SentimentAnalysis.ipynb

{
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     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.14.0.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.14.0.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd \n",
    "import numpy as np \n",
    "import nltk\n",
    "from nltk.sentiment.vader import SentimentIntensityAnalyzer\n",
    "import plotly.offline as py \n",
    "import plotly.graph_objs as go\n",
    "import re \n",
    "from textblob import TextBlob\n",
    "from wordcloud import WordCloud\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import cufflinks as cf\n",
    "%matplotlib inline\n",
    "from plotly.offline import init_notebook_mode, iplot\n",
    "init_notebook_mode(connected=True)\n",
    "cf.go_offline()\n",
    "from plotly.subplots import make_subplots\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "pd.set_option('display.max_colwidth', 200)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\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>Unnamed: 0</th>\n",
       "      <th>reviewerName</th>\n",
       "      <th>overall</th>\n",
       "      <th>reviewText</th>\n",
       "      <th>reviewTime</th>\n",
       "      <th>day_diff</th>\n",
       "      <th>helpful_yes</th>\n",
       "      <th>helpful_no</th>\n",
       "      <th>total_vote</th>\n",
       "      <th>score_pos_neg_diff</th>\n",
       "      <th>score_average_rating</th>\n",
       "      <th>wilson_lower_bound</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>No issues.</td>\n",
       "      <td>23-07-2014</td>\n",
       "      <td>138</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0mie</td>\n",
       "      <td>5</td>\n",
       "      <td>Purchased this for my device, it worked as advertised. You can never have too much phone memory, since I download a lot of stuff this was a no brainer for me.</td>\n",
       "      <td>25-10-2013</td>\n",
       "      <td>409</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1K3</td>\n",
       "      <td>4</td>\n",
       "      <td>it works as expected. I should have sprung for the higher capacity.  I think its made a bit cheesier than the earlier versions; the paint looks not as clean as before</td>\n",
       "      <td>23-12-2012</td>\n",
       "      <td>715</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1m2</td>\n",
       "      <td>5</td>\n",
       "      <td>This think has worked out great.Had a diff. bran 64gb card and if went south after 3 months.This one has held up pretty well since I had my S3, now on my Note3.*** update 3/21/14I've had this for ...</td>\n",
       "      <td>21-11-2013</td>\n",
       "      <td>382</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2&amp;amp;1/2Men</td>\n",
       "      <td>5</td>\n",
       "      <td>Bought it with Retail Packaging, arrived legit, in a orange envelope, english version not asian like the picture shows. arrived quickly, bought a 32 and 16 both retail packaging for my htc one sv ...</td>\n",
       "      <td>13-07-2013</td>\n",
       "      <td>513</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  reviewerName  overall  \\\n",
       "0           0           NaN        4   \n",
       "1           1          0mie        5   \n",
       "2           2           1K3        4   \n",
       "3           3           1m2        5   \n",
       "4           4  2&amp;1/2Men        5   \n",
       "\n",
       "                                                                                                                                                                                                reviewText  \\\n",
       "0                                                                                                                                                                                               No issues.   \n",
       "1                                           Purchased this for my device, it worked as advertised. You can never have too much phone memory, since I download a lot of stuff this was a no brainer for me.   \n",
       "2                                   it works as expected. I should have sprung for the higher capacity.  I think its made a bit cheesier than the earlier versions; the paint looks not as clean as before   \n",
       "3  This think has worked out great.Had a diff. bran 64gb card and if went south after 3 months.This one has held up pretty well since I had my S3, now on my Note3.*** update 3/21/14I've had this for ...   \n",
       "4  Bought it with Retail Packaging, arrived legit, in a orange envelope, english version not asian like the picture shows. arrived quickly, bought a 32 and 16 both retail packaging for my htc one sv ...   \n",
       "\n",
       "   reviewTime  day_diff  helpful_yes  helpful_no  total_vote  \\\n",
       "0  23-07-2014       138            0           0           0   \n",
       "1  25-10-2013       409            0           0           0   \n",
       "2  23-12-2012       715            0           0           0   \n",
       "3  21-11-2013       382            0           0           0   \n",
       "4  13-07-2013       513            0           0           0   \n",
       "\n",
       "   score_pos_neg_diff  score_average_rating  wilson_lower_bound  \n",
       "0                   0                   0.0                 0.0  \n",
       "1                   0                   0.0                 0.0  \n",
       "2                   0                   0.0                 0.0  \n",
       "3                   0                   0.0                 0.0  \n",
       "4                   0                   0.0                 0.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv(\"amazon.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        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>reviewerName</th>\n",
       "      <th>overall</th>\n",
       "      <th>reviewText</th>\n",
       "      <th>reviewTime</th>\n",
       "      <th>day_diff</th>\n",
       "      <th>helpful_yes</th>\n",
       "      <th>helpful_no</th>\n",
       "      <th>total_vote</th>\n",
       "      <th>score_pos_neg_diff</th>\n",
       "      <th>score_average_rating</th>\n",
       "      <th>wilson_lower_bound</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2031</th>\n",
       "      <td>Hyoun Kim \"Faluzure\"</td>\n",
       "      <td>5</td>\n",
       "      <td>[[ UPDATE - 6/19/2014 ]]So my lovely wife bought me a Samsung Galaxy Tab 4 for Father's Day and I've been loving it ever since.  Just as other with Samsung products, the Galaxy Tab 4 has the abili...</td>\n",
       "      <td>05-01-2013</td>\n",
       "      <td>702</td>\n",
       "      <td>1952</td>\n",
       "      <td>68</td>\n",
       "      <td>2020</td>\n",
       "      <td>1884</td>\n",
       "      <td>0.966337</td>\n",
       "      <td>0.957544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3449</th>\n",
       "      <td>NLee the Engineer</td>\n",
       "      <td>5</td>\n",
       "      <td>I have tested dozens of SDHC and micro-SDHC cards. One disturbing trend I noticed is that: the speed class rating for micro-SDHC is typically inflated. For example, a 'class-10' rating means the c...</td>\n",
       "      <td>26-09-2012</td>\n",
       "      <td>803</td>\n",
       "      <td>1428</td>\n",
       "      <td>77</td>\n",
       "      <td>1505</td>\n",
       "      <td>1351</td>\n",
       "      <td>0.948837</td>\n",
       "      <td>0.936519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4212</th>\n",
       "      <td>SkincareCEO</td>\n",
       "      <td>1</td>\n",
       "      <td>NOTE:  please read the last update (scroll to the bottom) - I'm leaving this review as 1 star as it appears to help others who purchased and had a similar experience.I give SanDisk 5 stars for cus...</td>\n",
       "      <td>08-05-2013</td>\n",
