yolo

app/app.py

@@ -25,23 +25,24 @@ server = app.server
 
 wine_similarity_df = pd.read_csv('data/wine_similarity.csv')
 wine_list = wine_similarity_df['NAME'].unique()
+# wine_list.sort()
 geo = pd.read_csv('data/processed_wineyards.csv')
 wine_regions=list(geo['Region'].unique()) + ['all']
 wine_country = list(geo['Country'].unique()) + ['all']
 # local_type = list(geo['LOCAL TYPE'].unique()) + ['all']
 
-# WT_GLOBAL = '*' if 
+user_rating_df = pd.read_csv('data/simulated_ratings.csv')
+user_rating_df.set_index('user', inplace=True)
+user_rating_df['user'] = user_rating_df.index
+user_ids = user_rating_df['user']
 
 
-# wine_country = geo['Country'].unique()
-
 
 ## Layout ##
 
 dashboard_layout =  html.Div([
-    dcc.Link('About this project', href='/wiki'),
-
-    dcc.Graph(id='graph-content'),
+    # dcc.Link('About this project', href='/wiki'),
+    html.H1(children='Wineyards around the world', style={'textAlign':'center'}),
     html.H1(children='Country', style={'textAlign':'center'}),
     dcc.Dropdown(wine_country, wine_country[-1], id='dropdown-wc'),
     html.H1(children='Region', style={'textAlign':'center'}),
@@ -50,7 +51,13 @@ dashboard_layout =  html.Div([
 
     html.H1(children='Wine Recommender', style={'textAlign':'center'}),
     dcc.Dropdown(wine_list, wine_list[0], id='dropdown-selection'),
-    html.Div(id='wine-recommendation', children=''),
+    html.Div(id='wine-recommendation', children='', style={'textAlign':'center'}),
+
+
+    html.H1(children='Wine Recommender based on feedback and other user', style={'textAlign':'center'}),
+    dcc.Dropdown(user_ids, user_ids[0], id='dropdown-selection-user'),
+    html.Div(id='wine-recommendation-from-user', children='', style={'textAlign':'center'}),
+
 ])
 
 
@@ -61,7 +68,6 @@ dashboard_layout =  html.Div([
 def set_wine_type_options(selected_wine_type):
     # Return the options based on the selected wine country
     pattern = r'.*' if selected_wine_type == 'all' else rf'{selected_wine_type}'
-    #selected_wine_type = r'*' if selected_wine_type == r'all' else selected_wine_type
     return list(geo[geo['Country'].str.match(pattern, na=False)]['Region'].unique()) + ['all']
 
 
@@ -108,27 +114,32 @@ def display_page(pathname):
 
 
 @app.callback(
-    Output('graph-content', 'figure'),
     Output('wine-recommendation', 'children'),
     Output('world-map-fig', 'figure'),
+    Output('wine-recommendation-from-user', 'children'),
     Input('dropdown-selection', 'value'),
     Input('dropdown-wr', 'value'),
-    Input('dropdown-wc', 'value')
+    Input('dropdown-wc', 'value'),
+    Input('dropdown-selection-user', 'value')
 )
-def update_graph(value,wr,wc):
+def update_graph(value,wr,wc, user_value):
     ### Wine Recommendation ###
     recommended_wines = None
     if value:
         recommended_wines = core.get_top_5_similar_wines(value, wine_similarity_df)[1:]
-        recommended_wines = "; ".join(recommended_wines)
+        recommended_wines = f"Based on ´{value}´, we recommend: "+"; ".join(recommended_wines)
+
+
+    ## Wine Recommendation from users feedback
+
+    wine_recommendation_from_user = core.recommend_wine_from_users(user_rating_df, user_value, 3)
+    wine_recommendation_from_user = f"Based on user information, we recommend: "+"; ".join(wine_recommendation_from_user)
 
 
     ### World Map of wineyards ###
 
     geo_df = pd.read_csv('data/processed_wineyards.csv')
     wr = r'.*' if wr == 'all' else rf'{wr}'
-    #wr = r'*' if wr == 'all' else wr # wine region poiseu tbm tinha assim, mas agr tenho 2 filtros nao posos fazer infinitas condicoes assim ja sao 4, rota 
-    #wc = r'*' if wc == 'all' else wc # wine country & geo_df['Country'].str.match(wc)
     wc = r'.*' if wc == 'all' else rf'{wc}'
     geo_df = geo_df[geo_df['Region'].str.contains(wr, case=False, na=False, regex=True) & geo_df['Country'].str.contains(wc, case=False, na=False, regex=True)]
 
