Merge remote-tracking branch 'origin/main'

epfl-ada · Dec 20, 2024 · 2b5a6b9 · 2b5a6b9
2 parents 555bf5c + 44e4817
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Showing 9 changed files with 128 additions and 48 deletions.
diff --git a/_includes/aroma_treemap.html b/_includes/aroma_treemap.html
diff --git a/_includes/mouthfeel_treemap.html b/_includes/mouthfeel_treemap.html
diff --git a/_includes/palate_treemap.html b/_includes/palate_treemap.html
diff --git a/_includes/taste_treemap.html b/_includes/taste_treemap.html
diff --git a/data_story_htlm.ipynb b/data_story_htlm.ipynb
@@ -8929,7 +8929,7 @@
     ")\n",
     "\n",
     "fig.show()\n",
-    "fig.write_html(\"src/graph/highest_rated_beer_styles_by_states_season.html\")"
+    "fig.write_html(\"_includes/highest_rated_beer_styles_by_states_season.html\")"
    ]
   },
   {
@@ -10809,8 +10809,8 @@
     "fig_high.show()\n",
     "fig_low.show()\n",
     "\n",
-    "fig_high.write_html(\"src/graph/season_ratings_high_abv.html\")\n",
-    "fig_low.write_html(\"src/graph/season_ratings_low_abv.html\")"
+    "fig_high.write_html(\"_includes/season_ratings_high_abv.html\")\n",
+    "fig_low.write_html(\"_includes/season_ratings_low_abv.html\")"
    ]
   },
   {

diff --git a/index.md b/index.md
@@ -138,7 +138,19 @@ While sentiment analysis uncovers the emotional tone behind a review, semantic a
 By analyzing the specific language used in high rated reviews, we can uncover the key qualities that turn a simple beer into a fan favorite. In this section, we will dive into a semantic comparison of beer reviews across seasons to explore which characteristics define the most-loved beers in each time of the year. 
 
 <div style="display: flex; justify-content: center;">
-  {% include mouthfeel_treemap.html.html %}
+  {% include palate_treemap.html %}
+</div>
+
+<div style="display: flex; justify-content: center;">
+  {% include aroma_treemap.html %}
+</div>
+
+<div style="display: flex; justify-content: center;">
+  {% include taste_treemap.html %}
+</div>
+
+<div style="display: flex; justify-content: center;">
+  {% include mouthfeel_treemap.html %}
 </div>
 
 ##### Winter: the warmth of rich flavors

diff --git a/milestoneP3 copy.ipynb b/milestoneP3 copy.ipynb
diff --git a/milestoneP3.ipynb b/milestoneP3.ipynb
diff --git a/src/scripts/semantic_analysis.py b/src/scripts/semantic_analysis.py
@@ -250,6 +250,10 @@ def analyse_flavours(reviews: pd.DataFrame):
 import matplotlib.pyplot as plt
 import seaborn as sns
 
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+
 def group_styles_by_flavours(reviews):
     """
     Groups beer reviews by style, normalizes flavour mentions, and plots the distribution.
@@ -266,21 +270,21 @@ def group_styles_by_flavours(reviews):
     flavours = ['hoppy', 'malty', 'fruity', 'spicy', 'citrus', 
                     'sweet', 'bitter', 'sour', 'tart', 'crisp']
 
-    # Validate that all necessary columns are present
+
     missing_flavours = [flavour for flavour in flavours if flavour not in reviews.columns]
     if missing_flavours:
         raise ValueError(f"The following flavour columns are missing in the DataFrame: {missing_flavours}")
+
     style_flavours = reviews.groupby('style_simp')[flavours].sum()
+
     print("Calculating total flavour mentions per style...")
     style_flavours['total_flavours'] = style_flavours.sum(axis=1)
     style_flavours['total_flavours'].replace(0, pd.NA, inplace=True)
     normalized_flavours = style_flavours[flavours].div(style_flavours['total_flavours'], axis=0) * 100
-
     normalized_flavours.dropna(inplace=True)
-
+    
     normalized_flavours = normalized_flavours.reset_index()
 
-    # Melt the DataFrame to long format for seaborn
     plot_data = normalized_flavours.melt(
         id_vars='style_simp', 
         value_vars=flavours, 
@@ -300,13 +304,23 @@ def group_styles_by_flavours(reviews):
         palette='Set2'  # Choose a color palette for better distinction
     )
 
+    # Set plot titles and labels
     plt.title('Normalized Flavour Occurrences in US Beer Reviews by Style', fontsize=16)
     plt.xlabel('Beer Style', fontsize=14)
     plt.ylabel('Percentage of Flavour Mentions (%)', fontsize=14)
+
+    # Rotate x-axis labels for better readability
     plt.xticks(rotation=45, ha='right', fontsize=12)
+
+    # Adjust legend
     plt.legend(title='Flavour', bbox_to_anchor=(1.05, 1), loc='upper left', fontsize=12)
+
+    # Improve layout to prevent clipping of labels and legend
     plt.tight_layout()
+
+    # Display the plot
     plt.show()
+
     return normalized_flavours