yolo

output_dataset.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c49abfa2591aac4b75847bb0f31e4ed5581eb94727308af9c5c6c31657d4946c
-size 22475137
+oid sha256:822e90e030672c607877152140280388b8a0d803489c396e06fc5b9e57fb0724
+size 22498566

par.py → process.py

@@ -28,18 +28,23 @@ def collect_data(directory):
     image_files = {re.search(r'(\d+)', filename).group(1): filename
                    for filename in os.listdir(directory) if filename.endswith('.jpg')}
 
-    # Iterate over all files in the directory and organize them by problem ID
-    for filename in os.listdir(directory):
-        problem_id = filename.split('.')[0]
-        file_type = filename.split('.')[-1]
-        file_path = os.path.join(directory, filename)
-
+    # Identify Markdown and solution Markdown files and establish correct problem IDs
+    markdown_files = [f for f in os.listdir(directory) if f.endswith('.md') or f.endswith('.sol.md')]
+    for mfile in markdown_files:
+        # Adjust the pattern if problem IDs include characters before "sol"
+        problem_id = re.sub(r'sol$', '', mfile.split('.')[0])  # Strip "sol" from end
         if problem_id not in data:
             data[problem_id] = {'Problem ID': problem_id, 'Images': [], 'in': None, 'out': None, 'cpp': None, 'md': None, 'sol.md': None}
 
-        if file_type in ['in', 'out', 'cpp', 'md', 'sol.md']:
-            content = encode_file(file_path)
-            if content is not None:
+    # Now associate other files with these problem IDs
+    for filename in os.listdir(directory):
+        problem_id = re.sub(r'sol$', '', filename.split('.')[0])  # Strip "sol" from end if present
+        if problem_id in data:  # Only process if the problem_id is recognized
+            file_type = filename.split('.')[-1]
+            file_path = os.path.join(directory, filename)
+            content = encode_file(file_path) if not filename.endswith('.jpg') else None
+
+            if file_type in ['in', 'out', 'cpp', 'md', 'sol.md']:
                 data[problem_id][file_type] = content
                 if file_type in ['md', 'sol.md']:
                     image_ids = extract_images(content)

viz.py

@@ -1,10 +1,15 @@
 import pandas as pd
+# pd.set_option('display.max_columns', None)  # None means no limit
+# pd.set_option('display.width', None)        # None means use the current terminal width
 
 # Load the Parquet file
 df = pd.read_parquet('output_dataset.parquet')
 
+print(df.columns)
+
 # Display the first few rows of the dataframe
-print(df.head())
+print(df)
 
 # Basic statistics for numerical columns
-print(df.describe())
+# print(df.describe())
+#