TextAnalysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline  \n",
    "from textblob import TextBlob\n",
    "##import re, string, unicodedata\n",
    "import nltk\n",
    "##import contractions\n",
    "##import inflect\n",
    " ## from bs4 import BeautifulSoup\n",
    "from nltk import word_tokenize, sent_tokenize\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem import LancasterStemmer, WordNetLemmatizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('survey1.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Thinking about the contact you have had with L&Q about your complaint, is there anything else we could have done better?'"
      ]
     },
     "execution_count": 279,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Question text'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Question text', 'Date', 'Comment', 'Unnamed: 3', 'Unnamed: 4'], dtype='object')"
      ]
     },
     "execution_count": 280,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.drop(['Question text','Unnamed: 3', 'Unnamed: 4'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(429, 2)"
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"My complaint lasted nearly a year, it is still ongoing. However, they have closed the complaint and would not agree to all the repairs being done. However, the complaints officer has closed the complaint without confirming it with me, which I was quite surprised about and upset about. I feel that the last repair that was to be done by LandQ, was not done to our standard and was not actually done. So but they closed the case to improve case which I am not happy about and overall none of the senior management acknowledged me at all. I copied in senior managers and the Director David Montague. He did not reply once, I was upset about that because we are all customers, which was quite upsetting because generally complaints are resolved very quickly. However, LandQ was very sluggish in this and they lost one of my complaints because apparently it disappeared on their system, which it didn't but it was just made up by one of the staff that it disappeared. I got a complaints number and they could not find that complaint, apparently it went through the system and I received a reference number, which I was quite confused about because they were lying! .           \""
      ]
     },
     "execution_count": 283,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Comment'][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [],
   "source": [
    "## To lower case everything\n",
    "df['Comment_short'] = df['Comment'].apply(lambda x: \" \".join(x.lower() for x in x.split()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"My complaint lasted nearly a year, it is still ongoing. However, they have closed the complaint and would not agree to all the repairs being done. However, the complaints officer has closed the complaint without confirming it with me, which I was quite surprised about and upset about. I feel that the last repair that was to be done by LandQ, was not done to our standard and was not actually done. So but they closed the case to improve case which I am not happy about and overall none of the senior management acknowledged me at all. I copied in senior managers and the Director David Montague. He did not reply once, I was upset about that because we are all customers, which was quite upsetting because generally complaints are resolved very quickly. However, LandQ was very sluggish in this and they lost one of my complaints because apparently it disappeared on their system, which it didn't but it was just made up by one of the staff that it disappeared. I got a complaints number and they could not find that complaint, apparently it went through the system and I received a reference number, which I was quite confused about because they were lying! .           \""
      ]
     },
     "execution_count": 285,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Comment'][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [],
   "source": [
    "## remove punctuation\n",
    "df['Comment_short'] = df['Comment_short'].str.replace('[^\\w\\s]','')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'my complaint lasted nearly a year it is still ongoing however they have closed the complaint and would not agree to all the repairs being done however the complaints officer has closed the complaint without confirming it with me which i was quite surprised about and upset about i feel that the last repair that was to be done by landq was not done to our standard and was not actually done so but they closed the case to improve case which i am not happy about and overall none of the senior management acknowledged me at all i copied in senior managers and the director david montague he did not reply once i was upset about that because we are all customers which was quite upsetting because generally complaints are resolved very quickly however landq was very sluggish in this and they lost one of my complaints because apparently it disappeared on their system which it didnt but it was just made up by one of the staff that it disappeared i got a complaints number and they could not find that complaint apparently it went through the system and i received a reference number which i was quite confused about because they were lying '"
      ]