       "      <td>579</td>\n",
       "      <td>1568</td>\n",
       "      <td>126</td>\n",
       "      <td>1694</td>\n",
       "      <td>1442</td>\n",
       "      <td>0.925620</td>\n",
       "      <td>0.912139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>Amazon Customer \"Kelly\"</td>\n",
       "      <td>1</td>\n",
       "      <td>If your card gets hot enough to be painful, it is defective and you need to contact SanDisk!From my experience, the larger micro SDs run hot on format and writing, but not to the pain threshold!I ...</td>\n",
       "      <td>09-02-2012</td>\n",
       "      <td>1033</td>\n",
       "      <td>422</td>\n",
       "      <td>73</td>\n",
       "      <td>495</td>\n",
       "      <td>349</td>\n",
       "      <td>0.852525</td>\n",
       "      <td>0.818577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4672</th>\n",
       "      <td>Twister</td>\n",
       "      <td>5</td>\n",
       "      <td>Sandisk announcement of the first 128GB micro SD took internet by storm. Our phones evolved into multimedia powerhouses with 5.5&amp;#34;-6&amp;#34; displays, desktop grade processing power, OTG support f...</td>\n",
       "      <td>03-07-2014</td>\n",
       "      <td>158</td>\n",
       "      <td>45</td>\n",
       "      <td>4</td>\n",
       "      <td>49</td>\n",
       "      <td>41</td>\n",
       "      <td>0.918367</td>\n",
       "      <td>0.808109</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 reviewerName  overall  \\\n",
       "2031     Hyoun Kim \"Faluzure\"        5   \n",
       "3449        NLee the Engineer        5   \n",
       "4212              SkincareCEO        1   \n",
       "317   Amazon Customer \"Kelly\"        1   \n",
       "4672                  Twister        5   \n",
       "\n",
       "                                                                                                                                                                                                   reviewText  \\\n",
       "2031  [[ UPDATE - 6/19/2014 ]]So my lovely wife bought me a Samsung Galaxy Tab 4 for Father's Day and I've been loving it ever since.  Just as other with Samsung products, the Galaxy Tab 4 has the abili...   \n",
       "3449  I have tested dozens of SDHC and micro-SDHC cards. One disturbing trend I noticed is that: the speed class rating for micro-SDHC is typically inflated. For example, a 'class-10' rating means the c...   \n",
       "4212  NOTE:  please read the last update (scroll to the bottom) - I'm leaving this review as 1 star as it appears to help others who purchased and had a similar experience.I give SanDisk 5 stars for cus...   \n",
       "317   If your card gets hot enough to be painful, it is defective and you need to contact SanDisk!From my experience, the larger micro SDs run hot on format and writing, but not to the pain threshold!I ...   \n",
       "4672  Sandisk announcement of the first 128GB micro SD took internet by storm. Our phones evolved into multimedia powerhouses with 5.5&#34;-6&#34; displays, desktop grade processing power, OTG support f...   \n",
       "\n",
       "      reviewTime  day_diff  helpful_yes  helpful_no  total_vote  \\\n",
       "2031  05-01-2013       702         1952          68        2020   \n",
       "3449  26-09-2012       803         1428          77        1505   \n",
       "4212  08-05-2013       579         1568         126        1694   \n",
       "317   09-02-2012      1033          422          73         495   \n",
       "4672  03-07-2014       158           45           4          49   \n",
       "\n",
       "      score_pos_neg_diff  score_average_rating  wilson_lower_bound  \n",
       "2031                1884              0.966337            0.957544  \n",
       "3449                1351              0.948837            0.936519  \n",
       "4212                1442              0.925620            0.912139  \n",
       "317                  349              0.852525            0.818577  \n",
       "4672                  41              0.918367            0.808109  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.sort_values(\"wilson_lower_bound\",ascending=False)\n",
    "df.drop(\"Unnamed: 0\",axis=1,inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Shape~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
      "Rows:  4915\n",
      "Columns:  11\n",
      "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Types~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
      "reviewerName             object\n",
      "overall                   int64\n",
      "reviewText               object\n",
      "reviewTime               object\n",
      "day_diff                  int64\n",
      "helpful_yes               int64\n",
      "helpful_no                int64\n",
      "total_vote                int64\n",
      "score_pos_neg_diff        int64\n",
      "score_average_rating    float64\n",
      "wilson_lower_bound      float64\n",
      "dtype: object\n",
      "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
      "              Missing Values  Ratio\n",
      "reviewerName               1   0.02\n",
      "reviewText                 1   0.02\n",
      "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Duplicated Values~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
      "0\n",
      "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Quantiles~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
      "                       0.00  0.05   0.50        0.95       0.99         1.00\n",
      "overall                 1.0   2.0    5.0    5.000000    5.00000     5.000000\n",
      "day_diff                1.0  98.0  431.0  748.000000  943.00000  1064.000000\n",
      "helpful_yes             0.0   0.0    0.0    1.000000    3.00000  1952.000000\n",
      "helpful_no              0.0   0.0    0.0    0.000000    2.00000   183.000000\n",
      "total_vote              0.0   0.0    0.0    1.000000    4.00000  2020.000000\n",
      "score_pos_neg_diff   -130.0   0.0    0.0    1.000000    2.00000  1884.000000\n",
      "score_average_rating    0.0   0.0    0.0    1.000000    1.00000     1.000000\n",
      "wilson_lower_bound      0.0   0.0    0.0    0.206549    0.34238     0.957544\n"
     ]
    }
   ],
   "source": [
    "def missing_values_analysis(df):\n",
    "    na_columns= [col for col in df.columns if df[col].isnull().sum()>0]\n",
    "    n_miss=df[na_columns].isnull().sum().sort_values(ascending = True)\n",
    "    ratio=(df[na_columns].isnull().sum()/df.shape[0]*100).sort_values(ascending = True)\n",
    "    missing_df=pd.concat([n_miss,np.round(ratio,2)],axis=1,keys=['Missing Values','Ratio'])\n",
    "    missing_df=pd.DataFrame(missing_df)\n",
    "    return missing_df\n",
    "\n",
    "def check_dataframe(df, head=5 , tail=5):\n",
    "    print(\"Shape\".center(82,\"~\"))\n",
    "    print(\"Rows: \",df.shape[0])\n",
    "    print(\"Columns: \",df.shape[1])\n",
    "    print(\"Types\".center(82,\"~\"))\n",
    "    print(df.dtypes)\n",
    "    print(\"\".center(82,\"~\"))\n",
    "    print(missing_values_analysis(df))\n",
    "    print(\"Duplicated Values\".center(82,\"~\"))\n",
    "    print(df.duplicated().sum())\n",
    "    print(\"Quantiles\".center(82,\"~\"))\n",
    "    print(df.quantile([0,0.05,0.50,0.95,0.99,1]).T)\n",
    "\n",
    "check_dataframe(df)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "\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>Variables</th>\n",
       "      <th>classes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>reviewText</td>\n",
       "      <td>4912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>reviewerName</td>\n",
       "      <td>4594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>reviewTime</td>\n",
       "      <td>690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>day_diff</td>\n",
