Vine_Review_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "broadband-duncan",
   "metadata": {},
   "outputs": [],
   "source": [
    "# deliverable 2 - Michael Mishkanian\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "dutch-tobacco",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>review_id</th>\n",
       "      <th>star_rating</th>\n",
       "      <th>helpful_votes</th>\n",
       "      <th>total_votes</th>\n",
       "      <th>vine</th>\n",
       "      <th>verified_purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RTIS3L2M1F5SM</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>R1ZV7R40OLHKD</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>R3BH071QLH8QMC</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R127K9NTSXA2YH</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>R32ZWUXDJPW27Q</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        review_id  star_rating  helpful_votes  total_votes vine  \\\n",
       "0   RTIS3L2M1F5SM            5              0            0    N   \n",
       "1   R1ZV7R40OLHKD            5              0            0    N   \n",
       "2  R3BH071QLH8QMC            1              0            1    N   \n",
       "3  R127K9NTSXA2YH            3              0            0    N   \n",
       "4  R32ZWUXDJPW27Q            4              0            0    N   \n",
       "\n",
       "  verified_purchase  \n",
       "0                 Y  \n",
       "1                 Y  \n",
       "2                 Y  \n",
       "3                 Y  \n",
       "4                 Y  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read in vine.csv as a dataframe\n",
    "vine_df = pd.read_csv(\"vine.csv\")\n",
    "vine_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cubic-fiction",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>review_id</th>\n",
       "      <th>star_rating</th>\n",
       "      <th>helpful_votes</th>\n",
       "      <th>total_votes</th>\n",
       "      <th>vine</th>\n",
       "      <th>verified_purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
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       "      <td>1</td>\n",
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       "      <td>N</td>\n",
       "      <td>N</td>\n",
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       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>R2CI0Y288CC7E2</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>35</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>R127WEQY2FM1T3</td>\n",
       "      <td>1</td>\n",
       "      <td>147</td>\n",
       "      <td>175</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>289</th>\n",
       "      <td>R3EZ0EPYLDA34S</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>31</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>R2FJ94555FZH32</td>\n",
       "      <td>2</td>\n",
       "      <td>55</td>\n",
       "      <td>60</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          review_id  star_rating  helpful_votes  total_votes vine  \\\n",
       "55    R4PKAZRQJJX14            1             21           34    N   \n",
       "74   R2CI0Y288CC7E2            1             21           35    N   \n",
       "209  R127WEQY2FM1T3            1            147          175    N   \n",
       "289  R3EZ0EPYLDA34S            1             14           31    N   \n",
       "483  R2FJ94555FZH32            2             55           60    N   \n",
       "\n",
       "    verified_purchase  \n",
       "55                  N  \n",
       "74                  Y  \n",
       "209                 Y  \n",
       "289                 Y  \n",
       "483                 N  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# filter to only get rows where there are at least 20 total votes\n",
    "vine_df_filtered_high_votes = vine_df[vine_df[\"total_votes\"] >= 20]\n",
    "vine_df_filtered_high_votes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "nervous-affiliation",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>review_id</th>\n",
       "      <th>star_rating</th>\n",
       "      <th>helpful_votes</th>\n",
       "      <th>total_votes</th>\n",
       "      <th>vine</th>\n",
       "      <th>verified_purchase</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>R4PKAZRQJJX14</td>\n",
       "      <td>1</td>\n",
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       "      <td>34</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
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       "      <th>74</th>\n",
       "      <td>R2CI0Y288CC7E2</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>35</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
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       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>R127WEQY2FM1T3</td>\n",
       "      <td>1</td>\n",
       "      <td>147</td>\n",
       "      <td>175</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>R2FJ94555FZH32</td>\n",
       "      <td>2</td>\n",
       "      <td>55</td>\n",
       "      <td>60</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>537</th>\n",
       "      <td>R1U3AR67RE273L</td>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "      <td>65</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          review_id  star_rating  helpful_votes  total_votes vine  \\\n",
       "55    R4PKAZRQJJX14            1             21           34    N   \n",
       "74   R2CI0Y288CC7E2            1             21           35    N   \n",
       "209  R127WEQY2FM1T3            1            147          175    N   \n",
       "483  R2FJ94555FZH32            2             55           60    N   \n",
       "537  R1U3AR67RE273L            1             51           65    N   \n",
       "\n",
       "    verified_purchase  \n",
       "55                  N  \n",
       "74                  Y  \n",
       "209                 Y  \n",
       "483                 N  \n",
       "537                 Y  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# filter2 to only get rows where helpful/total_votes is at least .50\n",
    "total_votes_filter1 = vine_df_filtered_high_votes[\"total_votes\"]\n",
    "helpful_votes_filter1 = vine_df_filtered_high_votes[\"helpful_votes\"]\n",
    "vine_df_filter2_helpful = vine_df_filtered_high_votes[(helpful_votes_filter1/total_votes_filter1) >= .50]\n",
    "vine_df_filter2_helpful.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "experienced-transcript",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>review_id</th>\n",
       "      <th>star_rating</th>\n",
       "      <th>helpful_votes</th>\n",
       "      <th>total_votes</th>\n",
       "      <th>vine</th>\n",
