Baraah A.

.user.yml

@@ -0,0 +1 @@
+id: 65fed7dc-cfb1-40ec-af82-fb56180cafce

AI_ASSIST.md

@@ -4,23 +4,29 @@ Document one place you used an LLM during this assignment.
 
 ## The problem
 
-<!-- TODO: describe the specific problem you asked an LLM about.
-     Example: "My safe_divide macro compiled but returned NULL for all rows even
-     when tip_amount and fare_amount were both non-zero." -->
-
-TODO
-
+While building the stg_trips staging model, i had an SQL syntax issue because i placed the "WHERE" clause before the "FROM" clause. 
 ## The prompt
 
 <!-- TODO: paste the exact prompt you sent to the LLM. -->
-
-TODO
-
+Im building a dbt staging model and my SQL query is failing. what is the problem here?
+my query was :
+SELECT
+    pickup_datetime,
+    pickup_location_id,
+    fare_amount,
+    tip_amount,
+    trip_distance,
+
+    {{ safe_divide('tip_amount', 'fare_amount') }} as tip_pct
+
+where pickup_location_id is not null
+FROM {{ source('nyc_taxi', 'raw_trips') }}
+  and fare_amount >= 0
 ## The response
 
 <!-- TODO: summarise or paste what the LLM returned. -->
 
-TODO
+the llm explained that SQL clauses follow a fixed order. The FROM clause must come before the WHERE clause because SQL needs to know the source table before applying filters. 
 
 ## Reflection
 
@@ -29,8 +35,7 @@ TODO
      'ratio' to 'tip_pct' to match the assignment schema." -->
 
 TODO
-
----
+i changed the query order so that "FROM" comes immediately after the SELECT columns, followed by the WHERE filters.
 
 > 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.

macros/safe_divide.sql

@@ -3,8 +3,9 @@
 -- Use for tip_pct = tip_amount / fare_amount and similar ratio columns.
 
 {% macro safe_divide(numerator, denominator) %}
-    -- TODO: implement the macro body.
-    -- Use NULLIF(denominator, 0) to avoid division-by-zero errors.
-    -- Return only the SQL expression (no SELECT, no semicolon).
-    NULL
+
+        {{ numerator }} / nullif({{ denominator }}, 0)
+
 {% endmacro %}
+
+

models/marts/_fct_daily_borough_stats.yml

@@ -3,22 +3,36 @@ version: 2
 models:
   - name: fct_daily_borough_stats
     description: >
-      TODO: state the grain (one row per ___), the source lineage
-      (built from ___ and ___), and at least one known caveat
-      (e.g. rows dropped in staging, any WARN-severity tests).
+      Daily borough-level taxi statistics with a grain of one row per
+      (pickup_borough, pickup_date). 
+      Built from stg_trips and stg_zones.
+      Trips with missing or invalid pickup locations are removed during staging
+      or excluded by the INNER JOIN. 
+      The avg_tip_pct warning test may return some rows where 
+      tips are higher than the fare amount.
+
+    tests:
+      - dbt_utils.unique_combination_of_columns:
+          combination_of_columns:
+            - pickup_borough
+            - pickup_date
     # TODO: Task 5 -- add the compound uniqueness test on the mart's primary
     # key (pickup_borough, pickup_date). You need the dbt_utils package for
     # this: declare it in packages.yml and run `dbt deps` first.
     columns:
       - name: pickup_borough
-        description: "TODO: explain what this column contains and where it comes from"
+        description: "The TLC borough where trips were picked up, sourced from stg_zones.borough"
+        tests:
+          - not_null
       - name: pickup_date
-        description: "TODO: explain units and how it is derived"
+        description: "The calendar date of the trip pickup, derived from pickup_datetime."
+        tests:
+          - not_null
       - name: trip_count
-        description: "TODO: explain what is counted (unit: number of trips)"
+        description: "The number of taxi trips picked up in the borough on that dat."
       - name: total_fare
-        description: "TODO: explain units (USD) and what fare_amount represents"
+        description: "The total fare amount collected in US dollars, calculated as the sum of fare_amount"
       - name: avg_tip_pct
-        description: "TODO: explain the ratio (tip_amount / fare_amount)"
+        description: "The average tipping ratio calculated as tip_amount divided by fare_amount."
       - name: avg_trip_distance
-        description: "TODO: explain units (miles, from TLC source data)"
+        description: "The average trip distance in miles based on the TLC trip_distance field"

models/marts/fct_daily_borough_stats.sql

@@ -2,6 +2,7 @@
 -- Grain: one row per (pickup_borough, pickup_date).
 -- Used to answer: trip volume, revenue, tipping behaviour, and distance profile
 -- per borough per day for January 2024.
+{{ config(materialized='table') }}
 