       "      <td>690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>wilson_lower_bound</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>score_average_rating</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>score_pos_neg_diff</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>total_vote</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>helpful_yes</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>helpful_no</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>overall</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Variables  classes\n",
       "0             reviewText     4912\n",
       "1           reviewerName     4594\n",
       "2             reviewTime      690\n",
       "3               day_diff      690\n",
       "4     wilson_lower_bound       40\n",
       "5   score_average_rating       28\n",
       "6     score_pos_neg_diff       27\n",
       "7             total_vote       26\n",
       "8            helpful_yes       23\n",
       "9             helpful_no       17\n",
       "10               overall        5"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def check_class(dataframe):\n",
    "    nunique_df=pd.DataFrame({\"Variables\": dataframe.columns,\n",
    "                            \"classes\":[dataframe[i].nunique()  \n",
    "                                       for i in dataframe.columns]})\n",
    "    nunique_df=nunique_df.sort_values(\"classes\",ascending=False)\n",
    "    nunique_df=nunique_df.reset_index(drop=True)\n",
    "    return nunique_df\n",
    "\n",
    "check_class(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "contraints=[\"#B34D22\",\"#EBE00C\",\"#1FEB0C\",\"0C92EB\",\"#EB0CD5\"]\n",
    "\n",
    "def categorical_variable_summary(df, column_name):\n",
    "    fig = make_subplots(rows=1,cols=2 , \n",
    "                        subplot_titles=(\"CountPlot\" , \"Percentage\"),\n",
    "                        specs=[[{'type': 'xy'},{'type' : 'domain'}]])\n",
    "\n",
    "    fig.add_traces(go.Bar( y=df[column_name].value_counts().values.tolist(),\n",
    "                        x=[str(i) for i in df[column_name].value_counts().index],\n",
    "                        text=df[column_name].value_counts().values.tolist(),\n",
    "                        textfont=dict(size=15,color=\"white\"),\n",
    "                        name=column_name,\n",
    "                        textPosition=\"auto\",\n",
    "                        showlegend=False,\n",
    "                        marker=dict(color=contraints , line=dict(color=\"#DBE6EC\",width=1))),\n",
    "                    row=1,col=1)\n",
    "    \n",
    "    fig.add_traces(go.Pie(labels=df[column_name].values_counts().keys(),\n",
    "                        values=df[column_name].value_counts().values,\n",
    "                        name=column_name,\n",
    "                        textinfo=\"label+percent\",\n",
    "                        textfont=dict(size=15,color=\"white\"),\n",
    "                        textposition=\"inside\",\n",
    "                        showlegend=False,\n",
    "                        marker=dict(colors=contraints))\n",
    "                        ,row=1,col=2)\n",
    "    fig.update_layout(title={\"text\":column_name,\"y\":0.9 , \"x\":0.5,'xanchor':'center' ,\"yanchor\":\"top\"},\n",
    "                        template=\"plotly_white\")\n",
    "    \n",
    "    iplot(fig)\n",
    "        \n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "\n    Invalid element(s) received for the 'color' property of bar.marker\n        Invalid elements include: ['0C92EB']\n\n    The 'color' property is a color and may be specified as:\n      - A hex string (e.g. '#ff0000')\n      - An rgb/rgba string (e.g. 'rgb(255,0,0)')\n      - An hsl/hsla string (e.g. 'hsl(0,100%,50%)')\n      - An hsv/hsva string (e.g. 'hsv(0,100%,100%)')\n      - A named CSS color:\n            aliceblue, antiquewhite, aqua, aquamarine, azure,\n            beige, bisque, black, blanchedalmond, blue,\n            blueviolet, brown, burlywood, cadetblue,\n            chartreuse, chocolate, coral, cornflowerblue,\n            cornsilk, crimson, cyan, darkblue, darkcyan,\n            darkgoldenrod, darkgray, darkgrey, darkgreen,\n            darkkhaki, darkmagenta, darkolivegreen, darkorange,\n            darkorchid, darkred, darksalmon, darkseagreen,\n            darkslateblue, darkslategray, darkslategrey,\n            darkturquoise, darkviolet, deeppink, deepskyblue,\n            dimgray, dimgrey, dodgerblue, firebrick,\n            floralwhite, forestgreen, fuchsia, gainsboro,\n            ghostwhite, gold, goldenrod, gray, grey, green,\n            greenyellow, honeydew, hotpink, indianred, indigo,\n            ivory, khaki, lavender, lavenderblush, lawngreen,\n            lemonchiffon, lightblue, lightcoral, lightcyan,\n            lightgoldenrodyellow, lightgray, lightgrey,\n            lightgreen, lightpink, lightsalmon, lightseagreen,\n            lightskyblue, lightslategray, lightslategrey,\n            lightsteelblue, lightyellow, lime, limegreen,\n            linen, magenta, maroon, mediumaquamarine,\n            mediumblue, mediumorchid, mediumpurple,\n            mediumseagreen, mediumslateblue, mediumspringgreen,\n            mediumturquoise, mediumvioletred, midnightblue,\n            mintcream, mistyrose, moccasin, navajowhite, navy,\n            oldlace, olive, olivedrab, orange, orangered,\n            orchid, palegoldenrod, palegreen, paleturquoise,\n            palevioletred, papayawhip, peachpuff, peru, pink,\n            plum, powderblue, purple, red, rosybrown,\n            royalblue, rebeccapurple, saddlebrown, salmon,\n            sandybrown, seagreen, seashell, sienna, silver,\n            skyblue, slateblue, slategray, slategrey, snow,\n            springgreen, steelblue, tan, teal, thistle, tomato,\n            turquoise, violet, wheat, white, whitesmoke,\n            yellow, yellowgreen\n      - A number that will be interpreted as a color\n        according to bar.marker.colorscale\n      - A list or array of any of the above",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32mc:\\Sagar Kumar\\NAVTTC-BATCH-3\\Internship\\SentimentAnalysis.ipynb Cell 7\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m categorical_variable_summary(df,\u001b[39m\"\u001b[39;49m\u001b[39moverall\u001b[39;49m\u001b[39m\"\u001b[39;49m)\n",
      "\u001b[1;32mc:\\Sagar Kumar\\NAVTTC-BATCH-3\\Internship\\SentimentAnalysis.ipynb Cell 7\u001b[0m in \u001b[0;36mcategorical_variable_summary\u001b[1;34m(df, column_name)\u001b[0m\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mcategorical_variable_summary\u001b[39m(df, column_name):\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=3'>4</a>\u001b[0m     fig \u001b[39m=\u001b[39m make_subplots(rows\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m,cols\u001b[39m=\u001b[39m\u001b[39m2\u001b[39m , \n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m                         subplot_titles\u001b[39m=\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39mCountPlot\u001b[39m\u001b[39m\"\u001b[39m , \u001b[39m\"\u001b[39m\u001b[39mPercentage\u001b[39m\u001b[39m\"\u001b[39m),\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=5'>6</a>\u001b[0m                         specs\u001b[39m=\u001b[39m[[{\u001b[39m'\u001b[39m\u001b[39mtype\u001b[39m\u001b[39m'\u001b[39m: \u001b[39m'\u001b[39m\u001b[39mxy\u001b[39m\u001b[39m'\u001b[39m},{\u001b[39m'\u001b[39m\u001b[39mtype\u001b[39m\u001b[39m'\u001b[39m : \u001b[39m'\u001b[39m\u001b[39mdomain\u001b[39m\u001b[39m'\u001b[39m}]])\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=7'>8</a>\u001b[0m     fig\u001b[39m.\u001b[39madd_traces(go\u001b[39m.\u001b[39;49mBar( y\u001b[39m=\u001b[39;49mdf[column_name]\u001b[39m.\u001b[39;49mvalue_counts()\u001b[39m.\u001b[39;49mvalues\u001b[39m.