive   \n",
       "37  2018_02  2018                           2  Negative   \n",
       "38  2018_03  2018                           3  Positive   \n",
       "39  2018_04  2018                           4  Negative   \n",
       "40  2018_05  2018                           5  Positive   \n",
       "41  2018_06  2018                           6  Negative   \n",
       "42  2018_07  2018                           7  Positive   \n",
       "43  2018_08  2018                           8  Positive   \n",
       "44  2018_09  2018                           9  Positive   \n",
       "45  2018_10  2018                          10  Positive   \n",
       "46  2018_11  2018                          11  Positive   \n",
       "47  2018_12  2018                          12  Positive   \n",
       "48  2018_13  2018                          13  Negative   \n",
       "49  2018_14  2018                          14  Positive   \n",
       "50  2018_15  2018                          15  Positive   \n",
       "51  2018_16  2018                          16  Positive   \n",
       "52  2018_17  2018                          17  Positive   \n",
       "53  2018_18  2018                          18  Positive   \n",
       "54  2018_19  2018                          19  Positive   \n",
       "\n",
       "    Q.1 The content was as described in publicity materials  \\\n",
       "0                                                 4.0         \n",
       "1                                                 5.0         \n",
       "2                                                 4.0         \n",
       "3                                                 4.0         \n",
       "4                                                 4.0         \n",
       "5                                                 5.0         \n",
       "6                                                 5.0         \n",
       "7                                                 2.0         \n",
       "8                                                 2.0         \n",
       "9                                                 5.0         \n",
       "10                                                5.0         \n",
       "11                                                4.0         \n",
       "12                                                4.0         \n",
       "13                                                4.0         \n",
       "14                                                3.0         \n",
       "15                                                4.0         \n",
       "16                                                3.0         \n",
       "17                                                3.0         \n",
       "18                                                5.0         \n",
       "19                                                5.0         \n",
       "20                                                5.0         \n",
       "21                                                5.0         \n",
       "22                                                5.0         \n",
       "23                                                5.0         \n",
       "24                                                5.0         \n",
       "25                                                5.0         \n",
       "26                                                5.0         \n",
       "27                                                5.0         \n",
       "28                                                2.0         \n",
       "29                                                3.0         \n",
       "30                                                4.0         \n",
       "31                                                NaN         \n",
       "32                                                4.0         \n",
       "33                                                5.0         \n",
       "34                                                4.0         \n",
       "35                                                4.0         \n",
       "36                                                3.0         \n",
       "37                                                2.0         \n",
       "38                                                3.0         \n",
       "39                                                4.0         \n",
       "40                                                5.0         \n",
       "41                                                2.0         \n",
       "42                                                5.0         \n",
       "43                                                3.0         \n",
       "44                                                5.0         \n",
       "45                                                5.0         \n",
       "46                                                2.0         \n",
       "47                                                4.0         \n",
       "48                                                2.0         \n",
       "49                                                5.0         \n",
       "50                                                4.0         \n",
       "51                                                5.0         \n",
       "52                                                4.0         \n",
       "53                                                4.0         \n",
       "54                                                5.0         \n",
       "\n",
       "    Q.2 The workshop was applicable to my job  \\\n",
       "0                                           4   \n",
       "1                                           4   \n",
       "2                                           4   \n",
       "3                                           4   \n",
       "4                                           4   \n",
       "5                                           5   \n",
       "6                                           3   \n",
       "7                                           3   \n",
       "8                                           2   \n",
       "9                                           4   \n",
       "10                                          4   \n",
       "11                                          3   \n",
       "12                                          3   \n",
       "13                                          4   \n",
       "14                                          3   \n",
       "15                                          4   \n",
       "16                                          4   \n",
       "17                                          3   \n",
       "18                                          1   \n",
       "19                                          5   \n",
       "20                                          3   \n",
       "21                                          3   \n",
       "22                                          5   \n",
       "23                                          5   \n",
       "24                                          3   \n",
       "25                                          4   \n",
       "26                                          4   \n",
       "27                                          5   \n",
       "28                                          3   \n",
       "29                                          3   \n",
       "30                                          4   \n",
       "31                                          1   \n",
       "32                                          2   \n",
       "33                                          5   \n",
       "34                                          4   \n",
       "35                                          4   \n",
       "36                                          4   \n",
       "37                                          1   \n",
       "38                                          4   \n",
       "39                                          1   \n",
       "40                                          3   \n",
       "41                                          3   \n",
       "42                                          5   \n",
       "43                                          3   \n",
       "44                                          5   \n",
       "45                                          5   \n",
       "46                                          4   \n",
       "47                                          5   \n",
       "48                                          3   \n",
       "49                                          4   \n",
       "50                                          5   \n",
       "51                                          4   \n",
       "52                                          5   \n",
       "53                                          4   \n",
       "54                                          5   \n",
       "\n",
       "    Q.3 I'll recommend this workshop to other conservators.  \\\n",
       "0                                                   4         \n",
       "1                                                   5         \n",
       "2                                                   4         \n",
       "3                                                   4         \n",
       "4                                                   5         \n",
       "5                                                   5         \n",
       "6                                                   5         \n",
       "7                                                   2         \n",
       "8                                                   4         \n",
       "9                                                   5         \n",
       "10                                                  5         \n",
       "11                                                  4         \n",
       "12                                                  5         \n",
       "13                                                  2         \n",
       "14                                                  2         \n",
       "15                                                  5         \n",
       "16                                                  4         \n",
       "17                                                  4         \n",
       "18                                                  1         \n",
       "19                                                  4         \n",
       "20                                                  5         \n",
       "21                                                  4         \n",
       "22                                                  5         \n",
       "23                                                  5         \n",
       "24                                                  4         \n",
       "25                                                  5         \n",
       "26                                                  4         \n",
       "27                                                  5         \n",
       "28                                                  3         \n",
       "29                                                  4         \n",
       "30                                                  4         \n",
       "31                                                  1         \n",
       "32                                                  5         \n",