 WITH trips AS (
     SELECT *
@@ -26,13 +27,27 @@ SELECT
     --   total_fare       NUMERIC  - sum(fare_amount)
     --   avg_tip_pct      NUMERIC  - avg(tip_pct)
     --   avg_trip_distance NUMERIC - avg(trip_distance)
-    NULL AS pickup_borough,
-    NULL AS pickup_date,
-    NULL AS trip_count,
-    NULL AS total_fare,
-    NULL AS avg_tip_pct,
-    NULL AS avg_trip_distance
+    z.borough AS pickup_borough,
+
+    t.pickup_datetime::date AS pickup_date,
+
+    count(*) AS trip_count,
+
+    sum(t.fare_amount) AS total_fare,
+
+    avg(t.tip_pct) AS avg_tip_pct,
+
+    avg(t.trip_distance) AS avg_trip_distance
+
 
 FROM trips t
 -- TODO: add JOIN to zones here
+INNER JOIN zones z
+
+    ON t.pickup_location_id = z.location_id
 -- TODO: add GROUP BY here
+GROUP BY
+
+    z.borough,
+
+    t.pickup_datetime::date

models/staging/_sources.yml

@@ -5,6 +5,6 @@ sources:
     schema: nyc_taxi     # TODO: confirm this matches the schema where raw_trips and raw_zones live
     tables:
       - name: raw_trips
-        description: "TODO: one sentence on what this table contains and its grain"
+        description: "Raw NYC green Taxi trip records, with one row representing one individual taxi trip."
       - name: raw_zones
-        description: "TODO: one sentence on what this table contains"
+        description: "Raw TLC taxi zone lookup table containing location IDs and borough/zone information."

models/staging/_stg_trips.yml

@@ -2,19 +2,23 @@ version: 2
 
 models:
   - name: stg_trips
-    description: "TODO: state the grain (one row per ___) and what source this reads from"
+    description: "One row per taxi trip from the raw_trips source after basic cleaning and filtering."
     columns:
       - name: pickup_datetime
-        description: "TODO"
+        description: "Timestamp when the trip started"
+        tests:
+          - not_null
         # TODO: Task 5 -- add not_null tests on every column used as a join or
         # group-by key. See the chapter's dbt Tests section for the syntax.
       - name: pickup_location_id
-        description: "TODO"
+        description: "TLC location ID where the trip was picked up."
+        tests:
+          - not_null
       - name: fare_amount
-        description: "TODO"
+        description: "Fare charged for the trip in US dollars"
       - name: tip_amount
-        description: "TODO"
+        description: "Tip paid by the passenger in US dollars"
       - name: trip_distance
-        description: "TODO"
+        description: "Distance travelled during the trip in miles"
       - name: tip_pct
-        description: "TODO"
+        description: "Tip as a percentage of the fare amount"

models/staging/_stg_zones.yml

@@ -2,11 +2,15 @@ version: 2
 
 models:
   - name: stg_zones
-    description: "TODO: state the grain and what source this reads from"
+    description: "One row per TLC taxi zone from the raw_zones source"
     columns:
       - name: location_id
-        description: "TODO"
+        description: "Unique identifier for each TLC taxi zone."
+        tests:
+          - not_null
+          - unique
+
         # TODO: Task 5 -- this column is the join key. Which two generic tests
         # guarantee a clean one-to-many join from stg_trips?
       - name: borough
-        description: "TODO"
+        description: "Borough that the taxi zone belongs to."

models/staging/stg_trips.sql

@@ -1,13 +1,18 @@
 -- Staging model: one row per NYC green taxi trip (January 2024).
 -- Renames source columns, adds derived columns, and filters bad rows.
 -- Downstream: fct_daily_borough_stats joins this to stg_zones.
+{{ config(materialized='view') }}
 