\u001b[39;49mtolist(),\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=8'>9</a>\u001b[0m                         x\u001b[39m=\u001b[39;49m[\u001b[39mstr\u001b[39;49m(i) \u001b[39mfor\u001b[39;49;00m i \u001b[39min\u001b[39;49;00m df[column_name]\u001b[39m.\u001b[39;49mvalue_counts()\u001b[39m.\u001b[39;49mindex],\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=9'>10</a>\u001b[0m                         text\u001b[39m=\u001b[39;49mdf[column_name]\u001b[39m.\u001b[39;49mvalue_counts()\u001b[39m.\u001b[39;49mvalues\u001b[39m.\u001b[39;49mtolist(),\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=10'>11</a>\u001b[0m                         textfont\u001b[39m=\u001b[39;49m\u001b[39mdict\u001b[39;49m(size\u001b[39m=\u001b[39;49m\u001b[39m15\u001b[39;49m,color\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mwhite\u001b[39;49m\u001b[39m\"\u001b[39;49m),\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=11'>12</a>\u001b[0m                         name\u001b[39m=\u001b[39;49mcolumn_name,\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=12'>13</a>\u001b[0m                         textPosition\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mauto\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=13'>14</a>\u001b[0m                         showlegend\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m,\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=14'>15</a>\u001b[0m                         marker\u001b[39m=\u001b[39;49m\u001b[39mdict\u001b[39;49m(color\u001b[39m=\u001b[39;49mcontraints , line\u001b[39m=\u001b[39;49m\u001b[39mdict\u001b[39;49m(color\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39m#DBE6EC\u001b[39;49m\u001b[39m\"\u001b[39;49m,width\u001b[39m=\u001b[39;49m\u001b[39m1\u001b[39;49m))),\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=15'>16</a>\u001b[0m                     row\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m,col\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m)\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=17'>18</a>\u001b[0m     fig\u001b[39m.\u001b[39madd_traces(go\u001b[39m.\u001b[39mPie(labels\u001b[39m=\u001b[39mdf[column_name]\u001b[39m.\u001b[39mvalues_counts()\u001b[39m.\u001b[39mkeys(),\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=18'>19</a>\u001b[0m                         values\u001b[39m=\u001b[39mdf[column_name]\u001b[39m.\u001b[39mvalue_counts()\u001b[39m.\u001b[39mvalues,\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=19'>20</a>\u001b[0m                         name\u001b[39m=\u001b[39mcolumn_name,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=24'>25</a>\u001b[0m                         marker\u001b[39m=\u001b[39m\u001b[39mdict\u001b[39m(colors\u001b[39m=\u001b[39mcontraints))\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=25'>26</a>\u001b[0m                         ,row\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m,col\u001b[39m=\u001b[39m\u001b[39m2\u001b[39m)\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=26'>27</a>\u001b[0m     fig\u001b[39m.\u001b[39mupdate_layout(title\u001b[39m=\u001b[39m{\u001b[39m\"\u001b[39m\u001b[39mtext\u001b[39m\u001b[39m\"\u001b[39m:column_name,\u001b[39m\"\u001b[39m\u001b[39my\u001b[39m\u001b[39m\"\u001b[39m:\u001b[39m0.9\u001b[39m , \u001b[39m\"\u001b[39m\u001b[39mx\u001b[39m\u001b[39m\"\u001b[39m:\u001b[39m0.5\u001b[39m,\u001b[39m'\u001b[39m\u001b[39mxanchor\u001b[39m\u001b[39m'\u001b[39m:\u001b[39m'\u001b[39m\u001b[39mcenter\u001b[39m\u001b[39m'\u001b[39m ,\u001b[39m\"\u001b[39m\u001b[39myanchor\u001b[39m\u001b[39m\"\u001b[39m:\u001b[39m\"\u001b[39m\u001b[39mtop\u001b[39m\u001b[39m\"\u001b[39m},\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Sagar%20Kumar/NAVTTC-BATCH-3/Internship/SentimentAnalysis.ipynb#X23sZmlsZQ%3D%3D?line=27'>28</a>\u001b[0m                         template\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mplotly_white\u001b[39m\u001b[39m\"\u001b[39m)\n",
      "File \u001b[1;32mc:\\Users\\Radhey_Radhey\\miniconda3\\lib\\site-packages\\plotly\\graph_objs\\_bar.py:3062\u001b[0m, in \u001b[0;36mBar.__init__\u001b[1;34m(self, arg, alignmentgroup, base, basesrc, cliponaxis, constraintext, customdata, customdatasrc, dx, dy, error_x, error_y, hoverinfo, hoverinfosrc, hoverlabel, hovertemplate, hovertemplatesrc, hovertext, hovertextsrc, ids, idssrc, insidetextanchor, insidetextfont, legendgroup, legendgrouptitle, legendrank, marker, meta, metasrc, name, offset, offsetgroup, offsetsrc, opacity, orientation, outsidetextfont, selected, selectedpoints, showlegend, stream, text, textangle, textfont, textposition, textpositionsrc, textsrc, texttemplate, texttemplatesrc, uid, uirevision, unselected, visible, width, widthsrc, x, x0, xaxis, xcalendar, xhoverformat, xperiod, xperiod0, xperiodalignment, xsrc, y, y0, yaxis, ycalendar, yhoverformat, yperiod, yperiod0, yperiodalignment, ysrc, **kwargs)\u001b[0m\n\u001b[0;32m   3060\u001b[0m _v \u001b[39m=\u001b[39m marker \u001b[39mif\u001b[39;00m marker \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m _v\n\u001b[0;32m   3061\u001b[0m \u001b[39mif\u001b[39;00m _v \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m-> 3062\u001b[0m     \u001b[39mself\u001b[39m[\u001b[39m\"\u001b[39m\u001b[39mmarker\u001b[39m\u001b[39m\"\u001b[39m] \u001b[39m=\u001b[39m _v\n\u001b[0;32m   3063\u001b[0m _v \u001b[39m=\u001b[39m arg\u001b[39m.\u001b[39mpop(\u001b[39m\"\u001b[39m\u001b[39mmeta\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mNone\u001b[39;00m)\n\u001b[0;32m   3064\u001b[0m _v \u001b[39m=\u001b[39m meta \u001b[39mif\u001b[39;00m meta \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m _v\n",
      "File \u001b[1;32mc:\\Users\\Radhey_Radhey\\miniconda3\\lib\\site-packages\\plotly\\basedatatypes.py:4851\u001b[0m, in \u001b[0;36mBasePlotlyType.__setitem__\u001b[1;34m(self, prop, value)\u001b[0m\n\u001b[0;32m   4849\u001b[0m \u001b[39m# ### Handle compound property ###\u001b[39;00m\n\u001b[0;32m   4850\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(validator, CompoundValidator):\n\u001b[1;32m-> 4851\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_set_compound_prop(prop, value)\n\u001b[0;32m   4853\u001b[0m \u001b[39m# ### Handle compound array property ###\u001b[39;00m\n\u001b[0;32m   4854\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(validator, (CompoundArrayValidator, BaseDataValidator)):\n",
      "File \u001b[1;32mc:\\Users\\Radhey_Radhey\\miniconda3\\lib\\site-packages\\plotly\\basedatatypes.py:5262\u001b[0m, in \u001b[0;36mBasePlotlyType._set_compound_prop\u001b[1;34m(self, prop, val)\u001b[0m\n\u001b[0;32m   5259\u001b[0m \u001b[39m# Import value\u001b[39;00m\n\u001b[0;32m   5260\u001b[0m \u001b[39m# ------------\u001b[39;00m\n\u001b[0;32m   5261\u001b[0m validator \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_get_validator(prop)\n\u001b[1;32m-> 5262\u001b[0m val \u001b[39m=\u001b[39m validator\u001b[39m.\u001b[39;49mvalidate_coerce(val, skip_invalid\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_skip_invalid)\n\u001b[0;32m   5264\u001b[0m \u001b[39m# Save deep copies of current and new states\u001b[39;00m\n\u001b[0;32m   5265\u001b[0m \u001b[39m# ------------------------------------------\u001b[39;00m\n\u001b[0;32m   5266\u001b[0m curr_val \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_compound_props\u001b[39m.\u001b[39mget(prop, \u001b[39mNone\u001b[39;00m)\n",
      "File \u001b[1;32mc:\\Users\\Radhey_Radhey\\miniconda3\\lib\\site-packages\\_plotly_utils\\basevalidators.py:2455\u001b[0m, in \u001b[0;36mCompoundValidator.validate_coerce\u001b[1;34m(self, v, skip_invalid, _validate)\u001b[0m\n\u001b[0;32m   2452\u001b[0m     v \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdata_class()\n\u001b[0;32m   2454\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(v, \u001b[39mdict\u001b[39m):\n\u001b[1;32m-> 2455\u001b[0m     v \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mdata_class(v, skip_invalid\u001b[39m=\u001b[39;49mskip_invalid, _validate\u001b[39m=\u001b[39;49m_validate)\n\u001b[0;32m   2457\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(v, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdata_class):\n\u001b[0;32m   2458\u001b[0m     \u001b[39m# Copy object\u001b[39;00m\n\u001b[0;32m   2459\u001b[0m     v \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdata_class(v)\n",