       "33                                                  5         \n",
       "34                                                  3         \n",
       "35                                                  4         \n",
       "36                                                  4         \n",
       "37                                                  1         \n",
       "38                                                  4         \n",
       "39                                                  3         \n",
       "40                                                  3         \n",
       "41                                                  3         \n",
       "42                                                  5         \n",
       "43                                                  4         \n",
       "44                                                  5         \n",
       "45                                                  4         \n",
       "46                                                  5         \n",
       "47                                                  5         \n",
       "48                                                  3         \n",
       "49                                                  5         \n",
       "50                                                  5         \n",
       "51                                                  5         \n",
       "52                                                  5         \n",
       "53                                                  4         \n",
       "54                                                  5         \n",
       "\n",
       "    Q.4 The program was well paced within the allotted time  \\\n",
       "0                                                   5         \n",
       "1                                                   5         \n",
       "2                                                   3         \n",
       "3                                                   3         \n",
       "4                                                   5         \n",
       "5                                                   5         \n",
       "6                                                   5         \n",
       "7                                                   1         \n",
       "8                                                   5         \n",
       "9                                                   5         \n",
       "10                                                  5         \n",
       "11                                                  5         \n",
       "12                                                  5         \n",
       "13                                                  4         \n",
       "14                                                  2         \n",
       "15                                                  2         \n",
       "16                                                  4         \n",
       "17                                                  4         \n",
       "18                                                  5         \n",
       "19                                                  5         \n",
       "20                                                  3         \n",
       "21                                                  3         \n",
       "22                                                  5         \n",
       "23                                                  4         \n",
       "24                                                  3         \n",
       "25                                                  5         \n",
       "26                                                  4         \n",
       "27                                                  4         \n",
       "28                                                  2         \n",
       "29                                                  3         \n",
       "30                                                  5         \n",
       "31                                                  4         \n",
       "32                                                  5         \n",
       "33                                                  5         \n",
       "34                                                  4         \n",
       "35                                                  4         \n",
       "36                                                  4         \n",
       "37                                                  2         \n",
       "38                                                  3         \n",
       "39                                                  1         \n",
       "40                                                  5         \n",
       "41                                                  2         \n",
       "42                                                  5         \n",
       "43                                                  5         \n",
       "44                                                  5         \n",
       "45                                                  3         \n",
       "46                                                  4         \n",
       "47                                                  5         \n",
       "48                                                  2         \n",
       "49                                                  5         \n",
       "50                                                  4         \n",
       "51                                                  5         \n",
       "52                                                  5         \n",
       "53                                                  3         \n",
       "54                                                  4         \n",
       "\n",
       "    Q.5 The instructor was a good communicator   \\\n",
       "0                                             4   \n",
       "1                                             5   \n",
       "2                                             4   \n",
       "3                                             4   \n",
       "4                                             4   \n",
       "5                                             4   \n",
       "6                                             5   \n",
       "7                                             1   \n",
       "8                                             4   \n",
       "9                                             4   \n",
       "10                                            5   \n",
       "11                                            4   \n",
       "12                                            5   \n",
       "13                                            3   \n",
       "14                                            3   \n",
       "15                                            3   \n",
       "16                                            5   \n",
       "17                                            4   \n",
       "18                                            3   \n",
       "19                                            4   \n",
       "20                                            5   \n",
       "21                                            5   \n",
       "22                                            5   \n",
       "23                                            4   \n",
       "24                                            4   \n",
       "25                                            5   \n",
       "26                                            5   \n",
       "27                                            5   \n",
       "28                                            3   \n",
       "29                                            2   \n",
       "30                                            5   \n",
       "31                                            3   \n",
       "32                                            5   \n",
       "33                                            5   \n",
       "34                                            4   \n",
       "35                                            5   \n",
       "36                                            5   \n",
       "37                                            1   \n",
       "38                                            4   \n",
       "39                                            2   \n",
       "40                                            5   \n",
       "41                                            2   \n",
       "42                                            5   \n",
       "43                                            5   \n",
       "44                                            5   \n",
       "45                                            4   \n",
       "46                                            5   \n",
       "47                                            4   \n",
       "48                                            5   \n",
       "49                                            5   \n",
       "50                                            5   \n",
       "51                                            4   \n",
       "52                                            4   \n",
       "53                                            4   \n",
       "54                                            5   \n",
       "\n",
       "    Q.6 The material was presented in an organized manner  \\\n",
       "0                                                   5       \n",
       "1                                                   4       \n",
       "2                                                   5       \n",
       "3                                                   3       \n",
       "4                                                   5       \n",
       "5                                                   5       \n",
       "6                                                   5       \n",
       "7                                                   1       \n",
       "8                                                   4       \n",
       "9                                                   5       \n",
       "10                                                  5       \n",
       "11                                                  5       \n",
       "12                                                  5       \n",
       "13                                                  3       \n",
       "14                                                  2       \n",
       "15                                                  4       \n",
       "16                                                  5       \n",
       "17                                                  4       \n",
       "18                                                  5       \n",
       "19                                                  5       \n",
       "20                                                  3       \n",
       "21                                                  4       \n",
       "22                                                  4       \n",
       "23                                                  5       \n",
       "24                                                  4       \n",
       "25                                                  5       \n",
       "26                                                  4       \n",
       "27                                                  5       \n",