     },
     "execution_count": 287,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Comment_short'][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'complaint lasted nearly year still ongoing however closed complaint would agree repairs done however complaints officer closed complaint without confirming quite surprised upset feel last repair done landq done standard actually done closed case improve case happy overall none senior management acknowledged copied senior managers director david montague reply upset customers quite upsetting generally complaints resolved quickly however landq sluggish lost one complaints apparently disappeared system didnt made one staff disappeared got complaints number could find complaint apparently went system received reference number quite confused lying'"
      ]
     },
     "execution_count": 288,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## remove stopwords\n",
    "from nltk.corpus import stopwords\n",
    "stop = stopwords.words('english')\n",
    "df['Comment_short'] = df['Comment_short'].apply(lambda x: \" \".join(x for x in x.split() if x not in stop))\n",
    "df['Comment_short'][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "complaint    213\n",
       "actually     131\n",
       "im           123\n",
       "thank        113\n",
       "know         104\n",
       "time         104\n",
       "dont          99\n",
       "get           99\n",
       "could         98\n",
       "going         97\n",
       "dtype: int64"
      ]
     },
     "execution_count": 289,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most = pd.Series(' '.join(df['Comment_short']).split()).value_counts()[:10]\n",
    "most"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    absolutely everything would changed everything...\n",
       "1        tried information problem making decision bye\n",
       "2    lasted nearly year still ongoing however close...\n",
       "3    think landq listen tenants properly make sure ...\n",
       "4    also scheming help people best opportunities p...\n",
       "Name: Comment_short, dtype: object"
      ]
     },
     "execution_count": 290,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most = list(most.index)\n",
    "df['Comment_short'] = df['Comment_short'].apply(lambda x: \" \".join(x for x in x.split() if x not in most))\n",
    "df['Comment_short'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'lasted nearly year still ongoing however closed would agree repairs done however complaints officer closed without confirming quite surprised upset feel last repair done landq done standard done closed case improve case happy overall none senior management acknowledged copied senior managers director david montague reply upset customers quite upsetting generally complaints resolved quickly however landq sluggish lost one complaints apparently disappeared system didnt made one staff disappeared got complaints number find apparently went system received reference number quite confused lying'"
      ]
     },
     "execution_count": 291,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Comment_short'][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "think     96\n",
       "ive       95\n",
       "people    93\n",
       "done      87\n",
       "back      79\n",
       "still     78\n",
       "need      78\n",
       "got       76\n",
       "would     75\n",
       "one       75\n",
       "dtype: int64"
      ]
     },
     "execution_count": 292,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most2 = pd.Series(' '.join(df['Comment_short']).split()).value_counts()[:10]\n",
    "most2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [],
   "source": [
    "from textblob import TextBlob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WordList(['lasted', 'nearly', 'year', 'still', 'ongoing', 'however', 'closed', 'would', 'agree', 'repairs', 'done', 'however', 'complaints', 'officer', 'closed', 'without', 'confirming', 'quite', 'surprised', 'upset', 'feel', 'last', 'repair', 'done', 'landq', 'done', 'standard', 'done', 'closed', 'case', 'improve', 'case', 'happy', 'overall', 'none', 'senior', 'management', 'acknowledged', 'copied', 'senior', 'managers', 'director', 'david', 'montague', 'reply', 'upset', 'customers', 'quite', 'upsetting', 'generally', 'complaints', 'resolved', 'quickly', 'however', 'landq', 'sluggish', 'lost', 'one', 'complaints', 'apparently', 'disappeared', 'system', 'didnt', 'made', 'one', 'staff', 'disappeared', 'got', 'complaints', 'number', 'find', 'apparently', 'went', 'system', 'received', 'reference', 'number', 'quite', 'confused', 'lying'])"
      ]
     },
     "execution_count": 294,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TextBlob(df['Comment_short'][2]).words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [],
   "source": [
    "#from nltk.stem import PorterStemmer\n",
    "#st = PorterStemmer()\n",
    "#df['Comment_short'] = df['Comment_short'].apply(lambda x: \" \".join([st.stem(word) for word in x.split()]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'lasted nearly year still ongoing however closed would agree repairs done however complaints officer closed without confirming quite surprised upset feel last repair done landq done standard done closed case improve case happy overall none senior management acknowledged copied senior managers director david montague reply upset customers quite upsetting generally complaints resolved quickly however landq sluggish lost one complaints apparently disappeared system didnt made one staff disappeared got complaints number find apparently went system received reference number quite confused lying'"
