Spaces:
Sleeping
Sleeping
Upload 3 files
Browse files- datacreation.ipynb +289 -1084
- pythonanalysis.ipynb +0 -0
- wine_data.csv +1001 -0
datacreation.ipynb
CHANGED
|
@@ -1,1087 +1,292 @@
|
|
| 1 |
{
|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
|
| 5 |
-
|
| 6 |
-
|
| 7 |
-
|
| 8 |
-
|
| 9 |
-
"# 🤖 **Data Collection, Creation, Storage, and Processing**\n"
|
| 10 |
-
]
|
| 11 |
-
},
|
| 12 |
-
{
|
| 13 |
-
"cell_type": "markdown",
|
| 14 |
-
"metadata": {
|
| 15 |
-
"id": "jpASMyIQMaAq"
|
| 16 |
-
},
|
| 17 |
-
"source": [
|
| 18 |
-
"## **1.** 📦 Install required packages"
|
| 19 |
-
]
|
| 20 |
-
},
|
| 21 |
-
{
|
| 22 |
-
"cell_type": "code",
|
| 23 |
-
"execution_count": 1,
|
| 24 |
-
"metadata": {
|
| 25 |
-
"colab": {
|
| 26 |
-
"base_uri": "https://localhost:8080/"
|
| 27 |
-
},
|
| 28 |
-
"id": "f48c8f8c",
|
| 29 |
-
"outputId": "13d0dd5e-82c6-489f-b1f0-e970186a4eb7"
|
| 30 |
-
},
|
| 31 |
-
"outputs": [
|
| 32 |
-
{
|
| 33 |
-
"output_type": "stream",
|
| 34 |
-
"name": "stdout",
|
| 35 |
-
"text": [
|
| 36 |
-
"Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.12/dist-packages (4.13.5)\n",
|
| 37 |
-
"Requirement already satisfied: pandas in /usr/local/lib/python3.12/dist-packages (2.2.2)\n",
|
| 38 |
-
"Requirement already satisfied: matplotlib in /usr/local/lib/python3.12/dist-packages (3.10.0)\n",
|
| 39 |
-
"Requirement already satisfied: seaborn in /usr/local/lib/python3.12/dist-packages (0.13.2)\n",
|
| 40 |
-
"Requirement already satisfied: numpy in /usr/local/lib/python3.12/dist-packages (2.0.2)\n",
|
| 41 |
-
"Requirement already satisfied: textblob in /usr/local/lib/python3.12/dist-packages (0.19.0)\n",
|
| 42 |
-
"Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.12/dist-packages (from beautifulsoup4) (2.8.3)\n",
|
| 43 |
-
"Requirement already satisfied: typing-extensions>=4.0.0 in /usr/local/lib/python3.12/dist-packages (from beautifulsoup4) (4.15.0)\n",
|
| 44 |
-
"Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.12/dist-packages (from pandas) (2.9.0.post0)\n",
|
| 45 |
-
"Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.12/dist-packages (from pandas) (2025.2)\n",
|
| 46 |
-
"Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.12/dist-packages (from pandas) (2025.3)\n",
|
| 47 |
-
"Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (1.3.3)\n",
|
| 48 |
-
"Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (0.12.1)\n",
|
| 49 |
-
"Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (4.61.1)\n",
|
| 50 |
-
"Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (1.4.9)\n",
|
| 51 |
-
"Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (26.0)\n",
|
| 52 |
-
"Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (11.3.0)\n",
|
| 53 |
-
"Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (3.3.2)\n",
|
| 54 |
-
"Requirement already satisfied: nltk>=3.9 in /usr/local/lib/python3.12/dist-packages (from textblob) (3.9.1)\n",
|
| 55 |
-
"Requirement already satisfied: click in /usr/local/lib/python3.12/dist-packages (from nltk>=3.9->textblob) (8.3.1)\n",
|
| 56 |
-
"Requirement already satisfied: joblib in /usr/local/lib/python3.12/dist-packages (from nltk>=3.9->textblob) (1.5.3)\n",
|
| 57 |
-
"Requirement already satisfied: regex>=2021.8.3 in /usr/local/lib/python3.12/dist-packages (from nltk>=3.9->textblob) (2025.11.3)\n",
|
| 58 |
-
"Requirement already satisfied: tqdm in /usr/local/lib/python3.12/dist-packages (from nltk>=3.9->textblob) (4.67.3)\n",
|
| 59 |
-
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n"
|
| 60 |
-
]
|
| 61 |
-
}
|
| 62 |
-
],
|
| 63 |
-
"source": [
|
| 64 |
-
"!pip install beautifulsoup4 pandas matplotlib seaborn numpy textblob"
|
| 65 |
-
]
|
| 66 |
-
},
|
| 67 |
-
{
|
| 68 |
-
"cell_type": "markdown",
|
| 69 |
-
"metadata": {
|
| 70 |
-
"id": "lquNYCbfL9IM"
|
| 71 |
-
},
|
| 72 |
-
"source": [
|
| 73 |
-
"## **2.** ⛏ Web-scrape all book titles, prices, and ratings from books.toscrape.com"
|
| 74 |
-
]
|
| 75 |
-
},
|
| 76 |
-
{
|
| 77 |
-
"cell_type": "markdown",
|
| 78 |
-
"metadata": {
|
| 79 |
-
"id": "0IWuNpxxYDJF"
|
| 80 |
-
},
|
| 81 |
-
"source": [
|
| 82 |
-
"### *a. Initial setup*\n",
|
| 83 |
-
"Define the base url of the website you will scrape as well as how and what you will scrape"
|
| 84 |
-
]
|
| 85 |
-
},
|
| 86 |
-
{
|
| 87 |
-
"cell_type": "code",
|
| 88 |
-
"execution_count": 2,
|
| 89 |
-
"metadata": {
|
| 90 |
-
"id": "91d52125"
|
| 91 |
-
},
|
| 92 |
-
"outputs": [],
|
| 93 |
-
"source": [
|
| 94 |
-
"import requests\n",
|
| 95 |
-
"from bs4 import BeautifulSoup\n",
|
| 96 |
-
"import pandas as pd\n",
|
| 97 |
-
"import time\n",
|
| 98 |
-
"\n",
|
| 99 |
-
"base_url = \"https://books.toscrape.com/catalogue/page-{}.html\"\n",
|
| 100 |
-
"headers = {\"User-Agent\": \"Mozilla/5.0\"}\n",
|
| 101 |
-
"\n",
|
| 102 |
-
"titles, prices, ratings = [], [], []"
|
| 103 |
-
]
|
| 104 |
-
},
|
| 105 |
-
{
|
| 106 |
-
"cell_type": "markdown",
|
| 107 |
-
"metadata": {
|
| 108 |
-
"id": "oCdTsin2Yfp3"
|
| 109 |
-
},
|
| 110 |
-
"source": [
|
| 111 |
-
"### *b. Fill titles, prices, and ratings from the web pages*"
|
| 112 |
-
]
|
| 113 |
-
},
|
| 114 |
-
{
|
| 115 |
-
"cell_type": "code",
|
| 116 |
-
"execution_count": 3,
|
| 117 |
-
"metadata": {
|
| 118 |
-
"id": "xqO5Y3dnYhxt"
|
| 119 |
-
},
|
| 120 |
-
"outputs": [],
|
| 121 |
-
"source": [
|
| 122 |
-
"# Loop through all 50 pages\n",
|
| 123 |
-
"for page in range(1, 51):\n",
|
| 124 |
-
" url = base_url.format(page)\n",
|
| 125 |
-
" response = requests.get(url, headers=headers)\n",
|
| 126 |
-
" soup = BeautifulSoup(response.content, \"html.parser\")\n",
|
| 127 |
-
" books = soup.find_all(\"article\", class_=\"product_pod\")\n",
|
| 128 |
-
"\n",
|
| 129 |
-
" for book in books:\n",
|
| 130 |
-
" titles.append(book.h3.a[\"title\"])\n",
|
| 131 |
-
" prices.append(float(book.find(\"p\", class_=\"price_color\").text[1:]))\n",
|
| 132 |
-
" ratings.append(book.p.get(\"class\")[1])\n",
|
| 133 |
-
"\n",
|
| 134 |
-
" time.sleep(0.5) # polite scraping delay"
|
| 135 |
-
]
|
| 136 |
-
},
|
| 137 |
-
{
|
| 138 |
-
"cell_type": "markdown",
|
| 139 |
-
"metadata": {
|
| 140 |
-
"id": "T0TOeRC4Yrnn"
|
| 141 |
-
},
|
| 142 |
-
"source": [
|
| 143 |
-
"### *c. ✋🏻🛑⛔️ Create a dataframe df_books that contains the now complete \"title\", \"price\", and \"rating\" objects*"
|
| 144 |
-
]
|
| 145 |
-
},
|
| 146 |
-
{
|
| 147 |
-
"cell_type": "code",
|
| 148 |
-
"execution_count": 4,
|
| 149 |
-
"metadata": {
|
| 150 |
-
"id": "l5FkkNhUYTHh"
|
| 151 |
-
},
|
| 152 |
-
"outputs": [],
|
| 153 |
-
"source": [
|
| 154 |
-
"# 🗂️ Create DataFrame\n",
|
| 155 |
-
"df_books = pd.DataFrame({\n",
|
| 156 |
-
" \"title\": titles,\n",
|
| 157 |
-
" \"price\": prices,\n",
|
| 158 |
-
" \"rating\": ratings\n",
|
| 159 |
-
"})"
|
| 160 |
-
]
|
| 161 |
-
},
|
| 162 |
-
{
|
| 163 |
-
"cell_type": "markdown",
|
| 164 |
-
"metadata": {
|
| 165 |
-
"id": "duI5dv3CZYvF"
|
| 166 |
-
},
|
| 167 |
-
"source": [
|
| 168 |
-
"### *d. Save web-scraped dataframe either as a CSV or Excel file*"
|
| 169 |
-
]
|
| 170 |
-
},
|
| 171 |
-
{
|
| 172 |
-
"cell_type": "code",
|
| 173 |
-
"execution_count": 5,
|
| 174 |
-
"metadata": {
|
| 175 |
-
"id": "lC1U_YHtZifh"
|
| 176 |
-
},
|
| 177 |
-
"outputs": [],
|
| 178 |
-
"source": [
|
| 179 |
-
"# 💾 Save to CSV\n",
|
| 180 |
-
"df_books.to_csv(\"books_data.csv\", index=False)\n",
|
| 181 |
-
"\n",
|
| 182 |
-
"# 💾 Or save to Excel\n",
|
| 183 |
-
"# df_books.to_excel(\"books_data.xlsx\", index=False)"
|
| 184 |
-
]
|
| 185 |
-
},
|
| 186 |
-
{
|
| 187 |
-
"cell_type": "markdown",
|
| 188 |
-
"metadata": {
|
| 189 |
-
"id": "qMjRKMBQZlJi"
|
| 190 |
-
},
|
| 191 |
-
"source": [
|
| 192 |
-
"### *e. ✋🏻🛑⛔️ View first fiew lines*"
|
| 193 |
-
]
|
| 194 |
-
},
|
| 195 |
-
{
|
| 196 |
-
"cell_type": "code",
|
| 197 |
-
"execution_count": 6,
|
| 198 |
-
"metadata": {
|
| 199 |
-
"colab": {
|
| 200 |
-
"base_uri": "https://localhost:8080/",
|
| 201 |
-
"height": 0
|
| 202 |
-
},
|
| 203 |
-
"id": "O_wIvTxYZqCK",
|
| 204 |
-
"outputId": "349b36b0-c008-4fd5-d4a4-dba38ae18337"
|
| 205 |
-
},
|
| 206 |
-
"outputs": [
|
| 207 |
-
{
|
| 208 |
-
"output_type": "execute_result",
|
| 209 |
-
"data": {
|
| 210 |
-
"text/plain": [
|
| 211 |
-
" title price rating\n",
|
| 212 |
-
"0 A Light in the Attic 51.77 Three\n",
|
| 213 |
-
"1 Tipping the Velvet 53.74 One\n",
|
| 214 |
-
"2 Soumission 50.10 One\n",
|
| 215 |
-
"3 Sharp Objects 47.82 Four\n",
|
| 216 |
-
"4 Sapiens: A Brief History of Humankind 54.23 Five"
|
| 217 |
-
],
|
| 218 |
-
"text/html": [
|
| 219 |
-
"\n",
|
| 220 |
-
" <div id=\"df-04c87660-4415-45e9-ad3b-3fa19d9402c2\" class=\"colab-df-container\">\n",
|
| 221 |
-
" <div>\n",
|
| 222 |
-
"<style scoped>\n",
|
| 223 |
-
" .dataframe tbody tr th:only-of-type {\n",
|
| 224 |
-
" vertical-align: middle;\n",
|
| 225 |
-
" }\n",
|
| 226 |
-
"\n",
|
| 227 |
-
" .dataframe tbody tr th {\n",
|
| 228 |
-
" vertical-align: top;\n",
|
| 229 |
-
" }\n",
|
| 230 |
-
"\n",
|
| 231 |
-
" .dataframe thead th {\n",
|
| 232 |
-
" text-align: right;\n",
|
| 233 |
-
" }\n",
|
| 234 |
-
"</style>\n",
|
| 235 |
-
"<table border=\"1\" class=\"dataframe\">\n",
|
| 236 |
-
" <thead>\n",
|
| 237 |
-
" <tr style=\"text-align: right;\">\n",
|
| 238 |
-
" <th></th>\n",
|
| 239 |
-
" <th>title</th>\n",
|
| 240 |
-
" <th>price</th>\n",
|
| 241 |
-
" <th>rating</th>\n",
|
| 242 |
-
" </tr>\n",
|
| 243 |
-
" </thead>\n",
|
| 244 |
-
" <tbody>\n",
|
| 245 |
-
" <tr>\n",
|
| 246 |
-
" <th>0</th>\n",
|
| 247 |
-
" <td>A Light in the Attic</td>\n",
|
| 248 |
-
" <td>51.77</td>\n",
|
| 249 |
-
" <td>Three</td>\n",
|
| 250 |
-
" </tr>\n",
|
| 251 |
-
" <tr>\n",
|
| 252 |
-
" <th>1</th>\n",
|
| 253 |
-
" <td>Tipping the Velvet</td>\n",
|
| 254 |
-
" <td>53.74</td>\n",
|
| 255 |
-
" <td>One</td>\n",
|
| 256 |
-
" </tr>\n",
|
| 257 |
-
" <tr>\n",
|
| 258 |
-
" <th>2</th>\n",
|
| 259 |
-
" <td>Soumission</td>\n",
|
| 260 |
-
" <td>50.10</td>\n",
|
| 261 |
-
" <td>One</td>\n",
|
| 262 |
-
" </tr>\n",
|
| 263 |
-
" <tr>\n",
|
| 264 |
-
" <th>3</th>\n",
|
| 265 |
-
" <td>Sharp Objects</td>\n",
|
| 266 |
-
" <td>47.82</td>\n",
|
| 267 |
-
" <td>Four</td>\n",
|
| 268 |
-
" </tr>\n",
|
| 269 |
-
" <tr>\n",
|
| 270 |
-
" <th>4</th>\n",
|
| 271 |
-
" <td>Sapiens: A Brief History of Humankind</td>\n",
|
| 272 |
-
" <td>54.23</td>\n",
|
| 273 |
-
" <td>Five</td>\n",
|
| 274 |
-
" </tr>\n",
|
| 275 |
-
" </tbody>\n",
|
| 276 |
-
"</table>\n",
|
| 277 |
-
"</div>\n",
|
| 278 |
-
" <div class=\"colab-df-buttons\">\n",
|
| 279 |
-
"\n",
|
| 280 |
-
" <div class=\"colab-df-container\">\n",
|
| 281 |
-
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-04c87660-4415-45e9-ad3b-3fa19d9402c2')\"\n",
|
| 282 |
-
" title=\"Convert this dataframe to an interactive table.\"\n",
|
| 283 |
-
" style=\"display:none;\">\n",
|
| 284 |
-
"\n",
|
| 285 |
-
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
|
| 286 |
-
" <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
|
| 287 |
-
" </svg>\n",
|
| 288 |
-
" </button>\n",
|
| 289 |
-
"\n",
|
| 290 |
-
" <style>\n",
|
| 291 |
-
" .colab-df-container {\n",
|
| 292 |
-
" display:flex;\n",
|
| 293 |
-
" gap: 12px;\n",
|
| 294 |
-
" }\n",
|
| 295 |
-
"\n",
|
| 296 |
-
" .colab-df-convert {\n",
|
| 297 |
-
" background-color: #E8F0FE;\n",
|
| 298 |
-
" border: none;\n",
|
| 299 |
-
" border-radius: 50%;\n",
|
| 300 |
-
" cursor: pointer;\n",
|
| 301 |
-
" display: none;\n",
|
| 302 |
-
" fill: #1967D2;\n",
|
| 303 |
-
" height: 32px;\n",
|
| 304 |
-
" padding: 0 0 0 0;\n",
|
| 305 |
-
" width: 32px;\n",
|
| 306 |
-
" }\n",
|
| 307 |
-
"\n",
|
| 308 |
-
" .colab-df-convert:hover {\n",
|
| 309 |
-
" background-color: #E2EBFA;\n",
|
| 310 |
-
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
| 311 |
-
" fill: #174EA6;\n",
|
| 312 |
-
" }\n",
|
| 313 |
-
"\n",
|
| 314 |
-
" .colab-df-buttons div {\n",
|
| 315 |
-
" margin-bottom: 4px;\n",
|
| 316 |
-
" }\n",
|
| 317 |
-
"\n",
|
| 318 |
-
" [theme=dark] .colab-df-convert {\n",
|
| 319 |
-
" background-color: #3B4455;\n",
|
| 320 |
-
" fill: #D2E3FC;\n",
|
| 321 |
-
" }\n",
|
| 322 |
-
"\n",
|
| 323 |
-
" [theme=dark] .colab-df-convert:hover {\n",
|
| 324 |
-
" background-color: #434B5C;\n",
|
| 325 |
-
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
|
| 326 |
-
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
|
| 327 |
-
" fill: #FFFFFF;\n",
|
| 328 |
-
" }\n",
|
| 329 |
-
" </style>\n",
|
| 330 |
-
"\n",
|
| 331 |
-
" <script>\n",
|
| 332 |
-
" const buttonEl =\n",
|
| 333 |
-
" document.querySelector('#df-04c87660-4415-45e9-ad3b-3fa19d9402c2 button.colab-df-convert');\n",
|
| 334 |
-
" buttonEl.style.display =\n",
|
| 335 |
-
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
| 336 |
-
"\n",
|
| 337 |
-
" async function convertToInteractive(key) {\n",
|
| 338 |
-
" const element = document.querySelector('#df-04c87660-4415-45e9-ad3b-3fa19d9402c2');\n",
|
| 339 |
-
" const dataTable =\n",
|
| 340 |
-
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
|
| 341 |
-
" [key], {});\n",
|
| 342 |
-
" if (!dataTable) return;\n",
|
| 343 |
-
"\n",
|
| 344 |
-
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
|
| 345 |
-
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
|
| 346 |
-
" + ' to learn more about interactive tables.';\n",
|
| 347 |
-
" element.innerHTML = '';\n",
|
| 348 |
-
" dataTable['output_type'] = 'display_data';\n",
|
| 349 |
-
" await google.colab.output.renderOutput(dataTable, element);\n",
|
| 350 |
-
" const docLink = document.createElement('div');\n",
|
| 351 |
-
" docLink.innerHTML = docLinkHtml;\n",
|
| 352 |
-
" element.appendChild(docLink);\n",
|
| 353 |
-
" }\n",
|
| 354 |
-
" </script>\n",
|
| 355 |
-
" </div>\n",
|
| 356 |
-
"\n",
|
| 357 |
-
"\n",
|
| 358 |
-
" </div>\n",
|
| 359 |
-
" </div>\n"
|
| 360 |
-
],
|
| 361 |
-
"application/vnd.google.colaboratory.intrinsic+json": {
|
| 362 |
-
"type": "dataframe",
|
| 363 |
-
"variable_name": "df_books",
|
| 364 |
-
"summary": "{\n \"name\": \"df_books\",\n \"rows\": 1000,\n \"fields\": [\n {\n \"column\": \"title\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 999,\n \"samples\": [\n \"The Grownup\",\n \"Persepolis: The Story of a Childhood (Persepolis #1-2)\",\n \"Ayumi's Violin\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"price\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 14.446689669952772,\n \"min\": 10.0,\n \"max\": 59.99,\n \"num_unique_values\": 903,\n \"samples\": [\n 19.73,\n 55.65,\n 46.31\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"rating\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"One\",\n \"Two\",\n \"Four\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
|
| 365 |
-
}
|
| 366 |
-
},
|
| 367 |
-
"metadata": {},
|
| 368 |
-
"execution_count": 6
|
| 369 |
-
}
|
| 370 |
-
],
|
| 371 |
-
"source": [
|
| 372 |
-
"df_books.head()"
|
| 373 |
-
]
|
| 374 |
-
},
|
| 375 |
-
{
|
| 376 |
-
"cell_type": "markdown",
|
| 377 |
-
"metadata": {
|
| 378 |
-
"id": "p-1Pr2szaqLk"
|
| 379 |
-
},
|
| 380 |
-
"source": [
|
| 381 |
-
"## **3.** 🧩 Create a meaningful connection between real & synthetic datasets"
|
| 382 |
-
]
|
| 383 |
-
},
|
| 384 |
-
{
|
| 385 |
-
"cell_type": "markdown",
|
| 386 |
-
"metadata": {
|
| 387 |
-
"id": "SIaJUGIpaH4V"
|
| 388 |
-
},
|
| 389 |
-
"source": [
|
| 390 |
-
"### *a. Initial setup*"
|
| 391 |
-
]
|
| 392 |
-
},
|
| 393 |
-
{
|
| 394 |
-
"cell_type": "code",
|
| 395 |
-
"execution_count": 7,
|
| 396 |
-
"metadata": {
|
| 397 |
-
"id": "-gPXGcRPuV_9"
|
| 398 |
-
},
|
| 399 |
-
"outputs": [],
|
| 400 |
-
"source": [
|
| 401 |
-
"import numpy as np\n",
|
| 402 |
-
"import random\n",
|
| 403 |
-
"from datetime import datetime\n",
|
| 404 |
-
"import warnings\n",
|
| 405 |
-
"\n",
|
| 406 |
-
"warnings.filterwarnings(\"ignore\")\n",
|
| 407 |
-
"random.seed(2025)\n",
|
| 408 |
-
"np.random.seed(2025)"
|
| 409 |
-
]
|
| 410 |
-
},
|
| 411 |
-
{
|
| 412 |
-
"cell_type": "markdown",
|
| 413 |
-
"metadata": {
|
| 414 |
-
"id": "pY4yCoIuaQqp"
|
| 415 |
-
},
|
| 416 |
-
"source": [
|
| 417 |
-
"### *b. Generate popularity scores based on rating (with some randomness) with a generate_popularity_score function*"
|
| 418 |
-
]
|
| 419 |
-
},
|
| 420 |
-
{
|
| 421 |
-
"cell_type": "code",
|
| 422 |
-
"execution_count": 8,
|
| 423 |
-
"metadata": {
|
| 424 |
-
"id": "mnd5hdAbaNjz"
|
| 425 |
-
},
|
| 426 |
-
"outputs": [],
|
| 427 |
-
"source": [
|
| 428 |
-
"def generate_popularity_score(rating):\n",
|
| 429 |
-
" base = {\"One\": 2, \"Two\": 3, \"Three\": 3, \"Four\": 4, \"Five\": 4}.get(rating, 3)\n",
|
| 430 |
-
" trend_factor = random.choices([-1, 0, 1], weights=[1, 3, 2])[0]\n",
|
| 431 |
-
" return int(np.clip(base + trend_factor, 1, 5))"
|
| 432 |
-
]
|
| 433 |
-
},
|
| 434 |
-
{
|
| 435 |
-
"cell_type": "markdown",
|
| 436 |
-
"metadata": {
|
| 437 |
-
"id": "n4-TaNTFgPak"
|
| 438 |
-
},
|
| 439 |
-
"source": [
|
| 440 |
-
"### *c. ✋🏻🛑⛔️ Run the function to create a \"popularity_score\" column from \"rating\"*"
|
| 441 |
-
]
|
| 442 |
-
},
|
| 443 |
-
{
|
| 444 |
-
"cell_type": "code",
|
| 445 |
-
"execution_count": 9,
|
| 446 |
-
"metadata": {
|
| 447 |
-
"id": "V-G3OCUCgR07"
|
| 448 |
-
},
|
| 449 |
-
"outputs": [],
|
| 450 |
-
"source": [
|
| 451 |
-
"df_books[\"popularity_score\"] = df_books[\"rating\"].apply(generate_popularity_score)"
|
| 452 |
-
]
|
| 453 |
-
},
|
| 454 |
-
{
|
| 455 |
-
"cell_type": "markdown",
|
| 456 |
-
"metadata": {
|
| 457 |
-
"id": "HnngRNTgacYt"
|
| 458 |
-
},
|
| 459 |
-
"source": [
|
| 460 |
-
"### *d. Decide on the sentiment_label based on the popularity score with a get_sentiment function*"
|
| 461 |
-
]
|
| 462 |
-
},
|
| 463 |
-
{
|
| 464 |
-
"cell_type": "code",
|
| 465 |
-
"execution_count": 10,
|
| 466 |
-
"metadata": {
|
| 467 |
-
"id": "kUtWmr8maZLZ"
|
| 468 |
-
},
|
| 469 |
-
"outputs": [],
|
| 470 |
-
"source": [
|
| 471 |
-
"def get_sentiment(popularity_score):\n",
|
| 472 |
-
" if popularity_score <= 2:\n",
|
| 473 |
-
" return \"negative\"\n",
|
| 474 |
-
" elif popularity_score == 3:\n",
|
| 475 |
-
" return \"neutral\"\n",
|
| 476 |
-
" else:\n",
|
| 477 |
-
" return \"positive\""
|
| 478 |
-
]
|
| 479 |
-
},
|
| 480 |
-
{
|
| 481 |
-
"cell_type": "markdown",
|
| 482 |
-
"metadata": {
|
| 483 |
-
"id": "HF9F9HIzgT7Z"
|
| 484 |
-
},
|
| 485 |
-
"source": [
|
| 486 |
-
"### *e. ✋🏻🛑⛔️ Run the function to create a \"sentiment_label\" column from \"popularity_score\"*"
|
| 487 |
-
]
|
| 488 |
-
},
|
| 489 |
-
{
|
| 490 |
-
"cell_type": "code",
|
| 491 |
-
"execution_count": 11,
|
| 492 |
-
"metadata": {
|
| 493 |
-
"id": "tafQj8_7gYCG"
|
| 494 |
-
},
|
| 495 |
-
"outputs": [],
|
| 496 |
-
"source": [
|
| 497 |
-
"df_books[\"sentiment_label\"] = df_books[\"popularity_score\"].apply(get_sentiment)"
|
| 498 |
-
]
|
| 499 |
-
},
|
| 500 |
-
{
|
| 501 |
-
"cell_type": "markdown",
|
| 502 |
-
"metadata": {
|
| 503 |
-
"id": "T8AdKkmASq9a"
|
| 504 |
-
},
|
| 505 |
-
"source": [
|
| 506 |
-
"## **4.** 📈 Generate synthetic book sales data of 18 months"
|
| 507 |
-
]
|
| 508 |
-
},
|
| 509 |
-
{
|
| 510 |
-
"cell_type": "markdown",
|
| 511 |
-
"metadata": {
|
| 512 |
-
"id": "OhXbdGD5fH0c"
|
| 513 |
-
},
|
| 514 |
-
"source": [
|
| 515 |
-
"### *a. Create a generate_sales_profit function that would generate sales patterns based on sentiment_label (with some randomness)*"
|
| 516 |
-
]
|
| 517 |
-
},
|
| 518 |
-
{
|
| 519 |
-
"cell_type": "code",
|
| 520 |
-
"execution_count": 12,
|
| 521 |
-
"metadata": {
|
| 522 |
-
"id": "qkVhYPXGbgEn"
|
| 523 |
-
},
|
| 524 |
-