       "28                                                  2       \n",
       "29                                                  3       \n",
       "30                                                  4       \n",
       "31                                                  1       \n",
       "32                                                  4       \n",
       "33                                                  5       \n",
       "34                                                  4       \n",
       "35                                                  4       \n",
       "36                                                  4       \n",
       "37                                                  3       \n",
       "38                                                  5       \n",
       "39                                                  2       \n",
       "40                                                  5       \n",
       "41                                                  2       \n",
       "42                                                  5       \n",
       "43                                                  5       \n",
       "44                                                  5       \n",
       "45                                                  4       \n",
       "46                                                  5       \n",
       "47                                                  4       \n",
       "48                                                  3       \n",
       "49                                                  5       \n",
       "50                                                  5       \n",
       "51                                                  5       \n",
       "52                                                  4       \n",
       "53                                                  4       \n",
       "54                                                  4       \n",
       "\n",
       "                         ...                        \\\n",
       "0                        ...                         \n",
       "1                        ...                         \n",
       "2                        ...                         \n",
       "3                        ...                         \n",
       "4                        ...                         \n",
       "5                        ...                         \n",
       "6                        ...                         \n",
       "7                        ...                         \n",
       "8                        ...                         \n",
       "9                        ...                         \n",
       "10                       ...                         \n",
       "11                       ...                         \n",
       "12                       ...                         \n",
       "13                       ...                         \n",
       "14                       ...                         \n",
       "15                       ...                         \n",
       "16                       ...                         \n",
       "17                       ...                         \n",
       "18                       ...                         \n",
       "19                       ...                         \n",
       "20                       ...                         \n",
       "21                       ...                         \n",
       "22                       ...                         \n",
       "23                       ...                         \n",
       "24                       ...                         \n",
       "25                       ...                         \n",
       "26                       ...                         \n",
       "27                       ...                         \n",
       "28                       ...                         \n",
       "29                       ...                         \n",
       "30                       ...                         \n",
       "31                       ...                         \n",
       "32                       ...                         \n",
       "33                       ...                         \n",
       "34                       ...                         \n",
       "35                       ...                         \n",
       "36                       ...                         \n",
       "37                       ...                         \n",
       "38                       ...                         \n",
       "39                       ...                         \n",
       "40                       ...                         \n",
       "41                       ...                         \n",
       "42                       ...                         \n",
       "43                       ...                         \n",
       "44                       ...                         \n",
       "45                       ...                         \n",
       "46                       ...                         \n",
       "47                       ...                         \n",
       "48                       ...                         \n",
       "49                       ...                         \n",
       "50                       ...                         \n",
       "51                       ...                         \n",
       "52                       ...                         \n",
       "53                       ...                         \n",
       "54                       ...                         \n",
       "\n",
       "    Q.19 Please indicate your top area of specialization using the list below  \\\n",
       "0                                                 NaN                           \n",
       "1                                              Others                           \n",
       "2                              Conservation education                           \n",
       "3                         Conservation administration                           \n",
       "4                                        Architecture                           \n",
       "5                                      Book And Paper                           \n",
       "6                                      Book And Paper                           \n",
       "7                              Conservation education                           \n",
       "8                                             Objects                           \n",
       "9                                        Architecture                           \n",
       "10                                       Architecture                           \n",
       "11                                       Architecture                           \n",
       "12                               Conservation science                           \n",
       "13                                             Others                           \n",
       "14                                    Natural Science                           \n",
       "15                                    Natural Science                           \n",
       "16                                             Others                           \n",
       "17                                             Others                           \n",
       "18                                             Others                           \n",
       "19                                    Natural Science                           \n",
       "20                             Conservation education                           \n",
       "21                             Conservation education                           \n",
       "22                                             Others                           \n",
       "23                                     Book And Paper                           \n",
       "24                                   Electronic Media                           \n",
       "25                                    Natural Science                           \n",
       "26                                             Others                           \n",
       "27                                             Others                           \n",
       "28                                            Objects                           \n",
       "29                                             Others                           \n",
       "30                             Conservation education                           \n",
       "31                                             Others                           \n",
       "32                                     Book And Paper                           \n",
       "33                                    Natural Science                           \n",
       "34                                             Others                           \n",
       "35                             Conservation education                           \n",
       "36                                   Electronic Media                           \n",
       "37                                   Electronic Media                           \n",
       "38                                             Others                           \n",
       "39                                             Others                           \n",
       "40                                    Natural Science                           \n",
       "41                                            Objects                           \n",
       "42                                                NaN                           \n",
       "43                                             Others                           \n",
       "44                                                NaN                           \n",
       "45                                    Natural Science                           \n",
       "46                             Conservation education                           \n",
       "47                                     Book And Paper                           \n",
       "48                                             Others                           \n",
       "49                                             Others                           \n",
       "50                               Conservation science                           \n",
       "51                                   Electronic Media                           \n",
       "52                                       Architecture                           \n",
       "53                                       Architecture                           \n",
       "54                                    Natural Science                           \n",
       "\n",
       "    Q.20 I'd be able to do y work better if I knew more about  \\\n",
       "0                                              R tool           \n",
       "1                          Deep learning using python           \n",
       "2              Application of R to business analytics           \n",
       "3                    Data analytics and Visualization           \n",
       "4             Big data analytics in practical aspects           \n",
       "5   Application of soft computing in software engi...           \n",