      "File \u001b[1;32mc:\\Users\\Radhey_Radhey\\miniconda3\\lib\\site-packages\\plotly\\graph_objs\\bar\\_marker.py:1124\u001b[0m, in \u001b[0;36mMarker.__init__\u001b[1;34m(self, arg, autocolorscale, cauto, cmax, cmid, cmin, color, coloraxis, colorbar, colorscale, colorsrc, line, opacity, opacitysrc, pattern, reversescale, showscale, **kwargs)\u001b[0m\n\u001b[0;32m   1122\u001b[0m _v \u001b[39m=\u001b[39m color \u001b[39mif\u001b[39;00m color \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m _v\n\u001b[0;32m   1123\u001b[0m \u001b[39mif\u001b[39;00m _v \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m-> 1124\u001b[0m     \u001b[39mself\u001b[39m[\u001b[39m\"\u001b[39m\u001b[39mcolor\u001b[39m\u001b[39m\"\u001b[39m] \u001b[39m=\u001b[39m _v\n\u001b[0;32m   1125\u001b[0m _v \u001b[39m=\u001b[39m arg\u001b[39m.\u001b[39mpop(\u001b[39m\"\u001b[39m\u001b[39mcoloraxis\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mNone\u001b[39;00m)\n\u001b[0;32m   1126\u001b[0m _v \u001b[39m=\u001b[39m coloraxis \u001b[39mif\u001b[39;00m coloraxis \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m _v\n",
      "File \u001b[1;32mc:\\Users\\Radhey_Radhey\\miniconda3\\lib\\site-packages\\plotly\\basedatatypes.py:4859\u001b[0m, in \u001b[0;36mBasePlotlyType.__setitem__\u001b[1;34m(self, prop, value)\u001b[0m\n\u001b[0;32m   4855\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_set_array_prop(prop, value)\n\u001b[0;32m   4857\u001b[0m     \u001b[39m# ### Handle simple property ###\u001b[39;00m\n\u001b[0;32m   4858\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[1;32m-> 4859\u001b[0m         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_set_prop(prop, value)\n\u001b[0;32m   4860\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m   4861\u001b[0m     \u001b[39m# Make sure properties dict is initialized\u001b[39;00m\n\u001b[0;32m   4862\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_init_props()\n",
      "File \u001b[1;32mc:\\Users\\Radhey_Radhey\\miniconda3\\lib\\site-packages\\plotly\\basedatatypes.py:5203\u001b[0m, in \u001b[0;36mBasePlotlyType._set_prop\u001b[1;34m(self, prop, val)\u001b[0m\n\u001b[0;32m   5201\u001b[0m         \u001b[39mreturn\u001b[39;00m\n\u001b[0;32m   5202\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[1;32m-> 5203\u001b[0m         \u001b[39mraise\u001b[39;00m err\n\u001b[0;32m   5205\u001b[0m \u001b[39m# val is None\u001b[39;00m\n\u001b[0;32m   5206\u001b[0m \u001b[39m# -----------\u001b[39;00m\n\u001b[0;32m   5207\u001b[0m \u001b[39mif\u001b[39;00m val \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m   5208\u001b[0m     \u001b[39m# Check if we should send null update\u001b[39;00m\n",
      "File \u001b[1;32mc:\\Users\\Radhey_Radhey\\miniconda3\\lib\\site-packages\\plotly\\basedatatypes.py:5198\u001b[0m, in \u001b[0;36mBasePlotlyType._set_prop\u001b[1;34m(self, prop, val)\u001b[0m\n\u001b[0;32m   5195\u001b[0m validator \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_get_validator(prop)\n\u001b[0;32m   5197\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m-> 5198\u001b[0m     val \u001b[39m=\u001b[39m validator\u001b[39m.\u001b[39;49mvalidate_coerce(val)\n\u001b[0;32m   5199\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mValueError\u001b[39;00m \u001b[39mas\u001b[39;00m err:\n\u001b[0;32m   5200\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_skip_invalid:\n",
      "File \u001b[1;32mc:\\Users\\Radhey_Radhey\\miniconda3\\lib\\site-packages\\_plotly_utils\\basevalidators.py:1368\u001b[0m, in \u001b[0;36mColorValidator.validate_coerce\u001b[1;34m(self, v, should_raise)\u001b[0m\n\u001b[0;32m   1365\u001b[0m invalid_els \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mfind_invalid_els(v, validated_v)\n\u001b[0;32m   1367\u001b[0m \u001b[39mif\u001b[39;00m invalid_els \u001b[39mand\u001b[39;00m should_raise:\n\u001b[1;32m-> 1368\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mraise_invalid_elements(invalid_els)\n\u001b[0;32m   1369\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m   1370\u001b[0m     v \u001b[39m=\u001b[39m validated_v\n",
      "File \u001b[1;32mc:\\Users\\Radhey_Radhey\\miniconda3\\lib\\site-packages\\_plotly_utils\\basevalidators.py:304\u001b[0m, in \u001b[0;36mBaseValidator.raise_invalid_elements\u001b[1;34m(self, invalid_els)\u001b[0m\n\u001b[0;32m    302\u001b[0m     \u001b[39mdef\u001b[39;00m \u001b[39mraise_invalid_elements\u001b[39m(\u001b[39mself\u001b[39m, invalid_els):\n\u001b[0;32m    303\u001b[0m         \u001b[39mif\u001b[39;00m invalid_els:\n\u001b[1;32m--> 304\u001b[0m             \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[0;32m    305\u001b[0m                 \u001b[39m\"\"\"\u001b[39;00m\n\u001b[0;32m    306\u001b[0m \u001b[39m    Invalid element(s) received for the '{name}' property of {pname}\u001b[39;00m\n\u001b[0;32m    307\u001b[0m \u001b[39m        Invalid elements include: {invalid}\u001b[39;00m\n\u001b[0;32m    308\u001b[0m \n\u001b[0;32m    309\u001b[0m \u001b[39m{valid_clr_desc}\"\"\"\u001b[39;00m\u001b[39m.\u001b[39mformat(\n\u001b[0;32m    310\u001b[0m                     name\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mplotly_name,\n\u001b[0;32m    311\u001b[0m                     pname\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mparent_name,\n\u001b[0;32m    312\u001b[0m                     invalid\u001b[39m=\u001b[39minvalid_els[:\u001b[39m10\u001b[39m],\n\u001b[0;32m    313\u001b[0m                     valid_clr_desc\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdescription(),\n\u001b[0;32m    314\u001b[0m                 )\n\u001b[0;32m    315\u001b[0m             )\n",
      "\u001b[1;31mValueError\u001b[0m: \n    Invalid element(s) received for the 'color' property of bar.marker\n        Invalid elements include: ['0C92EB']\n\n    The 'color' property is a color and may be specified as:\n      - A hex string (e.g. '#ff0000')\n      - An rgb/rgba string (e.g. 'rgb(255,0,0)')\n      - An hsl/hsla string (e.g. 'hsl(0,100%,50%)')\n      - An hsv/hsva string (e.g. 'hsv(0,100%,100%)')\n      - A named CSS color:\n            aliceblue, antiquewhite, aqua, aquamarine, azure,\n            beige, bisque, black, blanchedalmond, blue,\n            blueviolet, brown, burlywood, cadetblue,\n            chartreuse, chocolate, coral, cornflowerblue,\n            cornsilk, crimson, cyan, darkblue, darkcyan,\n            darkgoldenrod, darkgray, darkgrey, darkgreen,\n            darkkhaki, darkmagenta, darkolivegreen, darkorange,\n            darkorchid, darkred, darksalmon, darkseagreen,\n            darkslateblue, darkslategray, darkslategrey,\n            darkturquoise, darkviolet, deeppink, deepskyblue,\n            dimgray, dimgrey, dodgerblue, firebrick,\n            floralwhite, forestgreen, fuchsia, gainsboro,\n            ghostwhite, gold, goldenrod, gray, grey, green,\n            greenyellow, honeydew, hotpink, indianred, indigo,\n            ivory, khaki, lavender, lavenderblush, lawngreen,\n            lemonchiffon, lightblue, lightcoral, lightcyan,\n            lightgoldenrodyellow, lightgray, lightgrey,\n            lightgreen, lightpink, lightsalmon, lightseagreen,\n            lightskyblue, lightslategray, lightslategrey,\n            lightsteelblue, lightyellow, lime, limegreen,\n            linen, magenta, maroon, mediumaquamarine,\n            mediumblue, mediumorchid, mediumpurple,\n            mediumseagreen, mediumslateblue, mediumspringgreen,\n            mediumturquoise, mediumvioletred, midnightblue,\n            mintcream, mistyrose, moccasin, navajowhite, navy,\n            oldlace, olive, olivedrab, orange, orangered,\n            orchid, palegoldenrod, palegreen, paleturquoise,\n            palevioletred, papayawhip, peachpuff, peru, pink,\n            plum, powderblue, purple, red, rosybrown,\n            royalblue, rebeccapurple, saddlebrown, salmon,\n            sandybrown, seagreen, seashell, sienna, silver,\n            skyblue, slateblue, slategray, slategrey, snow,\n            springgreen, steelblue, tan, teal, thistle, tomato,\n            turquoise, violet, wheat, white, whitesmoke,\n            yellow, yellowgreen\n      - A number that will be interpreted as a color\n        according to bar.marker.colorscale\n      - A list or array of any of the above"