      ]
     },
     "execution_count": 296,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Comment_short'][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [],
   "source": [
    "#make wordcoud\n",
    "\n",
    "from wordcloud import WordCloud, STOPWORDS\n",
    "import matplotlib.pyplot as plt\n",
    "stopwords = set(STOPWORDS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def show_wordcloud(col, title = None):\n",
    "    wordcloud = WordCloud(\n",
    "        background_color='white',\n",
    "        stopwords=stopwords,\n",
    "        max_words=500,\n",
    "        max_font_size=40, \n",
    "        scale=3,\n",
    "        random_state=1\n",
    "    ).generate(str(col))\n",
    "\n",
    "    fig = plt.figure(1, figsize=(14, 14))\n",
    "    plt.axis('off')\n",
    "    if title: \n",
    "        fig.suptitle(title, fontsize=20)\n",
    "        fig.subplots_adjust(top=2.3)\n",
    "\n",
    "    plt.imshow(wordcloud)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "if __name__ == '__main__':\n",
    "\n",
    "    show_wordcloud(df['Comment'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {},
   "outputs": [],
   "source": [
    "from textblob import TextBlob\n",
    "statement = \"poor choice\" #testing\n",
    "sentiment1 = TextBlob(statement).sentiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sentiment(polarity=-0.4, subjectivity=0.6)"
      ]
     },
     "execution_count": 300,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sentiment1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sentiment(polarity=1.0, subjectivity=1.0)"
      ]
     },
     "execution_count": 301,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "statement = \"excellent goal\" \n",
    "sentiment2 = TextBlob(statement).sentiment\n",
    "sentiment2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {},
   "outputs": [],
   "source": [
    "def senti(x):\n",
    "    return TextBlob(x).sentiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['senti_score'] = df['Comment_short'].apply(senti)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                   (0.2, 0.9)\n",
       "1                                   (0.0, 0.0)\n",
       "2    (0.05595238095238097, 0.3619047619047619)\n",
       "3    (0.23928571428571427, 0.4984126984126985)\n",
       "4                                  (0.6, 0.25)\n",
       "Name: senti_score, dtype: object"
      ]
     },
     "execution_count": 304,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.senti_score.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(429, 4)"
      ]
     },
     "execution_count": 305,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\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>Date</th>\n",
       "      <th>Comment</th>\n",
       "      <th>Comment_short</th>\n",
       "      <th>senti_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01/01/2020 10:02</td>\n",
       "      <td>Absolutely everything, I would have changed ev...</td>\n",
       "      <td>absolutely everything would changed everything...</td>\n",
       "      <td>(0.2, 0.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01/01/2020 10:02</td>\n",
       "      <td>Tried to get more information about the proble...</td>\n",
       "      <td>tried information problem making decision bye</td>\n",
       "      <td>(0.0, 0.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01/01/2020 10:04</td>\n",
       "      <td>My complaint lasted nearly a year, it is still...</td>\n",
       "      <td>lasted nearly year still ongoing however close...</td>\n",
       "      <td>(0.05595238095238097, 0.3619047619047619)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>02/01/2020 10:02</td>\n",
       "      <td>I think LandQ should listen to their tenants p...</td>\n",
       "      <td>think landq listen tenants properly make sure ...</td>\n",
       "      <td>(0.23928571428571427, 0.4984126984126985)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>03/01/2020 10:03</td>\n",
       "      <td>I also scheming to help people that have best ...</td>\n",
       "      <td>also scheming help people best opportunities p...</td>\n",
       "      <td>(0.6, 0.25)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>27/11/2020 10:03</td>\n",
       "      <td>I actually responding to questions raised corr...</td>\n",
       "      <td>responding questions raised correctly giving r...</td>\n",
       "      <td>(0.01938775510204082, 0.4051020408163265)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>27/11/2020 10:03</td>\n",
       "      <td>Fine how it could be dealt with it is if I can...</td>\n",
       "      <td>fine dealt line home would processed would goo...</td>\n",
       "      <td>(0.3066666666666667, 0.35333333333333333)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>27/11/2020 10:04</td>\n",
       "      <td>To fix the actual problem, we're still nearly ...</td>\n",
       "      <td>fix actual problem still nearly 3 weeks hot wa...</td>\n",
