Add Chinese titles to graphs

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.ttf filter=lfs diff=lfs merge=lfs -text

mingliu.ttf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:00b16e0dc854c9d045aecc71aab9b0f76b07cad58cccb3e092ef3ef1da2dc997
+size 6272080

page_likert.py

@@ -3,10 +3,14 @@ import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
 from datasets import load_dataset
+from matplotlib.font_manager import FontProperties
 
 @st.cache_data
 def show():
 
+    # Chinese font
+    chinese_font = FontProperties(fname='mingliu.ttf')
+
     # Get Data
     dataset = load_dataset("krishaamer/taiwanese-college-students", data_files={'train': 'clean.csv'})
 
@@ -143,11 +147,11 @@ def show():
         # Loop through each category in likert_fields to create visualizations
         for category, fields in likert_fields.items():
             st.subheader(f'Distribution of Responses for {translation_mapping[category]}')
-            
+
             # Calculate the number of rows needed for this category
             num_fields = len(fields)
-            num_rows = -(-num_fields // 2)  # This is equivalent to ceil(num_fields / 2)
-            
+            num_rows = -(-num_fields // 2)  # Equivalent to ceil(num_fields / 2)
+
             # Create subplots with 2 columns for this category
             fig, axs = plt.subplots(num_rows, 2, figsize=(15, 5 * num_rows))
             axs = axs.flatten()  # Flatten the array of subplots
@@ -156,9 +160,12 @@ def show():
             for i, field in enumerate(fields):
                 # Create the bar plot
                 sns.countplot(x=f"{field} ({field_translation_mapping[category][i]})", data=df_translated, ax=axs[i])
-                
+
                 # Add title and labels
-                axs[i].set_title(field_translation_mapping[category][i])
+                title_chinese = field
+                title_english = field_translation_mapping[category][i]
+                axs[i].set_title(f"{title_chinese}\n{title_english}", fontproperties=chinese_font)  # Add both versions to the title
+
                 axs[i].set_xlabel('Likert Scale')
                 axs[i].set_ylabel('Frequency')
 
@@ -167,5 +174,4 @@ def show():
                 fig.delaxes(axs[i])
 
             # Show the plot in Streamlit
-            st.pyplot(fig)
-
+            st.pyplot(fig)