@@ -151,7 +162,7 @@ def update_graph(value,wr,wc):
     
 
 
-    return px.line(df, x='year', y='pop'), recommended_wines, world_map_fig
+    return recommended_wines, world_map_fig, wine_recommendation_from_user
 
 
 if __name__ == "__main__":

app/core.py

@@ -12,11 +12,13 @@ def get_top_5_similar_wines(wine_name: str, df: pd.DataFrame) -> pd.DataFrame:
 
     return res
 
-def recommend_wine(ratings_df, user, n=5):
-    user_cluster = ratings_df.loc[user, 'cluster']
-    user_ratings = ratings_df.loc[user].drop('cluster')
+def recommend_wine_from_users(df:pd.DataFrame, user:str, n=5):
+    user_cluster = df.loc[user, 'cluster']
+    user_ratings = df.loc[user].drop('cluster')
     user_unrated = user_ratings[user_ratings == 0].index
-    cluster_users = ratings_df[ratings_df['cluster'] == user_cluster]
-    cluster_avg = cluster_users.mean().drop('cluster')
+    cluster_users = df[df['cluster'] == user_cluster]
+    cluster_users.drop(['cluster', 'user'], axis=1, inplace=True)
+
+    cluster_avg = cluster_users.mean()
     cluster_avg = cluster_avg[user_unrated]
     return cluster_avg.sort_values(ascending=False).keys()[:n].tolist()