"outputs": [],
|
| 525 |
-
"source": [
|
| 526 |
-
"def generate_sales_profile(sentiment):\n",
|
| 527 |
-
" months = pd.date_range(end=datetime.today(), periods=18, freq=\"M\")\n",
|
| 528 |
-
"\n",
|
| 529 |
-
" if sentiment == \"positive\":\n",
|
| 530 |
-
" base = random.randint(200, 300)\n",
|
| 531 |
-
" trend = np.linspace(base, base + random.randint(20, 60), len(months))\n",
|
| 532 |
-
" elif sentiment == \"negative\":\n",
|
| 533 |
-
" base = random.randint(20, 80)\n",
|
| 534 |
-
" trend = np.linspace(base, base - random.randint(10, 30), len(months))\n",
|
| 535 |
-
" else: # neutral\n",
|
| 536 |
-
" base = random.randint(80, 160)\n",
|
| 537 |
-
" trend = np.full(len(months), base + random.randint(-10, 10))\n",
|
| 538 |
-
"\n",
|
| 539 |
-
" seasonality = 10 * np.sin(np.linspace(0, 3 * np.pi, len(months)))\n",
|
| 540 |
-
" noise = np.random.normal(0, 5, len(months))\n",
|
| 541 |
-
" monthly_sales = np.clip(trend + seasonality + noise, a_min=0, a_max=None).astype(int)\n",
|
| 542 |
-
"\n",
|
| 543 |
-
" return list(zip(months.strftime(\"%Y-%m\"), monthly_sales))"
|
| 544 |
-
]
|
| 545 |
-
},
|
| 546 |
-
{
|
| 547 |
-
"cell_type": "markdown",
|
| 548 |
-
"metadata": {
|
| 549 |
-
"id": "L2ak1HlcgoTe"
|
| 550 |
-
},
|
| 551 |
-
"source": [
|
| 552 |
-
"### *b. Run the function as part of building sales_data*"
|
| 553 |
-
]
|
| 554 |
-
},
|
| 555 |
-
{
|
| 556 |
-
"cell_type": "code",
|
| 557 |
-
"execution_count": 13,
|
| 558 |
-
"metadata": {
|
| 559 |
-
"id": "SlJ24AUafoDB"
|
| 560 |
-
},
|
| 561 |
-
"outputs": [],
|
| 562 |
-
"source": [
|
| 563 |
-
"sales_data = []\n",
|
| 564 |
-
"for _, row in df_books.iterrows():\n",
|
| 565 |
-
" records = generate_sales_profile(row[\"sentiment_label\"])\n",
|
| 566 |
-
" for month, units in records:\n",
|
| 567 |
-
" sales_data.append({\n",
|
| 568 |
-
" \"title\": row[\"title\"],\n",
|
| 569 |
-
" \"month\": month,\n",
|
| 570 |
-
" \"units_sold\": units,\n",
|
| 571 |
-
" \"sentiment_label\": row[\"sentiment_label\"]\n",
|
| 572 |
-
" })"
|
| 573 |
-
]
|
| 574 |
-
},
|
| 575 |
-
{
|
| 576 |
-
"cell_type": "markdown",
|
| 577 |
-
"metadata": {
|
| 578 |
-
"id": "4IXZKcCSgxnq"
|
| 579 |
-
},
|
| 580 |
-
"source": [
|
| 581 |
-
"### *c. ✋🏻🛑⛔️ Create a df_sales DataFrame from sales_data*"
|
| 582 |
-
]
|
| 583 |
-
},
|
| 584 |
-
{
|
| 585 |
-
"cell_type": "code",
|
| 586 |
-
"execution_count": 14,
|
| 587 |
-
"metadata": {
|
| 588 |
-
"id": "wcN6gtiZg-ws"
|
| 589 |
-
},
|
| 590 |
-
"outputs": [],
|
| 591 |
-
"source": [
|
| 592 |
-
"df_sales = pd.DataFrame(sales_data)"
|
| 593 |
-
]
|
| 594 |
-
},
|
| 595 |
-
{
|
| 596 |
-
"cell_type": "markdown",
|
| 597 |
-
"metadata": {
|
| 598 |
-
"id": "EhIjz9WohAmZ"
|
| 599 |
-
},
|
| 600 |
-
"source": [
|
| 601 |
-
"### *d. Save df_sales as synthetic_sales_data.csv & view first few lines*"
|
| 602 |
-
]
|
| 603 |
-
},
|
| 604 |
-
{
|
| 605 |
-
"cell_type": "code",
|
| 606 |
-
"execution_count": 15,
|
| 607 |
-
"metadata": {
|
| 608 |
-
"colab": {
|
| 609 |
-
"base_uri": "https://localhost:8080/"
|
| 610 |
-
},
|
| 611 |
-
"id": "MzbZvLcAhGaH",
|
| 612 |
-
"outputId": "c692bb04-7263-4115-a2ba-c72fe0180722"
|
| 613 |
-
},
|
| 614 |
-
"outputs": [
|
| 615 |
-
{
|
| 616 |
-
"output_type": "stream",
|
| 617 |
-
"name": "stdout",
|
| 618 |
-
"text": [
|
| 619 |
-
" title month units_sold sentiment_label\n",
|
| 620 |
-
"0 A Light in the Attic 2024-08 100 neutral\n",
|
| 621 |
-
"1 A Light in the Attic 2024-09 109 neutral\n",
|
| 622 |
-
"2 A Light in the Attic 2024-10 102 neutral\n",
|
| 623 |
-
"3 A Light in the Attic 2024-11 107 neutral\n",
|
| 624 |
-
"4 A Light in the Attic 2024-12 108 neutral\n"
|
| 625 |
-
]
|
| 626 |
-
}
|
| 627 |
-
],
|
| 628 |
-
"source": [
|
| 629 |
-
"df_sales.to_csv(\"synthetic_sales_data.csv\", index=False)\n",
|
| 630 |
-
"\n",
|
| 631 |
-
"print(df_sales.head())"
|
| 632 |
-
]
|
| 633 |
-
},
|
| 634 |
-
{
|
| 635 |
-
"cell_type": "markdown",
|
| 636 |
-
"metadata": {
|
| 637 |
-
"id": "7g9gqBgQMtJn"
|
| 638 |
-
},
|
| 639 |
-
"source": [
|
| 640 |
-
"## **5.** 🎯 Generate synthetic customer reviews"
|
| 641 |
-
]
|
| 642 |
-
},
|
| 643 |
-
{
|
| 644 |
-
"cell_type": "markdown",
|
| 645 |
-
"metadata": {
|
| 646 |
-
"id": "Gi4y9M9KuDWx"
|
| 647 |
-
},
|
| 648 |
-
"source": [
|
| 649 |
-
"### *a. ✋🏻🛑⛔️ Ask ChatGPT to create a list of 50 distinct generic book review texts for the sentiment labels \"positive\", \"neutral\", and \"negative\" called synthetic_reviews_by_sentiment*"
|
| 650 |
-
]
|
| 651 |
-
},
|
| 652 |
-
{
|
| 653 |
-
"cell_type": "code",
|
| 654 |
-
"execution_count": 16,
|
| 655 |
-
"metadata": {
|
| 656 |
-
"id": "b3cd2a50"
|
| 657 |
-
},
|
| 658 |
-
"outputs": [],
|
| 659 |
-
"source": [
|
| 660 |
-
"synthetic_reviews_by_sentiment = {\n",
|
| 661 |
-
" \"positive\": [\n",
|
| 662 |
-
" \"A compelling and heartwarming read that stayed with me long after I finished.\",\n",
|
| 663 |
-
" \"Brilliantly written! The characters were unforgettable and the plot was engaging.\",\n",
|
| 664 |
-
" \"One of the best books I've read this year — inspiring and emotionally rich.\",\n",
|
| 665 |
-
" \"The author's storytelling was vivid and powerful. Highly recommended!\",\n",
|
| 666 |
-
" \"An absolute masterpiece. I couldn't put it down from start to finish.\",\n",
|
| 667 |
-
" \"Gripping, intelligent, and beautifully crafted — I loved every page.\",\n",
|
| 668 |
-
" \"The emotional depth and layered narrative were just perfect.\",\n",
|
| 669 |
-
" \"A thought-provoking journey with stunning character development.\",\n",
|
| 670 |
-
" \"Everything about this book just clicked. A top-tier read!\",\n",
|
| 671 |
-
" \"A flawless blend of emotion, intrigue, and style. Truly impressive.\",\n",
|
| 672 |
-
" \"Absolutely stunning work of fiction. Five stars from me.\",\n",
|
| 673 |
-
" \"Remarkably executed with breathtaking prose.\",\n",
|
| 674 |
-
" \"The pacing was perfect and I was hooked from page one.\",\n",
|
| 675 |
-
" \"Heartfelt and hopeful — a story well worth telling.\",\n",
|
| 676 |
-
" \"A vivid journey through complex emotions and stunning imagery.\",\n",
|
| 677 |
-
" \"This book had soul. Every word felt like it mattered.\",\n",
|
| 678 |
-
" \"It delivered more than I ever expected. Powerful and wise.\",\n",
|
| 679 |
-
" \"The characters leapt off the page and into my heart.\",\n",
|
| 680 |
-
" \"I could see every scene clearly in my mind — beautifully descriptive.\",\n",
|
| 681 |
-
" \"Refreshing, original, and impossible to forget.\",\n",
|
| 682 |
-
" \"A radiant celebration of resilience and love.\",\n",
|
| 683 |
-
" \"Powerful themes handled with grace and insight.\",\n",
|
| 684 |
-
" \"An unforgettable literary experience.\",\n",
|
| 685 |
-
" \"The best book club pick we’ve had all year.\",\n",
|
| 686 |
-
" \"A layered, lyrical narrative that resonates deeply.\",\n",
|
| 687 |
-
" \"Surprising, profound, and deeply humane.\",\n",
|
| 688 |
-
" \"One of those rare books I wish I could read again for the first time.\",\n",
|
| 689 |
-
" \"Both epic and intimate — a perfect balance.\",\n",
|
| 690 |
-
" \"It reads like a love letter to the human spirit.\",\n",
|
| 691 |
-
" \"Satisfying and uplifting with a memorable ending.\",\n",
|
| 692 |
-
" \"This novel deserves every bit of praise it gets.\",\n",
|
| 693 |
-
" \"Introspective, emotional, and elegantly composed.\",\n",
|
| 694 |
-
" \"A tour de force in contemporary fiction.\",\n",
|
| 695 |
-
" \"Left me smiling, teary-eyed, and completely fulfilled.\",\n",
|
| 696 |
-
" \"A novel with the rare ability to entertain and enlighten.\",\n",
|
| 697 |
-
" \"Incredibly moving. I highlighted so many lines.\",\n",
|
| 698 |
-
" \"A smart, sensitive take on relationships and identity.\",\n",
|
| 699 |
-
" \"You feel wiser by the end of it.\",\n",
|
| 700 |
-
" \"A gorgeously crafted tale about hope and second chances.\",\n",
|
| 701 |
-
" \"Poignant and real — a beautiful escape.\",\n",
|
| 702 |
-
" \"Brims with insight and authenticity.\",\n",
|
| 703 |
-
" \"Compelling characters and a satisfying plot.\",\n",
|
| 704 |
-
" \"An empowering and important read.\",\n",
|
| 705 |
-
" \"Elegantly crafted and deeply humane.\",\n",
|
| 706 |
-
" \"Taut storytelling that never lets go.\",\n",
|
| 707 |
-
" \"Each chapter offered a new treasure.\",\n",
|
| 708 |
-
" \"Lyrical writing that stays with you.\",\n",
|
| 709 |
-
" \"A wonderful blend of passion and thoughtfulness.\",\n",
|
| 710 |
-
" \"Uplifting, honest, and completely engrossing.\",\n",
|
| 711 |
-
" \"This one made me believe in storytelling again.\"\n",
|
| 712 |
-
" ],\n",
|
| 713 |
-
" \"neutral\": [\n",
|
| 714 |
-
" \"An average book — not great, but not bad either.\",\n",
|
| 715 |
-
" \"Some parts really stood out, others felt a bit flat.\",\n",
|
| 716 |
-
" \"It was okay overall. A decent way to pass the time.\",\n",
|
| 717 |
-
" \"The writing was fine, though I didn’t fully connect with the story.\",\n",
|
| 718 |
-
" \"Had a few memorable moments but lacked depth in some areas.\",\n",
|
| 719 |
-
" \"A mixed experience — neither fully engaging nor forgettable.\",\n",
|
| 720 |
-
" \"There was potential, but it didn't quite come together for me.\",\n",
|
| 721 |
-
" \"A reasonable effort that just didn’t leave a lasting impression.\",\n",
|
| 722 |
-
" \"Serviceable but not something I'd go out of my way to recommend.\",\n",
|
| 723 |
-
" \"Not much to dislike, but not much to rave about either.\",\n",
|
| 724 |
-
" \"It had its strengths, though they didn’t shine consistently.\",\n",
|
| 725 |
-
" \"I’m on the fence — parts were enjoyable, others not so much.\",\n",
|
| 726 |
-
" \"The book had a unique concept but lacked execution.\",\n",
|
| 727 |
-
" \"A middle-of-the-road read.\",\n",
|
| 728 |
-
" \"Engaging at times, but it lost momentum.\",\n",
|
| 729 |
-
" \"Would have benefited from stronger character development.\",\n",
|
| 730 |
-
" \"It passed the time, but I wouldn't reread it.\",\n",
|
| 731 |
-
" \"The plot had some holes that affected immersion.\",\n",
|
| 732 |
-
" \"Mediocre pacing made it hard to stay invested.\",\n",
|
| 733 |
-
" \"Satisfying in parts, underwhelming in others.\",\n",
|
| 734 |
-
" \"Neutral on this one — didn’t love it or hate it.\",\n",
|
| 735 |
-
" \"Fairly forgettable but with glimpses of promise.\",\n",
|
| 736 |
-
" \"The themes were solid, but not well explored.\",\n",
|
| 737 |
-
" \"Competent, just not compelling.\",\n",
|
| 738 |
-
" \"Had moments of clarity and moments of confusion.\",\n",
|
| 739 |
-
" \"I didn’t regret reading it, but I wouldn’t recommend it.\",\n",
|
| 740 |
-
" \"Readable, yet uninspired.\",\n",
|
| 741 |
-
" \"There was a spark, but it didn’t ignite.\",\n",
|
| 742 |
-
" \"A slow burn that didn’t quite catch fire.\",\n",
|
| 743 |
-
" \"I expected more nuance given the premise.\",\n",
|
| 744 |
-
" \"A safe, inoffensive choice.\",\n",
|
| 745 |
-
" \"Some parts lagged, others piqued my interest.\",\n",
|
| 746 |
-
" \"Decent, but needed polish.\",\n",
|
| 747 |
-
" \"Moderately engaging but didn’t stick the landing.\",\n",
|
| 748 |
-
" \"It simply lacked that emotional punch.\",\n",
|
| 749 |
-
" \"Just fine — no better, no worse.\",\n",
|
| 750 |
-
" \"Some thoughtful passages amid otherwise dry writing.\",\n",
|
| 751 |
-
" \"I appreciated the ideas more than the execution.\",\n",
|
| 752 |
-
" \"Struggled with cohesion.\",\n",
|
| 753 |
-
" \"Solidly average.\",\n",
|
| 754 |
-
" \"Good on paper, flat in practice.\",\n",
|
| 755 |
-
" \"A few bright spots, but mostly dim.\",\n",
|
| 756 |
-
" \"The kind of book that fades from memory.\",\n",
|
| 757 |
-
" \"It scratched the surface but didn’t dig deep.\",\n",
|
| 758 |
-
" \"Standard fare with some promise.\",\n",
|
| 759 |
-
" \"Okay, but not memorable.\",\n",
|
| 760 |
-
" \"Had potential that went unrealized.\",\n",
|
| 761 |
-
" \"Could have been tighter, sharper, deeper.\",\n",
|
| 762 |
-
" \"A blend of mediocrity and mild interest.\",\n",
|
| 763 |
-
" \"I kept reading, but barely.\"\n",
|
| 764 |
-
" ],\n",
|
| 765 |
-
" \"negative\": [\n",
|
| 766 |
-
" \"I struggled to get through this one — it just didn’t grab me.\",\n",
|
| 767 |
-
" \"The plot was confusing and the characters felt underdeveloped.\",\n",
|
| 768 |
-
" \"Disappointing. I had high hopes, but they weren't met.\",\n",
|
| 769 |
-
" \"Uninspired writing and a story that never quite took off.\",\n",
|
| 770 |
-
" \"Unfortunately, it was dull and predictable throughout.\",\n",
|
| 771 |
-
" \"The pacing dragged and I couldn’t find anything compelling.\",\n",
|
| 772 |
-
" \"This felt like a chore to read — lacked heart and originality.\",\n",
|
| 773 |
-
" \"Nothing really worked for me in this book.\",\n",
|
| 774 |
-
" \"A frustrating read that left me unsatisfied.\",\n",
|
| 775 |
-
" \"I kept hoping it would improve, but it never did.\",\n",
|
| 776 |
-
" \"The characters didn’t feel real, and the dialogue was forced.\",\n",
|
| 777 |
-
" \"I couldn't connect with the story at all.\",\n",
|
| 778 |
-
" \"A slow, meandering narrative with little payoff.\",\n",
|
| 779 |
-
" \"Tried too hard to be deep, but just felt empty.\",\n",
|
| 780 |
-
" \"The tone was uneven and confusing.\",\n",
|
| 781 |
-
" \"Way too repetitive and lacking progression.\",\n",
|
| 782 |
-
" \"The ending was abrupt and unsatisfying.\",\n",
|
| 783 |
-
" \"No emotional resonance — I felt nothing throughout.\",\n",
|
| 784 |
-
" \"I expected much more, but this fell flat.\",\n",
|
| 785 |
-
" \"Poorly edited and full of clichés.\",\n",
|
| 786 |
-
" \"The premise was interesting, but poorly executed.\",\n",
|
| 787 |
-
" \"Just didn’t live up to the praise.\",\n",
|
| 788 |
-
" \"A disjointed mess from start to finish.\",\n",
|
| 789 |
-
" \"Overly long and painfully dull.\",\n",
|
| 790 |
-
" \"Dialogue that felt robotic and unrealistic.\",\n",
|
| 791 |
-
" \"A hollow shell of what it could’ve been.\",\n",
|
| 792 |
-
" \"It lacked a coherent structure.\",\n",
|
| 793 |
-
" \"More confusing than complex.\",\n",
|
| 794 |
-
" \"Reading it felt like a task, not a treat.\",\n",
|
| 795 |
-
" \"There was no tension, no emotion — just words.\",\n",
|
| 796 |
-
" \"Characters with no motivation or development.\",\n",
|
| 797 |
-
" \"The plot twists were nonsensical.\",\n",
|
| 798 |
-
" \"Regret buying this book.\",\n",
|
| 799 |
-
" \"Nothing drew me in, nothing made me stay.\",\n",
|
| 800 |
-
" \"Too many subplots and none were satisfying.\",\n",
|
| 801 |
-
" \"Tedious and unimaginative.\",\n",
|
| 802 |
-
" \"Like reading a rough draft.\",\n",
|
| 803 |
-
" \"Disjointed, distant, and disappointing.\",\n",
|
| 804 |
-
" \"A lot of buildup with no payoff.\",\n",
|
| 805 |
-
" \"I don’t understand the hype.\",\n",
|
| 806 |
-
" \"This book simply didn’t work.\",\n",
|
| 807 |
-
" \"Forgettable in every sense.\",\n",
|
| 808 |
-
" \"More effort should’ve gone into editing.\",\n",
|
| 809 |
-
" \"The story lost its way early on.\",\n",
|
| 810 |
-
" \"It dragged endlessly.\",\n",
|
| 811 |
-
" \"I kept checking how many pages were left.\",\n",
|
| 812 |
-
" \"This lacked vision and clarity.\",\n",
|
| 813 |
-
" \"I expected substance — got fluff.\",\n",
|
| 814 |
-
" \"It failed to make me care.\"\n",
|
| 815 |
-
" ]\n",
|
| 816 |
-
"}"
|
| 817 |
-
]
|
| 818 |
-
},
|
| 819 |
-
{
|
| 820 |
-
"cell_type": "markdown",
|
| 821 |
-
"metadata": {
|
| 822 |
-
"id": "fQhfVaDmuULT"
|
| 823 |
-
},
|
| 824 |
-
"source": [
|
| 825 |
-
"### *b. Generate 10 reviews per book using random sampling from the corresponding 50*"
|
| 826 |
-
]
|
| 827 |
-
},
|
| 828 |
-
{
|
| 829 |
-
"cell_type": "code",
|
| 830 |
-
"execution_count": 17,
|
| 831 |
-
"metadata": {
|
| 832 |
-
"id": "l2SRc3PjuTGM"
|
| 833 |
-
},
|
| 834 |
-
"outputs": [],
|
| 835 |
-
"source": [
|
| 836 |
-
"review_rows = []\n",
|
| 837 |
-
"for _, row in df_books.iterrows():\n",
|
| 838 |
-
" title = row['title']\n",
|
| 839 |
-
" sentiment_label = row['sentiment_label']\n",
|
| 840 |
-
" review_pool = synthetic_reviews_by_sentiment[sentiment_label]\n",
|
| 841 |
-
" sampled_reviews = random.sample(review_pool, 10)\n",
|
| 842 |
-
" for review_text in sampled_reviews:\n",
|
| 843 |
-
" review_rows.append({\n",
|
| 844 |
-
" \"title\": title,\n",
|
| 845 |
-
" \"sentiment_label\": sentiment_label,\n",
|
| 846 |
-
" \"review_text\": review_text,\n",
|
| 847 |
-
" \"rating\": row['rating'],\n",
|
| 848 |
-
" \"popularity_score\": row['popularity_score']\n",
|
| 849 |
-
" })"
|
| 850 |
-
]
|
| 851 |
-
},
|
| 852 |
-
{
|
| 853 |
-
"cell_type": "markdown",
|
| 854 |
-
"metadata": {
|
| 855 |
-
"id": "bmJMXF-Bukdm"
|
| 856 |
-
},
|
| 857 |
-
"source": [
|
| 858 |
-
"### *c. Create the final dataframe df_reviews & save it as synthetic_book_reviews.csv*"
|
| 859 |
-
]
|
| 860 |
-
},
|
| 861 |
-
{
|
| 862 |
-
"cell_type": "code",
|
| 863 |
-
"execution_count": 18,
|
| 864 |
-
"metadata": {
|
| 865 |
-
"id": "ZUKUqZsuumsp"
|
| 866 |
-
},
|
| 867 |
-
"outputs": [],
|
| 868 |
-
"source": [
|
| 869 |
-
"df_reviews = pd.DataFrame(review_rows)\n",
|
| 870 |
-
"df_reviews.to_csv(\"synthetic_book_reviews.csv\", index=False)"
|
| 871 |
-
]
|
| 872 |
-
},
|
| 873 |
-
{
|
| 874 |
-
"cell_type": "code",
|
| 875 |
-
"execution_count": 19,
|
| 876 |
-
"metadata": {
|
| 877 |
-
"colab": {
|
| 878 |
-
"base_uri": "https://localhost:8080/"
|
| 879 |
-
},
|
| 880 |
-
"id": "3946e521",
|
| 881 |
-
"outputId": "514d7bef-0488-4933-b03c-953b9e8a7f66"
|
| 882 |
-
},
|
| 883 |
-
"outputs": [
|
| 884 |
-
{
|
| 885 |
-
"output_type": "stream",
|
| 886 |
-
"name": "stdout",
|
| 887 |
-
"text": [
|
| 888 |
-
"✅ Wrote synthetic_title_level_features.csv\n",
|
| 889 |
-
"✅ Wrote synthetic_monthly_revenue_series.csv\n"
|
| 890 |
-
]
|
| 891 |
-
}
|
| 892 |
-
],
|
| 893 |
-
"source": [
|
| 894 |
-
"\n",
|
| 895 |
-
"# ============================================================\n",
|
| 896 |
-
"# ✅ Create \"R-ready\" derived inputs (root-level files)\n",
|
| 897 |
-
"# ============================================================\n",
|
| 898 |
-
"# These two files make the R notebook robust and fast:\n",
|
| 899 |
-
"# 1) synthetic_title_level_features.csv -> regression-ready, one row per title\n",
|
| 900 |
-
"# 2) synthetic_monthly_revenue_series.csv -> forecasting-ready, one row per month\n",
|
| 901 |
-
"\n",
|
| 902 |
-
"import numpy as np\n",
|
| 903 |
-
"\n",
|
| 904 |
-
"def _safe_num(s):\n",
|
| 905 |
-
" return pd.to_numeric(\n",
|
| 906 |
-
" pd.Series(s).astype(str).str.replace(r\"[^0-9.]\", \"\", regex=True),\n",
|
| 907 |
-
" errors=\"coerce\"\n",
|
| 908 |
-
" )\n",
|
| 909 |
-
"\n",
|
| 910 |
-
"# --- Clean book metadata (price/rating) ---\n",
|
| 911 |
-
"df_books_r = df_books.copy()\n",
|
| 912 |
-
"if \"price\" in df_books_r.columns:\n",
|
| 913 |
-
" df_books_r[\"price\"] = _safe_num(df_books_r[\"price\"])\n",
|
| 914 |
-
"if \"rating\" in df_books_r.columns:\n",
|
| 915 |
-
" df_books_r[\"rating\"] = _safe_num(df_books_r[\"rating\"])\n",
|
| 916 |
-
"\n",
|
| 917 |
-
"df_books_r[\"title\"] = df_books_r[\"title\"].astype(str).str.strip()\n",
|
| 918 |
-
"\n",
|
| 919 |
-
"# --- Clean sales ---\n",
|
| 920 |
-
"df_sales_r = df_sales.copy()\n",
|
| 921 |
-
"df_sales_r[\"title\"] = df_sales_r[\"title\"].astype(str).str.strip()\n",
|
| 922 |
-
"df_sales_r[\"month\"] = pd.to_datetime(df_sales_r[\"month\"], errors=\"coerce\")\n",
|
| 923 |
-
"df_sales_r[\"units_sold\"] = _safe_num(df_sales_r[\"units_sold\"])\n",
|
| 924 |
-
"\n",
|
| 925 |
-
"# --- Clean reviews ---\n",
|
| 926 |
-