       "6                                                 NaN           \n",
       "7                       Data Analytics and R language           \n",
       "8                                                 NaN           \n",
       "9   Real Application that can be used for researac...           \n",
       "10               Algorithmic details and applications           \n",
       "11  The proper use of mathematical functions used ...           \n",
       "12  Machine Learning techniques, supervised and un...           \n",
       "13                                   Machine Learning           \n",
       "14                                                NaN           \n",
       "15                                                NaN           \n",
       "16            Sentiment Analysis and Machine Learning           \n",
       "17             Natural Language Processing and Python           \n",
       "18  R plots and their significance, Prof. have don...           \n",
       "19                         Bio-Inspired Optimisations           \n",
       "20  Machine learning and genetic algorithm. Latest...           \n",
       "21                                                NaN           \n",
       "22                     Statistics and neural networks           \n",
       "23                                                NaN           \n",
       "24                                                NaN           \n",
       "25                                                NaN           \n",
       "26                Data Analytics and Machine learning           \n",
       "27                                 Genetic Algorithms           \n",
       "28  Reliability and Maintenance Analysis and Optim...           \n",
       "29  How to implement some machine learning algorithms           \n",
       "30                                      Data Analysis           \n",
       "31  Controlling my curiosity that forces me to ans...           \n",
       "32                             Mathematical Modelling           \n",
       "33                                            RStudio           \n",
       "34                              Data Analysis using R           \n",
       "35                                   Machine Learning           \n",
       "36                         Language, syntax and logic           \n",
       "37                                   machine learning           \n",
       "38                                         technology           \n",
       "39                                  Statistical tools           \n",
       "40               R and algorithms discussed in course           \n",
       "41                            linking of matlab and R           \n",
       "42                                                NaN           \n",
       "43                              upcoming technologies           \n",
       "44                                                NaN           \n",
       "45                                Data Visualisation            \n",
       "46         Machine learning and recommendation system           \n",
       "47                                                 MI           \n",
       "48  Interpretation of results produced by R for a ...           \n",
       "49                            working on HADOOP/spark           \n",
       "50  The recents advancements in supervised, unsupe...           \n",
       "51                                                NaN           \n",
       "52                             Data mining Techniques           \n",
       "53                        image processing techniques           \n",
       "54                            the concept of ontology           \n",
       "\n",
       "    Q.21 Topic 1 : Please describe the first of top two topics you would like to learn more about in the next 12 months  \\\n",
       "0                             Artificial Intelligence                                                                     \n",
       "1            NLP- Discussion of all processing units.                                                                     \n",
       "2              Business analytics with R for managers                                                                     \n",
       "3                 Data Visualization using R language                                                                     \n",
       "4                                    Machine learning                                                                     \n",
       "5                                              MATLAb                                                                     \n",
       "6                                             network                                                                     \n",
       "7                                          R Language                                                                     \n",
       "8                                  genetic algorithm                                                                      \n",
       "9                                       formal Method                                                                     \n",
       "10                                     Formal methods                                                                     \n",
       "11                                    Formal methods                                                                      \n",
       "12  Introduction to Machine Learning using Neural ...                                                                     \n",
       "13                                   Machine Learning                                                                     \n",
       "14                                     Neural Network                                                                     \n",
       "15            Neural Network and Pattern Recognition                                                                      \n",
       "16                                Sentiment Analysis                                                                      \n",
       "17              Natural Language Processing with NLTK                                                                     \n",
       "18                       R plots and its significance                                                                     \n",
       "19                   Honey Bee and swarm optimisation                                                                     \n",
       "20                                   machine learning                                                                     \n",
       "21                                                NaN                                                                     \n",
       "22                                         Statistics                                                                     \n",
       "23                                            Open CV                                                                     \n",
       "24            Machine Learning and Internet of Things                                                                     \n",
       "25                          Advanced Machine Learning                                                                     \n",
       "26    Health Care Analysis with performance guarentee                                                                     \n",
       "27                                 Genetic Algorithms                                                                     \n",
       "28                 Reliability and Maintenance System                                                                     \n",
       "29                        Software defined networking                                                                     \n",
       "30                                      Data Analysis                                                                     \n",
       "31                                 Support Vector M/C                                                                     \n",
       "32                                             Python                                                                     \n",
       "33                                  Genetic Algorithm                                                                     \n",
       "34                       Data Analysis using R MATLAB                                                                     \n",
       "35                      Neural Networks,Deep Learning                                                                     \n",
       "36                   Data mining and machine learning                                                                     \n",
       "37                                                NaN                                                                     \n",
       "38                                        Programming                                                                     \n",
       "39                   Programming in Statistical tools                                                                     \n",
       "40     Python based learning and algorithm generation                                                                     \n",
       "41              Advance Machine learning based on ANN                                                                     \n",
       "42                      Machine learning using python                                                                     \n",
       "43                                        data mining                                                                     \n",
       "44                                           Big data                                                                     \n",
       "45                                    Data Collection                                                                     \n",
       "46                              Recommendation System                                                                     \n",
       "47                                      Deep Learning                                                                     \n",
       "48  understanding statistical techniques for Data ...                                                                     \n",
       "49                            Big Data - HADOOP/SPARK                                                                     \n",
       "50                                 Recommender System                                                                     \n",
       "51                                                NaN                                                                     \n",
       "52                      Big data Analytics Techniques                                                                     \n",
       "53           image processing with feature extraction                                                                     \n",
       "54                       ontology matching algorithms                                                                     \n",
       "\n",
       "    Q.22 Topic 1: Preferred Level  \\\n",
       "0                             3.0   \n",
       "1                             2.0   \n",
