HackYourAssignment · hannahwn · Jul 16, 2026 · Jul 27, 2026 · Jul 27, 2026 · Jul 29, 2026
diff --git a/.gitignore b/.gitignore
@@ -87,6 +87,7 @@ web_modules/
 .env
 .env.*
 !.env.example
+.week11-streamlit/.env
 
 # parcel-bundler cache (https://parceljs.org/)
 .cache
@@ -156,3 +157,4 @@ dist
 vite.config.js.timestamp-*
 vite.config.ts.timestamp-*
 
+week11-streamlit/.env
diff --git a/AI_ASSIST.md b/AI_ASSIST.md
@@ -3,34 +3,38 @@
 Document one place you used an LLM during this assignment.
 
 ## The problem
+i did not know how to record myself using teams or zoom
 
-<!-- TODO: describe the specific problem you asked an LLM about.
-     Example: "My Streamlit KPI panel kept re-querying Postgres on every
-     sidebar interaction even though I wrapped run_query in @st.cache_data." -->
+## The prompt
 
-TODO
+how to record my screen and voice with my computer using teams or zoom
 
-## The prompt
+## The response
+🎥 Recording in Microsoft Teams
+Takeaway: You can record any meeting, even if you're alone, and Teams will capture your screen, microphone, and system audio (if enabled).
 
-<!-- TODO: paste the exact prompt you sent to the LLM. -->
+How to do it
+Open Teams and start a meeting
 
-TODO
+Click Calendar → Meet now, or open an existing meeting.
 
-## The response
+Join the meeting
 
-<!-- TODO: summarise or paste what the LLM returned. -->
+Turn on your microphone if you want your voice recorded.
 
-TODO
+Share your screen
 
-## Reflection
+Click Share (the square-with-arrow icon).
+
+Choose Screen, Window, or PowerPoint Live.
 
-<!-- TODO: what did you change, keep, or discard after reviewing the LLM's answer?
-     Be specific: "I kept the cache_data suggestion but changed ttl from 60 to 300
-     to match the mart's once-a-day refresh cadence." -->
+Start recording
 
-TODO
+Click More (···) → Start recording.
+
+## Reflection
 
----
+I need to join a meeting even if by myself there is no other way of recording and need to upgrade to premium so i switched to OBS.
 
 > Remember: never paste real connection strings, passwords, or PII into an LLM.
 > The NYC TLC dataset is public so sample rows are safe here, but practise the habit.
diff --git a/README.md b/README.md
@@ -52,9 +52,11 @@ Fill in `week11-streamlit/metric_definitions.md`: a five-field definition (name,
      2) Paste its link below, plus screenshots or a PDF export in this repo.
      3) Paste your 5-minute presentation recording link (keep it PRIVATE). -->
 
-- Metabase dashboard (in the **Week 11 Submissions** collection): TODO
-- Screenshots / PDF export: TODO
-- Presentation recording (private, hosted in the Azure `student-submissions` container): TODO
+- Metabase dashboard (in the **Week 11 Submissions** collection): 
+https://metabase-hyf.politepebble-abd3ebc2.westeurope.azurecontainerapps.io/dashboard/46-nyc-taxi-analytics-hannah
+- Screenshots / PDF export: screenshots are in the docs folder
+- Presentation recording (private, hosted in the Azure `student-submissions` container): 
+https://hyfstoragedev.blob.core.windows.net/student-submissions/week-11/hannahwn.mp4
 
 > ⚠️ **Keep the recording private.** It shows your screen and voice. Never make it public and never commit the `.mp4` (git history is forever). Check the frame for passwords, `.env` contents, or connection strings before uploading.
 

diff --git a/docs/metabase screenshot.png b/docs/metabase screenshot.png
diff --git a/docs/streamlit screenshot.png b/docs/streamlit screenshot.png
diff --git a/week11-streamlit/.env.example b/week11-streamlit/.env.example
@@ -1,6 +1,6 @@
 # PostgreSQL connection string (your Week 9/10 login)
 # Keep the database name as team1 and the ?sslmode=require suffix; only swap
 # in your own user, password, and host.
-POSTGRES_URL=postgresql://your-pg-user:your-pg-password@your-pg-host:5432/team1?sslmode=require
+POSTGRES_URL=postgresql://hannahwn:HhRHmt469pEm3Ou0@hyf-data-pg.postgres.database.azure.com:5432/team1?sslmode=require
 # Your dev schema name (e.g. dev_jana)
-DB_SCHEMA=dev_yourname
+DB_SCHEMA=dev_hannahwn
diff --git a/week11-streamlit/app.py b/week11-streamlit/app.py
@@ -18,28 +18,86 @@
 load_dotenv()  # reads .env file if present
 
 POSTGRES_URL = os.environ["POSTGRES_URL"]
-DB_SCHEMA = os.environ.get("DB_SCHEMA", "dev_yourname")
+DB_SCHEMA = os.environ.get("DB_SCHEMA", "dev_hannahwn")
 
 st.set_page_config(page_title="NYC Taxi Metrics", layout="wide")
 st.title("NYC Taxi Metrics")
 
 
+
+
 @st.cache_data(ttl=300)
 def run_query(sql: str) -> pd.DataFrame:
     engine = sqlalchemy.create_engine(POSTGRES_URL)
     with engine.connect() as conn:
         return pd.read_sql(sql, conn)
 