"df_reviews_r = df_reviews.copy()\n",
|
| 927 |
-
"df_reviews_r[\"title\"] = df_reviews_r[\"title\"].astype(str).str.strip()\n",
|
| 928 |
-
"df_reviews_r[\"sentiment_label\"] = df_reviews_r[\"sentiment_label\"].astype(str).str.lower().str.strip()\n",
|
| 929 |
-
"if \"rating\" in df_reviews_r.columns:\n",
|
| 930 |
-
" df_reviews_r[\"rating\"] = _safe_num(df_reviews_r[\"rating\"])\n",
|
| 931 |
-
"if \"popularity_score\" in df_reviews_r.columns:\n",
|
| 932 |
-
" df_reviews_r[\"popularity_score\"] = _safe_num(df_reviews_r[\"popularity_score\"])\n",
|
| 933 |
-
"\n",
|
| 934 |
-
"# --- Sentiment shares per title (from reviews) ---\n",
|
| 935 |
-
"sent_counts = (\n",
|
| 936 |
-
" df_reviews_r.groupby([\"title\", \"sentiment_label\"])\n",
|
| 937 |
-
" .size()\n",
|
| 938 |
-
" .unstack(fill_value=0)\n",
|
| 939 |
-
")\n",
|
| 940 |
-
"for lab in [\"positive\", \"neutral\", \"negative\"]:\n",
|
| 941 |
-
" if lab not in sent_counts.columns:\n",
|
| 942 |
-
" sent_counts[lab] = 0\n",
|
| 943 |
-
"\n",
|
| 944 |
-
"sent_counts[\"total_reviews\"] = sent_counts[[\"positive\", \"neutral\", \"negative\"]].sum(axis=1)\n",
|
| 945 |
-
"den = sent_counts[\"total_reviews\"].replace(0, np.nan)\n",
|
| 946 |
-
"sent_counts[\"share_positive\"] = sent_counts[\"positive\"] / den\n",
|
| 947 |
-
"sent_counts[\"share_neutral\"] = sent_counts[\"neutral\"] / den\n",
|
| 948 |
-
"sent_counts[\"share_negative\"] = sent_counts[\"negative\"] / den\n",
|
| 949 |
-
"sent_counts = sent_counts.reset_index()\n",
|
| 950 |
-
"\n",
|
| 951 |
-
"# --- Sales aggregation per title ---\n",
|
| 952 |
-
"sales_by_title = (\n",
|
| 953 |
-
" df_sales_r.dropna(subset=[\"title\"])\n",
|
| 954 |
-
" .groupby(\"title\", as_index=False)\n",
|
| 955 |
-
" .agg(\n",
|
| 956 |
-
" months_observed=(\"month\", \"nunique\"),\n",
|
| 957 |
-
" avg_units_sold=(\"units_sold\", \"mean\"),\n",
|
| 958 |
-
" total_units_sold=(\"units_sold\", \"sum\"),\n",
|
| 959 |
-
" )\n",
|
| 960 |
-
")\n",
|
| 961 |
-
"\n",
|
| 962 |
-
"# --- Title-level features (join sales + books + sentiment) ---\n",
|
| 963 |
-
"df_title = (\n",
|
| 964 |
-
" sales_by_title\n",
|
| 965 |
-
" .merge(df_books_r[[\"title\", \"price\", \"rating\"]], on=\"title\", how=\"left\")\n",
|
| 966 |
-
" .merge(sent_counts[[\"title\", \"share_positive\", \"share_neutral\", \"share_negative\", \"total_reviews\"]],\n",
|
| 967 |
-
" on=\"title\", how=\"left\")\n",
|
| 968 |
-
")\n",
|
| 969 |
-
"\n",
|
| 970 |
-
"df_title[\"avg_revenue\"] = df_title[\"avg_units_sold\"] * df_title[\"price\"]\n",
|
| 971 |
-
"df_title[\"total_revenue\"] = df_title[\"total_units_sold\"] * df_title[\"price\"]\n",
|
| 972 |
-
"\n",
|
| 973 |
-
"df_title.to_csv(\"synthetic_title_level_features.csv\", index=False)\n",
|
| 974 |
-
"print(\"✅ Wrote synthetic_title_level_features.csv\")\n",
|
| 975 |
-
"\n",
|
| 976 |
-
"# --- Monthly revenue series (proxy: units_sold * price) ---\n",
|
| 977 |
-
"monthly_rev = (\n",
|
| 978 |
-
" df_sales_r.merge(df_books_r[[\"title\", \"price\"]], on=\"title\", how=\"left\")\n",
|
| 979 |
-
")\n",
|
| 980 |
-
"monthly_rev[\"revenue\"] = monthly_rev[\"units_sold\"] * monthly_rev[\"price\"]\n",
|
| 981 |
-
"\n",
|
| 982 |
-
"df_monthly = (\n",
|
| 983 |
-
" monthly_rev.dropna(subset=[\"month\"])\n",
|
| 984 |
-
" .groupby(\"month\", as_index=False)[\"revenue\"]\n",
|
| 985 |
-
" .sum()\n",
|
| 986 |
-
" .rename(columns={\"revenue\": \"total_revenue\"})\n",
|
| 987 |
-
" .sort_values(\"month\")\n",
|
| 988 |
-
")\n",
|
| 989 |
-
"# if revenue is all NA (e.g., missing price), fallback to units_sold as a teaching proxy\n",
|
| 990 |
-
"if df_monthly[\"total_revenue\"].notna().sum() == 0:\n",
|
| 991 |
-
" df_monthly = (\n",
|
| 992 |
-
" df_sales_r.dropna(subset=[\"month\"])\n",
|
| 993 |
-
" .groupby(\"month\", as_index=False)[\"units_sold\"]\n",
|
| 994 |
-
" .sum()\n",
|
| 995 |
-
" .rename(columns={\"units_sold\": \"total_revenue\"})\n",
|
| 996 |
-
" .sort_values(\"month\")\n",
|
| 997 |
-
" )\n",
|
| 998 |
-
"\n",
|
| 999 |
-
"df_monthly[\"month\"] = pd.to_datetime(df_monthly[\"month\"], errors=\"coerce\").dt.strftime(\"%Y-%m-%d\")\n",
|
| 1000 |
-
"df_monthly.to_csv(\"synthetic_monthly_revenue_series.csv\", index=False)\n",
|
| 1001 |
-
"print(\"✅ Wrote synthetic_monthly_revenue_series.csv\")\n"
|
| 1002 |
-
]
|
| 1003 |
-
},
|
| 1004 |
-
{
|
| 1005 |
-
"cell_type": "markdown",
|
| 1006 |
-
"metadata": {
|
| 1007 |
-
"id": "RYvGyVfXuo54"
|
| 1008 |
-
},
|
| 1009 |
-
"source": [
|
| 1010 |
-
"### *d. ✋🏻🛑⛔️ View the first few lines*"
|
| 1011 |
-
]
|
| 1012 |
-
},
|
| 1013 |
-
{
|
| 1014 |
-
"cell_type": "code",
|
| 1015 |
-
"execution_count": 20,
|
| 1016 |
-
"metadata": {
|
| 1017 |
-
"colab": {
|
| 1018 |
-
"base_uri": "https://localhost:8080/"
|
| 1019 |
-
},
|
| 1020 |
-
"id": "xfE8NMqOurKo",
|
| 1021 |
-
"outputId": "191730ba-d5e2-4df7-97d2-99feb0b704af"
|
| 1022 |
-
},
|
| 1023 |
-
"outputs": [
|
| 1024 |
-
{
|
| 1025 |
-
"output_type": "stream",
|
| 1026 |
-
"name": "stdout",
|
| 1027 |
-
"text": [
|
| 1028 |
-
" title sentiment_label \\\n",
|
| 1029 |
-
"0 A Light in the Attic neutral \n",
|
| 1030 |
-
"1 A Light in the Attic neutral \n",
|
| 1031 |
-
"2 A Light in the Attic neutral \n",
|
| 1032 |
-
"3 A Light in the Attic neutral \n",
|
| 1033 |
-
"4 A Light in the Attic neutral \n",
|
| 1034 |
-
"\n",
|
| 1035 |
-
" review_text rating popularity_score \n",
|
| 1036 |
-
"0 Had potential that went unrealized. Three 3 \n",
|
| 1037 |
-
"1 The themes were solid, but not well explored. Three 3 \n",
|
| 1038 |
-
"2 It simply lacked that emotional punch. Three 3 \n",
|
| 1039 |
-
"3 Serviceable but not something I'd go out of my... Three 3 \n",
|
| 1040 |
-
"4 Standard fare with some promise. Three 3 \n"
|
| 1041 |
-
]
|
| 1042 |
-
}
|
| 1043 |
-
],
|
| 1044 |
-
"source": [
|
| 1045 |
-
"print(df_reviews.head())"
|
| 1046 |
-
]
|
| 1047 |
-
}
|
| 1048 |
-
],
|
| 1049 |
-
"metadata": {
|
| 1050 |
-
"colab": {
|
| 1051 |
-
"collapsed_sections": [
|
| 1052 |
-
"jpASMyIQMaAq",
|
| 1053 |
-
"lquNYCbfL9IM",
|
| 1054 |
-
"0IWuNpxxYDJF",
|
| 1055 |
-
"oCdTsin2Yfp3",
|
| 1056 |
-
"T0TOeRC4Yrnn",
|
| 1057 |
-
"duI5dv3CZYvF",
|
| 1058 |
-
"qMjRKMBQZlJi",
|
| 1059 |
-
"p-1Pr2szaqLk",
|
| 1060 |
-
"SIaJUGIpaH4V",
|
| 1061 |
-
"pY4yCoIuaQqp",
|
| 1062 |
-
"n4-TaNTFgPak",
|
| 1063 |
-
"HnngRNTgacYt",
|
| 1064 |
-
"HF9F9HIzgT7Z",
|
| 1065 |
-
"T8AdKkmASq9a",
|
| 1066 |
-
"OhXbdGD5fH0c",
|
| 1067 |
-
"L2ak1HlcgoTe",
|
| 1068 |
-
"4IXZKcCSgxnq",
|
| 1069 |
-
"EhIjz9WohAmZ",
|
| 1070 |
-
"Gi4y9M9KuDWx",
|
| 1071 |
-
"fQhfVaDmuULT",
|
| 1072 |
-
"bmJMXF-Bukdm",
|
| 1073 |
-
"RYvGyVfXuo54"
|
| 1074 |
-
],
|
| 1075 |
-
"provenance": []
|
| 1076 |
-
},
|
| 1077 |
-
"kernelspec": {
|
| 1078 |
-
"display_name": "Python 3",
|
| 1079 |
-
"name": "python3"
|
| 1080 |
-
},
|
| 1081 |
-
"language_info": {
|
| 1082 |
-
"name": "python"
|
| 1083 |
-
}
|
| 1084 |
},
|
| 1085 |
-
"
|
| 1086 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1087 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"nbformat": 4,
|
| 3 |
+
"nbformat_minor": 5,
|
| 4 |
+
"metadata": {
|
| 5 |
+
"kernelspec": {
|
| 6 |
+
"display_name": "Python 3",
|
| 7 |
+
"language": "python",
|
| 8 |
+
"name": "python3"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 9 |
},
|
| 10 |
+
"language_info": {
|
| 11 |
+
"name": "python",
|
| 12 |
+
"version": "3.10.0"
|
| 13 |
+
}
|
| 14 |
+
},
|
| 15 |
+
"cells": [
|
| 16 |
+
{
|
| 17 |
+
"cell_type": "markdown",
|
| 18 |
+
"metadata": {},
|
| 19 |
+
"source": [
|
| 20 |
+
"# \ud83c\udf77 **Data Collection, Creation, Storage, and Processing**\n\n**Business Problem:** How can a wine retailer optimize its pricing and inventory strategy using customer review sentiment (qualitative) and sales data (quantitative)?"
|
| 21 |
+
]
|
| 22 |
+
},
|
| 23 |
+
{
|
| 24 |
+
"cell_type": "markdown",
|
| 25 |
+
"metadata": {},
|
| 26 |
+
"source": [
|
| 27 |
+
"## **1.** \ud83d\udce6 Install required packages"
|
| 28 |
+
]
|
| 29 |
+
},
|
| 30 |
+
{
|
| 31 |
+
"cell_type": "code",
|
| 32 |
+
"metadata": {},
|
| 33 |
+
"source": [
|
| 34 |
+
"!pip install pandas numpy matplotlib seaborn vaderSentiment beautifulsoup4 requests textblob faker"
|
| 35 |
+
],
|
| 36 |
+
"outputs": [],
|
| 37 |
+
"execution_count": null
|
| 38 |
+
},
|
| 39 |
+
{
|
| 40 |
+
"cell_type": "markdown",
|
| 41 |
+
"metadata": {},
|
| 42 |
+
"source": [
|
| 43 |
+
"## **2.** \ud83c\udf10 Load the real-world wine dataset\n\nThe dataset is sourced from Kaggle's Wine Reviews dataset (https://www.kaggle.com/zynicide/wine-reviews), containing wine titles, countries, varieties, ratings (points), and prices."
|
| 44 |
+
]
|
| 45 |
+
},
|
| 46 |
+
{
|
| 47 |
+
"cell_type": "markdown",
|
| 48 |
+
"metadata": {},
|
| 49 |
+
"source": [
|
| 50 |
+
"### *a. Initial setup*"
|
| 51 |
+
]
|
| 52 |
+
},
|
| 53 |
+
{
|
| 54 |
+
"cell_type": "code",
|
| 55 |
+
"metadata": {},
|
| 56 |
+
"source": [
|
| 57 |
+
"import pandas as pd\nimport numpy as np\nimport random\nfrom datetime import datetime\nimport warnings\n\nwarnings.filterwarnings(\"ignore\")\nrandom.seed(2025)\nnp.random.seed(2025)"
|
| 58 |
+
],
|
| 59 |
+
"outputs": [],
|
| 60 |
+
"execution_count": null
|
| 61 |
+
},
|
| 62 |
+
{
|
| 63 |
+
"cell_type": "markdown",
|
| 64 |
+
"metadata": {},
|
| 65 |
+
"source": [
|
| 66 |
+
"### *b. Load the wine dataset*"
|
| 67 |
+
]
|
| 68 |
+
},
|
| 69 |
+
{
|
| 70 |
+
"cell_type": "code",
|
| 71 |
+
"metadata": {},
|
| 72 |
+
"source": [
|
| 73 |
+
"df_wines = pd.read_csv(\"wine_data.csv\")"
|
| 74 |
+
],
|
| 75 |
+
"outputs": [],
|
| 76 |
+
"execution_count": null
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"cell_type": "markdown",
|
| 80 |
+
"metadata": {},
|
| 81 |
+
"source": [
|
| 82 |
+
"### *c. View first few lines*"
|
| 83 |
+
]
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"cell_type": "code",
|
| 87 |
+
"metadata": {},
|
| 88 |
+
"source": [
|
| 89 |
+
"df_wines.head()"
|
| 90 |
+
],
|
| 91 |
+
"outputs": [],
|
| 92 |
+
"execution_count": null
|
| 93 |
+
},
|
| 94 |
+
{
|
| 95 |
+
"cell_type": "markdown",
|
| 96 |
+
"metadata": {},
|
| 97 |
+
"source": [
|
| 98 |
+
"### *d. Basic info*"
|
| 99 |
+
]
|
| 100 |
+
},
|
| 101 |
+
{
|
| 102 |
+
"cell_type": "code",
|
| 103 |
+
"metadata": {},
|
| 104 |
+
"source": [
|
| 105 |
+
"print(f\"Shape: {df_wines.shape}\")\nprint(f\"\\nColumns: {list(df_wines.columns)}\")\nprint(f\"\\nMissing values:\\n{df_wines.isnull().sum()}\")\nprint(f\"\\nPoints distribution:\\n{df_wines['points'].describe()}\")"
|
| 106 |
+
],
|
| 107 |
+
"outputs": [],
|
| 108 |
+
"execution_count": null
|
| 109 |
+
},
|
| 110 |
+
{
|
| 111 |
+
"cell_type": "markdown",
|
| 112 |
+
"metadata": {},
|
| 113 |
+
"source": [
|
| 114 |
+
"## **3.** \ud83e\udde9 Create a meaningful connection between real & synthetic datasets"
|
| 115 |
+
]
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"cell_type": "markdown",
|
| 119 |
+
"metadata": {},
|
| 120 |
+
"source": [
|
| 121 |
+
"### *a. Generate popularity scores based on points (with some randomness)*"
|
| 122 |
+
]
|
| 123 |
+
},
|
| 124 |
+
{
|
| 125 |
+
"cell_type": "code",
|
| 126 |
+
"metadata": {},
|
| 127 |
+
"source": [
|
| 128 |
+
"def generate_popularity_score(points):\n if points >= 95:\n base = 5\n elif points >= 90:\n base = 4\n elif points >= 85:\n base = 3\n elif points >= 82:\n base = 2\n else:\n base = 1\n trend_factor = random.choices([-1, 0, 1], weights=[1, 3, 2])[0]\n return int(np.clip(base + trend_factor, 1, 5))"
|
| 129 |
+
],
|
| 130 |
+
"outputs": [],
|
| 131 |
+
"execution_count": null
|
| 132 |
+
},
|
| 133 |
+
{
|
| 134 |
+
"cell_type": "markdown",
|
| 135 |
+
"metadata": {},
|
| 136 |
+
"source": [
|
| 137 |
+
"### *b. Run the function to create a \"popularity_score\" column*"
|
| 138 |
+
]
|
| 139 |
+
},
|
| 140 |
+
{
|
| 141 |
+
"cell_type": "code",
|
| 142 |
+
"metadata": {},
|
| 143 |
+
"source": [
|
| 144 |
+
"df_wines[\"popularity_score\"] = df_wines[\"points\"].apply(generate_popularity_score)"
|
| 145 |
+
],
|
| 146 |
+
"outputs": [],
|
| 147 |
+
"execution_count": null
|
| 148 |
+
},
|
| 149 |
+
{
|
| 150 |
+
"cell_type": "markdown",
|
| 151 |
+
"metadata": {},
|
| 152 |
+
"source": [
|
| 153 |
+
"### *c. Create sentiment labels from popularity scores*"
|
| 154 |
+
]
|
| 155 |
+
},
|
| 156 |
+
{
|
| 157 |
+
"cell_type": "code",
|
| 158 |
+
"metadata": {},
|
| 159 |
+
"source": [
|
| 160 |
+
"def get_sentiment(popularity_score):\n if popularity_score <= 2:\n return \"negative\"\n elif popularity_score == 3:\n return \"neutral\"\n else:\n return \"positive\"\n\ndf_wines[\"sentiment_label\"] = df_wines[\"popularity_score\"].apply(get_sentiment)"
|
| 161 |
+
],
|
| 162 |
+
"outputs": [],
|
| 163 |
+
"execution_count": null
|
| 164 |
+
},
|
| 165 |
+
{
|
| 166 |
+
"cell_type": "markdown",
|
| 167 |
+
"metadata": {},
|
| 168 |
+
"source": [
|
| 169 |
+
"## **4.** \ud83d\udcc8 Generate synthetic wine sales data (18 months)"
|
| 170 |
+
]
|
| 171 |
+
},
|
| 172 |
+
{
|
| 173 |
+
"cell_type": "markdown",
|
| 174 |
+
"metadata": {},
|
| 175 |
+
"source": [
|
| 176 |
+
"### *a. Create a generate_sales_profile function*"
|
| 177 |
+
]
|
| 178 |
+
},
|
| 179 |
+
{
|
| 180 |
+
"cell_type": "code",
|
| 181 |
+
"metadata": {},
|
| 182 |
+
"source": [
|
| 183 |
+
"def generate_sales_profile(sentiment, price):\n months = pd.date_range(end=datetime.today(), periods=18, freq=\"M\")\n price_factor = max(0.5, 1 - (price / 100)) # cheaper wines sell more\n \n if sentiment == \"positive\":\n base = int(random.randint(150, 250) * price_factor)\n trend = np.linspace(base, base + random.randint(20, 60), len(months))\n elif sentiment == \"negative\":\n base = int(random.randint(20, 60) * price_factor)\n trend = np.linspace(base, base - random.randint(5, 20), len(months))\n else:\n base = int(random.randint(70, 120) * price_factor)\n trend = np.linspace(base, base + random.randint(-10, 10), len(months))\n\n noise = np.random.normal(0, base * 0.1, len(months))\n units = np.maximum(1, trend + noise).astype(int)\n return list(zip(months, units))"
|
| 184 |
+
],
|
| 185 |
+
"outputs": [],
|
| 186 |
+
"execution_count": null
|
| 187 |
+
},
|
| 188 |
+
{
|
| 189 |
+
"cell_type": "markdown",
|
| 190 |
+
"metadata": {},
|
| 191 |
+
"source": [
|
| 192 |
+
"### *b. Build the sales dataset*"
|
| 193 |
+
]
|
| 194 |
+
},
|
| 195 |
+
{
|
| 196 |
+
"cell_type": "code",
|
| 197 |
+
"metadata": {},
|
| 198 |
+
"source": [
|
| 199 |
+
"sales_data = []\nfor _, row in df_wines.iterrows():\n records = generate_sales_profile(row[\"sentiment_label\"], row[\"price\"])\n for month, units in records:\n sales_data.append({\n \"title\": row[\"title\"],\n \"month\": month,\n \"units_sold\": units,\n \"sentiment_label\": row[\"sentiment_label\"],\n \"price\": row[\"price\"],\n \"popularity_score\": row[\"popularity_score\"],\n })\n\ndf_sales = pd.DataFrame(sales_data)"
|
| 200 |
+
],
|
| 201 |
+
"outputs": [],
|
| 202 |
+
"execution_count": null
|
| 203 |
+
},
|
| 204 |
+
{
|
| 205 |
+
"cell_type": "markdown",
|
| 206 |
+
"metadata": {},
|
| 207 |
+
"source": [
|
| 208 |
+
"### *c. Save and view*"
|
| 209 |
+
]
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"cell_type": "code",
|
| 213 |
+
"metadata": {},
|
| 214 |
+
"source": [
|
| 215 |
+
"df_sales.to_csv(\"synthetic_wine_sales.csv\", index=False)\nprint(f\"Sales dataset shape: {df_sales.shape}\")\nprint(df_sales.head())"
|
| 216 |
+
],
|
| 217 |
+
"outputs": [],
|
| 218 |
+
"execution_count": null
|
| 219 |
+
},
|
| 220 |
+
{
|
| 221 |
+
"cell_type": "markdown",
|
| 222 |
+
"metadata": {},
|
| 223 |
+
"source": [
|
| 224 |
+
"## **5.** \ud83c\udfaf Generate synthetic customer reviews"
|
| 225 |
+
]
|
| 226 |
+
},
|
| 227 |
+
{
|
| 228 |
+
"cell_type": "markdown",
|
| 229 |
+
"metadata": {},
|
| 230 |
+
"source": [
|
| 231 |
+
"### *a. Create review pools per sentiment category (generated with ChatGPT)*"
|
| 232 |
+
]
|
| 233 |
+
},
|
| 234 |
+
{
|
| 235 |
+
"cell_type": "code",
|
| 236 |
+
"metadata": {},
|
| 237 |
+
"source": [
|
| 238 |
+
"synthetic_reviews_by_sentiment = {\n \"positive\": [\n \"Exceptional wine with rich, complex flavours that linger beautifully on the palate.\",\n \"One of the finest bottles I have tasted this year, absolutely worth the price.\",\n \"Beautifully balanced with notes of dark fruit and a silky smooth finish.\",\n \"A stunning wine that pairs perfectly with any occasion. Highly recommended.\",\n \"Elegant and refined, this wine exceeded all my expectations.\",\n \"The aroma alone is captivating \u2014 cherry, oak, and a hint of vanilla.\",\n \"A true masterpiece from this winery. Will definitely be buying more.\",\n \"Smooth, sophisticated, and incredibly drinkable. A real crowd-pleaser.\",\n \"Outstanding quality for the price. This is a hidden gem.\",\n \"Deep colour, wonderful bouquet, and a long satisfying finish.\",\n \"This wine is a revelation. Every sip brings something new to discover.\",\n \"Perfect balance of acidity and tannins. A joy to drink.\",\n \"An absolute delight \u2014 fruity, fresh, and full of character.\",\n \"The craftsmanship behind this bottle is evident in every glass.\",\n \"Rich and velvety with a complexity that keeps you coming back.\",\n \"A gorgeous wine that shows what this region can produce at its best.\",\n \"Delightfully aromatic with layers of flavour that unfold gradually.\",\n \"Simply superb. This wine belongs on every serious collector's shelf.\",\n \"An impressive vintage that delivers on every front.\",\n \"A real treat for the senses. Would pair wonderfully with aged cheese.\",\n \"Bright and lively with a finish that goes on and on.\",\n \"Wonderfully expressive wine with great depth and personality.\",\n \"Perfectly aged and showing beautifully right now.\",\n \"A showstopper at dinner parties. Everyone asked about this bottle.\",\n \"Luxurious texture and impeccable balance. Worth every penny.\",\n \"This wine tells a story of its terroir in the most beautiful way.\",\n \"Vibrant fruit flavours with just the right amount of oak influence.\",\n \"A benchmark wine for the variety. Consistently excellent.\",\n \"So good I ordered a full case. Cannot recommend enough.\",\n \"The kind of wine that makes you stop and appreciate the moment.\",\n \"Floral nose, silky palate, and an incredibly clean finish.\",\n \"A wine that proves quality does not always mean expensive.\",\n \"Absolutely divine. This winery never disappoints.\",\n \"Complex, layered, and endlessly interesting. A true fine wine.\",\n \"This vintage is drinking perfectly right now. Do not miss it.\",\n \"Generous fruit, gentle spice, and a touch of minerality. Lovely.\",\n \"A wine that manages to be both powerful and graceful.\",\n \"One of the best values in wine today. Extraordinary quality.\",\n \"The finish alone makes this wine memorable. Pure elegance.\",\n \"A joyful wine that brings warmth and happiness with every glass.\",\n \"Incredible structure and aging potential. A serious wine.\",\n \"Harmonious from start to finish. Textbook winemaking.\",\n \"This wine has soul. You can taste the passion behind it.\",\n \"Brilliant colour and an intoxicating bouquet. Truly special.\",\n \"A wine lover's dream. Complex, balanced, and utterly delicious.\",\n \"Everything I look for in a great wine \u2014 and then some.\",\n \"Refined and polished with a beautiful aromatic profile.\",\n \"A stunning example of what modern winemaking can achieve.\",\n \"Pure pleasure in a glass. An unforgettable experience.