       "      <td>(0.05959595959595961, 0.5241414141414142)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>28/11/2020 10:03</td>\n",
       "      <td>I say I think you do not listen to residence I...</td>\n",
       "      <td>say think listen residence think addressed use...</td>\n",
       "      <td>(-0.27499999999999997, 0.425)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>28/11/2020 10:05</td>\n",
       "      <td>I spend over 12 an a half hours on the phone I...</td>\n",
       "      <td>spend 12 half hours phone phoned seven times y...</td>\n",
       "      <td>(-0.17407407407407405, 0.7351851851851854)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>429 rows × 4 columns</p>\n",
       "</div>"
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      "text/plain": [
       "                 Date                                            Comment  \\\n",
       "0    01/01/2020 10:02  Absolutely everything, I would have changed ev...   \n",
       "1    01/01/2020 10:02  Tried to get more information about the proble...   \n",
       "2    01/01/2020 10:04  My complaint lasted nearly a year, it is still...   \n",
       "3    02/01/2020 10:02  I think LandQ should listen to their tenants p...   \n",
       "4    03/01/2020 10:03  I also scheming to help people that have best ...   \n",
       "..                ...                                                ...   \n",
       "424  27/11/2020 10:03  I actually responding to questions raised corr...   \n",
       "425  27/11/2020 10:03  Fine how it could be dealt with it is if I can...   \n",
       "426  27/11/2020 10:04  To fix the actual problem, we're still nearly ...   \n",
       "427  28/11/2020 10:03  I say I think you do not listen to residence I...   \n",
       "428  28/11/2020 10:05  I spend over 12 an a half hours on the phone I...   \n",
       "\n",
       "                                         Comment_short  \\\n",
       "0    absolutely everything would changed everything...   \n",
       "1        tried information problem making decision bye   \n",
       "2    lasted nearly year still ongoing however close...   \n",
       "3    think landq listen tenants properly make sure ...   \n",
       "4    also scheming help people best opportunities p...   \n",
       "..                                                 ...   \n",
       "424  responding questions raised correctly giving r...   \n",
       "425  fine dealt line home would processed would goo...   \n",
       "426  fix actual problem still nearly 3 weeks hot wa...   \n",
       "427  say think listen residence think addressed use...   \n",
       "428  spend 12 half hours phone phoned seven times y...   \n",
       "\n",
       "                                    senti_score  \n",
       "0                                    (0.2, 0.9)  \n",
       "1                                    (0.0, 0.0)  \n",
       "2     (0.05595238095238097, 0.3619047619047619)  \n",
       "3     (0.23928571428571427, 0.4984126984126985)  \n",
       "4                                   (0.6, 0.25)  \n",
       "..                                          ...  \n",
       "424   (0.01938775510204082, 0.4051020408163265)  \n",
       "425   (0.3066666666666667, 0.35333333333333333)  \n",
       "426   (0.05959595959595961, 0.5241414141414142)  \n",
       "427               (-0.27499999999999997, 0.425)  \n",
       "428  (-0.17407407407407405, 0.7351851851851854)  \n",
       "\n",
       "[429 rows x 4 columns]"
      ]
     },
     "execution_count": 306,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>01/01/2020 10:02</td>\n",
       "      <td>Absolutely everything, I would have changed ev...</td>\n",
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       "      <td>01/01/2020 10:02</td>\n",
       "      <td>Tried to get more information about the proble...</td>\n",
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       "      <td>(0.0, 0.0)</td>\n",
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       "      <th>2</th>\n",
       "      <td>01/01/2020 10:04</td>\n",
       "      <td>My complaint lasted nearly a year, it is still...</td>\n",
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       "      <td>(0.05595238095238097, 0.3619047619047619)</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>02/01/2020 10:02</td>\n",
       "      <td>I think LandQ should listen to their tenants p...</td>\n",
       "      <td>think landq listen tenants properly make sure ...</td>\n",
       "      <td>(0.23928571428571427, 0.4984126984126985)</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>03/01/2020 10:03</td>\n",
       "      <td>I also scheming to help people that have best ...</td>\n",
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       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>27/11/2020 10:03</td>\n",
       "      <td>I actually responding to questions raised corr...</td>\n",
       "      <td>responding questions raised correctly giving r...</td>\n",
       "      <td>(0.01938775510204082, 0.4051020408163265)</td>\n",
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       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>27/11/2020 10:03</td>\n",
       "      <td>Fine how it could be dealt with it is if I can...</td>\n",