     ]
    }
   ],
   "source": [
    "categorical_variable_summary(df,\"overall\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2031    [[ UPDATE - 6/19/2014 ]]So my lovely wife bought me a Samsung Galaxy Tab 4 for Father's Day and I've been loving it ever since.  Just as other with Samsung products, the Galaxy Tab 4 has the abili...\n",
       "3449    I have tested dozens of SDHC and micro-SDHC cards. One disturbing trend I noticed is that: the speed class rating for micro-SDHC is typically inflated. For example, a 'class-10' rating means the c...\n",
       "4212    NOTE:  please read the last update (scroll to the bottom) - I'm leaving this review as 1 star as it appears to help others who purchased and had a similar experience.I give SanDisk 5 stars for cus...\n",
       "317     If your card gets hot enough to be painful, it is defective and you need to contact SanDisk!From my experience, the larger micro SDs run hot on format and writing, but not to the pain threshold!I ...\n",
       "4672    Sandisk announcement of the first 128GB micro SD took internet by storm. Our phones evolved into multimedia powerhouses with 5.5&#34;-6&#34; displays, desktop grade processing power, OTG support f...\n",
       "Name: reviewText, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.reviewText.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[[ UPDATE - 6/19/2014 ]]So my lovely wife bought me a Samsung Galaxy Tab 4 for Father\\'s Day and I\\'ve been loving it ever since.  Just as other with Samsung products, the Galaxy Tab 4 has the ability to add a microSD card to expand the memory on the device.  Since it\\'s been over a year, I decided to do some more research to see if SanDisk offered anything new.  As of 6/19/2014, their product lineup for microSD cards from worst to best (performance-wise) are the as follows:SanDiskSanDisk UltraSanDisk Ultra PLUSSanDisk ExtremeSanDisk Extreme PLUSSanDisk Extreme PRONow, the difference between all of these cards are simply the speed in which you can read/write data to the card.  Yes, the published rating of most all these cards (except the SanDisk regular) are Class 10/UHS-I but that\\'s just a rating... Actual real world performance does get better with each model, but with faster cards come more expensive prices.  Since Amazon doesn\\'t carry the Ultra PLUS model of microSD card, I had to do direct comparisons between the SanDisk Ultra ($34.27), Extreme ($57.95), and Extreme PLUS ($67.95).As mentioned in my earlier review, I purchased the SanDisk Ultra for my Galaxy S4.  My question was, did I want to pay over $20 more for a card that is faster than the one I already owned?  Or I could pay almost double to get SanDisk\\'s 2nd-most fastest microSD card.The Ultra works perfectly fine for my style of usage (storing/capturing pictures & HD video and movie playback) on my phone.  So in the end, I ended up just buying another SanDisk Ultra 64GB card.  I use my cell phone *more* than I do my tablet and if the card is good enough for my phone, it\\'s good enough for my tablet.  I don\\'t own a 4K HD camera or anything like that, so I honestly didn\\'t see a need to get one of the faster cards at this time.I am now a proud owner of 2 SanDisk Ultra cards and have absolutely 0 issues with it in my Samsung devices.[[ ORIGINAL REVIEW - 5/1/2013 ]]I haven\\'t had to buy a microSD card in a long time. The last time I bought one was for my cell phone over 2 years ago. But since my cellular contract was up, I knew I would have to get a newer card in addition to my new phone, the Samsung Galaxy S4. Reason for this is because I knew my small 16GB microSD card wasn\\'t going to cut it.Doing research on the Galaxy S4, I wanted to get the best card possible that had decent capacity (32 GB or greater). This led me to find that the Galaxy S4 supports the microSDXC Class 10 UHS-I card, which is the fastest possible given that class. Searching for that specifically on Amazon gave me results of only 3 vendors (as of April) that makes these microSDXC Class 10 UHS-1 cards. They are Sandisk (the majority), Samsung and Lexar. Nobody else makes these that are sold on Amazon.Seeing how SanDisk is a pretty good name out of the 3 (I\\'ve used them the most), I decided upon the SanDisk because Lexar was overpriced and the Samsung one was overpriced (as well as not eligible for Amazon Prime).But the scary thing is that when you filter by the SanDisk, you literally get DOZENS of options. All of them have different model numbers, different sizes, etc. Then there\\'s that confusion of what\\'s the difference between SDHC & SDXC?SDHC vs SDXC:SDHC stand for \"Secure Digital High Capacity\" and SDXC stands for \"Secure Digital eXtended Capacity\". Essentially these two cards are the same with the exception that SDHC only supports capcities up to 32GB and is formated with the FAT32 file system. The SDXC cards are formatted with the exFAT file system. If you use an SDXC card in a device, it must support that file system, otherwise it may not be recognizable and/or you have to reformat the card to FAT32.FAT32 vs exFAT:The differences between the two file systems means that FAT32 has a maximum file size of 4GB, limited by that file system. exFAT on the otherhand, supports file sizes up to 2TB (terabytes). The only thing you need to know here really is that it\\'s possible your device doesn\\'t support exFAT. If that\\'s the case, just reformat it to FAT32. REMEMBER FORMATTING ERASES ALL DATA!To clarify the model numbers, I I hopped over to the SanDisk official webpage. What I found there is that they offer two \"highspeed\" options for SanDisk cards. These are SanDisk Extreme Pro and SanDisk Ultra. SanDisk Extreme Pro is a line that supports read speeds up to 95MB/sec, however they are SDHC only. To make things worse, they are currently only available in 16GB & 8GB capacities. Since one of my requirements was to have a lot of storage, I ruled these out.The remaining devices listed on Amazon\\'s search were the SanDisk Ultra line. But here, confusion sets in because SanDisk separates these cards to two different devices. Cameras & mobile devices. Is there a real difference between the two or is this just a marketing stunt? Unfortunately I\\'m not sure but I do know the price difference between the two range from a couple cents to a few dollars. Since I wasn\\'t sure, I opted for the one specifically targeted for mobile devices (just in case there is some kind of compatibility issue). To find the exact model number, I would go to Sandisk\\'s webpage (sandisk.com) and compare their existing product lineup. From there, you get exact model numbers and you can then search Amazon for these model numbers. That is how I got mine (SDSDQUA-064G).As for speed tests, I haven\\'t run any specific testing, but copying 8 GB worth of data from my PC to the card literally took just a few minutes.One last note is that Amazon attaches additional characters to the end (for example SDSDQUA-064G-AFFP-A vs SDSDQUA-064G-U46A). The difference between the two is that the \"AFFP-A\" means \"Amazon Frustration Free Packaging\". Other than that, these are exactly the same.  If you\\'re wondering what I got (and want to use it in your Galaxy S4), I got the SDSDQUA-064G-u46A and it works like charm.'"