       "2                             3.0   \n",
       "3                             2.0   \n",
       "4                             3.0   \n",
       "5                             2.0   \n",
       "6                             2.0   \n",
       "7                             3.0   \n",
       "8                             3.0   \n",
       "9                             3.0   \n",
       "10                            3.0   \n",
       "11                            3.0   \n",
       "12                            3.0   \n",
       "13                            3.0   \n",
       "14                            2.0   \n",
       "15                            1.0   \n",
       "16                            3.0   \n",
       "17                            3.0   \n",
       "18                            3.0   \n",
       "19                            2.0   \n",
       "20                            2.0   \n",
       "21                            NaN   \n",
       "22                            1.0   \n",
       "23                            3.0   \n",
       "24                            2.0   \n",
       "25                            3.0   \n",
       "26                            3.0   \n",
       "27                            3.0   \n",
       "28                            2.0   \n",
       "29                            2.0   \n",
       "30                            2.0   \n",
       "31                            3.0   \n",
       "32                            3.0   \n",
       "33                            2.0   \n",
       "34                            1.0   \n",
       "35                            2.0   \n",
       "36                            3.0   \n",
       "37                            NaN   \n",
       "38                            2.0   \n",
       "39                            2.0   \n",
       "40                            2.0   \n",
       "41                            2.0   \n",
       "42                            2.0   \n",
       "43                            2.0   \n",
       "44                            1.0   \n",
       "45                            3.0   \n",
       "46                            3.0   \n",
       "47                            3.0   \n",
       "48                            1.0   \n",
       "49                            3.0   \n",
       "50                            3.0   \n",
       "51                            NaN   \n",
       "52                            3.0   \n",
       "53                            3.0   \n",
       "54                            2.0   \n",
       "\n",
       "    Q.23 Topic 1 : Preferred duration of program(days)  \\\n",
       "0                                                   7    \n",
       "1                                                  14    \n",
       "2                                                  10    \n",
       "3                                                   6    \n",
       "4                                                   3    \n",
       "5                                                   3    \n",
       "6                                                   3    \n",
       "7                                                   7    \n",
       "8                                                  15    \n",
       "9                                                  14    \n",
       "10                                                 14    \n",
       "11                                                 14    \n",
       "12                                                  5    \n",
       "13                                                NaN    \n",
       "14                                                NaN    \n",
       "15                                                  7    \n",
       "16                                                 14    \n",
       "17                                                 14    \n",
       "18                                                  7    \n",
       "19                                                  6    \n",
       "20                                                  7    \n",
       "21                                                NaN    \n",
       "22                                                NaN    \n",
       "23                                                  5    \n",
       "24                                                 10    \n",
       "25                                                  5    \n",
       "26                                                 10    \n",
       "27                                                 15    \n",
       "28                                                  7    \n",
       "29                                                  0    \n",
       "30                                                  5    \n",
       "31                                                NaN    \n",
       "32                                                 14    \n",
       "33                                                 10    \n",
       "34                                                  4    \n",
       "35                                                 10    \n",
       "36                                                 10    \n",
       "37                                                NaN    \n",
       "38                                                 20    \n",
       "39                                                any    \n",
       "40                                                  5    \n",
       "41                                                  5    \n",
       "42                                             05-Oct    \n",
       "43                                                  7    \n",
       "44                                              20-30    \n",
       "45                                                 15    \n",
       "46                                                 10    \n",
       "47                                                  5    \n",
       "48                                                  5    \n",
       "49                                                  7    \n",
       "50                                                  5    \n",
       "51                                                NaN    \n",
       "52                                                  4    \n",
       "53                                                  5    \n",
       "54                                                NaN    \n",
       "\n",
       "                    Q.24 Topic 1: Preferred Format  \\\n",
       "0   Interactive distance learning (i.e. web based)   \n",
       "1                                 Seminar/Workshop   \n",
       "2                                 Seminar/Workshop   \n",
       "3                                 Seminar/Workshop   \n",
       "4                                 Seminar/Workshop   \n",
       "5                                 Seminar/Workshop   \n",
       "6                                 Seminar/Workshop   \n",
       "7                                 Seminar/Workshop   \n",
       "8                                 Seminar/Workshop   \n",
       "9                                 Seminar/Workshop   \n",
       "10                                Seminar/Workshop   \n",
       "11                                Seminar/Workshop   \n",
       "12                                Seminar/Workshop   \n",
       "13                             Self Study Material   \n",
       "14  Interactive distance learning (i.e. web based)   \n",
       "15                                Seminar/Workshop   \n",
       "16                             Self Study Material   \n",
       "17                                Seminar/Workshop   \n",
       "18                                             NaN   \n",
       "19                                Seminar/Workshop   \n",
       "20                                Seminar/Workshop   \n",
       "21                                             NaN   \n",
       "22  Interactive distance learning (i.e. web based)   \n",
       "23                                Seminar/Workshop   \n",
       "24                             Self Study Material   \n",
       "25  Interactive distance learning (i.e. web based)   \n",
       "26                                          others   \n",
       "27                                Seminar/Workshop   \n",
       "28                                Seminar/Workshop   \n",
       "29  Interactive distance learning (i.e. web based)   \n",
       "30                                Seminar/Workshop   \n",
       "31  Interactive distance learning (i.e. web based)   \n",
       "32                                Seminar/Workshop   \n",
       "33                                Seminar/Workshop   \n",
       "34                                Seminar/Workshop   \n",
       "35                                Seminar/Workshop   \n",
       "36                                Seminar/Workshop   \n",
       "37                                             NaN   \n",
       "38                                Seminar/Workshop   \n",
       "39                                Seminar/Workshop   \n",
       "40                                Seminar/Workshop   \n",
       "41                                Seminar/Workshop   \n",
       "42                                Seminar/Workshop   \n",
       "43                                Seminar/Workshop   \n",
       "44                                Seminar/Workshop   \n",
       "45  Interactive distance learning (i.e. web based)   \n",
       "46                                Seminar/Workshop   \n",
       "47  Interactive distance learning (i.e. web based)   \n",
       "48                                Seminar/Workshop   \n",
       "49                                Seminar/Workshop   \n",
       "50                                Seminar/Workshop   \n",
       "51                                             NaN   \n",
       "52                                Seminar/Workshop   \n",
       "53                                Seminar/Workshop   \n",
       "54                                Seminar/Workshop   \n",
       "\n",
       "    Q.25 Topic 2 : Please describe the first of top two topics you would like to learn more about in the next 12 months  \\\n",
       "0   IOT and knowledge about Ardunio Uno (Programming)                                                                     \n",
       "1   Application of NLP process(sentimental analysi...                                                                     \n",
       "2   Business Analytics:Overview/ Handson various t...                                                                     \n",
       "3                                    Visual analytics                                                                     \n",
       "4                                 Recommender system                                                                      \n",
       "5                                                 IOT                                                                     \n",
       "6                                      MANET SECURITY                                                                     \n",
       "7                                   Machine Learning                                                                      \n",
