Vine_Review_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0722d89a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7255f974",
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>RDIJS7QYB6XNR</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>R36ED1U38IELG8</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>R1UE3RPRGCOLD</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R298788GS6I901</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RNX4EXOBBPN5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</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   RDIJS7QYB6XNR          5.0            0.0          0.0    N   \n",
       "1  R36ED1U38IELG8          5.0            0.0          0.0    N   \n",
       "2   R1UE3RPRGCOLD          2.0            1.0          1.0    N   \n",
       "3  R298788GS6I901          5.0            0.0          0.0    N   \n",
       "4    RNX4EXOBBPN5          1.0            1.0          1.0    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": [
    "# Create a DataFrame\n",
    "vine_csv = \"./Resources/vine_table.csv\"\n",
    "\n",
    "# Read the data\n",
    "vine_df = pd.read_csv(vine_csv)\n",
    "vine_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "940393a1",
   "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>104</th>\n",
       "      <td>ROP6ITXO8K5V2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>R3ND1LVU7AXCVF</td>\n",
       "      <td>1.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>R9I5FOLKU99RY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>R1QS8AOD6HX3ED</td>\n",
       "      <td>4.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>546</th>\n",
       "      <td>R3ED60RC69CCQ6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "          review_id  star_rating  helpful_votes  total_votes vine  \\\n",
       "104   ROP6ITXO8K5V2          5.0           23.0         27.0    N   \n",
       "311  R3ND1LVU7AXCVF          1.0           21.0         21.0    N   \n",
       "356   R9I5FOLKU99RY          5.0           19.0         20.0    Y   \n",
       "424  R1QS8AOD6HX3ED          4.0           59.0         81.0    N   \n",
       "546  R3ED60RC69CCQ6          5.0           22.0         23.0    Y   \n",
       "\n",
       "    verified_purchase  \n",
       "104                 Y  \n",
       "311                 Y  \n",
       "356                 N  \n",
       "424                 N  \n",
       "546                 N  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# retrieve all the rows where the total_votes count is equalto or greater than 20\n",
    "vine_df_total_votes = vine_df[vine_df[\"total_votes\"] >= 20]\n",
    "vine_df_total_votes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "19c39665",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 70474 entries, 104 to 4864246\n",
      "Data columns (total 6 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   review_id          70474 non-null  object \n",
      " 1   star_rating        70474 non-null  float64\n",
      " 2   helpful_votes      70474 non-null  float64\n",
      " 3   total_votes        70474 non-null  float64\n",
      " 4   vine               70474 non-null  object \n",
      " 5   verified_purchase  70474 non-null  object \n",
      "dtypes: float64(3), object(3)\n",
      "memory usage: 3.8+ MB\n"
     ]
    }
   ],
   "source": [
    "vine_df_total_votes.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8498e543",
   "metadata": {},
   "outputs": [
    {
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       "      <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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       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>ROP6ITXO8K5V2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>R3ND1LVU7AXCVF</td>\n",
       "      <td>1.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>R9I5FOLKU99RY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>R1QS8AOD6HX3ED</td>\n",
       "      <td>4.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>546</th>\n",
       "      <td>R3ED60RC69CCQ6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "          review_id  star_rating  helpful_votes  total_votes vine  \\\n",
       "104   ROP6ITXO8K5V2          5.0           23.0         27.0    N   \n",
       "311  R3ND1LVU7AXCVF          1.0           21.0         21.0    N   \n",
       "356   R9I5FOLKU99RY          5.0           19.0         20.0    Y   \n",
       "424  R1QS8AOD6HX3ED          4.0           59.0         81.0    N   \n",
       "546  R3ED60RC69CCQ6          5.0           22.0         23.0    Y   \n",
       "\n",
       "    verified_purchase  \n",
       "104                 Y  \n",
       "311                 Y  \n",
       "356                 N  \n",
       "424                 N  \n",
       "546                 N  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# retrieve all the rowswhere the number of helpful_votes divided by total_votes is equal to or greater than 50%\n",
    "vine_df_helpful = vine_df_total_votes[(vine_df_total_votes[\"helpful_votes\"]/vine_df_total_votes[\"total_votes\"]) >= 0.5]\n",
    "vine_df_helpful.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "009668e1",
   "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",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>R9I5FOLKU99RY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>546</th>\n",
       "      <td>R3ED60RC69CCQ6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>926</th>\n",
       "      <td>R2JM687C525WR9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7569</th>\n",
       "      <td>RUB4AUWGHG16G</td>\n",