app/dashboard copy.ipynb

@@ -1,229 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/ddcosta/Documents/TDV/.venv/lib/python3.9/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "        <iframe\n",
-       "            width=\"100%\"\n",
-       "            height=\"650\"\n",
-       "            src=\"http://0.0.0.0:8050/\"\n",
-       "            frameborder=\"0\"\n",
-       "            allowfullscreen\n",
-       "            \n",
-       "        ></iframe>\n",
-       "        "
-      ],
-      "text/plain": [
-       "<IPython.lib.display.IFrame at 0x15619fbe0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import os\n",
-    "import plotly.express as px\n",
-    "import plotly.graph_objects as go\n",
-    "import pandas as pd\n",
-    "from dash import Dash, html, dcc, Input, Output, callback\n",
-    "import plotly.express as px\n",
-    "import numpy as np\n",
-    "from plotly.subplots import make_subplots\n",
-    "import core\n",
-    "\n",
-    "df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminder_unfiltered.csv')\n",
-    "debug = False\n",
-    "\n",
-    "external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']\n",
-    "\n",
-    "app = Dash(__name__, external_stylesheets=external_stylesheets)\n",
-    "\n",
-    "app.layout = html.Div([\n",
-    "    dcc.Location(id='url', refresh=False),\n",
-    "    html.Div(id='page-content')\n",
-    "])\n",
-    "\n",
-    "server = app.server\n",
-    "\n",
-    "\n",
-    "wine_similarity_df = pd.read_csv('data/wine_similarity.csv')\n",
-    "wine_list = wine_similarity_df['NAME'].unique()\n",
-    "geo = pd.read_csv('data/processed_wineyards.csv')\n",
-    "wine_regions=list(geo['Region'].unique()) + ['all']\n",
-    "wine_country = list(geo['Country'].unique()) + ['all']\n",
-    "# local_type = list(geo['LOCAL TYPE'].unique()) + ['all']\n",
-    "\n",
-    "# WT_GLOBAL = '*' if \n",
-    "\n",
-    "\n",
-    "# wine_country = geo['Country'].unique()\n",
-    "\n",
-    "\n",
-    "## Layout ##\n",
-    "\n",
-    "dashboard_layout =  html.Div([\n",
-    "    dcc.Link('About this project', href='/wiki'),\n",
-    "\n",
-    "    dcc.Graph(id='graph-content'),\n",
-    "    html.H1(children='Country', style={'textAlign':'center'}),\n",
-    "    dcc.Dropdown(wine_country, wine_country[-1], id='dropdown-wc'),\n",
-    "    html.H1(children='Region', style={'textAlign':'center'}),\n",
-    "    dcc.Dropdown(['all'],'all', id='dropdown-wr'),\n",
-    "    dcc.Graph(id='world-map-fig'),\n",
-    "\n",
-    "    html.H1(children='Wine Recommender', style={'textAlign':'center'}),\n",
-    "    dcc.Dropdown(wine_list, wine_list[0], id='dropdown-selection'),\n",
-    "    html.Div(id='wine-recommendation', children=''),\n",
-    "])\n",
-    "\n",
-    "\n",
-    "@app.callback(\n",
-    "    Output('dropdown-wr', 'options'),\n",
-    "    Input('dropdown-wc', 'value')\n",
-    ")\n",
-    "def set_wine_type_options(selected_wine_type):\n",
-    "    # Return the options based on the selected wine country\n",
-    "    pattern = r'.*' if selected_wine_type == 'all' else rf'{selected_wine_type}'\n",
-    "    #selected_wine_type = r'*' if selected_wine_type == r'all' else selected_wine_type\n",
-    "    return list(geo[geo['Country'].str.match(pattern, na=False)]['Region'].unique()) + ['all']\n",
-    "\n",
-    "\n",
-    "wiki_layout = html.Div([\n",
-    "    dcc.Link('Dashboard', href='/'),\n",
-    "\n",
-    "    html.H1('About this project'),\n",
-    "\n",
-    "    html.Div([\n",
-    "        html.Div([\n",
-    "\n",
-    "                    html.H3('What is this project about?'),\n",
-    "\n",
-    "                    html.P('We are a group of 4 Computer Science Engineering Students with a solid Artificial Intelligence background.'),\n",
-    "                    html.P('This project aims to showcase AI applications for improving Wine Tourism for SOGRAPE.'),\n",
-    "\n",
-    "\n",