\",\n \"This is the wine I will be recommending to everyone this year.\"\n ],\n \"neutral\": [\n \"A decent wine that does its job without being particularly memorable.\",\n \"Perfectly acceptable for everyday drinking, nothing more nothing less.\",\n \"A straightforward wine with simple fruit flavours.\",\n \"Reliable and consistent, though it lacks real excitement.\",\n \"Good enough for a casual dinner but would not seek it out again.\",\n \"Middle of the road \u2014 not bad but not impressive either.\",\n \"A solid table wine at a fair price point.\",\n \"Pleasant enough on the palate but forgettable overall.\",\n \"Does what you expect for the price range. No surprises.\",\n \"A basic wine that fills a gap but does not inspire.\",\n \"Drinkable and inoffensive, suitable for large gatherings.\",\n \"It is fine. Nothing wrong with it but nothing exciting either.\",\n \"An average wine that will satisfy casual drinkers.\",\n \"Somewhat one-dimensional but clean and well-made.\",\n \"A reasonable choice if you are not looking for anything special.\",\n \"Not bad for the price but I have had better in this range.\",\n \"A competent wine without much personality.\",\n \"Simple and clean with modest fruit character.\",\n \"Okay for the price but I would not buy it again.\",\n \"An unremarkable but serviceable everyday wine.\",\n \"Neither impressive nor disappointing. Just average.\",\n \"A safe choice for when you do not know what to pick.\",\n \"Lacks complexity but is well-balanced for what it is.\",\n \"A standard offering from this region. No complaints.\",\n \"Meets expectations without exceeding them.\",\n \"The kind of wine you drink without really thinking about it.\",\n \"Perfectly fine but would not win any awards.\",\n \"A middle-ground wine suitable for any casual occasion.\",\n \"Uncomplicated and easy to drink. Nothing fancy.\",\n \"Acceptable quality at an acceptable price.\",\n \"It does its job. You could do worse for the money.\",\n \"A fair wine that represents its price point accurately.\",\n \"Light and simple \u2014 good for a hot afternoon, perhaps.\",\n \"Not a standout but not a disappointment either.\",\n \"A run-of-the-mill wine with standard characteristics.\",\n \"Drinkable but I would happily trade up for a few more euros.\",\n \"A no-frills wine for no-frills occasions.\",\n \"Average in every respect. The definition of mediocre.\",\n \"A passable wine that does not offend or excite.\",\n \"Consistent but uninspiring. A forgettable bottle.\",\n \"Neither here nor there. An okay wine.\",\n \"Functional wine for functional purposes.\",\n \"This wine is the equivalent of a shrug. It exists.\",\n \"An everyday wine that blends into the background.\",\n \"Does not stand out in a lineup but holds its own.\",\n \"A modest wine with modest ambitions.\",\n \"Satisfactory but leaves you wanting something more.\",\n \"A standard-issue wine with no real flaws or virtues.\",\n \"Unremarkable but perfectly drinkable.\",\n \"A wine that is easy to forget. Not terrible, not great.\"\n ],\n \"negative\": [\n \"Disappointing for the price. Thin and lacking any real character.\",\n \"Harsh tannins and an unpleasant bitter finish. Would not buy again.\",\n \"Tastes cheap and overly acidic. Not enjoyable at all.\",\n \"This wine fell flat \u2014 watery, bland, and overpriced.\",\n \"The flavour profile is muddled and confusing. Poor winemaking.\",\n \"Way too much oak. It tastes like you are drinking a barrel.\",\n \"Unbalanced and rough around the edges. Needs serious improvement.\",\n \"I could not finish the bottle. The aftertaste was terrible.\",\n \"Massively overpriced for the quality. A real letdown.\",\n \"Astringent and harsh with no redeeming qualities.\",\n \"The aroma was off-putting \u2014 smelled like vinegar.\",\n \"A wine that tries too hard and achieves too little.\",\n \"Flat and lifeless. No fruit, no complexity, no interest.\",\n \"Would not serve this to guests. Embarrassingly poor quality.\",\n \"Overly sweet and cloying. Lacks any sophistication.\",\n \"This wine is a cautionary tale about judging by the label.\",\n \"Thin, watery, and devoid of any character whatsoever.\",\n \"An unpleasant drinking experience from start to finish.\",\n \"Tastes like it was made in a hurry with no care.\",\n \"Rough, tannic, and completely out of balance.\",\n \"The worst wine I have had in this price range.\",\n \"Needs several more years \u2014 or maybe a different winemaker.\",\n \"Acidic and sharp with a finish that makes you wince.\",\n \"Not worth the glass it was poured into.\",\n \"A forgettable wine for all the wrong reasons.\",\n \"This bottle went straight down the sink after one glass.\",\n \"Dull, flat, and uninspiring. Avoid this one.\",\n \"Tastes oxidised and past its prime. Questionable storage.\",\n \"An aggressive wine that attacks rather than caresses the palate.\",\n \"I expected much more from this winery. Very disappointing.\",\n \"The tannins are so harsh they strip your mouth completely.\",\n \"No complexity, no depth, no reason to buy this wine.\",\n \"Cheap-tasting wine at a not-so-cheap price.\",\n \"A mess of a wine. Every element seems to fight the others.\",\n \"Sour and unripe. Tastes like it was harvested too early.\",\n \"One of the most underwhelming wines I have ever tasted.\",\n \"Thin body and a finish that disappears instantly.\",\n \"Off-putting nose and equally unpleasant on the palate.\",\n \"This wine does not live up to its reputation at all.\",\n \"Clumsy and awkward. Lacks finesse entirely.\",\n \"I wanted to like this wine but it gave me nothing to work with.\",\n \"Overworked and over-oaked. Lost all its fruit character.\",\n \"A wine that is hard to recommend to anyone.\",\n \"Surprisingly bad for a winery of this calibre.\",\n \"Flat, stale, and lacking any vibrancy.\",\n \"The kind of wine that makes you question the ratings.\",\n \"No redeeming features. A complete waste of money.\",\n \"Tastes manufactured rather than crafted. Very artificial.\",\n \"A harsh and unforgiving wine with zero charm.\",\n \"Bottom of the barrel quality. Stay away.\"\n ]\n}"
|
| 239 |
+
],
|
| 240 |
+
"outputs": [],
|
| 241 |
+
"execution_count": null
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"cell_type": "markdown",
|
| 245 |
+
"metadata": {},
|
| 246 |
+
"source": [
|
| 247 |
+
"### *b. Generate 10 reviews per wine*"
|
| 248 |
+
]
|
| 249 |
+
},
|
| 250 |
+
{
|
| 251 |
+
"cell_type": "code",
|
| 252 |
+
"metadata": {},
|
| 253 |
+
"source": [
|
| 254 |
+
"review_rows = []\nfor _, row in df_wines.iterrows():\n title = row['title']\n sentiment_label = row['sentiment_label']\n review_pool = synthetic_reviews_by_sentiment[sentiment_label]\n sampled_reviews = random.sample(review_pool, 10)\n for review_text in sampled_reviews:\n review_rows.append({\n \"title\": title,\n \"review_text\": review_text,\n \"sentiment_label\": sentiment_label,\n \"points\": row[\"points\"],\n \"price\": row[\"price\"],\n \"country\": row[\"country\"],\n \"variety\": row[\"variety\"],\n \"popularity_score\": row[\"popularity_score\"],\n })"
|
| 255 |
+
],
|
| 256 |
+
"outputs": [],
|
| 257 |
+
"execution_count": null
|
| 258 |
+
},
|
| 259 |
+
{
|
| 260 |
+
"cell_type": "markdown",
|
| 261 |
+
"metadata": {},
|
| 262 |
+
"source": [
|
| 263 |
+
"### *c. Create and save df_reviews*"
|
| 264 |
+
]
|
| 265 |
+
},
|
| 266 |
+
{
|
| 267 |
+
"cell_type": "code",
|
| 268 |
+
"metadata": {},
|
| 269 |
+
"source": [
|
| 270 |
+
"df_reviews = pd.DataFrame(review_rows)\ndf_reviews.to_csv(\"synthetic_wine_reviews.csv\", index=False)\nprint(f\"Reviews dataset shape: {df_reviews.shape}\")\nprint(df_reviews.head())"
|
| 271 |
+
],
|
| 272 |
+
"outputs": [],
|
| 273 |
+
"execution_count": null
|
| 274 |
+
},
|
| 275 |
+
{
|
| 276 |
+
"cell_type": "markdown",
|
| 277 |
+
"metadata": {},
|
| 278 |
+
"source": [
|
| 279 |
+
"## **6.** \u2705 Create derived inputs for analysis"
|
| 280 |
+
]
|
| 281 |
+
},
|
| 282 |
+
{
|
| 283 |
+
"cell_type": "code",
|
| 284 |
+
"metadata": {},
|
| 285 |
+
"source": [
|
| 286 |
+
"# Title-level features for analysis\ntitle_features = df_wines[[\"title\", \"country\", \"variety\", \"points\", \"price\", \"popularity_score\", \"sentiment_label\"]]\ntitle_features.to_csv(\"synthetic_title_level_features.csv\", index=False)\n\n# Monthly revenue series\ndf_sales[\"revenue\"] = df_sales[\"units_sold\"] * df_sales[\"price\"]\nmonthly_rev = df_sales.groupby(\"month\", as_index=False).agg(\n total_units_sold=(\"units_sold\", \"sum\"),\n total_revenue=(\"revenue\", \"sum\"),\n)\nmonthly_rev.to_csv(\"synthetic_monthly_revenue_series.csv\", index=False)\nprint(\"Derived files saved.\")\nprint(monthly_rev.head())"
|
| 287 |
+
],
|
| 288 |
+
"outputs": [],
|
| 289 |
+
"execution_count": null
|
| 290 |
+
}
|
| 291 |
+
]
|
| 292 |
}
|
pythonanalysis.ipynb
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
wine_data.csv
ADDED
|
@@ -0,0 +1,1001 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
title,country,variety,winery,points,price
|
| 2 |
+
Bodega San Pietro Cabernet Sauvignon 2023,US,Cabernet Sauvignon,Bodega San Pietro,89,30.0
|
| 3 |
+
Tenuta Moonlight Barbera 2015,Italy,Barbera,Tenuta Moonlight,87,9.0
|
| 4 |
+
Weingut du Soleil Verdejo 2017,Spain,Verdejo,Weingut du Soleil,90,28.0
|
| 5 |
+
Estate San Pietro Chardonnay 2016,US,Chardonnay,Estate San Pietro,94,31.0
|
| 6 |
+
Château Cedar Falls Cabernet Sauvignon 2023,France,Cabernet Sauvignon,Château Cedar Falls,87,30.0
|
| 7 |
+
Quinta Stone Creek Barbera 2018,Italy,Barbera,Quinta Stone Creek,87,13.0
|
| 8 |
+
Domaine El Dorado Cabernet Sauvignon 2016,US,Cabernet Sauvignon,Domaine El Dorado,94,51.0
|
| 9 |
+
Estate Stone Creek Merlot 2018,France,Merlot,Estate Stone Creek,91,36.0
|
| 10 |
+
Tenuta Alta Vista Cabernet Sauvignon 2022,US,Cabernet Sauvignon,Tenuta Alta Vista,86,17.0
|
| 11 |
+
Château El Dorado Syrah 2015,France,Syrah,Château El Dorado,90,22.0
|
| 12 |
+
Quinta Golden Valley Cabernet Sauvignon 2018,Argentina,Cabernet Sauvignon,Quinta Golden Valley,86,13.0
|
| 13 |
+
Bodega Sierra Zinfandel 2017,US,Zinfandel,Bodega Sierra,86,28.0
|
| 14 |
+
Vineyard Crystal Lake Primitivo 2021,Italy,Primitivo,Vineyard Crystal Lake,88,29.0
|
| 15 |
+
Château San Pietro Pinot Noir 2017,France,Pinot Noir,Château San Pietro,80,12.0
|
| 16 |
+
Quinta Cedar Falls Zinfandel 2023,US,Zinfandel,Quinta Cedar Falls,81,17.0
|
| 17 |
+
Domaine Starfall Syrah 2019,France,Syrah,Domaine Starfall,85,15.0
|
| 18 |
+
Cantina du Soleil Alvarinho 2019,Portugal,Alvarinho,Cantina du Soleil,83,12.0
|
| 19 |
+
Weingut Moonlight Riesling 2018,Austria,Riesling,Weingut Moonlight,89,23.0
|
| 20 |
+
Casa du Soleil Nebbiolo 2020,Italy,Nebbiolo,Casa du Soleil,84,21.0
|
| 21 |
+
Weingut El Dorado Tempranillo 2015,Spain,Tempranillo,Weingut El Dorado,82,28.0
|
| 22 |
+
Cantina La Rosa Primitivo 2023,Italy,Primitivo,Cantina La Rosa,93,48.0
|
| 23 |
+
Bodega Sierra Port 2023,Portugal,Port,Bodega Sierra,87,31.0
|
| 24 |
+
Tenuta Pacific Ridge Merlot 2021,Chile,Merlot,Tenuta Pacific Ridge,88,40.0
|
| 25 |
+
Domaine El Dorado Zweigelt 2018,Austria,Zweigelt,Domaine El Dorado,82,17.0
|
| 26 |
+
Tenuta du Soleil Sangiovese 2016,Italy,Sangiovese,Tenuta du Soleil,85,15.0
|
| 27 |
+
Estate La Rosa Cabernet Sauvignon 2023,US,Cabernet Sauvignon,Estate La Rosa,88,25.0
|
| 28 |
+
Quinta Crystal Lake Barbera 2022,Italy,Barbera,Quinta Crystal Lake,83,9.0
|
| 29 |
+
Domaine River Bend Barbera 2020,Italy,Barbera,Domaine River Bend,89,31.0
|
| 30 |
+
Domaine del Monte Merlot 2021,France,Merlot,Domaine del Monte,85,16.0
|
| 31 |
+
Cantina Verde Cabernet Sauvignon 2021,US,Cabernet Sauvignon,Cantina Verde,86,12.0
|
| 32 |
+
Cantina Starfall Barbera 2016,Italy,Barbera,Cantina Starfall,85,20.0
|
| 33 |
+
Tenuta Alta Vista Primitivo 2021,Italy,Primitivo,Tenuta Alta Vista,95,63.0
|
| 34 |
+
Bodega Oak Hill Garnacha 2015,Spain,Garnacha,Bodega Oak Hill,87,34.0
|
| 35 |
+
Weingut River Bend Zweigelt 2023,Austria,Zweigelt,Weingut River Bend,83,26.0
|
| 36 |
+
Château Crystal Lake Zinfandel 2023,US,Zinfandel,Château Crystal Lake,91,22.0
|
| 37 |
+
Casa Moonlight Pinot Grigio 2017,Italy,Pinot Grigio,Casa Moonlight,83,13.0
|
| 38 |
+
Quinta La Rosa Primitivo 2018,Italy,Primitivo,Quinta La Rosa,88,13.0
|
| 39 |
+
Quinta La Rosa Syrah 2021,France,Syrah,Quinta La Rosa,80,15.0
|
| 40 |
+
Tenuta Golden Valley Merlot 2018,US,Merlot,Tenuta Golden Valley,82,23.0
|
| 41 |
+
Estate La Rosa Pinot Noir 2015,France,Pinot Noir,Estate La Rosa,88,26.0
|
| 42 |
+
Tenuta Moonlight Verdejo 2019,Spain,Verdejo,Tenuta Moonlight,90,38.0
|
| 43 |
+
Estate Pacific Ridge Pinot Grigio 2017,Italy,Pinot Grigio,Estate Pacific Ridge,88,38.0
|
| 44 |
+
Casa du Soleil Syrah 2023,France,Syrah,Casa du Soleil,87,28.0
|
| 45 |
+
Domaine San Pietro Chardonnay 2023,France,Chardonnay,Domaine San Pietro,86,22.0
|
| 46 |
+
Tenuta Sierra Pinot Grigio 2023,Italy,Pinot Grigio,Tenuta Sierra,82,21.0
|
| 47 |
+
Weingut del Monte Tempranillo 2015,Spain,Tempranillo,Weingut del Monte,85,11.0
|
| 48 |
+
Cantina Starfall Pinot Noir 2021,France,Pinot Noir,Cantina Starfall,86,19.0
|
| 49 |
+
Bodega Starfall Tempranillo 2015,Spain,Tempranillo,Bodega Starfall,92,29.0
|
| 50 |
+
Château Pacific Ridge Syrah 2020,Argentina,Syrah,Château Pacific Ridge,89,29.0
|
| 51 |
+
Tenuta San Pietro Carmenère 2020,Chile,Carmenère,Tenuta San Pietro,80,18.0
|
| 52 |
+
Tenuta Alta Vista Tinto Roriz 2017,Portugal,Tinto Roriz,Tenuta Alta Vista,89,42.0
|
| 53 |
+
Vineyard El Dorado Carmenère 2019,Chile,Carmenère,Vineyard El Dorado,86,21.0
|
| 54 |
+
Cantina El Dorado Sangiovese 2018,Italy,Sangiovese,Cantina El Dorado,85,10.0
|
| 55 |
+
Tenuta El Dorado Cabernet Sauvignon 2015,Argentina,Cabernet Sauvignon,Tenuta El Dorado,90,31.0
|
| 56 |
+
Weingut Stone Creek Zinfandel 2023,US,Zinfandel,Weingut Stone Creek,92,36.0
|
| 57 |
+
Weingut Alta Vista Syrah 2019,France,Syrah,Weingut Alta Vista,91,23.0
|
| 58 |
+
Estate River Bend Primitivo 2023,Italy,Primitivo,Estate River Bend,84,19.0
|
| 59 |
+
Vineyard du Soleil Primitivo 2023,Italy,Primitivo,Vineyard du Soleil,86,9.0
|
| 60 |
+
Tenuta Stone Creek Semillon 2021,Australia,Semillon,Tenuta Stone Creek,89,38.0
|
| 61 |
+
Domaine Pacific Ridge Pinot Grigio 2023,Italy,Pinot Grigio,Domaine Pacific Ridge,91,39.0
|
| 62 |
+
Casa Verde Merlot 2018,France,Merlot,Casa Verde,86,20.0
|
| 63 |
+
Quinta Crystal Lake Merlot 2019,France,Merlot,Quinta Crystal Lake,87,31.0
|
| 64 |
+
Quinta Thunder Ridge Chardonnay 2020,France,Chardonnay,Quinta Thunder Ridge,83,11.0
|
| 65 |
+
Bodega La Rosa Albariño 2019,Spain,Albariño,Bodega La Rosa,83,20.0
|
| 66 |
+
Tenuta Pacific Ridge Verdejo 2018,Spain,Verdejo,Tenuta Pacific Ridge,91,33.0
|
| 67 |
+
Cantina Thunder Ridge Torrontés 2016,Argentina,Torrontés,Cantina Thunder Ridge,93,20.0
|
| 68 |
+
Cantina Oak Hill Verdejo 2018,Spain,Verdejo,Cantina Oak Hill,87,20.0
|
| 69 |
+
Domaine River Bend Sangiovese 2018,Italy,Sangiovese,Domaine River Bend,92,53.0
|
| 70 |
+
Domaine Cedar Falls Primitivo 2017,Italy,Primitivo,Domaine Cedar Falls,89,28.0
|
| 71 |
+
Cantina Thunder Ridge Syrah 2023,Argentina,Syrah,Cantina Thunder Ridge,85,25.0
|
| 72 |
+
Cantina Cedar Falls Syrah 2019,France,Syrah,Cantina Cedar Falls,89,23.0
|
| 73 |
+
Tenuta Sierra Alvarinho 2022,Portugal,Alvarinho,Tenuta Sierra,94,52.0
|
| 74 |
+
Casa La Rosa Pinot Grigio 2017,Italy,Pinot Grigio,Casa La Rosa,87,16.0
|
| 75 |
+
Domaine River Bend Barbera 2021,Italy,Barbera,Domaine River Bend,94,51.0
|
| 76 |
+
Vineyard Oak Hill Merlot 2015,France,Merlot,Vineyard Oak Hill,80,12.0
|
| 77 |
+
Estate Pacific Ridge Syrah 2021,Chile,Syrah,Estate Pacific Ridge,91,24.0
|
| 78 |
+
Quinta El Dorado Merlot 2022,Chile,Merlot,Quinta El Dorado,88,29.0
|
| 79 |
+
Vineyard Alta Vista Barbera 2022,Italy,Barbera,Vineyard Alta Vista,86,18.0
|
| 80 |
+
Quinta Crystal Lake Semillon 2015,Australia,Semillon,Quinta Crystal Lake,88,31.0
|
| 81 |
+
Château Sierra Barbera 2021,Italy,Barbera,Château Sierra,80,12.0
|
| 82 |
+
Vineyard Sierra Merlot 2021,France,Merlot,Vineyard Sierra,87,23.0
|
| 83 |
+
Château Stone Creek Chardonnay 2018,France,Chardonnay,Château Stone Creek,89,31.0
|
| 84 |
+
Tenuta du Soleil Cabernet Sauvignon 2017,US,Cabernet Sauvignon,Tenuta du Soleil,93,53.0
|
| 85 |
+
Tenuta Cedar Falls Barbera 2019,Italy,Barbera,Tenuta Cedar Falls,85,20.0
|
| 86 |
+
Domaine Alta Vista Port 2019,Portugal,Port,Domaine Alta Vista,84,25.0
|
| 87 |
+
Vineyard Oak Hill Sangiovese 2018,Italy,Sangiovese,Vineyard Oak Hill,85,24.0
|
| 88 |
+
Quinta San Pietro Nebbiolo 2015,Italy,Nebbiolo,Quinta San Pietro,91,26.0
|
| 89 |
+
Estate du Soleil Merlot 2021,France,Merlot,Estate du Soleil,89,26.0
|
| 90 |
+
Cantina Verde Malbec 2021,Argentina,Malbec,Cantina Verde,85,15.0
|
| 91 |
+
Casa Iron Gate Primitivo 2022,Italy,Primitivo,Casa Iron Gate,90,40.0
|
| 92 |
+
Domaine Sierra Syrah 2022,France,Syrah,Domaine Sierra,88,25.0
|
| 93 |
+
Estate du Soleil Barbera 2022,Italy,Barbera,Estate du Soleil,91,38.0
|
| 94 |
+
Weingut Golden Valley Cabernet Sauvignon 2019,Chile,Cabernet Sauvignon,Weingut Golden Valley,85,15.0
|
| 95 |
+
Tenuta La Rosa Sauvignon Blanc 2018,Chile,Sauvignon Blanc,Tenuta La Rosa,86,21.0
|
| 96 |
+
Cantina Iron Gate Zinfandel 2022,US,Zinfandel,Cantina Iron Gate,86,17.0
|
| 97 |
+
Tenuta Pacific Ridge Touriga Nacional 2020,Portugal,Touriga Nacional,Tenuta Pacific Ridge,82,13.0
|
| 98 |
+
Casa Golden Valley Verdejo 2020,Spain,Verdejo,Casa Golden Valley,89,31.0
|
| 99 |
+
Tenuta Golden Valley Chardonnay 2016,US,Chardonnay,Tenuta Golden Valley,89,20.0
|
| 100 |
+
Weingut Crystal Lake Pinot Noir 2023,US,Pinot Noir,Weingut Crystal Lake,88,22.0
|
| 101 |
+
Estate Alta Vista Tempranillo 2019,Spain,Tempranillo,Estate Alta Vista,87,26.0
|
| 102 |
+
Château Starfall Primitivo 2019,Italy,Primitivo,Château Starfall,82,7.0
|
| 103 |
+
Domaine du Soleil Pinot Noir 2019,US,Pinot Noir,Domaine du Soleil,86,25.0
|
| 104 |
+
Weingut Iron Gate Albariño 2016,Spain,Albariño,Weingut Iron Gate,86,24.0
|
| 105 |
+
Château Verde Cabernet Sauvignon 2017,Argentina,Cabernet Sauvignon,Château Verde,84,18.0
|
| 106 |
+
Casa River Bend Bonarda 2018,Argentina,Bonarda,Casa River Bend,87,12.0
|
| 107 |
+
Quinta River Bend Tinto Roriz 2019,Portugal,Tinto Roriz,Quinta River Bend,89,26.0
|
| 108 |
+
Tenuta Bella Notte Tempranillo 2019,Spain,Tempranillo,Tenuta Bella Notte,95,52.0
|
| 109 |
+
Bodega du Soleil Pinot Noir 2021,US,Pinot Noir,Bodega du Soleil,88,21.0
|
| 110 |
+
Weingut Pacific Ridge Verdejo 2022,Spain,Verdejo,Weingut Pacific Ridge,89,21.0
|
| 111 |
+
Quinta Bella Notte Nebbiolo 2021,Italy,Nebbiolo,Quinta Bella Notte,87,34.0
|
| 112 |
+
Bodega La Rosa Nebbiolo 2015,Italy,Nebbiolo,Bodega La Rosa,80,24.0
|
| 113 |
+
Weingut Cedar Falls Pinot Grigio 2016,Italy,Pinot Grigio,Weingut Cedar Falls,87,29.0
|
| 114 |
+
Casa Starfall Monastrell 2022,Spain,Monastrell,Casa Starfall,88,35.0
|
| 115 |
+
Estate Thunder Ridge Syrah 2019,France,Syrah,Estate Thunder Ridge,97,30.0
|
| 116 |
+
Quinta Crystal Lake Nebbiolo 2015,Italy,Nebbiolo,Quinta Crystal Lake,87,35.0
|
| 117 |
+
Bodega Iron Gate Zweigelt 2023,Austria,Zweigelt,Bodega Iron Gate,89,33.0
|
| 118 |
+
Cantina La Rosa Chardonnay 2022,US,Chardonnay,Cantina La Rosa,87,18.0
|
| 119 |
+
Bodega Golden Valley Cabernet Sauvignon 2021,France,Cabernet Sauvignon,Bodega Golden Valley,83,10.0
|
| 120 |
+
Casa del Monte Chardonnay 2022,US,Chardonnay,Casa del Monte,92,40.0
|
| 121 |
+
Vineyard Moonlight Pinot Grigio 2015,Italy,Pinot Grigio,Vineyard Moonlight,91,35.0
|
| 122 |
+
Casa Stone Creek Merlot 2022,US,Merlot,Casa Stone Creek,91,27.0