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       "'   UPDATE               So my lovely wife bought me a Samsung Galaxy Tab   for Father s Day and I ve been loving it ever since   Just as other with Samsung products  the Galaxy Tab   has the ability to add a microSD card to expand the memory on the device   Since it s been over a year  I decided to do some more research to see if SanDisk offered anything new   As of            their product lineup for microSD cards from worst to best  performance wise  are the as follows SanDiskSanDisk UltraSanDisk Ultra PLUSSanDisk ExtremeSanDisk Extreme PLUSSanDisk Extreme PRONow  the difference between all of these cards are simply the speed in which you can read write data to the card   Yes  the published rating of most all these cards  except the SanDisk regular  are Class    UHS I but that s just a rating    Actual real world performance does get better with each model  but with faster cards come more expensive prices   Since Amazon doesn t carry the Ultra PLUS model of microSD card  I had to do direct comparisons between the SanDisk Ultra           Extreme           and Extreme PLUS          As mentioned in my earlier review  I purchased the SanDisk Ultra for my Galaxy S    My question was  did I want to pay over     more for a card that is faster than the one I already owned   Or I could pay almost double to get SanDisk s  nd most fastest microSD card The Ultra works perfectly fine for my style of usage  storing capturing pictures   HD video and movie playback  on my phone   So in the end  I ended up just buying another SanDisk Ultra   GB card   I use my cell phone  more  than I do my tablet and if the card is good enough for my phone  it s good enough for my tablet   I don t own a  K HD camera or anything like that  so I honestly didn t see a need to get one of the faster cards at this time I am now a proud owner of   SanDisk Ultra cards and have absolutely   issues with it in my Samsung devices    ORIGINAL REVIEW              I haven t had to buy a microSD card in a long time  The last time I bought one was for my cell phone over   years ago  But since my cellular contract was up  I knew I would have to get a newer card in addition to my new phone  the Samsung Galaxy S   Reason for this is because I knew my small   GB microSD card wasn t going to cut it Doing research on the Galaxy S   I wanted to get the best card possible that had decent capacity     GB or greater   This led me to find that the Galaxy S  supports the microSDXC Class    UHS I card  which is the fastest possible given that class  Searching for that specifically on Amazon gave me results of only   vendors  as of April  that makes these microSDXC Class    UHS   cards  They are Sandisk  the majority   Samsung and Lexar  Nobody else makes these that are sold on Amazon Seeing how SanDisk is a pretty good name out of the    I ve used them the most   I decided upon the SanDisk because Lexar was overpriced and the Samsung one was overpriced  as well as not eligible for Amazon Prime  But the scary thing is that when you filter by the SanDisk  you literally get DOZENS of options  All of them have different model numbers  different sizes  etc  Then there s that confusion of what s the difference between SDHC   SDXC SDHC vs SDXC SDHC stand for  Secure Digital High Capacity  and SDXC stands for  Secure Digital eXtended Capacity   Essentially these two cards are the same with the exception that SDHC only supports capcities up to   GB and is formated with the FAT   file system  The SDXC cards are formatted with the exFAT file system  If you use an SDXC card in a device  it must support that file system  otherwise it may not be recognizable and or you have to reformat the card to FAT   FAT   vs exFAT The differences between the two file systems means that FAT   has a maximum file size of  GB  limited by that file system  exFAT on the otherhand  supports file sizes up to  TB  terabytes   The only thing you need to know here really is that it s possible your device doesn t support exFAT  If that s the case  just reformat it to FAT    REMEMBER FORMATTING ERASES ALL DATA To clarify the model numbers  I I hopped over to the SanDisk official webpage  What I found there is that they offer two  highspeed  options for SanDisk cards  These are SanDisk Extreme Pro and SanDisk Ultra  SanDisk Extreme Pro is a line that supports read speeds up to   MB sec  however they are SDHC only  To make things worse  they are currently only available in   GB    GB capacities  Since one of my requirements was to have a lot of storage  I ruled these out The remaining devices listed on Amazon s search were the SanDisk Ultra line  But here  confusion sets in because SanDisk separates these cards to two different devices  Cameras   mobile devices  Is there a real difference between the two or is this just a marketing stunt  Unfortunately I m not sure but I do know the price difference between the two range from a couple cents to a few dollars  Since I wasn t sure  I opted for the one specifically targeted for mobile devices  just in case there is some kind of compatibility issue   To find the exact model number  I would go to Sandisk s webpage  sandisk com  and compare their existing product lineup  From there  you get exact model numbers and you can then search Amazon for these model numbers  That is how I got mine  SDSDQUA    G  As for speed tests  I haven t run any specific testing  but copying   GB worth of data from my PC to the card literally took just a few minutes One last note is that Amazon attaches additional characters to the end  for example SDSDQUA    G AFFP A vs SDSDQUA    G U  A   The difference between the two is that the  AFFP A  means  Amazon Frustration Free Packaging   Other than that  these are exactly the same   If you re wondering what I got  and want to use it in your Galaxy S    I got the SDSDQUA    G u  A and it works like charm '"
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       " 'sdhc',\n",
       " 'only',\n",
       " 'supports',\n",
       " 'capcities',\n",
       " 'up',\n",
       " 'to',\n",
       " 'gb',\n",
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       " 'formated',\n",
       " 'with',\n",
       " 'the',\n",
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       " 'file',\n",
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       " 'sdxc',\n",
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       " 'formatted',\n",
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       " 'the',\n",
       " 'exfat',\n",
       " 'file',\n",
       " 'system',\n",
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       " 'you',\n",
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       " 'an',\n",
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       " 'system',\n",
       " 'otherwise',\n",
       " 'it',\n",
       " 'may',\n",
       " 'not',\n",
       " 'be',\n",
       " 'recognizable',\n",
       " 'and',\n",
       " 'or',\n",
       " 'you',\n",
       " 'have',\n",
       " 'to',\n",
       " 'reformat',\n",
       " 'the',\n",
       " 'card',\n",
       " 'to',\n",
       " 'fat',\n",
       " 'fat',\n",
       " 'vs',\n",
       " 'exfat',\n",
       " 'the',\n",
       " 'differences',\n",
       " 'between',\n",
       " 'the',\n",
       " 'two',\n",
       " 'file',\n",
       " 'systems',\n",
       " 'means',\n",
       " 'that',\n",
       " 'fat',\n",
       " 'has',\n",
       " 'a',\n",
       " 'maximum',\n",
       " 'file',\n",
       " 'size',\n",
       " 'of',\n",
       " 'gb',\n",
       " 'limited',\n",
       " 'by',\n",
       " 'that',\n",
       " 'file',\n",
       " 'system',\n",
       " 'exfat',\n",
       " 'on',\n",
       " 'the',\n",
       " 'otherhand',\n",
       " 'supports',\n",
       " 'file',\n",
       " 'sizes',\n",
       " 'up',\n",
       " 'to',\n",
       " 'tb',\n",
       " 'terabytes',\n",
       " 'the',\n",
       " 'only',\n",
       " 'thing',\n",
       " 'you',\n",
       " 'need',\n",
       " 'to',\n",
       " 'know',\n",
       " 'here',\n",
       " 'really',\n",
       " 'is',\n",
       " 'that',\n",
       " 'it',\n",
       " 's',\n",
       " 'possible',\n",