-    "                    html.H3('\\'Bout us'),\n",
-    "                    html.Img(src='/assets/tourdevino_logo.webp', style={'width': '40%', 'height': 'auto', 'display': 'block', 'margin-left': 'auto', 'margin-right': 'auto'}),\n",
-    "                    html.P('This project was developed by a team of 4, in the context of the SOGRAPE 2024 hackathon.'),\n",
-    "                    html.P('The team members are:'),\n",
-    "                    html.H4('Rui Melo'),\n",
-    "                    html.H4('André Catarino'),\n",
-    "                    html.H4('Dinis Costa'),\n",
-    "                    html.H4('Paulo Fidalgo'),\n",
-    "\n",
-    "\n",
-    "        ], className='six columns'),], className='row'),\n",
-    "],\n",
-    "style={'background-color': '#333', 'font-family': 'Fantasy', 'color': '#999', 'padding': '10px'}\n",
-    "\n",
-    ")\n",
-    "\n",
-    "# Update the index\n",
-    "@callback(Output('page-content', 'children'), Input('url', 'pathname'))\n",
-    "def display_page(pathname):\n",
-    "    if pathname == '/':\n",
-    "        return dashboard_layout\n",
-    "    elif pathname == '/wiki':\n",
-    "        return wiki_layout\n",
-    "    else:\n",
-    "        return '404'\n",
-    "    # You could also return a 404 \"URL not found\" page here\n",
-    "\n",
-    "\n",
-    "@app.callback(\n",
-    "    Output('graph-content', 'figure'),\n",
-    "    Output('wine-recommendation', 'children'),\n",
-    "    Output('world-map-fig', 'figure'),\n",
-    "    Input('dropdown-selection', 'value'),\n",
-    "    Input('dropdown-wr', 'value'),\n",
-    "    Input('dropdown-wc', 'value')\n",
-    ")\n",
-    "def update_graph(value,wr,wc):\n",
-    "    ### Wine Recommendation ###\n",
-    "    recommended_wines = None\n",
-    "    if value:\n",
-    "        recommended_wines = core.get_top_5_similar_wines(value, wine_similarity_df)[1:]\n",
-    "        recommended_wines = \"; \".join(recommended_wines)\n",
-    "\n",
-    "\n",
-    "    ### World Map of wineyards ###\n",
-    "\n",
-    "    geo_df = pd.read_csv('data/processed_wineyards.csv')\n",
-    "    wr = r'.*' if wr == 'all' else rf'{wr}'\n",
-    "    #wr = r'*' if wr == 'all' else wr # wine region poiseu tbm tinha assim, mas agr tenho 2 filtros nao posos fazer infinitas condicoes assim ja sao 4, rota \n",
-    "    #wc = r'*' if wc == 'all' else wc # wine country & geo_df['Country'].str.match(wc)\n",
-    "    wc = r'.*' if wc == 'all' else rf'{wc}'\n",
-    "    geo_df = geo_df[geo_df['Region'].str.contains(wr, case=False, na=False, regex=True) & geo_df['Country'].str.contains(wc, case=False, na=False, regex=True)]\n",
-    "\n",
-    "\n",
-    "    world_map_fig = px.scatter_map(geo_df,\n",
-    "                            lat=geo_df['coord_x'],\n",
-    "                            lon=geo_df['coord_y'],\n",
-    "                            hover_name=geo_df['name'],\n",
-    "                            zoom=4,\n",
-    "                            hover_data={\n",
-    "                                'IsTouristic': True,\n",
-    "                                'Wine Type': True,\n",
-    "                                'Country': True,\n",
-    "                                'Region': True,\n",
-    "                                'Address': True,\n",
-    "\n",
-    "                            },\n",
-    "                            title='Wineyards around the world',\n",
-    "                            )\n",
-    "    \n",
-    "\n",
-    "\n",
-    "    return px.line(df, x='year', y='pop'), recommended_wines, world_map_fig\n",
-    "\n",
-    "\n",
-    "if __name__ == \"__main__\":\n",
-    "    app.run_server(host=\"0.0.0.0\", port=\"8050\", debug=debug)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "atc-smart-shower-YhjpRjjr-py3.10",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.6"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