       "      <td>fine dealt line home would processed would goo...</td>\n",
       "      <td>(0.3066666666666667, 0.35333333333333333)</td>\n",
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       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>27/11/2020 10:04</td>\n",
       "      <td>To fix the actual problem, we're still nearly ...</td>\n",
       "      <td>fix actual problem still nearly 3 weeks hot wa...</td>\n",
       "      <td>(0.05959595959595961, 0.5241414141414142)</td>\n",
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       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>28/11/2020 10:03</td>\n",
       "      <td>I say I think you do not listen to residence I...</td>\n",
       "      <td>say think listen residence think addressed use...</td>\n",
       "      <td>(-0.27499999999999997, 0.425)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>28/11/2020 10:05</td>\n",
       "      <td>I spend over 12 an a half hours on the phone I...</td>\n",
       "      <td>spend 12 half hours phone phoned seven times y...</td>\n",
       "      <td>(-0.17407407407407405, 0.7351851851851854)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>429 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Date                                            Comment  \\\n",
       "0    01/01/2020 10:02  Absolutely everything, I would have changed ev...   \n",
       "1    01/01/2020 10:02  Tried to get more information about the proble...   \n",
       "2    01/01/2020 10:04  My complaint lasted nearly a year, it is still...   \n",
       "3    02/01/2020 10:02  I think LandQ should listen to their tenants p...   \n",
       "4    03/01/2020 10:03  I also scheming to help people that have best ...   \n",
       "..                ...                                                ...   \n",
       "424  27/11/2020 10:03  I actually responding to questions raised corr...   \n",
       "425  27/11/2020 10:03  Fine how it could be dealt with it is if I can...   \n",
       "426  27/11/2020 10:04  To fix the actual problem, we're still nearly ...   \n",
       "427  28/11/2020 10:03  I say I think you do not listen to residence I...   \n",
       "428  28/11/2020 10:05  I spend over 12 an a half hours on the phone I...   \n",
       "\n",
       "                                         Comment_short  \\\n",
       "0    absolutely everything would changed everything...   \n",
       "1        tried information problem making decision bye   \n",
       "2    lasted nearly year still ongoing however close...   \n",
       "3    think landq listen tenants properly make sure ...   \n",
       "4    also scheming help people best opportunities p...   \n",
       "..                                                 ...   \n",
       "424  responding questions raised correctly giving r...   \n",
       "425  fine dealt line home would processed would goo...   \n",
       "426  fix actual problem still nearly 3 weeks hot wa...   \n",
       "427  say think listen residence think addressed use...   \n",
       "428  spend 12 half hours phone phoned seven times y...   \n",
       "\n",
       "                                    senti_score  \n",
       "0                                    (0.2, 0.9)  \n",
       "1                                    (0.0, 0.0)  \n",
       "2     (0.05595238095238097, 0.3619047619047619)  \n",
       "3     (0.23928571428571427, 0.4984126984126985)  \n",
       "4                                   (0.6, 0.25)  \n",
       "..                                          ...  \n",
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       "426   (0.05959595959595961, 0.5241414141414142)  \n",
       "427               (-0.27499999999999997, 0.425)  \n",
       "428  (-0.17407407407407405, 0.7351851851851854)  \n",
       "\n",
       "[429 rows x 4 columns]"
      ]
     },
     "execution_count": 307,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.round(3)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['senti_score'][0][0]\n",
    "df['Polarity'] = df['senti_score'].apply(lambda x: x[0])\n",
    "df['Subjectivity'] = df['senti_score'].apply(lambda x: x[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {},
   "outputs": [
    {
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       "      <td>02/01/2020 10:02</td>\n",
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       "      <td>03/01/2020 10:03</td>\n",
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       "      <td>Fine how it could be dealt with it is if I can...</td>\n",
       "      <td>fine dealt line home would processed would goo...</td>\n",
       "      <td>(0.3066666666666667, 0.35333333333333333)</td>\n",
       "      <td>0.306667</td>\n",
       "      <td>0.353333</td>\n",
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       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>27/11/2020 10:04</td>\n",
       "      <td>To fix the actual problem, we're still nearly ...</td>\n",
       "      <td>fix actual problem still nearly 3 weeks hot wa...</td>\n",
       "      <td>(0.05959595959595961, 0.5241414141414142)</td>\n",
       "      <td>0.059596</td>\n",
       "      <td>0.524141</td>\n",
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       "      <th>427</th>\n",
       "      <td>28/11/2020 10:03</td>\n",