|
| 123 |
+
Weingut Cedar Falls Cabernet Sauvignon 2022,US,Cabernet Sauvignon,Weingut Cedar Falls,84,14.0
|
| 124 |
+
Weingut Starfall Primitivo 2015,Italy,Primitivo,Weingut Starfall,93,52.0
|
| 125 |
+
Domaine Cedar Falls Tempranillo 2016,Spain,Tempranillo,Domaine Cedar Falls,82,18.0
|
| 126 |
+
Casa Sierra Pinot Noir 2021,US,Pinot Noir,Casa Sierra,90,34.0
|
| 127 |
+
Vineyard Bella Notte Cabernet Sauvignon 2023,Argentina,Cabernet Sauvignon,Vineyard Bella Notte,96,38.0
|
| 128 |
+
Vineyard Golden Valley Pinot Noir 2023,US,Pinot Noir,Vineyard Golden Valley,84,19.0
|
| 129 |
+
Quinta Crystal Lake Chardonnay 2022,France,Chardonnay,Quinta Crystal Lake,85,12.0
|
| 130 |
+
Casa Starfall Merlot 2021,Chile,Merlot,Casa Starfall,88,24.0
|
| 131 |
+
Tenuta Crystal Lake Monastrell 2021,Spain,Monastrell,Tenuta Crystal Lake,85,28.0
|
| 132 |
+
Vineyard Oak Hill Barbera 2017,Italy,Barbera,Vineyard Oak Hill,81,15.0
|
| 133 |
+
Estate San Pietro Tempranillo 2022,Spain,Tempranillo,Estate San Pietro,88,24.0
|
| 134 |
+
Bodega La Rosa Barbera 2022,Italy,Barbera,Bodega La Rosa,83,7.0
|
| 135 |
+
Domaine Golden Valley Alvarinho 2023,Portugal,Alvarinho,Domaine Golden Valley,89,27.0
|
| 136 |
+
Cantina Starfall Cabernet Sauvignon 2015,France,Cabernet Sauvignon,Cantina Starfall,84,24.0
|
| 137 |
+
Tenuta La Rosa Pinot Noir 2021,US,Pinot Noir,Tenuta La Rosa,94,52.0
|
| 138 |
+
Château del Monte Grüner Veltliner 2020,Austria,Grüner Veltliner,Château del Monte,84,19.0
|
| 139 |
+
Tenuta Moonlight Alvarinho 2021,Portugal,Alvarinho,Tenuta Moonlight,86,17.0
|
| 140 |
+
Vineyard Thunder Ridge Garnacha 2018,Spain,Garnacha,Vineyard Thunder Ridge,91,19.0
|
| 141 |
+
Weingut Cedar Falls Verdejo 2019,Spain,Verdejo,Weingut Cedar Falls,83,12.0
|
| 142 |
+
Bodega La Rosa Zinfandel 2022,US,Zinfandel,Bodega La Rosa,88,36.0
|
| 143 |
+
Weingut Cedar Falls Müller-Thurgau 2019,Germany,Müller-Thurgau,Weingut Cedar Falls,93,39.0
|
| 144 |
+
Vineyard Crystal Lake Barbera 2020,Italy,Barbera,Vineyard Crystal Lake,81,17.0
|
| 145 |
+
Vineyard Sierra Monastrell 2015,Spain,Monastrell,Vineyard Sierra,88,20.0
|
| 146 |
+
Weingut El Dorado Tempranillo 2020,Spain,Tempranillo,Weingut El Dorado,89,41.0
|
| 147 |
+
Bodega San Pietro Nebbiolo 2015,Italy,Nebbiolo,Bodega San Pietro,91,39.0
|
| 148 |
+
Bodega La Rosa Merlot 2019,France,Merlot,Bodega La Rosa,83,10.0
|
| 149 |
+
Casa Stone Creek Merlot 2023,France,Merlot,Casa Stone Creek,82,8.0
|
| 150 |
+
Cantina Pacific Ridge Monastrell 2020,Spain,Monastrell,Cantina Pacific Ridge,90,36.0
|
| 151 |
+
Tenuta Oak Hill Cabernet Sauvignon 2023,Argentina,Cabernet Sauvignon,Tenuta Oak Hill,89,34.0
|
| 152 |
+
Cantina Stone Creek Merlot 2019,France,Merlot,Cantina Stone Creek,89,18.0
|
| 153 |
+
Château Thunder Ridge Monastrell 2023,Spain,Monastrell,Château Thunder Ridge,89,16.0
|
| 154 |
+
Cantina Pacific Ridge Syrah 2021,France,Syrah,Cantina Pacific Ridge,85,8.0
|
| 155 |
+
Cantina San Pietro Sangiovese 2016,Italy,Sangiovese,Cantina San Pietro,88,32.0
|
| 156 |
+
Casa River Bend Primitivo 2017,Italy,Primitivo,Casa River Bend,89,19.0
|
| 157 |
+
Weingut del Monte Carmenère 2020,Chile,Carmenère,Weingut del Monte,85,23.0
|
| 158 |
+
Domaine Stone Creek Barbera 2023,Italy,Barbera,Domaine Stone Creek,95,66.0
|
| 159 |
+
Domaine Cedar Falls Cabernet Sauvignon 2016,Australia,Cabernet Sauvignon,Domaine Cedar Falls,89,15.0
|
| 160 |
+
Estate El Dorado Merlot 2017,US,Merlot,Estate El Dorado,83,17.0
|
| 161 |
+
Tenuta Crystal Lake Port 2018,Portugal,Port,Tenuta Crystal Lake,90,24.0
|
| 162 |
+
Quinta du Soleil Torrontés 2019,Argentina,Torrontés,Quinta du Soleil,84,11.0
|
| 163 |
+
Bodega San Pietro Cabernet Sauvignon 2015,Chile,Cabernet Sauvignon,Bodega San Pietro,91,48.0
|
| 164 |
+
Estate du Soleil Pinot Grigio 2017,Italy,Pinot Grigio,Estate du Soleil,92,42.0
|
| 165 |
+
Domaine Iron Gate Pinot Noir 2022,France,Pinot Noir,Domaine Iron Gate,84,21.0
|
| 166 |
+
Tenuta Thunder Ridge Baga 2015,Portugal,Baga,Tenuta Thunder Ridge,91,36.0
|
| 167 |
+
Château del Monte Merlot 2022,US,Merlot,Château del Monte,89,26.0
|
| 168 |
+
Cantina La Rosa Cabernet Sauvignon 2016,Argentina,Cabernet Sauvignon,Cantina La Rosa,91,39.0
|
| 169 |
+
Quinta Starfall Pinot Noir 2020,France,Pinot Noir,Quinta Starfall,95,26.0
|
| 170 |
+
Quinta River Bend Syrah 2016,France,Syrah,Quinta River Bend,87,23.0
|
| 171 |
+
Casa Bella Notte Touriga Nacional 2021,Portugal,Touriga Nacional,Casa Bella Notte,84,24.0
|
| 172 |
+
Vineyard River Bend Garnacha 2016,Spain,Garnacha,Vineyard River Bend,84,20.0
|
| 173 |
+
Bodega Iron Gate Cabernet Sauvignon 2016,France,Cabernet Sauvignon,Bodega Iron Gate,84,18.0
|
| 174 |
+
Estate Verde Sangiovese 2023,Italy,Sangiovese,Estate Verde,87,10.0
|
| 175 |
+
Vineyard Stone Creek Primitivo 2021,Italy,Primitivo,Vineyard Stone Creek,89,32.0
|
| 176 |
+
Estate San Pietro Carmenère 2023,Chile,Carmenère,Estate San Pietro,89,40.0
|
| 177 |
+
Casa Stone Creek Barbera 2016,Italy,Barbera,Casa Stone Creek,91,21.0
|
| 178 |
+
Casa Thunder Ridge Baga 2023,Portugal,Baga,Casa Thunder Ridge,88,19.0
|
| 179 |
+
Weingut Golden Valley Pinot Grigio 2020,Italy,Pinot Grigio,Weingut Golden Valley,93,21.0
|
| 180 |
+
Bodega du Soleil Nebbiolo 2016,Italy,Nebbiolo,Bodega du Soleil,86,20.0
|
| 181 |
+
Bodega Stone Creek Pinot Noir 2019,US,Pinot Noir,Bodega Stone Creek,98,47.0
|
| 182 |
+
Bodega Alta Vista Merlot 2015,US,Merlot,Bodega Alta Vista,90,38.0
|
| 183 |
+
Quinta Cedar Falls Chardonnay 2021,US,Chardonnay,Quinta Cedar Falls,84,16.0
|
| 184 |
+
Weingut Crystal Lake Syrah 2022,France,Syrah,Weingut Crystal Lake,83,12.0
|
| 185 |
+
Quinta del Monte Monastrell 2015,Spain,Monastrell,Quinta del Monte,89,17.0
|
| 186 |
+
Weingut Golden Valley Nebbiolo 2016,Italy,Nebbiolo,Weingut Golden Valley,87,31.0
|
| 187 |
+
Tenuta Moonlight Barbera 2023,Italy,Barbera,Tenuta Moonlight,90,21.0
|
| 188 |
+
Château River Bend Bonarda 2015,Argentina,Bonarda,Château River Bend,89,23.0
|
| 189 |
+
Quinta Oak Hill Tempranillo 2021,Spain,Tempranillo,Quinta Oak Hill,87,30.0
|
| 190 |
+
Quinta Cedar Falls Merlot 2020,France,Merlot,Quinta Cedar Falls,84,9.0
|
| 191 |
+
Casa La Rosa Sangiovese 2021,Italy,Sangiovese,Casa La Rosa,81,15.0
|
| 192 |
+
Domaine Moonlight Sauvignon Blanc 2016,Chile,Sauvignon Blanc,Domaine Moonlight,86,19.0
|
| 193 |
+
Bodega El Dorado Garnacha 2016,Spain,Garnacha,Bodega El Dorado,91,43.0
|
| 194 |
+
Domaine Alta Vista Nebbiolo 2022,Italy,Nebbiolo,Domaine Alta Vista,88,14.0
|
| 195 |
+
Quinta Thunder Ridge Verdejo 2020,Spain,Verdejo,Quinta Thunder Ridge,83,20.0
|
| 196 |
+
Cantina Pacific Ridge Sauvignon Blanc 2019,Chile,Sauvignon Blanc,Cantina Pacific Ridge,88,13.0
|
| 197 |
+
Cantina del Monte Monastrell 2015,Spain,Monastrell,Cantina del Monte,89,26.0
|
| 198 |
+
Domaine Thunder Ridge Cabernet Sauvignon 2023,France,Cabernet Sauvignon,Domaine Thunder Ridge,84,17.0
|
| 199 |
+
Château Cedar Falls Syrah 2018,France,Syrah,Château Cedar Falls,88,30.0
|
| 200 |
+
Cantina San Pietro Merlot 2020,France,Merlot,Cantina San Pietro,88,31.0
|
| 201 |
+
Tenuta Cedar Falls Grüner Veltliner 2022,Austria,Grüner Veltliner,Tenuta Cedar Falls,83,13.0
|
| 202 |
+
Weingut Oak Hill Verdejo 2021,Spain,Verdejo,Weingut Oak Hill,89,19.0
|
| 203 |
+
Estate La Rosa Baga 2020,Portugal,Baga,Estate La Rosa,90,22.0
|
| 204 |
+
Quinta Verde Barbera 2020,Italy,Barbera,Quinta Verde,92,33.0
|
| 205 |
+
Vineyard Verde Nebbiolo 2016,Italy,Nebbiolo,Vineyard Verde,92,47.0
|
| 206 |
+
Bodega Moonlight Merlot 2016,France,Merlot,Bodega Moonlight,82,17.0
|
| 207 |
+
Weingut Alta Vista Zinfandel 2018,US,Zinfandel,Weingut Alta Vista,84,11.0
|
| 208 |
+
Bodega La Rosa Merlot 2019,France,Merlot,Bodega La Rosa,90,30.0
|
| 209 |
+
Casa del Monte Malbec 2020,Argentina,Malbec,Casa del Monte,90,32.0
|
| 210 |
+
Bodega Alta Vista Syrah 2017,Chile,Syrah,Bodega Alta Vista,90,20.0
|
| 211 |
+
Tenuta Cedar Falls Cabernet Sauvignon 2019,US,Cabernet Sauvignon,Tenuta Cedar Falls,100,56.0
|
| 212 |
+
Cantina Bella Notte Tinto Roriz 2020,Portugal,Tinto Roriz,Cantina Bella Notte,90,21.0
|
| 213 |
+
Weingut Oak Hill Merlot 2023,US,Merlot,Weingut Oak Hill,92,51.0
|
| 214 |
+
Bodega Sierra Garnacha 2015,Spain,Garnacha,Bodega Sierra,91,46.0
|
| 215 |
+
Casa San Pietro Chardonnay 2019,US,Chardonnay,Casa San Pietro,90,27.0
|
| 216 |
+
Bodega River Bend Nebbiolo 2016,Italy,Nebbiolo,Bodega River Bend,86,22.0
|
| 217 |
+
Château River Bend Pinot Noir 2015,Germany,Pinot Noir,Château River Bend,91,47.0
|
| 218 |
+
Estate El Dorado Cabernet Sauvignon 2015,France,Cabernet Sauvignon,Estate El Dorado,84,20.0
|
| 219 |
+
Bodega Verde Chardonnay 2015,France,Chardonnay,Bodega Verde,87,31.0
|
| 220 |
+
Cantina Cedar Falls Merlot 2015,France,Merlot,Cantina Cedar Falls,86,18.0
|
| 221 |
+
Casa Thunder Ridge Shiraz 2023,Australia,Shiraz,Casa Thunder Ridge,88,25.0
|
| 222 |
+
Tenuta River Bend Cabernet Sauvignon 2022,France,Cabernet Sauvignon,Tenuta River Bend,97,34.0
|
| 223 |
+
Casa Crystal Lake Barbera 2018,Italy,Barbera,Casa Crystal Lake,80,12.0
|
| 224 |
+
Tenuta Crystal Lake Chardonnay 2021,US,Chardonnay,Tenuta Crystal Lake,90,31.0
|
| 225 |
+
Casa Starfall Sangiovese 2023,Italy,Sangiovese,Casa Starfall,81,16.0
|
| 226 |
+
Cantina del Monte Baga 2021,Portugal,Baga,Cantina del Monte,86,19.0
|
| 227 |
+
Domaine Stone Creek Zweigelt 2018,Austria,Zweigelt,Domaine Stone Creek,92,42.0
|
| 228 |
+
Estate Verde Cabernet Sauvignon 2015,US,Cabernet Sauvignon,Estate Verde,88,34.0
|
| 229 |
+
Cantina Iron Gate Cabernet Sauvignon 2017,France,Cabernet Sauvignon,Cantina Iron Gate,83,17.0
|
| 230 |
+
Château Pacific Ridge Malbec 2018,Argentina,Malbec,Château Pacific Ridge,85,26.0
|
| 231 |
+
Weingut Moonlight Nebbiolo 2021,Italy,Nebbiolo,Weingut Moonlight,90,38.0
|
| 232 |
+
Tenuta Pacific Ridge Welschriesling 2020,Austria,Welschriesling,Tenuta Pacific Ridge,85,11.0
|
| 233 |
+
Domaine Stone Creek Carmenère 2021,Chile,Carmenère,Domaine Stone Creek,88,31.0
|
| 234 |
+
Bodega Iron Gate Merlot 2022,Chile,Merlot,Bodega Iron Gate,88,32.0
|
| 235 |
+
Vineyard La Rosa Syrah 2021,France,Syrah,Vineyard La Rosa,85,9.0
|
| 236 |
+
Domaine Golden Valley Pinot Noir 2019,US,Pinot Noir,Domaine Golden Valley,96,47.0
|
| 237 |
+
Cantina Stone Creek Syrah 2022,France,Syrah,Cantina Stone Creek,90,32.0
|
| 238 |
+
Château La Rosa Pinot Grigio 2021,Italy,Pinot Grigio,Château La Rosa,80,18.0
|
| 239 |
+
Quinta Cedar Falls Pinot Noir 2015,France,Pinot Noir,Quinta Cedar Falls,88,30.0
|
| 240 |
+
Vineyard Crystal Lake Nebbiolo 2015,Italy,Nebbiolo,Vineyard Crystal Lake,85,19.0
|
| 241 |
+
Domaine Crystal Lake Zinfandel 2017,US,Zinfandel,Domaine Crystal Lake,91,44.0
|
| 242 |
+
Domaine du Soleil Albariño 2017,Spain,Albariño,Domaine du Soleil,84,12.0
|
| 243 |
+
Weingut Cedar Falls Albariño 2018,Spain,Albariño,Weingut Cedar Falls,87,25.0
|
| 244 |
+
Tenuta San Pietro Zweigelt 2017,Austria,Zweigelt,Tenuta San Pietro,90,42.0
|
| 245 |
+
Domaine Golden Valley Merlot 2020,Chile,Merlot,Domaine Golden Valley,91,28.0
|
| 246 |
+
Bodega Alta Vista Merlot 2020,US,Merlot,Bodega Alta Vista,83,23.0
|
| 247 |
+
Tenuta Iron Gate Tempranillo 2015,Spain,Tempranillo,Tenuta Iron Gate,86,31.0
|
| 248 |
+
Casa Verde Syrah 2016,France,Syrah,Casa Verde,86,22.0
|
| 249 |
+
Casa River Bend Barbera 2021,Italy,Barbera,Casa River Bend,85,26.0
|
| 250 |
+
Domaine Cedar Falls Malbec 2022,Argentina,Malbec,Domaine Cedar Falls,95,28.0
|
| 251 |
+
Casa Crystal Lake Chardonnay 2017,US,Chardonnay,Casa Crystal Lake,89,24.0
|
| 252 |
+
Château San Pietro Port 2023,Portugal,Port,Château San Pietro,82,22.0
|
| 253 |
+
Tenuta Stone Creek Nebbiolo 2023,Italy,Nebbiolo,Tenuta Stone Creek,91,30.0
|
| 254 |
+
Casa Sierra Carmenère 2017,Chile,Carmenère,Casa Sierra,96,39.0
|
| 255 |
+
Bodega Crystal Lake Merlot 2017,US,Merlot,Bodega Crystal Lake,92,38.0
|
| 256 |
+
Quinta del Monte Primitivo 2015,Italy,Primitivo,Quinta del Monte,81,21.0
|
| 257 |
+
Quinta River Bend Primitivo 2015,Italy,Primitivo,Quinta River Bend,86,13.0
|
| 258 |
+
Cantina El Dorado Verdejo 2021,Spain,Verdejo,Cantina El Dorado,93,38.0
|
| 259 |
+
Vineyard Iron Gate Chardonnay 2022,France,Chardonnay,Vineyard Iron Gate,85,15.0
|
| 260 |
+
Estate Stone Creek Primitivo 2021,Italy,Primitivo,Estate Stone Creek,89,25.0
|
| 261 |
+
Tenuta Cedar Falls Pinot Grigio 2016,Italy,Pinot Grigio,Tenuta Cedar Falls,91,29.0
|
| 262 |
+
Vineyard Thunder Ridge Pinot Noir 2021,France,Pinot Noir,Vineyard Thunder Ridge,84,7.0
|
| 263 |
+
Estate Bella Notte Nebbiolo 2017,Italy,Nebbiolo,Estate Bella Notte,87,34.0
|
| 264 |
+
Cantina du Soleil Verdejo 2016,Spain,Verdejo,Cantina du Soleil,80,22.0
|
| 265 |
+
Quinta Stone Creek Müller-Thurgau 2015,Germany,Müller-Thurgau,Quinta Stone Creek,83,13.0
|
| 266 |
+
Cantina Pacific Ridge Barbera 2023,Italy,Barbera,Cantina Pacific Ridge,86,26.0
|
| 267 |
+
Estate Oak Hill Sangiovese 2020,Italy,Sangiovese,Estate Oak Hill,83,21.0
|
| 268 |
+
Casa Pacific Ridge Sangiovese 2016,Italy,Sangiovese,Casa Pacific Ridge,94,40.0
|
| 269 |
+
Quinta Thunder Ridge Merlot 2016,France,Merlot,Quinta Thunder Ridge,82,18.0
|
| 270 |
+
Estate Starfall Sangiovese 2020,Italy,Sangiovese,Estate Starfall,86,22.0
|
| 271 |
+
Château del Monte Port 2015,Portugal,Port,Château del Monte,88,26.0
|
| 272 |
+
Bodega Thunder Ridge Pinot Grigio 2023,Italy,Pinot Grigio,Bodega Thunder Ridge,93,49.0
|
| 273 |
+
Quinta Pacific Ridge Primitivo 2020,Italy,Primitivo,Quinta Pacific Ridge,82,14.0
|
| 274 |
+
Weingut Iron Gate Verdejo 2015,Spain,Verdejo,Weingut Iron Gate,92,40.0
|
| 275 |
+
Château Thunder Ridge Chardonnay 2022,France,Chardonnay,Château Thunder Ridge,88,36.0
|
| 276 |
+
Quinta Iron Gate Syrah 2017,France,Syrah,Quinta Iron Gate,84,21.0
|
| 277 |
+
Tenuta del Monte Verdejo 2016,Spain,Verdejo,Tenuta del Monte,89,33.0
|
| 278 |
+
Tenuta River Bend Barbera 2023,Italy,Barbera,Tenuta River Bend,88,17.0
|
| 279 |
+
Château Verde Tinto Roriz 2023,Portugal,Tinto Roriz,Château Verde,85,25.0
|
| 280 |
+
Vineyard Golden Valley Pinot Grigio 2017,Italy,Pinot Grigio,Vineyard Golden Valley,88,35.0
|
| 281 |
+
Weingut Thunder Ridge Verdejo 2022,Spain,Verdejo,Weingut Thunder Ridge,86,16.0
|
| 282 |
+
Weingut Pacific Ridge Nebbiolo 2018,Italy,Nebbiolo,Weingut Pacific Ridge,88,18.0
|
| 283 |
+
Weingut Pacific Ridge Zinfandel 2016,US,Zinfandel,Weingut Pacific Ridge,90,24.0
|
| 284 |
+
Estate Verde Verdejo 2019,Spain,Verdejo,Estate Verde,94,44.0
|
| 285 |
+
Weingut Iron Gate Sangiovese 2018,Italy,Sangiovese,Weingut Iron Gate,83,15.0
|
| 286 |
+
Weingut Verde Primitivo 2016,Italy,Primitivo,Weingut Verde,96,39.0
|
| 287 |
+
Casa El Dorado Merlot 2018,US,Merlot,Casa El Dorado,80,8.0
|
| 288 |
+
Bodega du Soleil Barbera 2023,Italy,Barbera,Bodega du Soleil,87,19.0
|
| 289 |
+
Cantina Iron Gate Riesling 2018,Austria,Riesling,Cantina Iron Gate,90,34.0
|
| 290 |
+
Domaine Crystal Lake Alvarinho 2018,Portugal,Alvarinho,Domaine Crystal Lake,89,26.0
|
| 291 |
+
Bodega del Monte Tempranillo 2021,Spain,Tempranillo,Bodega del Monte,85,18.0
|
| 292 |
+
Weingut del Monte Port 2015,Portugal,Port,Weingut del Monte,87,36.0
|
| 293 |
+
Weingut Cedar Falls Syrah 2023,France,Syrah,Weingut Cedar Falls,86,20.0
|
| 294 |
+
Tenuta San Pietro Garnacha 2020,Spain,Garnacha,Tenuta San Pietro,85,21.0
|
| 295 |
+
Château Golden Valley Barbera 2019,Italy,Barbera,Château Golden Valley,91,41.0
|
| 296 |
+
Vineyard River Bend Garnacha 2023,Spain,Garnacha,Vineyard River Bend,89,26.0
|
| 297 |
+
Bodega Iron Gate Merlot 2020,France,Merlot,Bodega Iron Gate,85,15.0
|
| 298 |
+
Weingut Golden Valley Shiraz 2019,Australia,Shiraz,Weingut Golden Valley,91,24.0
|
| 299 |
+
Tenuta del Monte Verdejo 2016,Spain,Verdejo,Tenuta del Monte,89,19.0
|
| 300 |
+
Weingut San Pietro Garnacha 2019,Spain,Garnacha,Weingut San Pietro,91,31.0
|
| 301 |
+
Bodega Cedar Falls Pinot Noir 2020,France,Pinot Noir,Bodega Cedar Falls,90,19.0
|
| 302 |
+
Tenuta El Dorado Syrah 2016,France,Syrah,Tenuta El Dorado,84,26.0
|
| 303 |
+
Quinta San Pietro Verdejo 2015,Spain,Verdejo,Quinta San Pietro,85,14.0
|
| 304 |
+
Bodega Golden Valley Syrah 2023,Argentina,Syrah,Bodega Golden Valley,90,24.0
|
| 305 |
+
Casa Cedar Falls Pinot Noir 2015,France,Pinot Noir,Casa Cedar Falls,90,36.0
|
| 306 |
+
Casa Cedar Falls Verdejo 2019,Spain,Verdejo,Casa Cedar Falls,87,22.0
|
| 307 |
+
Tenuta Crystal Lake Zinfandel 2016,US,Zinfandel,Tenuta Crystal Lake,88,14.0
|
| 308 |
+
Château La Rosa Pinot Grigio 2022,Italy,Pinot Grigio,Château La Rosa,93,46.0
|
| 309 |
+
Vineyard Stone Creek Barbera 2021,Italy,Barbera,Vineyard Stone Creek,85,9.0
|
| 310 |
+
Casa Verde Merlot 2020,France,Merlot,Casa Verde,90,30.0
|
| 311 |
+
Tenuta du Soleil Primitivo 2015,Italy,Primitivo,Tenuta du Soleil,87,16.0
|
| 312 |
+
Casa Oak Hill Blaufränkisch 2018,Austria,Blaufränkisch,Casa Oak Hill,87,26.0
|
| 313 |
+
Domaine del Monte Pinot Grigio 2021,Italy,Pinot Grigio,Domaine del Monte,92,22.0
|
| 314 |
+
Quinta del Monte Cabernet Sauvignon 2022,US,Cabernet Sauvignon,Quinta del Monte,91,21.0
|
| 315 |
+
Cantina El Dorado Tempranillo 2023,Spain,Tempranillo,Cantina El Dorado,91,21.0
|
| 316 |
+
Tenuta Crystal Lake Sangiovese 2020,Italy,Sangiovese,Tenuta Crystal Lake,93,34.0
|
| 317 |
+
Casa El Dorado Monastrell 2021,Spain,Monastrell,Casa El Dorado,88,25.0
|
| 318 |
+
Bodega River Bend Chardonnay 2023,France,Chardonnay,Bodega River Bend,90,34.0
|
| 319 |
+
Casa Golden Valley Monastrell 2021,Spain,Monastrell,Casa Golden Valley,86,29.0
|
| 320 |
+
Cantina El Dorado Cabernet Sauvignon 2018,France,Cabernet Sauvignon,Cantina El Dorado,89,29.0
|
| 321 |
+
Casa River Bend Pinot Noir 2021,France,Pinot Noir,Casa River Bend,87,33.0
|
| 322 |
+
Estate La Rosa Garnacha 2022,Spain,Garnacha,Estate La Rosa,88,20.0
|
| 323 |
+
Château Sierra Malbec 2021,Argentina,Malbec,Château Sierra,90,36.0
|
| 324 |
+
Quinta Starfall Merlot 2018,US,Merlot,Quinta Starfall,84,6.0
|
| 325 |
+
Tenuta Bella Notte Monastrell 2016,Spain,Monastrell,Tenuta Bella Notte,96,45.0
|
| 326 |
+
Tenuta Oak Hill Zinfandel 2018,US,Zinfandel,Tenuta Oak Hill,83,25.0
|
| 327 |
+
Estate Pacific Ridge Monastrell 2019,Spain,Monastrell,Estate Pacific Ridge,83,16.0
|
| 328 |
+
Cantina Golden Valley Merlot 2018,France,Merlot,Cantina Golden Valley,92,39.0
|
| 329 |
+
Bodega du Soleil Merlot 2019,France,Merlot,Bodega du Soleil,91,26.0
|
| 330 |
+
Bodega Bella Notte Verdejo 2020,Spain,Verdejo,Bodega Bella Notte,90,32.0
|
| 331 |
+
Estate Sierra Primitivo 2022,Italy,Primitivo,Estate Sierra,90,39.0
|
| 332 |
+
Estate Alta Vista Silvaner 2017,Germany,Silvaner,Estate Alta Vista,87,25.0
|
| 333 |
+
Château Moonlight Zinfandel 2015,US,Zinfandel,Château Moonlight,84,18.0
|
| 334 |
+
Château River Bend Malbec 2017,Argentina,Malbec,Château River Bend,88,37.0
|
| 335 |
+
Tenuta Moonlight Torrontés 2022,Argentina,Torrontés,Tenuta Moonlight,85,7.0
|
| 336 |
+
Cantina Iron Gate Syrah 2015,France,Syrah,Cantina Iron Gate,91,43.0
|
| 337 |
+
Weingut Starfall Primitivo 2019,Italy,Primitivo,Weingut Starfall,87,15.0
|
| 338 |
+
Domaine San Pietro Barbera 2023,Italy,Barbera,Domaine San Pietro,84,26.0
|
| 339 |
+
Estate Sierra Nebbiolo 2021,Italy,Nebbiolo,Estate Sierra,86,19.0
|
| 340 |
+
Tenuta Pacific Ridge Barbera 2016,Italy,Barbera,Tenuta Pacific Ridge,89,24.0
|
| 341 |
+
Casa Iron Gate Cabernet Sauvignon 2015,US,Cabernet Sauvignon,Casa Iron Gate,85,11.0
|
| 342 |
+
Estate Crystal Lake Pinot Noir 2016,US,Pinot Noir,Estate Crystal Lake,84,17.0
|
| 343 |
+
Quinta Iron Gate Carmenère 2019,Chile,Carmenère,Quinta Iron Gate,88,25.0
|
| 344 |
+
Casa Crystal Lake Sangiovese 2015,Italy,Sangiovese,Casa Crystal Lake,88,26.0
|
| 345 |
+