       "8                               Statistical technique                                                                     \n",
       "9                               Software Engineering                                                                      \n",
       "10                               Software Engineering                                                                     \n",
       "11                                      Optimisataion                                                                     \n",
       "12                                 Recommended System                                                                     \n",
       "13                                         Statistics                                                                     \n",
       "14                                       Fuzzy System                                                                     \n",
       "15                                    R Norm Software                                                                     \n",
       "16                                   Machine Learning                                                                     \n",
       "17         Information Retrieval with R/ Python/ NLTK                                                                     \n",
       "18                                                NaN                                                                     \n",
       "19                       Non-linear optimisation tool                                                                     \n",
       "20                                  Genetic algorithm                                                                     \n",
       "21                                                NaN                                                                     \n",
       "22                        Machine learning techniques                                                                     \n",
       "23                                                NaN                                                                     \n",
       "24                                  Big Data Analysis                                                                     \n",
       "25  Use of Big Data analytics for industrial appli...                                                                     \n",
       "26                        Cloud computing for textile                                                                     \n",
       "27                        Natural Language Processing                                                                     \n",
       "28                            Optimization Techniques                                                                     \n",
       "29                  Deep learning and neural networks                                                                     \n",
       "30                                 Recommender System                                                                     \n",
       "31                                    Social Networks                                                                     \n",
       "32                                   Image Processing                                                                     \n",
       "33            Machine Learning using neural networks.                                                                     \n",
       "34                       Quality Control(Statistical)                                                                     \n",
       "35                                   Machine Learning                                                                     \n",
       "36                                  Genetic Algorithm                                                                     \n",
       "37                                                NaN                                                                     \n",
       "38                                           Painting                                                                     \n",
       "39                                        Data mining                                                                     \n",
       "40  Matlab tools specially analytical / statistica...                                                                     \n",
       "41     Machine learning based on deep neural networks                                                                     \n",
       "42                                                NaN                                                                     \n",
       "43                                          animation                                                                     \n",
       "44                                                NaN                                                                     \n",
       "45                                    Data Processing                                                                     \n",
       "46                                                NaN                                                                     \n",
       "47                                 MI and Data Mining                                                                     \n",
       "48  Web based follow-up with industry experts for ...                                                                     \n",
       "49                                  Big data - Python                                                                     \n",
       "50             MAchine learning using neural networks                                                                     \n",
       "51                                                NaN                                                                     \n",
       "52                     Tools used to explore Big Data                                                                     \n",
       "53  Tools used to implement features in images and...                                                                     \n",
       "54                                    Match selection                                                                     \n",
       "\n",
       "    Q.26 Topic 2 : Preferred duration of program(days)  \\\n",
       "0                                                  14    \n",
       "1                                                  14    \n",
       "2                                                  10    \n",
       "3                                                   4    \n",
       "4                                                   3    \n",
       "5                                                   3    \n",
       "6                                                   3    \n",
       "7                                                   7    \n",
       "8                                                  15    \n",
       "9                                                  14    \n",
       "10                                                 14    \n",
       "11                                                  5    \n",
       "12                                                  5    \n",
       "13                                                NaN    \n",
       "14                                                NaN    \n",
       "15                                                  7    \n",
       "16                                                 14    \n",
       "17                                                 14    \n",
       "18                                                NaN    \n",
       "19                                                NaN    \n",
       "20                                                NaN    \n",
       "21                                                NaN    \n",
       "22                                                NaN    \n",
       "23                                                NaN    \n",
       "24                                                 10    \n",
       "25                                                  5    \n",
       "26                                                 10    \n",
       "27                                                 15    \n",
       "28                                                  7    \n",
       "29                                                  0    \n",
       "30                                                  5    \n",
       "31                                                  2    \n",
       "32                                                 14    \n",
       "33                                                  7    \n",
       "34                                                  4    \n",
       "35                                                NaN    \n",
       "36                                                 10    \n",
       "37                                                NaN    \n",
       "38                                                 20    \n",
       "39                                                any    \n",
       "40                                                  5    \n",
       "41                                             05-Oct    \n",
       "42                                                NaN    \n",
       "43                                                  7    \n",
       "44                                                NaN    \n",
       "45                                                 15    \n",
       "46                                                  R    \n",
       "47                                                  5    \n",
       "48                                                  1    \n",
       "49                                                  7    \n",
       "50                                                  5    \n",
       "51                                                NaN    \n",
       "52                                                  4    \n",
       "53                                                 10    \n",
       "54                                                NaN    \n",
       "\n",
       "    Q.27 Topic 2: Preferred Level  \\\n",
       "0                             2.0   \n",
       "1                             3.0   \n",
       "2                             NaN   \n",
       "3                             1.0   \n",
       "4                             3.0   \n",
       "5                             2.0   \n",
       "6                             3.0   \n",
       "7                             3.0   \n",
       "8                             3.0   \n",
       "9                             3.0   \n",
       "10                            3.0   \n",
       "11                            3.0   \n",
       "12                            3.0   \n",
       "13                            3.0   \n",
       "14                            2.0   \n",
       "15                            3.0   \n",
       "16                            2.0   \n",
       "17                            3.0   \n",
       "18                            NaN   \n",
       "19                            2.0   \n",
       "20                            3.0   \n",
       "21                            NaN   \n",
       "22                            3.0   \n",
       "23                            NaN   \n",
       "24                            2.0   \n",