       "      <td>I say I think you do not listen to residence I...</td>\n",
       "      <td>say think listen residence think addressed use...</td>\n",
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       "      <td>I spend over 12 an a half hours on the phone I...</td>\n",
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       "      <td>-0.174074</td>\n",
       "      <td>0.735185</td>\n",
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      "text/plain": [
       "                 Date                                            Comment  \\\n",
       "0    01/01/2020 10:02  Absolutely everything, I would have changed ev...   \n",
       "1    01/01/2020 10:02  Tried to get more information about the proble...   \n",
       "2    01/01/2020 10:04  My complaint lasted nearly a year, it is still...   \n",
       "3    02/01/2020 10:02  I think LandQ should listen to their tenants p...   \n",
       "4    03/01/2020 10:03  I also scheming to help people that have best ...   \n",
       "..                ...                                                ...   \n",
       "424  27/11/2020 10:03  I actually responding to questions raised corr...   \n",
       "425  27/11/2020 10:03  Fine how it could be dealt with it is if I can...   \n",
       "426  27/11/2020 10:04  To fix the actual problem, we're still nearly ...   \n",
       "427  28/11/2020 10:03  I say I think you do not listen to residence I...   \n",
       "428  28/11/2020 10:05  I spend over 12 an a half hours on the phone I...   \n",
       "\n",
       "                                         Comment_short  \\\n",
       "0    absolutely everything would changed everything...   \n",
       "1        tried information problem making decision bye   \n",
       "2    lasted nearly year still ongoing however close...   \n",
       "3    think landq listen tenants properly make sure ...   \n",
       "4    also scheming help people best opportunities p...   \n",
       "..                                                 ...   \n",
       "424  responding questions raised correctly giving r...   \n",
       "425  fine dealt line home would processed would goo...   \n",
       "426  fix actual problem still nearly 3 weeks hot wa...   \n",
       "427  say think listen residence think addressed use...   \n",
       "428  spend 12 half hours phone phoned seven times y...   \n",
       "\n",
       "                                    senti_score  Polarity  Subjectivity  \n",
       "0                                    (0.2, 0.9)  0.200000      0.900000  \n",
       "1                                    (0.0, 0.0)  0.000000      0.000000  \n",
       "2     (0.05595238095238097, 0.3619047619047619)  0.055952      0.361905  \n",
       "3     (0.23928571428571427, 0.4984126984126985)  0.239286      0.498413  \n",
       "4                                   (0.6, 0.25)  0.600000      0.250000  \n",
       "..                                          ...       ...           ...  \n",
       "424   (0.01938775510204082, 0.4051020408163265)  0.019388      0.405102  \n",
       "425   (0.3066666666666667, 0.35333333333333333)  0.306667      0.353333  \n",
       "426   (0.05959595959595961, 0.5241414141414142)  0.059596      0.524141  \n",
       "427               (-0.27499999999999997, 0.425) -0.275000      0.425000  \n",
       "428  (-0.17407407407407405, 0.7351851851851854) -0.174074      0.735185  \n",
       "\n",
       "[429 rows x 6 columns]"
      ]
     },
     "execution_count": 309,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Polarity</th>\n",
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       "      <td>429.000000</td>\n",
       "      <td>429.000000</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.070625</td>\n",
       "      <td>0.379614</td>\n",
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       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.254151</td>\n",
       "      <td>0.278515</td>\n",
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       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
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       "      <th>50%</th>\n",
       "      <td>0.006250</td>\n",
       "      <td>0.405429</td>\n",
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       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.571429</td>\n",
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       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.800000</td>\n",
       "      <td>1.000000</td>\n",
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      "text/plain": [
       "         Polarity  Subjectivity\n",
       "count  429.000000    429.000000\n",
       "mean     0.070625      0.379614\n",
       "std      0.254151      0.278515\n",
       "min     -1.000000      0.000000\n",
       "25%      0.000000      0.100000\n",
       "50%      0.006250      0.405429\n",
       "75%      0.200000      0.571429\n",
       "max      0.800000      1.000000"
      ]
     },
     "execution_count": 310,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {},
   "outputs": [
    {
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       "      <td>would good cladding tested building</td>\n",
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      "text/plain": [
       "                 Date                                            Comment  \\\n",