Bodega Oak Hill Pinot Grigio 2016,Italy,Pinot Grigio,Bodega Oak Hill,85,7.0
|
| 346 |
+
Vineyard Starfall Syrah 2020,France,Syrah,Vineyard Starfall,86,20.0
|
| 347 |
+
Domaine Moonlight Pinot Noir 2020,France,Pinot Noir,Domaine Moonlight,88,34.0
|
| 348 |
+
Quinta Thunder Ridge Barbera 2021,Italy,Barbera,Quinta Thunder Ridge,82,8.0
|
| 349 |
+
Cantina Iron Gate Gewürztraminer 2018,Germany,Gewürztraminer,Cantina Iron Gate,82,8.0
|
| 350 |
+
Vineyard La Rosa Merlot 2019,France,Merlot,Vineyard La Rosa,85,19.0
|
| 351 |
+
Bodega Oak Hill Touriga Nacional 2020,Portugal,Touriga Nacional,Bodega Oak Hill,87,11.0
|
| 352 |
+
Estate Sierra Chardonnay 2016,France,Chardonnay,Estate Sierra,89,15.0
|
| 353 |
+
Casa River Bend Nebbiolo 2016,Italy,Nebbiolo,Casa River Bend,93,38.0
|
| 354 |
+
Estate Oak Hill Pinot Grigio 2015,Italy,Pinot Grigio,Estate Oak Hill,91,37.0
|
| 355 |
+
Casa El Dorado Merlot 2023,France,Merlot,Casa El Dorado,87,31.0
|
| 356 |
+
Weingut Iron Gate Barbera 2017,Italy,Barbera,Weingut Iron Gate,87,14.0
|
| 357 |
+
Domaine Stone Creek Barbera 2019,Italy,Barbera,Domaine Stone Creek,83,12.0
|
| 358 |
+
Domaine Verde Silvaner 2019,Germany,Silvaner,Domaine Verde,87,20.0
|
| 359 |
+
Estate Cedar Falls Barbera 2020,Italy,Barbera,Estate Cedar Falls,86,19.0
|
| 360 |
+
Tenuta Iron Gate Syrah 2020,France,Syrah,Tenuta Iron Gate,89,18.0
|
| 361 |
+
Cantina Crystal Lake Barbera 2018,Italy,Barbera,Cantina Crystal Lake,84,20.0
|
| 362 |
+
Domaine Crystal Lake Cabernet Sauvignon 2018,France,Cabernet Sauvignon,Domaine Crystal Lake,90,38.0
|
| 363 |
+
Château Cedar Falls Verdejo 2018,Spain,Verdejo,Château Cedar Falls,94,34.0
|
| 364 |
+
Vineyard Iron Gate Cabernet Sauvignon 2017,France,Cabernet Sauvignon,Vineyard Iron Gate,87,23.0
|
| 365 |
+
Vineyard Oak Hill Pinot Noir 2016,US,Pinot Noir,Vineyard Oak Hill,89,18.0
|
| 366 |
+
Casa River Bend Syrah 2023,France,Syrah,Casa River Bend,90,29.0
|
| 367 |
+
Quinta La Rosa Pinot Grigio 2016,Italy,Pinot Grigio,Quinta La Rosa,86,27.0
|
| 368 |
+
Quinta Oak Hill Alvarinho 2020,Portugal,Alvarinho,Quinta Oak Hill,88,20.0
|
| 369 |
+
Tenuta Moonlight Silvaner 2023,Germany,Silvaner,Tenuta Moonlight,88,12.0
|
| 370 |
+
Cantina Crystal Lake Verdejo 2023,Spain,Verdejo,Cantina Crystal Lake,88,18.0
|
| 371 |
+
Domaine San Pietro Sangiovese 2017,Italy,Sangiovese,Domaine San Pietro,84,14.0
|
| 372 |
+
Cantina Stone Creek Cabernet Sauvignon 2022,France,Cabernet Sauvignon,Cantina Stone Creek,88,21.0
|
| 373 |
+
Domaine du Soleil Barbera 2020,Italy,Barbera,Domaine du Soleil,89,22.0
|
| 374 |
+
Casa Alta Vista Pinot Noir 2023,US,Pinot Noir,Casa Alta Vista,93,56.0
|
| 375 |
+
Vineyard Alta Vista Primitivo 2017,Italy,Primitivo,Vineyard Alta Vista,91,31.0
|
| 376 |
+
Tenuta Cedar Falls Zinfandel 2021,US,Zinfandel,Tenuta Cedar Falls,96,46.0
|
| 377 |
+
Domaine Crystal Lake Pinot Noir 2016,France,Pinot Noir,Domaine Crystal Lake,84,17.0
|
| 378 |
+
Cantina San Pietro Baga 2019,Portugal,Baga,Cantina San Pietro,91,23.0
|
| 379 |
+
Quinta Oak Hill Zinfandel 2021,US,Zinfandel,Quinta Oak Hill,88,28.0
|
| 380 |
+
Bodega Pacific Ridge Monastrell 2016,Spain,Monastrell,Bodega Pacific Ridge,96,41.0
|
| 381 |
+
Bodega Stone Creek Chardonnay 2017,US,Chardonnay,Bodega Stone Creek,84,10.0
|
| 382 |
+
Vineyard Alta Vista Albariño 2022,Spain,Albariño,Vineyard Alta Vista,84,19.0
|
| 383 |
+
Bodega Alta Vista Pinot Noir 2020,US,Pinot Noir,Bodega Alta Vista,85,18.0
|
| 384 |
+
Château Iron Gate Syrah 2017,Argentina,Syrah,Château Iron Gate,80,10.0
|
| 385 |
+
Cantina River Bend Barbera 2022,Italy,Barbera,Cantina River Bend,85,23.0
|
| 386 |
+
Château El Dorado Merlot 2019,France,Merlot,Château El Dorado,84,12.0
|
| 387 |
+
Cantina Crystal Lake Nebbiolo 2022,Italy,Nebbiolo,Cantina Crystal Lake,88,22.0
|
| 388 |
+
Casa Stone Creek Tempranillo 2023,Spain,Tempranillo,Casa Stone Creek,89,27.0
|
| 389 |
+
Tenuta River Bend Malbec 2016,Argentina,Malbec,Tenuta River Bend,95,54.0
|
| 390 |
+
Cantina Sierra Pinot Noir 2020,US,Pinot Noir,Cantina Sierra,91,35.0
|
| 391 |
+
Tenuta Bella Notte Carmenère 2020,Chile,Carmenère,Tenuta Bella Notte,85,23.0
|
| 392 |
+
Bodega Bella Notte Syrah 2018,Chile,Syrah,Bodega Bella Notte,84,15.0
|
| 393 |
+
Casa Alta Vista Syrah 2020,Argentina,Syrah,Casa Alta Vista,89,22.0
|
| 394 |
+
Casa San Pietro Zweigelt 2017,Austria,Zweigelt,Casa San Pietro,82,12.0
|
| 395 |
+
Bodega Verde Silvaner 2018,Germany,Silvaner,Bodega Verde,95,67.0
|
| 396 |
+
Vineyard Iron Gate Pinot Grigio 2017,Italy,Pinot Grigio,Vineyard Iron Gate,92,50.0
|
| 397 |
+
Domaine La Rosa Monastrell 2021,Spain,Monastrell,Domaine La Rosa,86,20.0
|
| 398 |
+
Cantina Iron Gate Monastrell 2020,Spain,Monastrell,Cantina Iron Gate,81,25.0
|
| 399 |
+
Estate La Rosa Tempranillo 2023,Spain,Tempranillo,Estate La Rosa,93,46.0
|
| 400 |
+
Estate Pacific Ridge Merlot 2020,France,Merlot,Estate Pacific Ridge,87,28.0
|
| 401 |
+
Estate del Monte Garnacha 2015,Spain,Garnacha,Estate del Monte,92,38.0
|
| 402 |
+
Bodega Cedar Falls Barbera 2022,Italy,Barbera,Bodega Cedar Falls,81,17.0
|
| 403 |
+
Bodega Pacific Ridge Barbera 2017,Italy,Barbera,Bodega Pacific Ridge,85,16.0
|
| 404 |
+
Domaine Stone Creek Sauvignon Blanc 2017,Chile,Sauvignon Blanc,Domaine Stone Creek,88,16.0
|
| 405 |
+
Vineyard La Rosa Pinot Grigio 2016,Italy,Pinot Grigio,Vineyard La Rosa,88,33.0
|
| 406 |
+
Casa Cedar Falls Barbera 2015,Italy,Barbera,Casa Cedar Falls,86,15.0
|
| 407 |
+
Vineyard Verde Pinot Grigio 2022,Italy,Pinot Grigio,Vineyard Verde,90,45.0
|
| 408 |
+
Domaine Golden Valley Barbera 2020,Italy,Barbera,Domaine Golden Valley,83,16.0
|
| 409 |
+
Bodega Verde Cabernet Sauvignon 2016,Chile,Cabernet Sauvignon,Bodega Verde,87,25.0
|
| 410 |
+
Estate Bella Notte Tempranillo 2017,Spain,Tempranillo,Estate Bella Notte,88,23.0
|
| 411 |
+
Domaine San Pietro Semillon 2017,Australia,Semillon,Domaine San Pietro,90,40.0
|
| 412 |
+
Vineyard Golden Valley Baga 2017,Portugal,Baga,Vineyard Golden Valley,90,35.0
|
| 413 |
+
Quinta Pacific Ridge Sangiovese 2015,Italy,Sangiovese,Quinta Pacific Ridge,83,15.0
|
| 414 |
+
Tenuta Oak Hill Bonarda 2019,Argentina,Bonarda,Tenuta Oak Hill,81,15.0
|
| 415 |
+
Cantina Thunder Ridge Pinot Noir 2016,US,Pinot Noir,Cantina Thunder Ridge,93,34.0
|
| 416 |
+
Bodega Oak Hill Tempranillo 2021,Spain,Tempranillo,Bodega Oak Hill,89,45.0
|
| 417 |
+
Domaine du Soleil Pinot Noir 2016,France,Pinot Noir,Domaine du Soleil,85,26.0
|
| 418 |
+
Vineyard Moonlight Nebbiolo 2019,Italy,Nebbiolo,Vineyard Moonlight,94,20.0
|
| 419 |
+
Vineyard La Rosa Merlot 2023,US,Merlot,Vineyard La Rosa,88,30.0
|
| 420 |
+
Casa Bella Notte Garnacha 2017,Spain,Garnacha,Casa Bella Notte,92,27.0
|
| 421 |
+
Domaine Pacific Ridge Albariño 2021,Spain,Albariño,Domaine Pacific Ridge,88,31.0
|
| 422 |
+
Vineyard San Pietro Pinot Noir 2022,US,Pinot Noir,Vineyard San Pietro,96,24.0
|
| 423 |
+
Bodega San Pietro Cabernet Sauvignon 2015,US,Cabernet Sauvignon,Bodega San Pietro,95,41.0
|
| 424 |
+
Casa Moonlight Cabernet Sauvignon 2019,US,Cabernet Sauvignon,Casa Moonlight,87,23.0
|
| 425 |
+
Domaine du Soleil Nebbiolo 2020,Italy,Nebbiolo,Domaine du Soleil,91,45.0
|
| 426 |
+
Quinta La Rosa Bonarda 2022,Argentina,Bonarda,Quinta La Rosa,90,29.0
|
| 427 |
+
Bodega Stone Creek Monastrell 2017,Spain,Monastrell,Bodega Stone Creek,93,29.0
|
| 428 |
+
Domaine El Dorado Chardonnay 2023,France,Chardonnay,Domaine El Dorado,84,24.0
|
| 429 |
+
Vineyard Verde Sangiovese 2017,Italy,Sangiovese,Vineyard Verde,90,24.0
|
| 430 |
+
Vineyard El Dorado Shiraz 2020,Australia,Shiraz,Vineyard El Dorado,92,43.0
|
| 431 |
+
Estate San Pietro Pinot Grigio 2023,Italy,Pinot Grigio,Estate San Pietro,80,9.0
|
| 432 |
+
Château Oak Hill Cabernet Sauvignon 2016,US,Cabernet Sauvignon,Château Oak Hill,83,17.0
|
| 433 |
+
Domaine Starfall Sauvignon Blanc 2022,Chile,Sauvignon Blanc,Domaine Starfall,80,18.0
|
| 434 |
+
Quinta El Dorado Nebbiolo 2022,Italy,Nebbiolo,Quinta El Dorado,86,21.0
|
| 435 |
+
Casa El Dorado Merlot 2017,France,Merlot,Casa El Dorado,90,47.0
|
| 436 |
+
Château Golden Valley Barbera 2015,Italy,Barbera,Château Golden Valley,94,26.0
|
| 437 |
+
Domaine Bella Notte Tinto Roriz 2023,Portugal,Tinto Roriz,Domaine Bella Notte,88,35.0
|
| 438 |
+
Bodega Sierra Blaufränkisch 2016,Austria,Blaufränkisch,Bodega Sierra,94,36.0
|
| 439 |
+
Estate Cedar Falls Nebbiolo 2016,Italy,Nebbiolo,Estate Cedar Falls,82,22.0
|
| 440 |
+
Domaine Crystal Lake Verdejo 2015,Spain,Verdejo,Domaine Crystal Lake,81,17.0
|
| 441 |
+
Estate Oak Hill Pinot Noir 2020,France,Pinot Noir,Estate Oak Hill,87,15.0
|
| 442 |
+
Bodega Crystal Lake Cabernet Sauvignon 2016,France,Cabernet Sauvignon,Bodega Crystal Lake,89,28.0
|
| 443 |
+
Domaine Starfall Nebbiolo 2020,Italy,Nebbiolo,Domaine Starfall,87,19.0
|
| 444 |
+
Domaine La Rosa Pinot Noir 2017,Germany,Pinot Noir,Domaine La Rosa,80,16.0
|
| 445 |
+
Château Bella Notte Bonarda 2020,Argentina,Bonarda,Château Bella Notte,87,31.0
|
| 446 |
+
Château Pacific Ridge Nebbiolo 2019,Italy,Nebbiolo,Château Pacific Ridge,82,22.0
|
| 447 |
+
Cantina Starfall Torrontés 2023,Argentina,Torrontés,Cantina Starfall,90,18.0
|
| 448 |
+
Domaine du Soleil Barbera 2015,Italy,Barbera,Domaine du Soleil,89,23.0
|
| 449 |
+
Estate La Rosa Torrontés 2019,Argentina,Torrontés,Estate La Rosa,84,17.0
|
| 450 |
+
Cantina Verde Shiraz 2016,Australia,Shiraz,Cantina Verde,85,6.0
|
| 451 |
+
Château Alta Vista Cabernet Sauvignon 2021,Australia,Cabernet Sauvignon,Château Alta Vista,83,18.0
|
| 452 |
+
Vineyard Alta Vista Cabernet Sauvignon 2020,Argentina,Cabernet Sauvignon,Vineyard Alta Vista,87,21.0
|
| 453 |
+
Bodega del Monte Nebbiolo 2018,Italy,Nebbiolo,Bodega del Monte,91,27.0
|
| 454 |
+
Château La Rosa Zinfandel 2019,US,Zinfandel,Château La Rosa,84,17.0
|
| 455 |
+
Casa El Dorado Merlot 2023,France,Merlot,Casa El Dorado,90,28.0
|
| 456 |
+
Casa Iron Gate Tinto Roriz 2020,Portugal,Tinto Roriz,Casa Iron Gate,85,19.0
|
| 457 |
+
Château Golden Valley Semillon 2018,Australia,Semillon,Château Golden Valley,84,12.0
|
| 458 |
+
Casa Stone Creek Pinot Grigio 2018,Italy,Pinot Grigio,Casa Stone Creek,87,21.0
|
| 459 |
+
Casa del Monte Grüner Veltliner 2018,Austria,Grüner Veltliner,Casa del Monte,83,11.0
|
| 460 |
+
Bodega Alta Vista Albariño 2018,Spain,Albariño,Bodega Alta Vista,85,20.0
|
| 461 |
+
Estate Crystal Lake Monastrell 2017,Spain,Monastrell,Estate Crystal Lake,83,16.0
|
| 462 |
+
Cantina Starfall Garnacha 2019,Spain,Garnacha,Cantina Starfall,95,61.0
|
| 463 |
+
Tenuta du Soleil Sangiovese 2023,Italy,Sangiovese,Tenuta du Soleil,88,14.0
|
| 464 |
+
Bodega Golden Valley Monastrell 2017,Spain,Monastrell,Bodega Golden Valley,85,19.0
|
| 465 |
+
Bodega San Pietro Cabernet Sauvignon 2023,Australia,Cabernet Sauvignon,Bodega San Pietro,88,12.0
|
| 466 |
+
Vineyard Crystal Lake Carmenère 2016,Chile,Carmenère,Vineyard Crystal Lake,87,26.0
|
| 467 |
+
Vineyard Iron Gate Cabernet Sauvignon 2020,France,Cabernet Sauvignon,Vineyard Iron Gate,87,12.0
|
| 468 |
+
Estate El Dorado Primitivo 2017,Italy,Primitivo,Estate El Dorado,90,41.0
|
| 469 |
+
Quinta Oak Hill Cabernet Sauvignon 2015,France,Cabernet Sauvignon,Quinta Oak Hill,91,26.0
|
| 470 |
+
Tenuta Crystal Lake Pinot Grigio 2016,Italy,Pinot Grigio,Tenuta Crystal Lake,85,29.0
|
| 471 |
+
Estate Golden Valley Chardonnay 2017,Australia,Chardonnay,Estate Golden Valley,85,10.0
|
| 472 |
+
Estate Cedar Falls Cabernet Sauvignon 2015,US,Cabernet Sauvignon,Estate Cedar Falls,86,27.0
|
| 473 |
+
Domaine du Soleil Pinot Noir 2015,France,Pinot Noir,Domaine du Soleil,80,18.0
|
| 474 |
+
Cantina Oak Hill Merlot 2020,France,Merlot,Cantina Oak Hill,81,28.0
|
| 475 |
+
Quinta El Dorado Tempranillo 2017,Spain,Tempranillo,Quinta El Dorado,93,54.0
|
| 476 |
+
Domaine La Rosa Tempranillo 2020,Spain,Tempranillo,Domaine La Rosa,94,32.0
|
| 477 |
+
Domaine Golden Valley Barbera 2022,Italy,Barbera,Domaine Golden Valley,87,11.0
|
| 478 |
+
Vineyard Alta Vista Zinfandel 2015,US,Zinfandel,Vineyard Alta Vista,90,38.0
|
| 479 |
+
Casa Starfall Nebbiolo 2019,Italy,Nebbiolo,Casa Starfall,89,38.0
|
| 480 |
+
Quinta Starfall Chardonnay 2022,US,Chardonnay,Quinta Starfall,100,40.0
|
| 481 |
+
Quinta Iron Gate Pinot Grigio 2018,Italy,Pinot Grigio,Quinta Iron Gate,92,16.0
|
| 482 |
+
Domaine Iron Gate Nebbiolo 2016,Italy,Nebbiolo,Domaine Iron Gate,87,14.0
|
| 483 |
+
Weingut La Rosa Merlot 2023,France,Merlot,Weingut La Rosa,84,22.0
|
| 484 |
+
Cantina del Monte Cabernet Sauvignon 2019,France,Cabernet Sauvignon,Cantina del Monte,81,20.0
|
| 485 |
+
Château Verde Cabernet Sauvignon 2016,France,Cabernet Sauvignon,Château Verde,88,17.0
|
| 486 |
+
Quinta El Dorado Pinot Grigio 2023,Italy,Pinot Grigio,Quinta El Dorado,84,20.0
|
| 487 |
+
Casa Iron Gate Barbera 2018,Italy,Barbera,Casa Iron Gate,82,20.0
|
| 488 |
+
Château Moonlight Tempranillo 2023,Spain,Tempranillo,Château Moonlight,85,21.0
|
| 489 |
+
Cantina Alta Vista Syrah 2017,Argentina,Syrah,Cantina Alta Vista,83,19.0
|
| 490 |
+
Vineyard Bella Notte Riesling 2017,Austria,Riesling,Vineyard Bella Notte,94,28.0
|
| 491 |
+
Domaine La Rosa Bonarda 2021,Argentina,Bonarda,Domaine La Rosa,91,32.0
|
| 492 |
+
Cantina du Soleil Verdejo 2023,Spain,Verdejo,Cantina du Soleil,87,17.0
|
| 493 |
+
Quinta Crystal Lake Touriga Nacional 2016,Portugal,Touriga Nacional,Quinta Crystal Lake,93,32.0
|
| 494 |
+
Casa Stone Creek Semillon 2021,Australia,Semillon,Casa Stone Creek,88,35.0
|
| 495 |
+
Bodega Sierra Merlot 2021,France,Merlot,Bodega Sierra,84,18.0
|
| 496 |
+
Vineyard Golden Valley Primitivo 2018,Italy,Primitivo,Vineyard Golden Valley,94,47.0
|
| 497 |
+
Château Golden Valley Barbera 2019,Italy,Barbera,Château Golden Valley,90,47.0
|
| 498 |
+
Tenuta Verde Merlot 2019,France,Merlot,Tenuta Verde,83,24.0
|
| 499 |
+
Vineyard Thunder Ridge Blaufränkisch 2016,Austria,Blaufränkisch,Vineyard Thunder Ridge,87,25.0
|
| 500 |
+
Cantina Moonlight Nebbiolo 2020,Italy,Nebbiolo,Cantina Moonlight,84,21.0
|
| 501 |
+
Casa Oak Hill Syrah 2017,Argentina,Syrah,Casa Oak Hill,82,15.0
|
| 502 |
+
Tenuta Bella Notte Baga 2015,Portugal,Baga,Tenuta Bella Notte,91,38.0
|
| 503 |
+
Tenuta Sierra Barbera 2020,Italy,Barbera,Tenuta Sierra,95,26.0
|
| 504 |
+
Château El Dorado Syrah 2020,Argentina,Syrah,Château El Dorado,82,21.0
|
| 505 |
+
Quinta Starfall Albariño 2020,Spain,Albariño,Quinta Starfall,90,28.0
|
| 506 |
+
Weingut du Soleil Cabernet Sauvignon 2021,France,Cabernet Sauvignon,Weingut du Soleil,85,23.0
|
| 507 |
+
Tenuta El Dorado Primitivo 2018,Italy,Primitivo,Tenuta El Dorado,86,20.0
|
| 508 |
+
Château Iron Gate Merlot 2017,France,Merlot,Château Iron Gate,85,22.0
|
| 509 |
+
Quinta Pacific Ridge Merlot 2019,US,Merlot,Quinta Pacific Ridge,84,17.0
|
| 510 |
+
Tenuta Cedar Falls Merlot 2019,France,Merlot,Tenuta Cedar Falls,88,32.0
|
| 511 |
+
Casa Stone Creek Merlot 2023,US,Merlot,Casa Stone Creek,84,11.0
|
| 512 |
+
Cantina La Rosa Merlot 2020,US,Merlot,Cantina La Rosa,89,26.0
|
| 513 |
+
Weingut Bella Notte Zweigelt 2017,Austria,Zweigelt,Weingut Bella Notte,87,26.0
|
| 514 |
+
Quinta Oak Hill Garnacha 2020,Spain,Garnacha,Quinta Oak Hill,87,34.0
|
| 515 |
+
Weingut River Bend Cabernet Sauvignon 2021,US,Cabernet Sauvignon,Weingut River Bend,84,26.0
|
| 516 |
+
Tenuta Golden Valley Chardonnay 2018,France,Chardonnay,Tenuta Golden Valley,85,25.0
|
| 517 |
+
Casa Pacific Ridge Zinfandel 2017,US,Zinfandel,Casa Pacific Ridge,91,47.0
|
| 518 |
+
Bodega Sierra Syrah 2023,Argentina,Syrah,Bodega Sierra,90,18.0
|
| 519 |
+
Domaine El Dorado Port 2020,Portugal,Port,Domaine El Dorado,84,28.0
|
| 520 |
+
Estate Sierra Pinot Grigio 2019,Italy,Pinot Grigio,Estate Sierra,88,29.0
|
| 521 |
+
Quinta Crystal Lake Tempranillo 2016,Spain,Tempranillo,Quinta Crystal Lake,91,38.0
|
| 522 |
+
Vineyard Moonlight Garnacha 2019,Spain,Garnacha,Vineyard Moonlight,81,22.0
|
| 523 |
+
Vineyard Crystal Lake Pinot Noir 2022,France,Pinot Noir,Vineyard Crystal Lake,90,18.0
|
| 524 |
+
Bodega Golden Valley Nebbiolo 2015,Italy,Nebbiolo,Bodega Golden Valley,85,21.0
|
| 525 |
+
Quinta Alta Vista Pinot Grigio 2022,Italy,Pinot Grigio,Quinta Alta Vista,90,27.0
|
| 526 |
+
Vineyard Oak Hill Touriga Nacional 2021,Portugal,Touriga Nacional,Vineyard Oak Hill,84,12.0
|
| 527 |
+
Estate du Soleil Silvaner 2020,Germany,Silvaner,Estate du Soleil,80,11.0
|
| 528 |
+
Tenuta El Dorado Baga 2020,Portugal,Baga,Tenuta El Dorado,81,16.0
|
| 529 |
+
Bodega La Rosa Chardonnay 2015,France,Chardonnay,Bodega La Rosa,88,24.0
|
| 530 |
+
Casa Golden Valley Cabernet Sauvignon 2021,France,Cabernet Sauvignon,Casa Golden Valley,89,28.0
|
| 531 |
+
Estate Bella Notte Cabernet Sauvignon 2017,Chile,Cabernet Sauvignon,Estate Bella Notte,84,21.0
|
| 532 |
+
Bodega Bella Notte Silvaner 2015,Germany,Silvaner,Bodega Bella Notte,90,15.0
|
| 533 |
+
Château Oak Hill Garnacha 2019,Spain,Garnacha,Château Oak Hill,81,15.0
|
| 534 |
+
Domaine du Soleil Baga 2015,Portugal,Baga,Domaine du Soleil,87,21.0
|
| 535 |
+
Weingut Iron Gate Zinfandel 2017,US,Zinfandel,Weingut Iron Gate,83,12.0
|
| 536 |
+
Casa Sierra Sangiovese 2017,Italy,Sangiovese,Casa Sierra,85,17.0
|
| 537 |
+
Weingut San Pietro Chardonnay 2016,France,Chardonnay,Weingut San Pietro,88,27.0
|
| 538 |
+
Casa Bella Notte Verdejo 2020,Spain,Verdejo,Casa Bella Notte,84,10.0
|
| 539 |
+
Tenuta Iron Gate Chardonnay 2020,US,Chardonnay,Tenuta Iron Gate,86,16.0
|
| 540 |
+
Quinta Iron Gate Sangiovese 2017,Italy,Sangiovese,Quinta Iron Gate,92,47.0
|
| 541 |
+
Weingut El Dorado Müller-Thurgau 2022,Germany,Müller-Thurgau,Weingut El Dorado,85,15.0
|
| 542 |
+
Bodega del Monte Zweigelt 2019,Austria,Zweigelt,Bodega del Monte,91,21.0
|
| 543 |
+
Château du Soleil Cabernet Sauvignon 2017,France,Cabernet Sauvignon,Château du Soleil,83,11.0
|
| 544 |
+
Quinta Sierra Pinot Noir 2016,US,Pinot Noir,Quinta Sierra,90,32.0
|
| 545 |
+
Cantina Sierra Cabernet Sauvignon 2021,France,Cabernet Sauvignon,Cantina Sierra,93,28.0
|
| 546 |
+
Bodega San Pietro Zinfandel 2017,US,Zinfandel,Bodega San Pietro,80,23.0
|
| 547 |
+
Domaine River Bend Cabernet Sauvignon 2022,US,Cabernet Sauvignon,Domaine River Bend,84,28.0
|
| 548 |
+
Estate Thunder Ridge Cabernet Sauvignon 2015,Argentina,Cabernet Sauvignon,Estate Thunder Ridge,90,21.0
|
| 549 |
+
Vineyard Cedar Falls Cabernet Sauvignon 2015,Chile,Cabernet Sauvignon,Vineyard Cedar Falls,87,22.0
|
| 550 |
+
Casa Crystal Lake Pinot Grigio 2018,Italy,Pinot Grigio,Casa Crystal Lake,89,22.0
|
| 551 |
+
Quinta San Pietro Zweigelt 2021,Austria,Zweigelt,Quinta San Pietro,85,20.0
|
| 552 |
+
Vineyard Verde Pinot Noir 2023,US,Pinot Noir,Vineyard Verde,88,27.0
|
| 553 |
+
Bodega Moonlight Syrah 2022,Chile,Syrah,Bodega Moonlight,87,17.0
|
| 554 |
+
Tenuta Golden Valley Cabernet Sauvignon 2019,Chile,Cabernet Sauvignon,Tenuta Golden Valley,92,24.0
|
| 555 |
+
Tenuta La Rosa Nebbiolo 2022,Italy,Nebbiolo,Tenuta La Rosa,89,28.0
|
| 556 |
+
Cantina Golden Valley Syrah 2016,France,Syrah,Cantina Golden Valley,89,32.0
|
| 557 |
+
Casa Starfall Grüner Veltliner 2015,Austria,Grüner Veltliner,Casa Starfall,86,13.0
|
| 558 |
+
Casa Starfall Syrah 2018,Argentina,Syrah,Casa Starfall,86,29.0
|
| 559 |
+
Château El Dorado Zinfandel 2022,US,Zinfandel,Château El Dorado,86,25.0
|
| 560 |
+
Estate Cedar Falls Syrah 2016,France,Syrah,Estate Cedar Falls,89,33.0
|
| 561 |
+
Weingut Starfall Nebbiolo 2023,Italy,Nebbiolo,Weingut Starfall,86,11.0
|
| 562 |
+
Bodega River Bend Chardonnay 2016,France,Chardonnay,Bodega River Bend,89,14.0
|
| 563 |
+
Vineyard Bella Notte Pinot Noir 2022,France,Pinot Noir,Vineyard Bella Notte,96,41.0
|
| 564 |
+
Vineyard del Monte Torrontés 2016,Argentina,Torrontés,Vineyard del Monte,91,35.0