       "25                            3.0   \n",
       "26                            3.0   \n",
       "27                            2.0   \n",
       "28                            2.0   \n",
       "29                            2.0   \n",
       "30                            2.0   \n",
       "31                            1.0   \n",
       "32                            3.0   \n",
       "33                            3.0   \n",
       "34                            1.0   \n",
       "35                            2.0   \n",
       "36                            3.0   \n",
       "37                            NaN   \n",
       "38                            2.0   \n",
       "39                            2.0   \n",
       "40                            3.0   \n",
       "41                            2.0   \n",
       "42                            NaN   \n",
       "43                            2.0   \n",
       "44                            NaN   \n",
       "45                            3.0   \n",
       "46                            3.0   \n",
       "47                            3.0   \n",
       "48                            2.0   \n",
       "49                            3.0   \n",
       "50                            3.0   \n",
       "51                            NaN   \n",
       "52                            3.0   \n",
       "53                            3.0   \n",
       "54                            3.0   \n",
       "\n",
       "                    Q.28 Topic 2: Preferred Format  \n",
       "0                                 Seminar/Workshop  \n",
       "1                                 Seminar/Workshop  \n",
       "2                                 Seminar/Workshop  \n",
       "3                                 Seminar/Workshop  \n",
       "4                                 Seminar/Workshop  \n",
       "5                                 Seminar/Workshop  \n",
       "6                                 Seminar/Workshop  \n",
       "7                                 Seminar/Workshop  \n",
       "8                                 Seminar/Workshop  \n",
       "9                                 Seminar/Workshop  \n",
       "10                                Seminar/Workshop  \n",
       "11                                Seminar/Workshop  \n",
       "12                                Seminar/Workshop  \n",
       "13                             Self Study Material  \n",
       "14                             Self Study Material  \n",
       "15                                Seminar/Workshop  \n",
       "16                                Seminar/Workshop  \n",
       "17                                Seminar/Workshop  \n",
       "18                                             NaN  \n",
       "19                                Seminar/Workshop  \n",
       "20                                Seminar/Workshop  \n",
       "21                                             NaN  \n",
       "22                                Seminar/Workshop  \n",
       "23                                             NaN  \n",
       "24                             Self Study Material  \n",
       "25  Interactive distance learning (i.e. web based)  \n",
       "26                                          others  \n",
       "27                                Seminar/Workshop  \n",
       "28                                Seminar/Workshop  \n",
       "29  Interactive distance learning (i.e. web based)  \n",
       "30                                Seminar/Workshop  \n",
       "31                                Seminar/Workshop  \n",
       "32                                Seminar/Workshop  \n",
       "33                                Seminar/Workshop  \n",
       "34                                Seminar/Workshop  \n",
       "35  Interactive distance learning (i.e. web based)  \n",
       "36                                Seminar/Workshop  \n",
       "37                                             NaN  \n",
       "38                                Seminar/Workshop  \n",
       "39                                Seminar/Workshop  \n",
       "40                                Seminar/Workshop  \n",
       "41                                Seminar/Workshop  \n",
       "42                                             NaN  \n",
       "43                                Seminar/Workshop  \n",
       "44                                             NaN  \n",
       "45  Interactive distance learning (i.e. web based)  \n",
       "46                             Self Study Material  \n",
       "47  Interactive distance learning (i.e. web based)  \n",
       "48  Interactive distance learning (i.e. web based)  \n",
       "49                                Seminar/Workshop  \n",
       "50                                Seminar/Workshop  \n",
       "51                                             NaN  \n",
       "52                                Seminar/Workshop  \n",
       "53                                Seminar/Workshop  \n",
       "54  Interactive distance learning (i.e. web based)  \n",
       "\n",
       "[55 rows x 32 columns]"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "text = data['Q.16 What did you most appreciate / enjoy/think was the best about the course? Any suggestions for improvements. '].to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "text['Q.16 What did you most appreciate / enjoy/think was the best about the course? Any suggestions for improvements. '].fillna(value = ' ' , inplace= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "text['length']= text['Q.16 What did you most appreciate / enjoy/think was the best about the course? Any suggestions for improvements. '].apply(len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "#def tex_process(text1):\n",
    "#    nopunc = [char for char in text1 if char not in string.punctuation]\n",
    "#    nopunc = ''.join(nopunc)\n",
    "#    return [word for word in nopunc.split() if word.lower not in stopwords.words('english') ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "#text['break'] = text['Q.16 What did you most appreciate / enjoy/think was the best about the course? Any suggestions for improvements. '].apply(tex_process)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    All sessions were good but I enjoyed Prof. M.M...\n",
       "1    Lab session enjoyed\\nSuggestion- Please use go...\n",
       "2    I appreciate the positive attitude and efforts...\n",
       "3                              Lab sessions\\nHandouts \n",
       "4    At the end of practical session, Assignment sh...\n",
       "Name: Q.16 What did you most appreciate / enjoy/think was the best about the course? Any suggestions for improvements. , dtype: object"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " text['Q.16 What did you most appreciate / enjoy/think was the best about the course? Any suggestions for improvements. '].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"All sessions were good but I enjoyed Prof. M.M.Gore lecture, in his lecture we can relate the topic with our real environment. Prof.Sudeep Sanyal's lecture was very good.\""
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text.iloc[0][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th># POS</th>\n",
       "      <th>ID</th>\n",
       "      <th>PosScore</th>\n",
       "      <th>NegScore</th>\n",
       "      <th>SynsetTerms</th>\n",
       "      <th>Gloss</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "      <td>1740.0</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.00</td>\n",
       "      <td>able#1</td>\n",
       "      <td>(usually followed by `to') having the necessar...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>a</td>\n",
       "      <td>2098.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.75</td>\n",
       "      <td>unable#1</td>\n",
       "      <td>(usually followed by `to') not having the nece...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>a</td>\n",
       "      <td>2312.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>dorsal#2 abaxial#1</td>\n",
       "      <td>facing away from the axis of an organ or organ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>a</td>\n",
       "      <td>2527.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>ventral#2 adaxial#1</td>\n",
       "      <td>nearest to or facing toward the axis of an org...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>a</td>\n",
       "      <td>2730.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>acroscopic#1</td>\n",
       "      <td>facing or on the side toward the apex</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  # POS      ID  PosScore  NegScore          SynsetTerms  \\\n",
       "0     a  1740.0     0.125      0.00               able#1   \n",
       "1     a  2098.0     0.000      0.75             unable#1   \n",
       "2     a  2312.0     0.000      0.00   dorsal#2 abaxial#1   \n",
       "3     a  2527.0     0.000      0.00  ventral#2 adaxial#1   \n",
       "4     a  2730.0     0.000      0.00         acroscopic#1   \n",
       "\n",
       "                                               Gloss  \n",
       "0  (usually followed by `to') having the necessar...  \n",
       "1  (usually followed by `to') not having the nece...  \n",
       "2  facing away from the axis of an organ or organ...  \n",
       "3  nearest to or facing toward the axis of an org...  \n",
       "4              facing or on the side toward the apex  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sentword = pd.read_csv(\"SentiWordNet_3.0.0_20130122.txt\", sep=\"\\t\", skiprows=26)\n",
    "sentword.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NLTK Downloader\n",
      "---------------------------------------------------------------------------\n",
      "    d) Download   l) List    u) Update   c) Config   h) Help   q) Quit\n",
      "---------------------------------------------------------------------------\n",
      "Downloader> d\n",
      "\n",
      "Download which package (l=list; x=cancel)?\n",
      "  Identifier> vader_lexicon\n",
      "    Downloading package vader_lexicon to\n",
      "        C:\\Users\\Admin\\AppData\\Roaming\\nltk_data...\n",
      "      Package vader_lexicon is already up-to-date!\n",
      "\n",
      "---------------------------------------------------------------------------\n",
      "    d) Download   l) List    u) Update   c) Config   h) Help   q) Quit\n",
      "---------------------------------------------------------------------------\n",
      "Downloader> q\n"
     ]
    }
   ],
   "source": [
    "nltk.download_shell()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.sentiment.vader import SentimentIntensityAnalyzer as SIA\n",
    "sentences =[\"great movie that was , acting was amazing\"]\n",
    "sid = SIA()\n",
    "for sentence in sentences:\n",
    "    ss = sid.polarity_scores(sentence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "def polarity_score(text1):\n",
    "    sentences = [text1]\n",
    "    sid = SIA()\n",
    "    for sentence in sentences:\n",
    "        ss = sid.polarity_scores(sentence)\n",
    "    val = ss['pos']-ss['neg']\n",
    "    return val "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'neg': 0.0, 'neu': 0.701, 'pos': 0.299, 'compound': 0.882}]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['score'] = text['Q.16 What did you most appreciate / enjoy/think was the best about the course? Any suggestions for improvements. '].apply(polarity_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>year</th>\n",