       "257  05/08/2020 10:03  Yeah, I'm very happy that everything is resolv...   \n",
       "262  06/08/2020 10:03  Hi I am still waiting for a person to give me ...   \n",
       "258  05/08/2020 10:03  Well it would have been helpful if my complain...   \n",
       "12   08/01/2020 10:02  I'm actually still waiting for my complaint to...   \n",
       "75   12/02/2020 10:03  It would be good if you could get the cladding...   \n",
       "\n",
       "                                         Comment_short  \\\n",
       "257  yeah happy everything resolved took quite took...   \n",
       "262  hi still waiting person give call dealing alre...   \n",
       "258  well would helpful resolved successfully hasnt...   \n",
       "12   still waiting knowledge sums somebody contact ...   \n",
       "75                 would good cladding tested building   \n",
       "\n",
       "                   senti_score  Polarity  Subjectivity  \n",
       "257                 (0.8, 1.0)      0.80          1.00  \n",
       "262                (0.8, 0.75)      0.80          0.75  \n",
       "258               (0.75, 0.95)      0.75          0.95  \n",
       "12   (0.7, 0.6000000000000001)      0.70          0.60  \n",
       "75   (0.7, 0.6000000000000001)      0.70          0.60  "
      ]
     },
     "execution_count": 311,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.nlargest(5,['Polarity'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"Yeah, I'm very happy that everything is resolved, it took quite a while, it took about a year but in the end, thank you More Than.\""
      ]
     },
     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Comment'][257]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "                 Date                                            Comment  \\\n",
       "41   28/01/2020 10:03  Yeah you could of actually listened and resolv...   \n",
       "326  01/10/2020 10:03  Not twisting the figures so that my stage 3 co...   \n",
       "332  02/10/2020 10:03  My complaint could have been reviewed and deal...   \n",
       "47   29/01/2020 10:03                           Could have got bad (?).    \n",
       "253  01/08/2020 10:04  Very bad everything was very very bad thank yo...   \n",
       "65   07/02/2020 10:03  Well I think you could of understood the stres...   \n",
       "214  02/07/2020 10:04                                    Bloody useless.   \n",
       "422  27/11/2020 10:02  I haven't got hours to explain all the crap I ...   \n",
       "62   05/02/2020 10:03  It would help if they could send someone who c...   \n",
       "293  03/09/2020 10:03  I actually haven't got anyone to speak to me a...   \n",
       "\n",
       "                                         Comment_short  \\\n",
       "41   yeah listened resolved issue instead waiting 4...   \n",
       "326  twisting figures stage 3 stays stage 1 ie comp...   \n",
       "332  reviewed dealt rather ignored dealt ive waited...   \n",
       "47                                             got bad   \n",
       "253                             bad everything bad bye   \n",
       "65   well think understood stress cold poorly feel ...   \n",
       "214                                     bloody useless   \n",
       "422  havent got hours explain crap queue suggest so...   \n",
       "62   would help send someone sort problems weve spe...   \n",
       "293  havent got anyone speak ive complained 2 times...   \n",
       "\n",
       "                                   senti_score  Polarity  Subjectivity  \n",
       "41                                 (-1.0, 1.0) -1.000000      1.000000  \n",
       "326                                (-0.8, 0.8) -0.800000      0.800000  \n",
       "332                                (-0.8, 1.0) -0.800000      1.000000  \n",
       "47   (-0.6999999999999998, 0.6666666666666666) -0.700000      0.666667  \n",
       "253  (-0.6999999999999998, 0.6666666666666666) -0.700000      0.666667  \n",
       "65   (-0.6666666666666666, 0.8666666666666667) -0.666667      0.866667  \n",
       "214                              (-0.65, 0.55) -0.650000      0.550000  \n",
       "422  (-0.5458333333333334, 0.6708333333333334) -0.545833      0.670833  \n",
       "62   (-0.5333333333333333, 0.7000000000000001) -0.533333      0.700000  \n",
       "293                            (-0.525, 0.475) -0.525000      0.475000  "
      ]
     },
     "execution_count": 313,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.nsmallest(10,['Polarity'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"I haven't got hours to explain all the crap I have been through with in a queue so I suggest that someone called me to fifteen months after buying this fact from you I'm still living in hell it and I have asked meantime someone senior to call me and no one ever done with you guys should hang their heads in shame I've worked hard all my life I paid a lot of money for this that and you don't even care\""
      ]
     },
     "execution_count": 314,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Comment'][326]\n",
    "df['Comment'][422]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# did it change over time?\n",
    "# the volume of the survey per month?"
   ]
  }
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