|
| 565 |
+
Casa Verde Tinto Roriz 2022,Portugal,Tinto Roriz,Casa Verde,86,21.0
|
| 566 |
+
Quinta Iron Gate Sangiovese 2023,Italy,Sangiovese,Quinta Iron Gate,92,37.0
|
| 567 |
+
Bodega San Pietro Port 2021,Portugal,Port,Bodega San Pietro,86,19.0
|
| 568 |
+
Vineyard River Bend Merlot 2018,US,Merlot,Vineyard River Bend,80,22.0
|
| 569 |
+
Bodega Verde Cabernet Sauvignon 2021,France,Cabernet Sauvignon,Bodega Verde,83,23.0
|
| 570 |
+
Estate Starfall Merlot 2018,US,Merlot,Estate Starfall,80,17.0
|
| 571 |
+
Bodega Alta Vista Primitivo 2023,Italy,Primitivo,Bodega Alta Vista,86,26.0
|
| 572 |
+
Casa Iron Gate Monastrell 2021,Spain,Monastrell,Casa Iron Gate,88,33.0
|
| 573 |
+
Château Moonlight Merlot 2016,US,Merlot,Château Moonlight,94,39.0
|
| 574 |
+
Weingut Alta Vista Nebbiolo 2019,Italy,Nebbiolo,Weingut Alta Vista,89,12.0
|
| 575 |
+
Weingut Bella Notte Pinot Noir 2023,US,Pinot Noir,Weingut Bella Notte,87,31.0
|
| 576 |
+
Casa El Dorado Barbera 2023,Italy,Barbera,Casa El Dorado,91,28.0
|
| 577 |
+
Weingut del Monte Syrah 2021,France,Syrah,Weingut del Monte,80,25.0
|
| 578 |
+
Weingut Bella Notte Cabernet Sauvignon 2022,France,Cabernet Sauvignon,Weingut Bella Notte,88,29.0
|
| 579 |
+
Quinta Bella Notte Bonarda 2018,Argentina,Bonarda,Quinta Bella Notte,91,41.0
|
| 580 |
+
Bodega Moonlight Pinot Noir 2016,France,Pinot Noir,Bodega Moonlight,82,18.0
|
| 581 |
+
Bodega Crystal Lake Merlot 2019,France,Merlot,Bodega Crystal Lake,92,27.0
|
| 582 |
+
Bodega Golden Valley Barbera 2015,Italy,Barbera,Bodega Golden Valley,89,28.0
|
| 583 |
+
Quinta Starfall Baga 2020,Portugal,Baga,Quinta Starfall,86,23.0
|
| 584 |
+
Casa La Rosa Pinot Grigio 2023,Italy,Pinot Grigio,Casa La Rosa,90,38.0
|
| 585 |
+
Tenuta Bella Notte Primitivo 2020,Italy,Primitivo,Tenuta Bella Notte,97,47.0
|
| 586 |
+
Casa Iron Gate Cabernet Sauvignon 2023,France,Cabernet Sauvignon,Casa Iron Gate,88,23.0
|
| 587 |
+
Tenuta Thunder Ridge Malbec 2018,Argentina,Malbec,Tenuta Thunder Ridge,88,16.0
|
| 588 |
+
Domaine Oak Hill Gewürztraminer 2019,Germany,Gewürztraminer,Domaine Oak Hill,86,22.0
|
| 589 |
+
Estate Moonlight Monastrell 2023,Spain,Monastrell,Estate Moonlight,84,12.0
|
| 590 |
+
Estate Moonlight Chardonnay 2016,France,Chardonnay,Estate Moonlight,91,30.0
|
| 591 |
+
Casa du Soleil Pinot Noir 2016,Germany,Pinot Noir,Casa du Soleil,84,27.0
|
| 592 |
+
Domaine Bella Notte Nebbiolo 2023,Italy,Nebbiolo,Domaine Bella Notte,88,32.0
|
| 593 |
+
Bodega du Soleil Cabernet Sauvignon 2022,Argentina,Cabernet Sauvignon,Bodega du Soleil,86,28.0
|
| 594 |
+
Weingut Starfall Cabernet Sauvignon 2016,US,Cabernet Sauvignon,Weingut Starfall,89,13.0
|
| 595 |
+
Cantina Oak Hill Garnacha 2021,Spain,Garnacha,Cantina Oak Hill,89,36.0
|
| 596 |
+
Quinta La Rosa Merlot 2015,France,Merlot,Quinta La Rosa,92,42.0
|
| 597 |
+
Weingut Pacific Ridge Cabernet Sauvignon 2016,US,Cabernet Sauvignon,Weingut Pacific Ridge,85,16.0
|
| 598 |
+
Château Iron Gate Merlot 2017,France,Merlot,Château Iron Gate,86,22.0
|
| 599 |
+
Casa Pacific Ridge Garnacha 2017,Spain,Garnacha,Casa Pacific Ridge,84,24.0
|
| 600 |
+
Casa Verde Cabernet Sauvignon 2016,France,Cabernet Sauvignon,Casa Verde,86,21.0
|
| 601 |
+
Domaine Pacific Ridge Primitivo 2018,Italy,Primitivo,Domaine Pacific Ridge,89,31.0
|
| 602 |
+
Casa Verde Chardonnay 2017,US,Chardonnay,Casa Verde,91,31.0
|
| 603 |
+
Bodega Crystal Lake Primitivo 2015,Italy,Primitivo,Bodega Crystal Lake,84,17.0
|
| 604 |
+
Weingut La Rosa Syrah 2019,Chile,Syrah,Weingut La Rosa,91,33.0
|
| 605 |
+
Bodega El Dorado Primitivo 2016,Italy,Primitivo,Bodega El Dorado,93,37.0
|
| 606 |
+
Cantina Golden Valley Chardonnay 2019,France,Chardonnay,Cantina Golden Valley,89,35.0
|
| 607 |
+
Estate River Bend Pinot Noir 2017,US,Pinot Noir,Estate River Bend,95,45.0
|
| 608 |
+
Vineyard Sierra Nebbiolo 2020,Italy,Nebbiolo,Vineyard Sierra,84,24.0
|
| 609 |
+
Estate Pacific Ridge Pinot Grigio 2022,Italy,Pinot Grigio,Estate Pacific Ridge,83,21.0
|
| 610 |
+
Weingut Verde Garnacha 2023,Spain,Garnacha,Weingut Verde,80,14.0
|
| 611 |
+
Casa du Soleil Sangiovese 2021,Italy,Sangiovese,Casa du Soleil,93,52.0
|
| 612 |
+
Casa Starfall Port 2022,Portugal,Port,Casa Starfall,90,42.0
|
| 613 |
+
Quinta Pacific Ridge Pinot Noir 2017,US,Pinot Noir,Quinta Pacific Ridge,87,17.0
|
| 614 |
+
Château El Dorado Verdejo 2017,Spain,Verdejo,Château El Dorado,89,17.0
|
| 615 |
+
Quinta Verde Port 2022,Portugal,Port,Quinta Verde,83,12.0
|
| 616 |
+
Domaine Sierra Shiraz 2020,Australia,Shiraz,Domaine Sierra,97,38.0
|
| 617 |
+
Vineyard Iron Gate Nebbiolo 2022,Italy,Nebbiolo,Vineyard Iron Gate,88,30.0
|
| 618 |
+
Casa Sierra Carmenère 2019,Chile,Carmenère,Casa Sierra,88,33.0
|
| 619 |
+
Estate Crystal Lake Verdejo 2016,Spain,Verdejo,Estate Crystal Lake,90,25.0
|
| 620 |
+
Vineyard Stone Creek Albariño 2020,Spain,Albariño,Vineyard Stone Creek,89,35.0
|
| 621 |
+
Bodega Cedar Falls Albariño 2017,Spain,Albariño,Bodega Cedar Falls,88,27.0
|
| 622 |
+
Bodega Alta Vista Primitivo 2020,Italy,Primitivo,Bodega Alta Vista,84,15.0
|
| 623 |
+
Estate San Pietro Cabernet Sauvignon 2022,US,Cabernet Sauvignon,Estate San Pietro,89,31.0
|
| 624 |
+
Vineyard du Soleil Zinfandel 2018,US,Zinfandel,Vineyard du Soleil,95,29.0
|
| 625 |
+
Casa del Monte Primitivo 2017,Italy,Primitivo,Casa del Monte,93,38.0
|
| 626 |
+
Vineyard Thunder Ridge Pinot Grigio 2015,Italy,Pinot Grigio,Vineyard Thunder Ridge,94,57.0
|
| 627 |
+
Quinta Iron Gate Sauvignon Blanc 2022,Chile,Sauvignon Blanc,Quinta Iron Gate,85,19.0
|
| 628 |
+
Bodega Thunder Ridge Barbera 2023,Italy,Barbera,Bodega Thunder Ridge,84,22.0
|
| 629 |
+
Domaine El Dorado Cabernet Sauvignon 2021,France,Cabernet Sauvignon,Domaine El Dorado,87,31.0
|
| 630 |
+
Casa River Bend Chardonnay 2017,France,Chardonnay,Casa River Bend,88,16.0
|
| 631 |
+
Château Starfall Pinot Noir 2023,US,Pinot Noir,Château Starfall,92,37.0
|
| 632 |
+
Quinta Starfall Touriga Nacional 2015,Portugal,Touriga Nacional,Quinta Starfall,81,12.0
|
| 633 |
+
Château Moonlight Merlot 2021,Chile,Merlot,Château Moonlight,94,41.0
|
| 634 |
+
Quinta Crystal Lake Barbera 2016,Italy,Barbera,Quinta Crystal Lake,87,26.0
|
| 635 |
+
Domaine Pacific Ridge Cabernet Sauvignon 2023,France,Cabernet Sauvignon,Domaine Pacific Ridge,86,16.0
|
| 636 |
+
Château Crystal Lake Pinot Noir 2023,France,Pinot Noir,Château Crystal Lake,83,14.0
|
| 637 |
+
Estate River Bend Sangiovese 2020,Italy,Sangiovese,Estate River Bend,81,12.0
|
| 638 |
+
Casa River Bend Barbera 2020,Italy,Barbera,Casa River Bend,91,35.0
|
| 639 |
+
Casa Iron Gate Zinfandel 2017,US,Zinfandel,Casa Iron Gate,88,29.0
|
| 640 |
+
Quinta Stone Creek Syrah 2021,France,Syrah,Quinta Stone Creek,82,23.0
|
| 641 |
+
Bodega San Pietro Cabernet Sauvignon 2018,US,Cabernet Sauvignon,Bodega San Pietro,82,20.0
|
| 642 |
+
Château Alta Vista Monastrell 2021,Spain,Monastrell,Château Alta Vista,86,26.0
|
| 643 |
+
Cantina Thunder Ridge Riesling 2021,Germany,Riesling,Cantina Thunder Ridge,94,57.0
|
| 644 |
+
Château Oak Hill Pinot Grigio 2021,Italy,Pinot Grigio,Château Oak Hill,86,10.0
|
| 645 |
+
Château Alta Vista Merlot 2022,US,Merlot,Château Alta Vista,81,21.0
|
| 646 |
+
Casa Pacific Ridge Pinot Noir 2018,France,Pinot Noir,Casa Pacific Ridge,87,34.0
|
| 647 |
+
Quinta Alta Vista Primitivo 2015,Italy,Primitivo,Quinta Alta Vista,86,23.0
|
| 648 |
+
Weingut Oak Hill Chardonnay 2020,France,Chardonnay,Weingut Oak Hill,80,18.0
|
| 649 |
+
Domaine La Rosa Zinfandel 2023,US,Zinfandel,Domaine La Rosa,87,24.0
|
| 650 |
+
Weingut El Dorado Syrah 2018,France,Syrah,Weingut El Dorado,87,28.0
|
| 651 |
+
Vineyard Moonlight Albariño 2016,Spain,Albariño,Vineyard Moonlight,90,30.0
|
| 652 |
+
Casa Sierra Verdejo 2023,Spain,Verdejo,Casa Sierra,95,43.0
|
| 653 |
+
Vineyard Crystal Lake Syrah 2022,Argentina,Syrah,Vineyard Crystal Lake,92,28.0
|
| 654 |
+
Cantina Crystal Lake Alvarinho 2015,Portugal,Alvarinho,Cantina Crystal Lake,86,26.0
|
| 655 |
+
Tenuta El Dorado Monastrell 2020,Spain,Monastrell,Tenuta El Dorado,83,14.0
|
| 656 |
+
Weingut El Dorado Cabernet Sauvignon 2019,France,Cabernet Sauvignon,Weingut El Dorado,98,47.0
|
| 657 |
+
Cantina Golden Valley Pinot Grigio 2020,Italy,Pinot Grigio,Cantina Golden Valley,88,23.0
|
| 658 |
+
Tenuta Iron Gate Primitivo 2018,Italy,Primitivo,Tenuta Iron Gate,88,27.0
|
| 659 |
+
Tenuta El Dorado Nebbiolo 2020,Italy,Nebbiolo,Tenuta El Dorado,87,25.0
|
| 660 |
+
Cantina Thunder Ridge Sangiovese 2015,Italy,Sangiovese,Cantina Thunder Ridge,88,12.0
|
| 661 |
+
Estate Thunder Ridge Baga 2020,Portugal,Baga,Estate Thunder Ridge,87,35.0
|
| 662 |
+
Casa Sierra Verdejo 2021,Spain,Verdejo,Casa Sierra,85,22.0
|
| 663 |
+
Vineyard Iron Gate Primitivo 2023,Italy,Primitivo,Vineyard Iron Gate,85,13.0
|
| 664 |
+
Bodega Cedar Falls Pinot Grigio 2016,Italy,Pinot Grigio,Bodega Cedar Falls,87,23.0
|
| 665 |
+
Tenuta Oak Hill Zinfandel 2016,US,Zinfandel,Tenuta Oak Hill,85,9.0
|
| 666 |
+
Weingut El Dorado Syrah 2019,France,Syrah,Weingut El Dorado,85,18.0
|
| 667 |
+
Vineyard Bella Notte Verdejo 2021,Spain,Verdejo,Vineyard Bella Notte,88,18.0
|
| 668 |
+
Cantina Alta Vista Chardonnay 2017,US,Chardonnay,Cantina Alta Vista,86,17.0
|
| 669 |
+
Tenuta Starfall Riesling 2021,Austria,Riesling,Tenuta Starfall,94,56.0
|
| 670 |
+
Bodega Iron Gate Cabernet Sauvignon 2015,Chile,Cabernet Sauvignon,Bodega Iron Gate,80,19.0
|
| 671 |
+
Casa Starfall Barbera 2020,Italy,Barbera,Casa Starfall,92,31.0
|
| 672 |
+
Château Oak Hill Alvarinho 2016,Portugal,Alvarinho,Château Oak Hill,92,34.0
|
| 673 |
+
Domaine Cedar Falls Cabernet Sauvignon 2020,US,Cabernet Sauvignon,Domaine Cedar Falls,80,10.0
|
| 674 |
+
Weingut Stone Creek Cabernet Sauvignon 2015,France,Cabernet Sauvignon,Weingut Stone Creek,86,27.0
|
| 675 |
+
Tenuta Crystal Lake Cabernet Sauvignon 2023,France,Cabernet Sauvignon,Tenuta Crystal Lake,86,32.0
|
| 676 |
+
Cantina Cedar Falls Pinot Grigio 2016,Italy,Pinot Grigio,Cantina Cedar Falls,82,18.0
|
| 677 |
+
Bodega Golden Valley Cabernet Sauvignon 2021,France,Cabernet Sauvignon,Bodega Golden Valley,84,23.0
|
| 678 |
+
Domaine Alta Vista Merlot 2020,US,Merlot,Domaine Alta Vista,83,21.0
|
| 679 |
+
Quinta Oak Hill Pinot Grigio 2019,Italy,Pinot Grigio,Quinta Oak Hill,95,53.0
|
| 680 |
+
Cantina River Bend Sauvignon Blanc 2017,Chile,Sauvignon Blanc,Cantina River Bend,91,41.0
|
| 681 |
+
Weingut La Rosa Sangiovese 2018,Italy,Sangiovese,Weingut La Rosa,93,24.0
|
| 682 |
+
Cantina Starfall Sangiovese 2015,Italy,Sangiovese,Cantina Starfall,90,27.0
|
| 683 |
+
Domaine Sierra Barbera 2017,Italy,Barbera,Domaine Sierra,83,24.0
|
| 684 |
+
Weingut Cedar Falls Barbera 2017,Italy,Barbera,Weingut Cedar Falls,85,12.0
|
| 685 |
+
Estate Iron Gate Nebbiolo 2022,Italy,Nebbiolo,Estate Iron Gate,89,20.0
|
| 686 |
+
Bodega Starfall Welschriesling 2017,Austria,Welschriesling,Bodega Starfall,83,23.0
|
| 687 |
+
Quinta River Bend Albariño 2023,Spain,Albariño,Quinta River Bend,90,36.0
|
| 688 |
+
Casa El Dorado Merlot 2016,US,Merlot,Casa El Dorado,87,17.0
|
| 689 |
+
Château du Soleil Cabernet Sauvignon 2023,France,Cabernet Sauvignon,Château du Soleil,86,14.0
|
| 690 |
+
Château Iron Gate Torrontés 2022,Argentina,Torrontés,Château Iron Gate,90,27.0
|
| 691 |
+
Château Starfall Merlot 2020,France,Merlot,Château Starfall,89,36.0
|
| 692 |
+
Vineyard Oak Hill Primitivo 2018,Italy,Primitivo,Vineyard Oak Hill,86,16.0
|
| 693 |
+
Quinta Sierra Merlot 2019,France,Merlot,Quinta Sierra,92,40.0
|
| 694 |
+
Domaine Alta Vista Merlot 2017,US,Merlot,Domaine Alta Vista,83,20.0
|
| 695 |
+
Quinta Iron Gate Merlot 2018,France,Merlot,Quinta Iron Gate,90,31.0
|
| 696 |
+
Bodega San Pietro Pinot Noir 2019,France,Pinot Noir,Bodega San Pietro,90,20.0
|
| 697 |
+
Bodega du Soleil Merlot 2022,France,Merlot,Bodega du Soleil,86,20.0
|
| 698 |
+
Estate Cedar Falls Barbera 2015,Italy,Barbera,Estate Cedar Falls,89,28.0
|
| 699 |
+
Domaine Starfall Pinot Noir 2022,France,Pinot Noir,Domaine Starfall,82,15.0
|
| 700 |
+
Domaine El Dorado Pinot Grigio 2021,Italy,Pinot Grigio,Domaine El Dorado,91,47.0
|
| 701 |
+
Tenuta Cedar Falls Tinto Roriz 2016,Portugal,Tinto Roriz,Tenuta Cedar Falls,87,25.0
|
| 702 |
+
Weingut Golden Valley Garnacha 2017,Spain,Garnacha,Weingut Golden Valley,85,19.0
|
| 703 |
+
Domaine Sierra Cabernet Sauvignon 2022,US,Cabernet Sauvignon,Domaine Sierra,92,44.0
|
| 704 |
+
Tenuta San Pietro Pinot Noir 2018,US,Pinot Noir,Tenuta San Pietro,85,10.0
|
| 705 |
+
Quinta San Pietro Chardonnay 2021,US,Chardonnay,Quinta San Pietro,82,15.0
|
| 706 |
+
Cantina Thunder Ridge Touriga Nacional 2017,Portugal,Touriga Nacional,Cantina Thunder Ridge,81,24.0
|
| 707 |
+
Quinta Golden Valley Chardonnay 2015,France,Chardonnay,Quinta Golden Valley,90,25.0
|
| 708 |
+
Bodega Iron Gate Nebbiolo 2018,Italy,Nebbiolo,Bodega Iron Gate,82,24.0
|
| 709 |
+
Cantina Bella Notte Syrah 2015,France,Syrah,Cantina Bella Notte,95,59.0
|
| 710 |
+
Château Iron Gate Chardonnay 2022,US,Chardonnay,Château Iron Gate,80,17.0
|
| 711 |
+
Bodega Starfall Verdejo 2020,Spain,Verdejo,Bodega Starfall,94,45.0
|
| 712 |
+
Casa Alta Vista Merlot 2016,France,Merlot,Casa Alta Vista,88,25.0
|
| 713 |
+
Estate Cedar Falls Albariño 2015,Spain,Albariño,Estate Cedar Falls,87,16.0
|
| 714 |
+
Château Thunder Ridge Baga 2020,Portugal,Baga,Château Thunder Ridge,85,12.0
|
| 715 |
+
Casa Oak Hill Port 2018,Portugal,Port,Casa Oak Hill,89,19.0
|
| 716 |
+
Weingut Golden Valley Albariño 2021,Spain,Albariño,Weingut Golden Valley,87,23.0
|
| 717 |
+
Château Verde Cabernet Sauvignon 2017,US,Cabernet Sauvignon,Château Verde,92,26.0
|
| 718 |
+
Château Crystal Lake Cabernet Sauvignon 2021,Chile,Cabernet Sauvignon,Château Crystal Lake,88,14.0
|
| 719 |
+
Château Stone Creek Merlot 2018,US,Merlot,Château Stone Creek,88,29.0
|
| 720 |
+
Cantina La Rosa Cabernet Sauvignon 2022,US,Cabernet Sauvignon,Cantina La Rosa,86,18.0
|
| 721 |
+
Vineyard Stone Creek Malbec 2015,Argentina,Malbec,Vineyard Stone Creek,87,23.0
|
| 722 |
+
Weingut La Rosa Bonarda 2018,Argentina,Bonarda,Weingut La Rosa,89,32.0
|
| 723 |
+
Vineyard Bella Notte Riesling 2018,Germany,Riesling,Vineyard Bella Notte,81,9.0
|
| 724 |
+
Casa Starfall Garnacha 2021,Spain,Garnacha,Casa Starfall,82,24.0
|
| 725 |
+
Vineyard San Pietro Merlot 2017,US,Merlot,Vineyard San Pietro,90,27.0
|
| 726 |
+
Bodega Starfall Baga 2022,Portugal,Baga,Bodega Starfall,88,21.0
|
| 727 |
+
Estate River Bend Cabernet Sauvignon 2021,Australia,Cabernet Sauvignon,Estate River Bend,87,30.0
|
| 728 |
+
Tenuta Oak Hill Bonarda 2023,Argentina,Bonarda,Tenuta Oak Hill,88,28.0
|
| 729 |
+
Vineyard du Soleil Cabernet Sauvignon 2015,Australia,Cabernet Sauvignon,Vineyard du Soleil,89,24.0
|
| 730 |
+
Weingut du Soleil Welschriesling 2019,Austria,Welschriesling,Weingut du Soleil,85,6.0
|
| 731 |
+
Weingut Starfall Riesling 2023,Austria,Riesling,Weingut Starfall,84,15.0
|
| 732 |
+
Estate Verde Verdejo 2017,Spain,Verdejo,Estate Verde,88,13.0
|
| 733 |
+
Weingut La Rosa Syrah 2021,France,Syrah,Weingut La Rosa,84,11.0
|
| 734 |
+
Cantina Alta Vista Garnacha 2022,Spain,Garnacha,Cantina Alta Vista,89,36.0
|
| 735 |
+
Weingut del Monte Syrah 2021,Argentina,Syrah,Weingut del Monte,81,16.0
|
| 736 |
+
Vineyard River Bend Sangiovese 2016,Italy,Sangiovese,Vineyard River Bend,92,47.0
|
| 737 |
+
Château Oak Hill Cabernet Sauvignon 2015,Chile,Cabernet Sauvignon,Château Oak Hill,89,38.0
|
| 738 |
+
Estate Moonlight Chardonnay 2018,France,Chardonnay,Estate Moonlight,89,25.0
|
| 739 |
+
Quinta Moonlight Barbera 2016,Italy,Barbera,Quinta Moonlight,91,50.0
|
| 740 |
+
Estate La Rosa Pinot Grigio 2022,Italy,Pinot Grigio,Estate La Rosa,94,47.0
|
| 741 |
+
Vineyard Moonlight Tempranillo 2021,Spain,Tempranillo,Vineyard Moonlight,92,35.0
|
| 742 |
+
Tenuta Iron Gate Port 2021,Portugal,Port,Tenuta Iron Gate,80,20.0
|
| 743 |
+
Casa El Dorado Pinot Noir 2018,US,Pinot Noir,Casa El Dorado,82,24.0
|
| 744 |
+
Domaine San Pietro Barbera 2021,Italy,Barbera,Domaine San Pietro,85,21.0
|
| 745 |
+
Château Pacific Ridge Cabernet Sauvignon 2017,France,Cabernet Sauvignon,Château Pacific Ridge,88,17.0
|
| 746 |
+
Quinta Verde Welschriesling 2022,Austria,Welschriesling,Quinta Verde,90,43.0
|
| 747 |
+
Domaine San Pietro Nebbiolo 2015,Italy,Nebbiolo,Domaine San Pietro,85,12.0
|
| 748 |
+
Weingut du Soleil Primitivo 2020,Italy,Primitivo,Weingut du Soleil,88,39.0
|
| 749 |
+
Estate Bella Notte Cabernet Sauvignon 2023,US,Cabernet Sauvignon,Estate Bella Notte,84,14.0
|
| 750 |
+
Cantina Thunder Ridge Primitivo 2017,Italy,Primitivo,Cantina Thunder Ridge,85,14.0
|
| 751 |
+
Casa del Monte Cabernet Sauvignon 2019,US,Cabernet Sauvignon,Casa del Monte,82,21.0
|
| 752 |
+
Weingut del Monte Pinot Grigio 2022,Italy,Pinot Grigio,Weingut del Monte,84,16.0
|
| 753 |
+
Estate San Pietro Cabernet Sauvignon 2015,US,Cabernet Sauvignon,Estate San Pietro,82,14.0
|
| 754 |
+
Domaine Golden Valley Merlot 2022,France,Merlot,Domaine Golden Valley,84,12.0
|
| 755 |
+
Cantina Starfall Syrah 2015,Chile,Syrah,Cantina Starfall,92,20.0
|
| 756 |
+
Bodega du Soleil Primitivo 2020,Italy,Primitivo,Bodega du Soleil,84,15.0
|
| 757 |
+
Casa Sierra Chardonnay 2015,US,Chardonnay,Casa Sierra,98,55.0
|
| 758 |
+
Château Starfall Zinfandel 2019,US,Zinfandel,Château Starfall,89,41.0
|
| 759 |
+
Domaine Oak Hill Pinot Grigio 2023,Italy,Pinot Grigio,Domaine Oak Hill,88,35.0
|
| 760 |
+
Vineyard El Dorado Müller-Thurgau 2017,Germany,Müller-Thurgau,Vineyard El Dorado,84,24.0
|
| 761 |
+
Casa Verde Cabernet Sauvignon 2018,France,Cabernet Sauvignon,Casa Verde,90,39.0
|
| 762 |
+
Bodega Pacific Ridge Merlot 2023,US,Merlot,Bodega Pacific Ridge,85,22.0
|
| 763 |
+
Bodega Crystal Lake Riesling 2017,Australia,Riesling,Bodega Crystal Lake,88,42.0
|
| 764 |
+
Bodega Golden Valley Syrah 2017,France,Syrah,Bodega Golden Valley,98,57.0
|
| 765 |
+
Vineyard Pacific Ridge Chardonnay 2022,US,Chardonnay,Vineyard Pacific Ridge,87,28.0
|
| 766 |
+
Bodega Alta Vista Chardonnay 2015,US,Chardonnay,Bodega Alta Vista,92,22.0
|
| 767 |
+
Quinta El Dorado Baga 2018,Portugal,Baga,Quinta El Dorado,85,20.0
|
| 768 |
+
Cantina Verde Sangiovese 2023,Italy,Sangiovese,Cantina Verde,87,23.0
|
| 769 |
+
Vineyard Iron Gate Cabernet Sauvignon 2022,Argentina,Cabernet Sauvignon,Vineyard Iron Gate,95,51.0
|
| 770 |
+
Château Sierra Nebbiolo 2021,Italy,Nebbiolo,Château Sierra,85,13.0
|
| 771 |
+
Cantina Thunder Ridge Nebbiolo 2022,Italy,Nebbiolo,Cantina Thunder Ridge,95,49.0
|
| 772 |
+
Château Thunder Ridge Zinfandel 2021,US,Zinfandel,Château Thunder Ridge,90,40.0
|
| 773 |
+
Quinta Starfall Zinfandel 2023,US,Zinfandel,Quinta Starfall,85,22.0
|
| 774 |
+
Château El Dorado Cabernet Sauvignon 2023,US,Cabernet Sauvignon,Château El Dorado,90,31.0
|
| 775 |
+
Château Bella Notte Tempranillo 2019,Spain,Tempranillo,Château Bella Notte,91,36.0
|
| 776 |
+
Bodega River Bend Cabernet Sauvignon 2019,France,Cabernet Sauvignon,Bodega River Bend,90,35.0
|
| 777 |
+
Cantina Cedar Falls Cabernet Sauvignon 2016,US,Cabernet Sauvignon,Cantina Cedar Falls,81,25.0
|
| 778 |
+
Casa Verde Cabernet Sauvignon 2021,US,Cabernet Sauvignon,Casa Verde,85,14.0
|
| 779 |
+
Tenuta Cedar Falls Merlot 2016,France,Merlot,Tenuta Cedar Falls,87,14.0
|
| 780 |
+
Domaine Cedar Falls Pinot Noir 2020,France,Pinot Noir,Domaine Cedar Falls,87,22.0
|
| 781 |
+
Quinta Alta Vista Barbera 2021,Italy,Barbera,Quinta Alta Vista,90,43.0
|
| 782 |
+
Quinta Verde Tempranillo 2017,Spain,Tempranillo,Quinta Verde,88,36.0
|
| 783 |
+
Weingut Pacific Ridge Cabernet Sauvignon 2022,Chile,Cabernet Sauvignon,Weingut Pacific Ridge,82,15.0
|
| 784 |
+
Tenuta du Soleil Pinot Noir 2019,France,Pinot Noir,Tenuta du Soleil,89,15.0