       "      <th>Form No : (Sample Year/01)</th>\n",
       "      <th>Lable</th>\n",
       "      <th>Q.1 The content was as described in publicity materials</th>\n",
       "      <th>Q.2 The workshop was applicable to my job</th>\n",
       "      <th>Q.3 I'll recommend this workshop to other conservators.</th>\n",
       "      <th>Q.4 The program was well paced within the allotted time</th>\n",
       "      <th>Q.5 The instructor was a good communicator</th>\n",
       "      <th>Q.6 The material was presented in an organized manner</th>\n",
       "      <th>...</th>\n",
       "      <th>Q.20 I'd be able to do y work better if I knew more about</th>\n",
       "      <th>Q.21 Topic 1 : Please describe the first of top two topics you would like to learn more about in the next 12 months</th>\n",
       "      <th>Q.22 Topic 1: Preferred Level</th>\n",
       "      <th>Q.23 Topic 1 : Preferred duration of program(days)</th>\n",
       "      <th>Q.24 Topic 1: Preferred Format</th>\n",
       "      <th>Q.25 Topic 2 : Please describe the first of top two topics you would like to learn more about in the next 12 months</th>\n",
       "      <th>Q.26 Topic 2 : Preferred duration of program(days)</th>\n",
       "      <th>Q.27 Topic 2: Preferred Level</th>\n",
       "      <th>Q.28 Topic 2: Preferred Format</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017_01</td>\n",
       "      <td>2017</td>\n",
       "      <td>1</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>R tool</td>\n",
       "      <td>Artificial Intelligence</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Interactive distance learning (i.e. web based)</td>\n",
       "      <td>IOT and knowledge about Ardunio Uno (Programming)</td>\n",
       "      <td>14</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>0.299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017_02</td>\n",
       "      <td>2017</td>\n",
       "      <td>2</td>\n",
       "      <td>Positive</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Deep learning using python</td>\n",
       "      <td>NLP- Discussion of all processing units.</td>\n",
       "      <td>2.0</td>\n",
       "      <td>14</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Application of NLP process(sentimental analysi...</td>\n",
       "      <td>14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>0.468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017_03</td>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Application of R to business analytics</td>\n",
       "      <td>Business analytics with R for managers</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Business Analytics:Overview/ Handson various t...</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>0.089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017_04</td>\n",
       "      <td>2017</td>\n",
       "      <td>4</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>Data analytics and Visualization</td>\n",
       "      <td>Data Visualization using R language</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Visual analytics</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017_05</td>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "      <td>Positive</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Big data analytics in practical aspects</td>\n",
       "      <td>Machine learning</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>Recommender system</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Seminar/Workshop</td>\n",
       "      <td>0.071</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 33 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID  year  Form No : (Sample Year/01)     Lable  \\\n",
       "0  2017_01  2017                           1  Positive   \n",
       "1  2017_02  2017                           2  Positive   \n",
       "2  2017_03  2017                           3  Positive   \n",
       "3  2017_04  2017                           4  Positive   \n",
       "4  2017_05  2017                           5  Positive   \n",
       "\n",
       "   Q.1 The content was as described in publicity materials  \\\n",
       "0                                                4.0         \n",
       "1                                                5.0         \n",
       "2                                                4.0         \n",
       "3                                                4.0         \n",
       "4                                                4.0         \n",
       "\n",
       "   Q.2 The workshop was applicable to my job  \\\n",
       "0                                          4   \n",
       "1                                          4   \n",
       "2                                          4   \n",
       "3                                          4   \n",
       "4                                          4   \n",
       "\n",
       "   Q.3 I'll recommend this workshop to other conservators.  \\\n",
       "0                                                  4         \n",
       "1                                                  5         \n",
       "2                                                  4         \n",
       "3                                                  4         \n",
       "4                                                  5         \n",
       "\n",
       "   Q.4 The program was well paced within the allotted time  \\\n",
       "0                                                  5         \n",
       "1                                                  5         \n",
       "2                                                  3         \n",
       "3                                                  3         \n",
       "4                                                  5         \n",
       "\n",
       "   Q.5 The instructor was a good communicator   \\\n",
       "0                                            4   \n",
       "1                                            5   \n",
       "2                                            4   \n",
       "3                                            4   \n",
       "4                                            4   \n",
       "\n",
       "   Q.6 The material was presented in an organized manner  ...    \\\n",
       "0                                                  5      ...     \n",
       "1                                                  4      ...     \n",
       "2                                                  5      ...     \n",
       "3                                                  3      ...     \n",
       "4                                                  5      ...     \n",
       "\n",
       "   Q.20 I'd be able to do y work better if I knew more about  \\\n",
       "0                                             R tool           \n",
       "1                         Deep learning using python           \n",
       "2             Application of R to business analytics           \n",
       "3                   Data analytics and Visualization           \n",
       "4            Big data analytics in practical aspects           \n",
       "\n",
       "   Q.21 Topic 1 : Please describe the first of top two topics you would like to learn more about in the next 12 months  \\\n",
       "0                            Artificial Intelligence                                                                     \n",
       "1           NLP- Discussion of all processing units.                                                                     \n",
       "2             Business analytics with R for managers                                                                     \n",
       "3                Data Visualization using R language                                                                     \n",
       "4                                   Machine learning                                                                     \n",
       "\n",
       "   Q.22 Topic 1: Preferred Level  \\\n",
       "0                            3.0   \n",
       "1                            2.0   \n",
       "2                            3.0   \n",
       "3                            2.0   \n",
       "4                            3.0   \n",
       "\n",
       "   Q.23 Topic 1 : Preferred duration of program(days)  \\\n",
       "0                                                  7    \n",
       "1                                                 14    \n",
       "2                                                 10    \n",
       "3                                                  6    \n",
       "4                                                  3    \n",
       "\n",
       "                   Q.24 Topic 1: Preferred Format  \\\n",
       "0  Interactive distance learning (i.e. web based)   \n",
       "1                                Seminar/Workshop   \n",
       "2                                Seminar/Workshop   \n",
       "3                                Seminar/Workshop   \n",
       "4                                Seminar/Workshop   \n",
       "\n",
       "   Q.25 Topic 2 : Please describe the first of top two topics you would like to learn more about in the next 12 months  \\\n",
       "0  IOT and knowledge about Ardunio Uno (Programming)                                                                     \n",
       "1  Application of NLP process(sentimental analysi...                                                                     \n",
       "2  Business Analytics:Overview/ Handson various t...                                                                     \n",
       "3                                   Visual analytics                                                                     \n",
       "4                                Recommender system                                                                      \n",
       "\n",
       "   Q.26 Topic 2 : Preferred duration of program(days)  \\\n",
       "0                                                 14    \n",
       "1                                                 14    \n",
       "2                                                 10    \n",
       "3                                                  4    \n",
       "4                                                  3    \n",
       "\n",
       "   Q.27 Topic 2: Preferred Level  Q.28 Topic 2: Preferred Format  score  \n",
       "0                            2.0                Seminar/Workshop  0.299  \n",
       "1                            3.0                Seminar/Workshop  0.468  \n",
       "2                            NaN                Seminar/Workshop  0.089  \n",
       "3                            1.0                Seminar/Workshop  0.000  \n",
       "4                            3.0                Seminar/Workshop  0.071  \n",
       "\n",
       "[5 rows x 33 columns]"
      ]
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   "cell_type": "code",
   "execution_count": 134,
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    "data.to_csv('lastone.csv')"
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   "cell_type": "code",
   "execution_count": 107,
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