app/dashboard.ipynb

@@ -2,9 +2,19 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/b4/lwfgccm95kqd2skcwvrt2fr00000gn/T/ipykernel_33833/349649994.py:58: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
@@ -20,11 +30,31 @@
        "        "
       ],
       "text/plain": [
-       "<IPython.lib.display.IFrame at 0x169ff4f10>"
+       "<IPython.lib.display.IFrame at 0x2adb0eb30>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/ruimelo/Documents/GitHub/eda/app/core.py:20: SettingWithCopyWarning:\n",
+      "\n",
+      "\n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "\n",
+      "/Users/ruimelo/Documents/GitHub/eda/app/core.py:20: SettingWithCopyWarning:\n",
+      "\n",
+      "\n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "\n"
+     ]
     }
    ],
    "source": [
@@ -55,23 +85,24 @@
     "\n",
     "wine_similarity_df = pd.read_csv('data/wine_similarity.csv')\n",
     "wine_list = wine_similarity_df['NAME'].unique()\n",
+    "# wine_list.sort()\n",
     "geo = pd.read_csv('data/processed_wineyards.csv')\n",
     "wine_regions=list(geo['Region'].unique()) + ['all']\n",
     "wine_country = list(geo['Country'].unique()) + ['all']\n",
     "# local_type = list(geo['LOCAL TYPE'].unique()) + ['all']\n",
     "\n",
-    "# WT_GLOBAL = '*' if \n",
-    "\n",
+    "user_rating_df = pd.read_csv('data/simulated_ratings.csv')\n",
+    "user_rating_df.set_index('user', inplace=True)\n",
+    "user_rating_df['user'] = user_rating_df.index\n",
+    "user_ids = user_rating_df['user']\n",
     "\n",
-    "# wine_country = geo['Country'].unique()\n",
     "\n",
     "\n",
     "## Layout ##\n",
     "\n",
     "dashboard_layout =  html.Div([\n",
-    "    dcc.Link('About this project', href='/wiki'),\n",
-    "\n",
-    "    dcc.Graph(id='graph-content'),\n",
+    "    # dcc.Link('About this project', href='/wiki'),\n",
+    "    html.H1(children='Wineyards around the world', style={'textAlign':'center'}),\n",
     "    html.H1(children='Country', style={'textAlign':'center'}),\n",
     "    dcc.Dropdown(wine_country, wine_country[-1], id='dropdown-wc'),\n",
     "    html.H1(children='Region', style={'textAlign':'center'}),\n",
@@ -80,7 +111,13 @@
     "\n",
     "    html.H1(children='Wine Recommender', style={'textAlign':'center'}),\n",
     "    dcc.Dropdown(wine_list, wine_list[0], id='dropdown-selection'),\n",
-    "    html.Div(id='wine-recommendation', children=''),\n",
+    "    html.Div(id='wine-recommendation', children='', style={'textAlign':'center'}),\n",
+    "\n",
+    "\n",
+    "    html.H1(children='Wine Recommender based on feedback and other user', style={'textAlign':'center'}),\n",
+    "    dcc.Dropdown(user_ids, user_ids[0], id='dropdown-selection-user'),\n",
+    "    html.Div(id='wine-recommendation-from-user', children='', style={'textAlign':'center'}),\n",
+    "\n",
     "])\n",
     "\n",
     "\n",
@@ -91,7 +128,6 @@
     "def set_wine_type_options(selected_wine_type):\n",
     "    # Return the options based on the selected wine country\n",
     "    pattern = r'.*' if selected_wine_type == 'all' else rf'{selected_wine_type}'\n",
-    "    #selected_wine_type = r'*' if selected_wine_type == r'all' else selected_wine_type\n",
     "    return list(geo[geo['Country'].str.match(pattern, na=False)]['Region'].unique()) + ['all']\n",
     "\n",
     "\n",
@@ -138,27 +174,32 @@
     "\n",
     "\n",
     "@app.callback(\n",
-    "    Output('graph-content', 'figure'),\n",
     "    Output('wine-recommendation', 'children'),\n",
     "    Output('world-map-fig', 'figure'),\n",
+    "    Output('wine-recommendation-from-user', 'children'),\n",
     "    Input('dropdown-selection', 'value'),\n",
     "    Input('dropdown-wr', 'value'),\n",
-    "    Input('dropdown-wc', 'value')\n",
+    "    Input('dropdown-wc', 'value'),\n",
+    "    Input('dropdown-selection-user', 'value')\n",
     ")\n",
-    "def update_graph(value,wr,wc):\n",
+    "def update_graph(value,wr,wc, user_value):\n",
     "    ### Wine Recommendation ###\n",
     "    recommended_wines = None\n",
     "    if value:\n",
     "        recommended_wines = core.get_top_5_similar_wines(value, wine_similarity_df)[1:]\n",
-    "        recommended_wines = \"; \".join(recommended_wines)\n",
+    "        recommended_wines = f\"Based on ´{value}´, we recommend: \"+\"; \".join(recommended_wines)\n",
+    "\n",
+    "\n",
+    "    ## Wine Recommendation from users feedback\n",
+    "\n",
+    "    wine_recommendation_from_user = core.recommend_wine_from_users(user_rating_df, user_value, 3)\n",
+    "    wine_recommendation_from_user = f\"Based on user information, we recommend: \"+\"; \".join(wine_recommendation_from_user)\n",
     "\n",
     "\n",
     "    ### World Map of wineyards ###\n",
     "\n",
     "    geo_df = pd.read_csv('data/processed_wineyards.csv')\n",
     "    wr = r'.*' if wr == 'all' else rf'{wr}'\n",
-    "    #wr = r'*' if wr == 'all' else wr # wine region poiseu tbm tinha assim, mas agr tenho 2 filtros nao posos fazer infinitas condicoes assim ja sao 4, rota \n",
-    "    #wc = r'*' if wc == 'all' else wc # wine country & geo_df['Country'].str.match(wc)\n",
     "    wc = r'.*' if wc == 'all' else rf'{wc}'\n",
     "    geo_df = geo_df[geo_df['Region'].str.contains(wr, case=False, na=False, regex=True) & geo_df['Country'].str.contains(wc, case=False, na=False, regex=True)]\n",
     "\n",
@@ -181,7 +222,7 @@
     "    \n",
     "\n",
     "\n",
-    "    return px.line(df, x='year', y='pop'), recommended_wines, world_map_fig\n",
+    "    return recommended_wines, world_map_fig, wine_recommendation_from_user\n",
     "\n",
     "\n",
     "if __name__ == \"__main__\":\n",

app/data/simulated_ratings.csv

@@ -1,101 +1,101 @@
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