|
| 785 |
+
Château Thunder Ridge Barbera 2022,Italy,Barbera,Château Thunder Ridge,90,40.0
|
| 786 |
+
Cantina La Rosa Primitivo 2015,Italy,Primitivo,Cantina La Rosa,90,34.0
|
| 787 |
+
Tenuta del Monte Primitivo 2017,Italy,Primitivo,Tenuta del Monte,92,32.0
|
| 788 |
+
Quinta Thunder Ridge Pinot Grigio 2019,Italy,Pinot Grigio,Quinta Thunder Ridge,91,26.0
|
| 789 |
+
Bodega Alta Vista Chardonnay 2019,France,Chardonnay,Bodega Alta Vista,89,17.0
|
| 790 |
+
Cantina Crystal Lake Merlot 2020,US,Merlot,Cantina Crystal Lake,87,25.0
|
| 791 |
+
Vineyard La Rosa Shiraz 2021,Australia,Shiraz,Vineyard La Rosa,81,18.0
|
| 792 |
+
Weingut Golden Valley Malbec 2023,Argentina,Malbec,Weingut Golden Valley,89,19.0
|
| 793 |
+
Domaine Crystal Lake Pinot Noir 2023,France,Pinot Noir,Domaine Crystal Lake,88,31.0
|
| 794 |
+
Weingut River Bend Blaufränkisch 2020,Austria,Blaufränkisch,Weingut River Bend,89,35.0
|
| 795 |
+
Bodega Thunder Ridge Syrah 2022,France,Syrah,Bodega Thunder Ridge,82,22.0
|
| 796 |
+
Quinta El Dorado Albariño 2019,Spain,Albariño,Quinta El Dorado,83,13.0
|
| 797 |
+
Domaine Bella Notte Grüner Veltliner 2021,Austria,Grüner Veltliner,Domaine Bella Notte,92,25.0
|
| 798 |
+
Tenuta du Soleil Cabernet Sauvignon 2018,France,Cabernet Sauvignon,Tenuta du Soleil,87,24.0
|
| 799 |
+
Casa Starfall Chardonnay 2020,US,Chardonnay,Casa Starfall,90,36.0
|
| 800 |
+
Quinta Thunder Ridge Touriga Nacional 2015,Portugal,Touriga Nacional,Quinta Thunder Ridge,88,27.0
|
| 801 |
+
Cantina Iron Gate Torrontés 2015,Argentina,Torrontés,Cantina Iron Gate,88,20.0
|
| 802 |
+
Casa Golden Valley Zinfandel 2022,US,Zinfandel,Casa Golden Valley,91,24.0
|
| 803 |
+
Casa Pacific Ridge Tinto Roriz 2020,Portugal,Tinto Roriz,Casa Pacific Ridge,85,17.0
|
| 804 |
+
Estate La Rosa Tempranillo 2017,Spain,Tempranillo,Estate La Rosa,88,22.0
|
| 805 |
+
Casa Alta Vista Chardonnay 2021,France,Chardonnay,Casa Alta Vista,86,16.0
|
| 806 |
+
Estate del Monte Sangiovese 2019,Italy,Sangiovese,Estate del Monte,86,29.0
|
| 807 |
+
Weingut Bella Notte Merlot 2023,France,Merlot,Weingut Bella Notte,86,24.0
|
| 808 |
+
Tenuta La Rosa Chardonnay 2022,France,Chardonnay,Tenuta La Rosa,88,17.0
|
| 809 |
+
Estate Iron Gate Albariño 2023,Spain,Albariño,Estate Iron Gate,86,22.0
|
| 810 |
+
Casa Verde Cabernet Sauvignon 2018,France,Cabernet Sauvignon,Casa Verde,93,32.0
|
| 811 |
+
Domaine du Soleil Zinfandel 2019,US,Zinfandel,Domaine du Soleil,84,21.0
|
| 812 |
+
Château San Pietro Semillon 2023,Australia,Semillon,Château San Pietro,87,27.0
|
| 813 |
+
Tenuta Golden Valley Alvarinho 2018,Portugal,Alvarinho,Tenuta Golden Valley,86,16.0
|
| 814 |
+
Domaine Sierra Pinot Grigio 2017,Italy,Pinot Grigio,Domaine Sierra,93,44.0
|
| 815 |
+
Casa San Pietro Sangiovese 2018,Italy,Sangiovese,Casa San Pietro,88,17.0
|
| 816 |
+
Weingut Crystal Lake Verdejo 2018,Spain,Verdejo,Weingut Crystal Lake,92,26.0
|
| 817 |
+
Cantina del Monte Pinot Grigio 2017,Italy,Pinot Grigio,Cantina del Monte,82,17.0
|
| 818 |
+
Vineyard Oak Hill Sangiovese 2017,Italy,Sangiovese,Vineyard Oak Hill,89,14.0
|
| 819 |
+
Cantina Thunder Ridge Merlot 2020,US,Merlot,Cantina Thunder Ridge,91,40.0
|
| 820 |
+
Casa La Rosa Pinot Noir 2022,France,Pinot Noir,Casa La Rosa,88,32.0
|
| 821 |
+
Cantina San Pietro Tempranillo 2022,Spain,Tempranillo,Cantina San Pietro,92,51.0
|
| 822 |
+
Bodega Thunder Ridge Merlot 2019,France,Merlot,Bodega Thunder Ridge,85,23.0
|
| 823 |
+
Estate Golden Valley Riesling 2022,Australia,Riesling,Estate Golden Valley,93,34.0
|
| 824 |
+
Cantina Alta Vista Tempranillo 2019,Spain,Tempranillo,Cantina Alta Vista,97,47.0
|
| 825 |
+
Vineyard San Pietro Baga 2020,Portugal,Baga,Vineyard San Pietro,86,21.0
|
| 826 |
+
Vineyard Crystal Lake Tempranillo 2021,Spain,Tempranillo,Vineyard Crystal Lake,86,25.0
|
| 827 |
+
Vineyard La Rosa Nebbiolo 2020,Italy,Nebbiolo,Vineyard La Rosa,93,47.0
|
| 828 |
+
Quinta Golden Valley Primitivo 2023,Italy,Primitivo,Quinta Golden Valley,94,46.0
|
| 829 |
+
Quinta Iron Gate Pinot Noir 2016,US,Pinot Noir,Quinta Iron Gate,85,14.0
|
| 830 |
+
Cantina Alta Vista Albariño 2019,Spain,Albariño,Cantina Alta Vista,86,12.0
|
| 831 |
+
Quinta Oak Hill Riesling 2020,Germany,Riesling,Quinta Oak Hill,86,24.0
|
| 832 |
+
Quinta du Soleil Tempranillo 2017,Spain,Tempranillo,Quinta du Soleil,82,16.0
|
| 833 |
+
Quinta Cedar Falls Zinfandel 2018,US,Zinfandel,Quinta Cedar Falls,84,16.0
|
| 834 |
+
Weingut River Bend Pinot Grigio 2020,Italy,Pinot Grigio,Weingut River Bend,83,19.0
|
| 835 |
+
Vineyard Verde Welschriesling 2019,Austria,Welschriesling,Vineyard Verde,84,17.0
|
| 836 |
+
Casa Stone Creek Primitivo 2016,Italy,Primitivo,Casa Stone Creek,87,24.0
|
| 837 |
+
Vineyard Golden Valley Carmenère 2021,Chile,Carmenère,Vineyard Golden Valley,88,23.0
|
| 838 |
+
Cantina Verde Merlot 2018,France,Merlot,Cantina Verde,94,46.0
|
| 839 |
+
Bodega Verde Monastrell 2015,Spain,Monastrell,Bodega Verde,84,17.0
|
| 840 |
+
Vineyard Verde Sangiovese 2016,Italy,Sangiovese,Vineyard Verde,91,29.0
|
| 841 |
+
Quinta River Bend Barbera 2017,Italy,Barbera,Quinta River Bend,87,34.0
|
| 842 |
+
Estate El Dorado Albariño 2017,Spain,Albariño,Estate El Dorado,87,23.0
|
| 843 |
+
Tenuta Moonlight Chardonnay 2019,France,Chardonnay,Tenuta Moonlight,90,37.0
|
| 844 |
+
Château Crystal Lake Syrah 2022,France,Syrah,Château Crystal Lake,83,12.0
|
| 845 |
+
Domaine Verde Cabernet Sauvignon 2023,US,Cabernet Sauvignon,Domaine Verde,89,36.0
|
| 846 |
+
Quinta La Rosa Zweigelt 2018,Austria,Zweigelt,Quinta La Rosa,88,19.0
|
| 847 |
+
Quinta Pacific Ridge Tempranillo 2015,Spain,Tempranillo,Quinta Pacific Ridge,89,33.0
|
| 848 |
+
Casa Iron Gate Semillon 2020,Australia,Semillon,Casa Iron Gate,89,34.0
|
| 849 |
+
Quinta Pacific Ridge Cabernet Sauvignon 2019,France,Cabernet Sauvignon,Quinta Pacific Ridge,97,35.0
|
| 850 |
+
Weingut Thunder Ridge Barbera 2015,Italy,Barbera,Weingut Thunder Ridge,85,19.0
|
| 851 |
+
Weingut Sierra Chardonnay 2017,France,Chardonnay,Weingut Sierra,85,7.0
|
| 852 |
+
Domaine Thunder Ridge Chardonnay 2017,US,Chardonnay,Domaine Thunder Ridge,85,15.0
|
| 853 |
+
Bodega Sierra Chardonnay 2018,Australia,Chardonnay,Bodega Sierra,85,18.0
|
| 854 |
+
Domaine Verde Verdejo 2017,Spain,Verdejo,Domaine Verde,85,20.0
|
| 855 |
+
Cantina Alta Vista Cabernet Sauvignon 2018,Argentina,Cabernet Sauvignon,Cantina Alta Vista,92,41.0
|
| 856 |
+
Domaine del Monte Monastrell 2017,Spain,Monastrell,Domaine del Monte,93,22.0
|
| 857 |
+
Casa El Dorado Albariño 2021,Spain,Albariño,Casa El Dorado,85,18.0
|
| 858 |
+
Vineyard du Soleil Zinfandel 2019,US,Zinfandel,Vineyard du Soleil,84,12.0
|
| 859 |
+
Casa del Monte Riesling 2016,Australia,Riesling,Casa del Monte,89,23.0
|
| 860 |
+
Weingut Golden Valley Cabernet Sauvignon 2019,Australia,Cabernet Sauvignon,Weingut Golden Valley,85,22.0
|
| 861 |
+
Cantina El Dorado Chardonnay 2018,France,Chardonnay,Cantina El Dorado,90,26.0
|
| 862 |
+
Château La Rosa Garnacha 2015,Spain,Garnacha,Château La Rosa,88,15.0
|
| 863 |
+
Tenuta Pacific Ridge Syrah 2019,France,Syrah,Tenuta Pacific Ridge,81,12.0
|
| 864 |
+
Quinta Bella Notte Sangiovese 2016,Italy,Sangiovese,Quinta Bella Notte,94,40.0
|
| 865 |
+
Vineyard Crystal Lake Cabernet Sauvignon 2017,US,Cabernet Sauvignon,Vineyard Crystal Lake,95,31.0
|
| 866 |
+
Domaine Cedar Falls Cabernet Sauvignon 2019,Chile,Cabernet Sauvignon,Domaine Cedar Falls,85,14.0
|
| 867 |
+
Weingut del Monte Alvarinho 2021,Portugal,Alvarinho,Weingut del Monte,86,20.0
|
| 868 |
+
Bodega Cedar Falls Chardonnay 2016,France,Chardonnay,Bodega Cedar Falls,89,27.0
|
| 869 |
+
Cantina San Pietro Garnacha 2017,Spain,Garnacha,Cantina San Pietro,89,27.0
|
| 870 |
+
Cantina Sierra Albariño 2016,Spain,Albariño,Cantina Sierra,90,26.0
|
| 871 |
+
Cantina du Soleil Sangiovese 2022,Italy,Sangiovese,Cantina du Soleil,96,47.0
|
| 872 |
+
Weingut Verde Sangiovese 2020,Italy,Sangiovese,Weingut Verde,87,32.0
|
| 873 |
+
Cantina Iron Gate Semillon 2021,Australia,Semillon,Cantina Iron Gate,84,14.0
|
| 874 |
+
Cantina San Pietro Chardonnay 2023,France,Chardonnay,Cantina San Pietro,82,11.0
|
| 875 |
+
Château La Rosa Cabernet Sauvignon 2020,Australia,Cabernet Sauvignon,Château La Rosa,85,13.0
|
| 876 |
+
Weingut Bella Notte Monastrell 2017,Spain,Monastrell,Weingut Bella Notte,87,15.0
|
| 877 |
+
Vineyard San Pietro Albariño 2020,Spain,Albariño,Vineyard San Pietro,95,48.0
|
| 878 |
+
Tenuta du Soleil Albariño 2018,Spain,Albariño,Tenuta du Soleil,85,16.0
|
| 879 |
+
Cantina Starfall Tempranillo 2022,Spain,Tempranillo,Cantina Starfall,88,33.0
|
| 880 |
+
Château Oak Hill Riesling 2016,Germany,Riesling,Château Oak Hill,87,9.0
|
| 881 |
+
Casa Verde Primitivo 2018,Italy,Primitivo,Casa Verde,92,38.0
|
| 882 |
+
Château Iron Gate Shiraz 2015,Australia,Shiraz,Château Iron Gate,98,63.0
|
| 883 |
+
Weingut San Pietro Nebbiolo 2022,Italy,Nebbiolo,Weingut San Pietro,85,13.0
|
| 884 |
+
Domaine Iron Gate Merlot 2018,US,Merlot,Domaine Iron Gate,86,18.0
|
| 885 |
+
Vineyard Golden Valley Nebbiolo 2016,Italy,Nebbiolo,Vineyard Golden Valley,92,38.0
|
| 886 |
+
Tenuta del Monte Welschriesling 2017,Austria,Welschriesling,Tenuta del Monte,90,30.0
|
| 887 |
+
Bodega Stone Creek Chardonnay 2023,France,Chardonnay,Bodega Stone Creek,95,40.0
|
| 888 |
+
Domaine Thunder Ridge Nebbiolo 2021,Italy,Nebbiolo,Domaine Thunder Ridge,90,36.0
|
| 889 |
+
Château Alta Vista Touriga Nacional 2016,Portugal,Touriga Nacional,Château Alta Vista,86,20.0
|
| 890 |
+
Cantina Verde Merlot 2018,US,Merlot,Cantina Verde,90,40.0
|
| 891 |
+
Bodega Thunder Ridge Pinot Grigio 2015,Italy,Pinot Grigio,Bodega Thunder Ridge,92,36.0
|
| 892 |
+
Weingut Stone Creek Albariño 2021,Spain,Albariño,Weingut Stone Creek,91,31.0
|
| 893 |
+
Domaine Thunder Ridge Nebbiolo 2020,Italy,Nebbiolo,Domaine Thunder Ridge,90,30.0
|
| 894 |
+
Tenuta Sierra Syrah 2015,Chile,Syrah,Tenuta Sierra,92,36.0
|
| 895 |
+
Cantina Iron Gate Nebbiolo 2017,Italy,Nebbiolo,Cantina Iron Gate,92,48.0
|
| 896 |
+
Tenuta River Bend Sangiovese 2019,Italy,Sangiovese,Tenuta River Bend,93,23.0
|
| 897 |
+
Casa Alta Vista Merlot 2017,France,Merlot,Casa Alta Vista,90,23.0
|
| 898 |
+
Tenuta Cedar Falls Tinto Roriz 2020,Portugal,Tinto Roriz,Tenuta Cedar Falls,87,17.0
|
| 899 |
+
Tenuta San Pietro Cabernet Sauvignon 2018,France,Cabernet Sauvignon,Tenuta San Pietro,88,15.0
|
| 900 |
+
Cantina Crystal Lake Pinot Noir 2022,US,Pinot Noir,Cantina Crystal Lake,92,29.0
|
| 901 |
+
Cantina Alta Vista Barbera 2021,Italy,Barbera,Cantina Alta Vista,84,18.0
|
| 902 |
+
Weingut Bella Notte Merlot 2020,France,Merlot,Weingut Bella Notte,89,35.0
|
| 903 |
+
Cantina Cedar Falls Primitivo 2021,Italy,Primitivo,Cantina Cedar Falls,86,9.0
|
| 904 |
+
Bodega Thunder Ridge Pinot Grigio 2017,Italy,Pinot Grigio,Bodega Thunder Ridge,88,17.0
|
| 905 |
+
Casa Iron Gate Verdejo 2018,Spain,Verdejo,Casa Iron Gate,93,45.0
|
| 906 |
+
Tenuta El Dorado Albariño 2020,Spain,Albariño,Tenuta El Dorado,88,24.0
|
| 907 |
+
Bodega Crystal Lake Pinot Noir 2015,France,Pinot Noir,Bodega Crystal Lake,88,35.0
|
| 908 |
+
Casa del Monte Chardonnay 2021,France,Chardonnay,Casa del Monte,82,11.0
|
| 909 |
+
Domaine Cedar Falls Albariño 2022,Spain,Albariño,Domaine Cedar Falls,90,41.0
|
| 910 |
+
Vineyard Bella Notte Primitivo 2017,Italy,Primitivo,Vineyard Bella Notte,90,40.0
|
| 911 |
+
Cantina Pacific Ridge Pinot Noir 2017,France,Pinot Noir,Cantina Pacific Ridge,96,48.0
|
| 912 |
+
Cantina Cedar Falls Merlot 2017,US,Merlot,Cantina Cedar Falls,86,18.0
|
| 913 |
+
Cantina du Soleil Merlot 2016,Chile,Merlot,Cantina du Soleil,88,24.0
|
| 914 |
+
Weingut Thunder Ridge Cabernet Sauvignon 2023,France,Cabernet Sauvignon,Weingut Thunder Ridge,88,23.0
|
| 915 |
+
Estate del Monte Garnacha 2023,Spain,Garnacha,Estate del Monte,94,47.0
|
| 916 |
+
Estate Cedar Falls Gewürztraminer 2015,Germany,Gewürztraminer,Estate Cedar Falls,87,24.0
|
| 917 |
+
Casa Bella Notte Pinot Noir 2017,France,Pinot Noir,Casa Bella Notte,89,34.0
|
| 918 |
+
Quinta Bella Notte Riesling 2018,Austria,Riesling,Quinta Bella Notte,90,34.0
|
| 919 |
+
Château La Rosa Cabernet Sauvignon 2020,France,Cabernet Sauvignon,Château La Rosa,88,25.0
|
| 920 |
+
Cantina Starfall Merlot 2023,France,Merlot,Cantina Starfall,86,24.0
|
| 921 |
+
Domaine Bella Notte Merlot 2022,Chile,Merlot,Domaine Bella Notte,88,32.0
|
| 922 |
+
Domaine San Pietro Barbera 2017,Italy,Barbera,Domaine San Pietro,92,46.0
|
| 923 |
+
Casa du Soleil Pinot Noir 2019,France,Pinot Noir,Casa du Soleil,83,22.0
|
| 924 |
+
Vineyard Cedar Falls Syrah 2015,France,Syrah,Vineyard Cedar Falls,88,34.0
|
| 925 |
+
Casa Golden Valley Chardonnay 2021,France,Chardonnay,Casa Golden Valley,85,15.0
|
| 926 |
+
Casa Starfall Monastrell 2022,Spain,Monastrell,Casa Starfall,92,38.0
|
| 927 |
+
Bodega Sierra Verdejo 2018,Spain,Verdejo,Bodega Sierra,81,16.0
|
| 928 |
+
Estate Pacific Ridge Monastrell 2022,Spain,Monastrell,Estate Pacific Ridge,85,15.0
|
| 929 |
+
Weingut Alta Vista Müller-Thurgau 2017,Germany,Müller-Thurgau,Weingut Alta Vista,89,41.0
|
| 930 |
+
Estate Crystal Lake Torrontés 2017,Argentina,Torrontés,Estate Crystal Lake,94,25.0
|
| 931 |
+
Château Golden Valley Cabernet Sauvignon 2020,France,Cabernet Sauvignon,Château Golden Valley,87,18.0
|
| 932 |
+
Weingut San Pietro Barbera 2015,Italy,Barbera,Weingut San Pietro,85,13.0
|
| 933 |
+
Estate Verde Merlot 2015,France,Merlot,Estate Verde,95,61.0
|
| 934 |
+
Weingut Iron Gate Welschriesling 2019,Austria,Welschriesling,Weingut Iron Gate,82,21.0
|
| 935 |
+
Cantina Golden Valley Müller-Thurgau 2016,Germany,Müller-Thurgau,Cantina Golden Valley,80,23.0
|
| 936 |
+
Weingut du Soleil Cabernet Sauvignon 2021,US,Cabernet Sauvignon,Weingut du Soleil,89,21.0
|
| 937 |
+
Château Thunder Ridge Pinot Noir 2018,US,Pinot Noir,Château Thunder Ridge,85,11.0
|
| 938 |
+
Tenuta du Soleil Garnacha 2016,Spain,Garnacha,Tenuta du Soleil,83,24.0
|
| 939 |
+
Casa Oak Hill Albariño 2018,Spain,Albariño,Casa Oak Hill,90,41.0
|
| 940 |
+
Estate Oak Hill Verdejo 2017,Spain,Verdejo,Estate Oak Hill,88,33.0
|
| 941 |
+
Weingut Stone Creek Zinfandel 2020,US,Zinfandel,Weingut Stone Creek,85,14.0
|
| 942 |
+
Cantina River Bend Merlot 2022,France,Merlot,Cantina River Bend,82,17.0
|
| 943 |
+
Quinta Thunder Ridge Merlot 2016,France,Merlot,Quinta Thunder Ridge,91,39.0
|
| 944 |
+
Estate La Rosa Pinot Grigio 2021,Italy,Pinot Grigio,Estate La Rosa,90,35.0
|
| 945 |
+
Bodega Starfall Barbera 2022,Italy,Barbera,Bodega Starfall,87,22.0
|
| 946 |
+
Weingut Starfall Pinot Noir 2022,US,Pinot Noir,Weingut Starfall,95,38.0
|
| 947 |
+
Casa Cedar Falls Pinot Grigio 2018,Italy,Pinot Grigio,Casa Cedar Falls,83,19.0
|
| 948 |
+
Cantina San Pietro Sangiovese 2019,Italy,Sangiovese,Cantina San Pietro,81,10.0
|
| 949 |
+
Château San Pietro Merlot 2019,France,Merlot,Château San Pietro,85,24.0
|
| 950 |
+
Cantina Crystal Lake Tempranillo 2021,Spain,Tempranillo,Cantina Crystal Lake,87,23.0
|
| 951 |
+
Estate Moonlight Merlot 2015,Chile,Merlot,Estate Moonlight,88,39.0
|
| 952 |
+
Cantina Verde Torrontés 2020,Argentina,Torrontés,Cantina Verde,87,20.0
|
| 953 |
+
Estate del Monte Pinot Grigio 2019,Italy,Pinot Grigio,Estate del Monte,89,27.0
|
| 954 |
+
Bodega San Pietro Chardonnay 2017,France,Chardonnay,Bodega San Pietro,82,21.0
|
| 955 |
+
Weingut Sierra Monastrell 2020,Spain,Monastrell,Weingut Sierra,93,52.0
|
| 956 |
+
Bodega Moonlight Primitivo 2019,Italy,Primitivo,Bodega Moonlight,87,16.0
|
| 957 |
+
Bodega San Pietro Merlot 2018,France,Merlot,Bodega San Pietro,92,39.0
|
| 958 |
+
Casa Thunder Ridge Nebbiolo 2023,Italy,Nebbiolo,Casa Thunder Ridge,89,40.0
|
| 959 |
+
Vineyard Cedar Falls Syrah 2016,Argentina,Syrah,Vineyard Cedar Falls,89,37.0
|
| 960 |
+
Weingut Stone Creek Nebbiolo 2017,Italy,Nebbiolo,Weingut Stone Creek,90,41.0
|
| 961 |
+
Bodega Pacific Ridge Syrah 2015,Argentina,Syrah,Bodega Pacific Ridge,89,35.0
|
| 962 |
+
Bodega El Dorado Cabernet Sauvignon 2019,US,Cabernet Sauvignon,Bodega El Dorado,90,29.0
|
| 963 |
+
Domaine La Rosa Nebbiolo 2015,Italy,Nebbiolo,Domaine La Rosa,93,54.0
|
| 964 |
+
Casa Crystal Lake Tinto Roriz 2015,Portugal,Tinto Roriz,Casa Crystal Lake,88,11.0
|
| 965 |
+
Château San Pietro Monastrell 2016,Spain,Monastrell,Château San Pietro,90,17.0
|
| 966 |
+
Estate du Soleil Chardonnay 2016,Australia,Chardonnay,Estate du Soleil,87,20.0
|
| 967 |
+
Bodega Moonlight Pinot Grigio 2018,Italy,Pinot Grigio,Bodega Moonlight,93,52.0
|
| 968 |
+
Château Moonlight Tempranillo 2018,Spain,Tempranillo,Château Moonlight,85,13.0
|
| 969 |
+
Château San Pietro Chardonnay 2018,US,Chardonnay,Château San Pietro,95,36.0
|
| 970 |
+
Cantina San Pietro Riesling 2017,Australia,Riesling,Cantina San Pietro,87,22.0
|
| 971 |
+
Vineyard San Pietro Cabernet Sauvignon 2020,Argentina,Cabernet Sauvignon,Vineyard San Pietro,82,16.0
|
| 972 |
+
Estate Pacific Ridge Sangiovese 2023,Italy,Sangiovese,Estate Pacific Ridge,88,26.0
|
| 973 |
+
Weingut Cedar Falls Cabernet Sauvignon 2019,US,Cabernet Sauvignon,Weingut Cedar Falls,85,10.0
|
| 974 |
+
Vineyard Bella Notte Zinfandel 2016,US,Zinfandel,Vineyard Bella Notte,91,25.0
|
| 975 |
+
Château Iron Gate Merlot 2016,Chile,Merlot,Château Iron Gate,85,21.0
|
| 976 |
+
Bodega Oak Hill Syrah 2021,France,Syrah,Bodega Oak Hill,86,17.0
|
| 977 |
+
Bodega La Rosa Cabernet Sauvignon 2020,US,Cabernet Sauvignon,Bodega La Rosa,80,25.0
|
| 978 |
+
Vineyard San Pietro Zweigelt 2018,Austria,Zweigelt,Vineyard San Pietro,86,20.0
|
| 979 |
+
Quinta Crystal Lake Cabernet Sauvignon 2019,Argentina,Cabernet Sauvignon,Quinta Crystal Lake,80,17.0
|
| 980 |
+
Vineyard Iron Gate Tinto Roriz 2023,Portugal,Tinto Roriz,Vineyard Iron Gate,81,18.0
|
| 981 |
+
Cantina El Dorado Merlot 2017,France,Merlot,Cantina El Dorado,91,20.0
|
| 982 |
+
Château Alta Vista Sangiovese 2021,Italy,Sangiovese,Château Alta Vista,91,43.0
|
| 983 |
+
Domaine La Rosa Chardonnay 2023,US,Chardonnay,Domaine La Rosa,89,22.0
|
| 984 |
+
Cantina Moonlight Tinto Roriz 2019,Portugal,Tinto Roriz,Cantina Moonlight,84,16.0
|
| 985 |
+
Château River Bend Verdejo 2016,Spain,Verdejo,Château River Bend,87,29.0
|
| 986 |
+
Château del Monte Cabernet Sauvignon 2017,France,Cabernet Sauvignon,Château del Monte,87,28.0
|
| 987 |
+
Vineyard Verde Monastrell 2019,Spain,Monastrell,Vineyard Verde,83,18.0
|
| 988 |
+
Cantina Starfall Zinfandel 2023,US,Zinfandel,Cantina Starfall,94,52.0
|
| 989 |
+
Château Oak Hill Albariño 2019,Spain,Albariño,Château Oak Hill,91,31.0
|
| 990 |
+
Weingut Golden Valley Albariño 2015,Spain,Albariño,Weingut Golden Valley,87,23.0
|
| 991 |
+
Quinta du Soleil Sangiovese 2020,Italy,Sangiovese,Quinta du Soleil,88,16.0
|
| 992 |
+
Estate del Monte Merlot 2018,France,Merlot,Estate del Monte,88,21.0
|
| 993 |
+
Domaine Pacific Ridge Pinot Grigio 2016,Italy,Pinot Grigio,Domaine Pacific Ridge,80,24.0
|
| 994 |
+
Vineyard Crystal Lake Chardonnay 2023,France,Chardonnay,Vineyard Crystal Lake,87,17.0
|
| 995 |
+
Château Golden Valley Cabernet Sauvignon 2021,Australia,Cabernet Sauvignon,Château Golden Valley,85,11.0
|
| 996 |
+
Domaine Bella Notte Monastrell 2020,Spain,Monastrell,Domaine Bella Notte,83,22.0
|
| 997 |
+
Vineyard Bella Notte Monastrell 2022,Spain,Monastrell,Vineyard Bella Notte,86,12.0
|
| 998 |
+
Weingut Sierra Cabernet Sauvignon 2015,US,Cabernet Sauvignon,Weingut Sierra,95,58.0
|
| 999 |
+
Domaine Crystal Lake Syrah 2016,France,Syrah,Domaine Crystal Lake,90,25.0
|
| 1000 |
+
Cantina River Bend Monastrell 2018,Spain,Monastrell,Cantina River Bend,85,16.0
|
| 1001 |
+
Weingut River Bend Chardonnay 2023,France,Chardonnay,Weingut River Bend,90,32.0
|