       "      <th>verified_purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32611</th>\n",
       "      <td>R3KKUSGFZWSUIY</td>\n",
       "      <td>5</td>\n",
       "      <td>56</td>\n",
       "      <td>63</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
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       "      <th>33112</th>\n",
       "      <td>R10FO5UKKVZBK2</td>\n",
       "      <td>3</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69680</th>\n",
       "      <td>RM4KSGEOR7MU1</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>24</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155361</th>\n",
       "      <td>RG7VRMYLEXD23</td>\n",
       "      <td>4</td>\n",
       "      <td>22</td>\n",
       "      <td>26</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239327</th>\n",
       "      <td>R11O4YSCPSNL6L</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>26</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             review_id  star_rating  helpful_votes  total_votes vine  \\\n",
       "32611   R3KKUSGFZWSUIY            5             56           63    Y   \n",
       "33112   R10FO5UKKVZBK2            3             23           23    Y   \n",
       "69680    RM4KSGEOR7MU1            5             19           24    Y   \n",
       "155361   RG7VRMYLEXD23            4             22           26    Y   \n",
       "239327  R11O4YSCPSNL6L            3             20           26    Y   \n",
       "\n",
       "       verified_purchase  \n",
       "32611                  N  \n",
       "33112                  N  \n",
       "69680                  N  \n",
       "155361                 N  \n",
       "239327                 N  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# filter3 to only get rows that are part of \"vine\" program\n",
    "vine_df_filter3_vine_yes = vine_df_filter2_helpful[vine_df_filter2_helpful[\"vine\"]==\"Y\"]\n",
    "vine_df_filter3_vine_yes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "blocked-preparation",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>review_id</th>\n",
       "      <th>star_rating</th>\n",
       "      <th>helpful_votes</th>\n",
       "      <th>total_votes</th>\n",
       "      <th>vine</th>\n",
       "      <th>verified_purchase</th>\n",
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       "      <th>55</th>\n",
       "      <td>R4PKAZRQJJX14</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>34</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
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       "      <th>74</th>\n",
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       "      <td>1</td>\n",
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       "      <td>35</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
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       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>R127WEQY2FM1T3</td>\n",
       "      <td>1</td>\n",
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       "      <td>175</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
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       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>R2FJ94555FZH32</td>\n",
       "      <td>2</td>\n",
       "      <td>55</td>\n",
       "      <td>60</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>537</th>\n",
       "      <td>R1U3AR67RE273L</td>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "      <td>65</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          review_id  star_rating  helpful_votes  total_votes vine  \\\n",
       "55    R4PKAZRQJJX14            1             21           34    N   \n",
       "74   R2CI0Y288CC7E2            1             21           35    N   \n",
       "209  R127WEQY2FM1T3            1            147          175    N   \n",
       "483  R2FJ94555FZH32            2             55           60    N   \n",
       "537  R1U3AR67RE273L            1             51           65    N   \n",
       "\n",
       "    verified_purchase  \n",
       "55                  N  \n",
       "74                  Y  \n",
       "209                 Y  \n",
       "483                 N  \n",
       "537                 Y  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# filter4 to only get rows that are NOT part of \"vine\" program\n",
    "vine_df_filter4_vine_no = vine_df_filter2_helpful[vine_df_filter2_helpful[\"vine\"]==\"N\"]\n",
    "vine_df_filter4_vine_no.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "dramatic-atmosphere",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "94"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# total number of paid reviews (vine=yes)\n",
    "total_paid_reviews = len(vine_df_filter3_vine_yes)\n",
    "total_paid_reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "coordinated-heart",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40471"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# total number of unpaid reviews (vine=no)\n",
    "total_unpaid_reviews = len(vine_df_filter4_vine_no)\n",
    "total_unpaid_reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "popular-nirvana",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "48"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of 5-star paid reviews (vine=yes)\n",
    "paid_five_star_reviews_num = len(vine_df_filter3_vine_yes[vine_df_filter3_vine_yes[\"star_rating\"]==5])\n",
    "paid_five_star_reviews_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "jewish-version",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15663"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of 5-star unpaid reviews (vine=no)\n",
    "unpaid_five_star_reviews_num = len(vine_df_filter4_vine_no[vine_df_filter4_vine_no[\"star_rating\"]==5])\n",
    "unpaid_five_star_reviews_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "satisfactory-lithuania",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "51.06382978723404"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# percent of 5-star reviews for paid (vine=yes)\n",
    "percent_of_paid_5star = (paid_five_star_reviews_num/total_paid_reviews)*100\n",
    "percent_of_paid_5star"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "eight-programming",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "38.701786464381904"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# percent of 5-star reviews for unpaid (vine=no)\n",
    "percent_of_unpaid_5star = (unpaid_five_star_reviews_num/total_unpaid_reviews)*100\n",
    "percent_of_unpaid_5star"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "mental-matrix",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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