       "      <td>4.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20672</th>\n",
       "      <td>R1S3IDYJUA6V2G</td>\n",
       "      <td>5.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "            review_id  star_rating  helpful_votes  total_votes vine  \\\n",
       "356     R9I5FOLKU99RY          5.0           19.0         20.0    Y   \n",
       "546    R3ED60RC69CCQ6          5.0           22.0         23.0    Y   \n",
       "926    R2JM687C525WR9          3.0           33.0         33.0    Y   \n",
       "7569    RUB4AUWGHG16G          4.0           25.0         27.0    Y   \n",
       "20672  R1S3IDYJUA6V2G          5.0           28.0         32.0    Y   \n",
       "\n",
       "      verified_purchase  \n",
       "356                   N  \n",
       "546                   N  \n",
       "926                   N  \n",
       "7569                  N  \n",
       "20672                 N  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# retrieve all the rows where a review was written as part of the Vine program (paid)\n",
    "vine_df_program = vine_df_helpful[vine_df_helpful[\"vine\"] == 'Y']\n",
    "vine_df_program.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "41a96048",
   "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",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>ROP6ITXO8K5V2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>R3ND1LVU7AXCVF</td>\n",
       "      <td>1.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>R1QS8AOD6HX3ED</td>\n",
       "      <td>4.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1176</th>\n",
       "      <td>R2LWX4TZ67FWPT</td>\n",
       "      <td>4.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1515</th>\n",
       "      <td>R29IYHPYD14AGI</td>\n",
       "      <td>3.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "           review_id  star_rating  helpful_votes  total_votes vine  \\\n",
       "104    ROP6ITXO8K5V2          5.0           23.0         27.0    N   \n",
       "311   R3ND1LVU7AXCVF          1.0           21.0         21.0    N   \n",
       "424   R1QS8AOD6HX3ED          4.0           59.0         81.0    N   \n",
       "1176  R2LWX4TZ67FWPT          4.0           50.0         50.0    N   \n",
       "1515  R29IYHPYD14AGI          3.0           84.0         84.0    N   \n",
       "\n",
       "     verified_purchase  \n",
       "104                  Y  \n",
       "311                  Y  \n",
       "424                  N  \n",
       "1176                 N  \n",
       "1515                 Y  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# retrieve all the rows where the review was not part of the Vine program (unpaid)\n",
    "vine_df_program_N = vine_df_helpful[vine_df_helpful[\"vine\"] == 'N']\n",
    "vine_df_program_N.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "08dafbd9",
   "metadata": {},
   "outputs": [],
   "source": [
    "#total number of reviews\n",
    "vine_total = vine_df_helpful[vine_df_helpful.columns[0]].count()\n",
    "# number of 5-star reviews\n",
    "five_stars = vine_df_helpful[vine_df_helpful[\"star_rating\"] == 5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fa9118d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# percentage of 5-star reviews (paid)\n",
    "five_stars_Y_ = vine_df_program[vine_df_program[\"star_rating\"] == 5]\n",
    "five_stars_Y = ((five_stars_Y_[five_stars_Y_.columns[0]].count())/vine_total)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5b63c0dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# percentage of 5-star reviews (unpaid)\n",
    "five_stars_N_ = vine_df_program_N[vine_df_program_N[\"star_rating\"] == 5]\n",
    "five_stars_N = ((five_stars_N_[five_stars_N_.columns[0]].count())/vine_total)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "68ff8435",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total_Reviews</th>\n",
       "      <th>5_stars</th>\n",
       "      <th>Vine_Y</th>\n",
       "      <th>Vine_N</th>\n",
       "      <th>Vine_Y_5_Stars</th>\n",
       "      <th>Vine_N_5_Stars</th>\n",
       "      <th>Perc_5_stars_vine_Y</th>\n",
       "      <th>Perc_5_stars_vine_N</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63294</td>\n",
       "      <td>30414</td>\n",
       "      <td>1266</td>\n",
       "      <td>62028</td>\n",
       "      <td>432</td>\n",
       "      <td>29982</td>\n",
       "      <td>0.682529</td>\n",
       "      <td>47.369419</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Total_Reviews  5_stars  Vine_Y  Vine_N  Vine_Y_5_Stars  Vine_N_5_Stars  \\\n",
       "0          63294    30414    1266   62028             432           29982   \n",
       "\n",
       "   Perc_5_stars_vine_Y  Perc_5_stars_vine_N  \n",
       "0             0.682529            47.369419  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Summary dataframe\n",
    "vine_anlysis_review = pd.DataFrame({'Total_Reviews': [vine_total],\n",
    "                      '5_stars': [five_stars[five_stars.columns[0]].count()],\n",
    "                      'Vine_Y':  [vine_df_program[vine_df_program.columns[0]].count()],\n",
    "                      'Vine_N':  [vine_df_program_N[vine_df_program_N.columns[0]].count()], \n",
    "                      'Vine_Y_5_Stars':  [(five_stars_Y_[five_stars_Y_.columns[0]].count())],\n",
    "                      'Vine_N_5_Stars':  [(five_stars_N_[five_stars_N_.columns[0]].count())],             \n",
    "                      'Perc_5_stars_vine_Y':  [five_stars_Y],\n",
    "                      'Perc_5_stars_vine_N': [five_stars_N]\n",
    "                     })\n",
    "vine_anlysis_review"
   ]
  }
 ],
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