+st.sidebar.header("Filters")
+
+payment_types = run_query(f"""
+    SELECT DISTINCT payment_type_label
+    FROM {DB_SCHEMA}.fct_trips
+    WHERE payment_type_label IS NOT NULL
+    ORDER BY payment_type_label
+""")["payment_type_label"].tolist()
+
+selected_payment_type = st.sidebar.selectbox(
+    "Payment type",
+    ["All"] + payment_types
+)
+
+if selected_payment_type == "All":
+    where_clause = ""
+else:
+    where_clause = f"WHERE payment_type_label = '{selected_payment_type}'"
+
 
 st.subheader("Headline KPIs")
+KPIs= run_query(f"""
+    SELECT
+        COUNT(*) AS total_trips,
+        AVG(trip_distance) AS avg_trip_distance,
+        AVG(fare_per_mile) AS avg_fare_per_mile
+    FROM {DB_SCHEMA}.fct_trips
+    {where_clause}
+""").iloc[0]
+
+col1, col2, col3 = st.columns(3)
+col1.metric("Total Trips", f"{KPIs['total_trips']:,}")
+col2.metric("Avg Trip Distance (miles)", f"{KPIs['avg_trip_distance']:.2f}")
+col3.metric("Avg Fare per Mile ($)", f"{KPIs['avg_fare_per_mile']:.2f}")
+
 
-# TODO: query total trip count, average trip_distance, and average
-# fare_per_mile from {DB_SCHEMA}.fct_trips through run_query(), then
-# render three tiles side by side with st.columns(3) and .metric().
-# This is deliberately not the total-trips/avg-fare/total-revenue trio
-# from the chapter: trip_distance and fare_per_mile are different columns,
-# so copying the chapter's SQL verbatim will not answer this.
-raise NotImplementedError(
-    "TODO: implement the headline KPIs panel (total trips, avg trip "
-    "distance, avg fare per mile) from fct_trips."
+
+
+st.subheader("Trip Distance Distribution")
+hourly_dist = run_query(f"""
+    SELECT
+        EXTRACT(HOUR FROM pickup_datetime) AS hour_of_day,
+        COUNT(*) AS trip_count
+    FROM {DB_SCHEMA}.fct_trips
+    GROUP BY 1
+    ORDER BY 1
+""")
+
+if hourly_dist.empty:
+    st.warning("No data available for the selected filters.")
+else:
+    st.bar_chart(hourly_dist.set_index("hour_of_day")["trip_count"])
+
+
+st.subheader("Data Freshness")
+freshness = run_query(f"""
+    SELECT
+        MAX(pickup_datetime) AS last_pickup,
+        MAX(dropoff_datetime) AS last_dropoff
+    FROM {DB_SCHEMA}.fct_trips
+""").iloc[0]    
+
+col1, col2 = st.columns(2)
+
+col1.metric("Row count", f"{KPIs['total_trips']:,}")
+col2.metric(
+    "Last pickup", str(freshness["last_pickup"])[:16] if freshness["last_pickup"] else "unknown"
 )
+
diff --git a/week11-streamlit/metric_definitions.md b/week11-streamlit/metric_definitions.md
@@ -0,0 +1,51 @@
+# Metric definitions
+
+Five fields per metric: Name, Description, Calculation, Data source, Refresh frequency. One block per panel. Copy this file to `metric_definitions.md` inside your `week11-streamlit/` folder and fill it in.
+
+## Metabase panels
+
+<!-- One block per Question: trip count by payment type, average fare per
+     mile by dropoff borough, average trip duration by hour of day. -->
+
+### Panel 1: 
+
+- **Name**: Trip count by payment type
+- **Description**: Helps identify which payment type is preffered
+- **Calculation**: sum of payments grouped by type of payment
+- **Data source**: fct_trips
+- **Refresh frequency**: every time fct_trips is built
+
+### Panel 2: 
+
+- **Name**: Average fare per mile by dropoff borough
+- **Description**: Helps show the average money paid per mile in every borough
+- **Calculation**: finding the average of of fare paid by mile and grouping per borough
+- **Data source**: the fct_trips
+- **Refresh frequency**: every time fct_trips is built
+
+### Panel 3: 
+
+- **Name**: Average trip duration per hour
+- **Description**: Shows which hours are busiest by average
+- **Calculation**: we deduct the pickup time time from dropoff time and then find average
+- **Data source**: fct_trips
+- **Refresh frequency**: every time fct_trips is run
+
+## Streamlit panels
+
+<!-- Headline KPIs panel: total trips, average trip distance, average
+     fare per mile. -->
+
+### Panel 1: 
+
+- **Name**: Headline KPIs
+- **Description**: total trips,average_trip distance,average fare per mile
+- **Calculation**:  COUNT(*) AS total_trips,
+        AVG(trip_distance) AS avg_trip_distance,
+        AVG(fare_per_mile) AS avg_fare_per_mile
+- **Data source**: fct_trips
+- **Refresh frequency**: when data is cached
+
+<!-- Add more ### Panel blocks under either section if you build more (the Required tier adds
+     an hour-of-day trend and a freshness panel to Streamlit; a Metabase date filter is Extra,
+     bonus credit, not required). -->