       " 'your',\n",
       " 'device',\n",
       " 'doesn',\n",
       " 't',\n",
       " 'support',\n",
       " 'exfat',\n",
       " 'if',\n",
       " 'that',\n",
       " 's',\n",
       " 'the',\n",
       " 'case',\n",
       " 'just',\n",
       " 'reformat',\n",
       " 'it',\n",
       " 'to',\n",
       " 'fat',\n",
       " 'remember',\n",
       " 'formatting',\n",
       " 'erases',\n",
       " 'all',\n",
       " 'data',\n",
       " 'to',\n",
       " 'clarify',\n",
       " 'the',\n",
       " 'model',\n",
       " 'numbers',\n",
       " 'i',\n",
       " 'i',\n",
       " 'hopped',\n",
       " 'over',\n",
       " 'to',\n",
       " 'the',\n",
       " 'sandisk',\n",
       " 'official',\n",
       " 'webpage',\n",
       " 'what',\n",
       " 'i',\n",
       " 'found',\n",
       " 'there',\n",
       " 'is',\n",
       " 'that',\n",
       " 'they',\n",
       " 'offer',\n",
       " 'two',\n",
       " 'highspeed',\n",
       " 'options',\n",
       " 'for',\n",
       " 'sandisk',\n",
       " 'cards',\n",
       " 'these',\n",
       " 'are',\n",
       " 'sandisk',\n",
       " 'extreme',\n",
       " 'pro',\n",
       " 'and',\n",
       " 'sandisk',\n",
       " 'ultra',\n",
       " 'sandisk',\n",
       " 'extreme',\n",
       " 'pro',\n",
       " 'is',\n",
       " 'a',\n",
       " 'line',\n",
       " 'that',\n",
       " 'supports',\n",
       " 'read',\n",
       " 'speeds',\n",
       " 'up',\n",
       " 'to',\n",
       " 'mb',\n",
       " 'sec',\n",
       " 'however',\n",
       " 'they',\n",
       " 'are',\n",
       " 'sdhc',\n",
       " 'only',\n",
       " 'to',\n",
       " 'make',\n",
       " 'things',\n",
       " 'worse',\n",
       " 'they',\n",
       " 'are',\n",
       " 'currently',\n",
       " 'only',\n",
       " 'available',\n",
       " 'in',\n",
       " 'gb',\n",
       " 'gb',\n",
       " 'capacities',\n",
       " 'since',\n",
       " 'one',\n",
       " 'of',\n",
       " 'my',\n",
       " 'requirements',\n",
       " 'was',\n",
       " 'to',\n",
       " 'have',\n",
       " 'a',\n",
       " 'lot',\n",
       " 'of',\n",
       " 'storage',\n",
       " 'i',\n",
       " 'ruled',\n",
       " 'these',\n",
       " 'out',\n",
       " 'the',\n",
       " 'remaining',\n",
       " 'devices',\n",
       " 'listed',\n",
       " 'on',\n",
       " 'amazon',\n",
       " 's',\n",
       " 'search',\n",
       " 'were',\n",
       " 'the',\n",
       " 'sandisk',\n",
       " 'ultra',\n",
       " 'line',\n",
       " 'but',\n",
       " 'here',\n",
       " 'confusion',\n",
       " 'sets',\n",
       " 'in',\n",
       " 'because',\n",
       " 'sandisk',\n",
       " 'separates',\n",
       " 'these',\n",
       " 'cards',\n",
       " 'to',\n",
       " 'two',\n",
       " 'different',\n",
       " 'devices',\n",
       " 'cameras',\n",
       " 'mobile',\n",
       " 'devices',\n",
       " 'is',\n",
       " 'there',\n",
       " 'a',\n",
       " 'real',\n",
       " 'difference',\n",
       " 'between',\n",
       " 'the',\n",
       " 'two',\n",
       " 'or',\n",
       " 'is',\n",
       " 'this',\n",
       " 'just',\n",
       " 'a',\n",
       " 'marketing',\n",
       " 'stunt',\n",
       " 'unfortunately',\n",
       " 'i',\n",
       " 'm',\n",
       " 'not',\n",
       " 'sure',\n",
       " 'but',\n",
       " 'i',\n",
       " 'do',\n",
       " 'know',\n",
       " 'the',\n",
       " 'price',\n",
       " 'difference',\n",
       " 'between',\n",
       " 'the',\n",
       " 'two',\n",
       " 'range',\n",
       " 'from',\n",
       " 'a',\n",
       " 'couple',\n",
       " 'cents',\n",
       " 'to',\n",
       " 'a',\n",
       " 'few',\n",
       " 'dollars',\n",
       " 'since',\n",
       " 'i',\n",
       " 'wasn',\n",
       " 't',\n",
       " 'sure',\n",
       " 'i',\n",
       " 'opted',\n",
       " 'for',\n",
       " 'the',\n",
       " 'one',\n",
       " 'specifically',\n",
       " 'targeted',\n",
       " 'for',\n",
       " 'mobile',\n",
       " 'devices',\n",
       " 'just',\n",
       " 'in',\n",
       " 'case',\n",
       " 'there',\n",
       " 'is',\n",
       " 'some',\n",
       " 'kind',\n",
       " 'of',\n",
       " 'compatibility',\n",
       " 'issue',\n",
       " 'to',\n",
       " 'find',\n",
       " 'the',\n",
       " 'exact',\n",
       " 'model',\n",
       " 'number',\n",
       " 'i',\n",
       " 'would',\n",
       " 'go',\n",
       " 'to',\n",
       " 'sandisk',\n",
       " 's',\n",
       " 'webpage',\n",
       " 'sandisk',\n",
       " 'com',\n",
       " 'and',\n",
       " 'compare',\n",
       " 'their',\n",
       " 'existing',\n",
       " 'product',\n",
       " 'lineup',\n",
       " 'from',\n",
       " 'there',\n",
       " 'you',\n",
       " 'get',\n",
       " 'exact',\n",
       " 'model',\n",
       " 'numbers',\n",
       " 'and',\n",
       " 'you',\n",
       " 'can',\n",
       " 'then',\n",
       " 'search',\n",
       " 'amazon',\n",
       " 'for',\n",
       " 'these',\n",
       " 'model',\n",
       " 'numbers',\n",
       " 'that',\n",
       " 'is',\n",
       " 'how',\n",
       " 'i',\n",
       " 'got',\n",
       " 'mine',\n",
       " 'sdsdqua',\n",
       " 'g',\n",
       " 'as',\n",
       " 'for',\n",
       " 'speed',\n",
       " 'tests',\n",
       " 'i',\n",
       " 'haven',\n",
       " 't',\n",
       " 'run',\n",
       " 'any',\n",
       " 'specific',\n",
       " 'testing',\n",
       " 'but',\n",
       " 'copying',\n",
       " 'gb',\n",
       " 'worth',\n",
       " 'of',\n",
       " 'data',\n",
       " 'from',\n",
       " 'my',\n",
       " 'pc',\n",
       " 'to',\n",
       " 'the',\n",
       " 'card',\n",
       " 'literally',\n",
       " 'took',\n",
       " 'just',\n",
       " 'a',\n",
       " 'few',\n",
       " 'minutes',\n",
       " 'one',\n",
       " 'last',\n",
       " 'note',\n",
       " 'is',\n",
       " ...]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "review_example=review_example.lower().split()\n",
    "review_example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2031       update               so my lovely wife bought me a samsung galaxy tab   for father s day and i ve been loving it ever since   just as other with samsung products  the galaxy tab   has the abili...\n",
       "3449    i have tested dozens of sdhc and micro sdhc cards  one disturbing trend i noticed is that  the speed class rating for micro sdhc is typically inflated  for example  a  class     rating means the c...\n",
       "4212    note   please read the last update  scroll to the bottom    i m leaving this review as   star as it appears to help others who purchased and had a similar experience i give sandisk   stars for cus...\n",
       "317     if your card gets hot enough to be painful  it is defective and you need to contact sandisk from my experience  the larger micro sds run hot on format and writing  but not to the pain threshold i ...\n",
       "4672    sandisk announcement of the first    gb micro sd took internet by storm  our phones evolved into multimedia powerhouses with                 displays  desktop grade processing power  otg support f...\n",
       "Name: reviewText, dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rt = lambda x: re.sub(\"[^a-zA-Z]\",\" \",str(x))\n",
    "df[\"reviewText\"]=df[\"reviewText\"].map(rt)\n",
    "df[\"reviewText\"]=df[\"reviewText\"].str.lower()\n",
    "df[\"reviewText\"].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer\n",
    "df[['polarity' , 'subjectivity']]=df['reviewText'].apply(lambda Text:pd.Series(TextBlob(Text).sentiment))\n",
    "\n",
    "for index , row in df['reviewText'].iteritems():\n",
    "    score = SentimentIntensityAnalyzer().polarity_scores(row)\n",
    "    neg = score['neg']\n",
    "    neu = score['neu']\n",
    "    pos = score['pos']\n",
    "    if neg>pos:\n",
    "        df.loc[index,'sentiment']='negative'\n",
    "    elif pos>neg:\n",
    "        df.loc[index,'sentiment']='postive'\n",
    "    else:\n",
    "        df.loc[index,'sentiment']='neutral'"
   ]
  }
 ],
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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