Bugs table

app.py

@@ -16,8 +16,7 @@ def fetch_data():
     for issue in issues:
         issues_data.append(
             {
-                'Number': issue.number,
-                'Title': issue.title, 
+                'Issue': f"{issue.number} - {issue.title}", 
                 'State': issue.state, 
                 'Created at': issue.created_at, 
                 'Closed at': issue.closed_at,
@@ -34,8 +33,7 @@ def save_data(df):
 
 
 st.title(f"GitHub Issues Dashboard for {repo.name}")
-
-fetching_data = st.empty()
+status = st.status(label="Loading data...", state="running")
 
 try:
     df = pd.read_json("issues.json")
@@ -43,8 +41,6 @@ except:
     df = fetch_data()
     save_data(df)
 
-status = st.status(label="Loading data...", state="running")
-
 # Section 1: Issue activity metrics
 st.header("Issue activity metrics")
 
@@ -65,47 +61,77 @@ with col2:
 # # TODO Dataframe: Unresolved conversations
 # ## Issues with new comments. Sorted by number of new comments (based on timeframe above) and/or date of last comment.
 
-# Section 2: Issue classification
-st.header("Issue classification")
-
-## Dataframe: Number of open issues by label.
-st.subheader("Top ten labels by number of open issues:")
-open_issues_exploded = open_issues.explode("Labels")
-label_counts = open_issues_exploded.value_counts("Labels").to_frame()
-
-def generate_labels_link(labels):
-    links = []
-    for label in labels:
-        label = label.replace(" ", "+")
-        links.append(f"https://github.com/argilla-io/argilla/issues?q=is:open+is:issue+label:%22{label}%22")
-    return links
-
-label_counts['Link'] = generate_labels_link(label_counts.index)
-
+st.subheader("Latest bugs 🐞")
+bug_issues = open_issues[open_issues["Labels"].apply(lambda labels: "type: bug" in labels)]
+bug_issues = bug_issues[["Issue","Labels","Created at","URL"]]
 st.dataframe(
-    label_counts.head(10),
+    bug_issues.sort_values(by="Created at", ascending=False),
+    hide_index=True,
     column_config={
-        "count": st.column_config.NumberColumn("Count"),
-        "Link": st.column_config.LinkColumn("Link", display_text="🔗")
+        "Issue": st.column_config.TextColumn("Issue", width=400),
+        "Labels": st.column_config.TextColumn("Labels"),
+        "Created at": st.column_config.DatetimeColumn("Created at"),
+        "URL": st.column_config.LinkColumn("🔗", display_text="🔗")
     }
 )
 
-# ## Dataframe: Number of open bugs by severity level. Critical, major, minor
+# Section 2: Issue classification
+st.header("Issue classification")
+col1, col2 = st.columns(2)
 
+## Dataframe: Number of open issues by label.
+with col1:
+    st.subheader("Top ten labels 🔖")
+    open_issues_exploded = open_issues.explode("Labels")
+    label_counts = open_issues_exploded.value_counts("Labels").to_frame()
+
+    def generate_labels_link(labels):
+        links = []
+        for label in labels:
+            label = label.replace(" ", "+")
+            links.append(f"https://github.com/argilla-io/argilla/issues?q=is:open+is:issue+label:%22{label}%22")
+        return links
+    
+    def generate_label_categories(labels):
+        categories = []
+        sub_categories = []
+        for label in labels:
+            cats = label.split(": ")
+            categories.append(cats[0])
+            try:
+                sub_categories.append(cats[1])
+            except:
+                sub_categories.append(None)
+        return categories,sub_categories
+
+    label_counts['Link'] = generate_labels_link(label_counts.index)
+    # label_counts['Category'], label_counts['Subcategory'] = generate_label_categories(label_counts.index)
+
+    st.dataframe(
+        label_counts.head(10),
+        column_config={
+            "Labels": st.column_config.TextColumn("Labels"),
+            "count": st.column_config.NumberColumn("Count"),
+            "Link": st.column_config.LinkColumn("Link", display_text="🔗")
+        }
+    )
+
+## Dataframe: Number of open bugs ordered by date
+    
 # ## Cloud of words: Issue titles and description
 
 # # Community engagement
 st.header("Community engagement")
 # ## Dataframe: Latest issues open by the community
 # ## Dataframe: issues sorted by number of comments
-engagement_df = open_issues[["Number","Title","Reactions","Comments","URL"]].sort_values(by=["Reactions", "Comments"], ascending=False).head(10)
+st.subheader("Top engaging issues 💬")
+engagement_df = open_issues[["Issue","Reactions","Comments","URL"]].sort_values(by=["Reactions", "Comments"], ascending=False).head(10)
 st.dataframe(
     engagement_df,
     hide_index=True,
     use_container_width=True,
     column_config={
-        "Number": st.column_config.NumberColumn("No."),
-        "Title": st.column_config.TextColumn("Title", width=400),
+        "Issue": st.column_config.TextColumn("Issue", width=400),
         "Reactions": st.column_config.NumberColumn("Reactions", format="%d 👍"),
         "Comments": st.column_config.NumberColumn("Comments", format="%d 💬"),
         "URL": st.column_config.LinkColumn("🔗", display_text="🔗")