 SELECT
-    -- TODO: select the columns you need for the mart:
-    --   pickup_datetime, pickup_location_id, fare_amount, tip_amount, trip_distance
-    --
-    -- TODO: add tip_pct using {{ safe_divide('tip_amount', 'fare_amount') }}
-    --
-    -- TODO: filter out rows where pickup_location_id IS NULL or fare_amount < 0
+    pickup_datetime,
+    pickup_location_id,
+    fare_amount,
+    tip_amount,
+    trip_distance,
+
+    {{ safe_divide('tip_amount', 'fare_amount') }} as tip_pct
 
 FROM {{ source('nyc_taxi', 'raw_trips') }}
+
+where pickup_location_id is not null
+  and fare_amount >= 0

models/staging/stg_zones.sql

@@ -1,7 +1,8 @@
 -- Staging model: one row per TLC zone (265 zones).
 -- Exposes location_id and borough for use as a lookup in the mart.
+{{ config(materialized='view') }}
 
 SELECT
-    -- TODO: select location_id and borough from {{ source('nyc_taxi', 'raw_zones') }}
-
+    location_id,
+    borough
 FROM {{ source('nyc_taxi', 'raw_zones') }}

package-lock.yml

@@ -0,0 +1,5 @@
+packages:
+  - name: dbt_utils
+    package: dbt-labs/dbt_utils
+    version: 1.3.0
+sha1_hash: 226ae69cdfbc9367e2aa2c472b01f99dbce11de0

packages.yml

@@ -2,4 +2,6 @@
 # `dbt deps` to install it. You need it for the compound uniqueness test
 # on the mart. See https://hub.getdbt.com/dbt-labs/dbt_utils/latest/
 # for the package block syntax.
-packages: []
+packages:
+  - package: dbt-labs/dbt_utils
+    version: 1.3.0

reports/answers.md

@@ -1,6 +1,6 @@
 # Business Question Answers
 
-Queries run against `dev_<your_name>.fct_daily_borough_stats`.
+Queries run against `dev_baraah.fct_daily_borough_stats`.
 
 ## Q1: Highest total `total_fare` across the whole loaded dataset
 
@@ -9,10 +9,20 @@ Queries run against `dev_<your_name>.fct_daily_borough_stats`.
 ```sql
 -- TODO: query fct_daily_borough_stats grouped by pickup_borough, sum total_fare, order DESC
 ```
-
-**Result:** TODO
-
-**Interpretation:** TODO (one sentence)
+SELECT
+    pickup_borough,
+    SUM(total_fare) AS total_revenue
+FROM dev_baraah.fct_daily_borough_stats
+GROUP BY pickup_borough
+ORDER BY total_revenue DESC
+LIMIT 1;
+**Result:** 
+ pickup_borough | total_revenue 
+----------------+---------------
+ Manhattan      |     493955.62
+(1 row)
+
+**Interpretation:** The borough with the highest total fare revenue across the loaded dataset was Manhattan $493955.62.
 
 ---
 
@@ -23,10 +33,20 @@ Queries run against `dev_<your_name>.fct_daily_borough_stats`.
 ```sql
 -- TODO: query fct_daily_borough_stats grouped by pickup_date, sum trip_count, order DESC LIMIT 1
 ```
-
-**Result:** TODO
-
-**Interpretation:** TODO (one sentence)
+SELECT
+    pickup_date,
+    SUM(trip_count) AS total_trips
+FROM dev_baraah.fct_daily_borough_stats
+GROUP BY pickup_date
+ORDER BY total_trips DESC
+LIMIT 1;
+**Result:** 
+ pickup_date | total_trips 
+-------------+-------------
+ 2024-01-17  |        2221
+(1 row)
+
+**Interpretation:** The busiest day in the dataset was 2024-01-17 with 2221 trips across all boroughs.
 
 ---
 
@@ -37,10 +57,25 @@ Queries run against `dev_<your_name>.fct_daily_borough_stats`.
 ```sql
 -- TODO: query fct_daily_borough_stats order by avg_tip_pct DESC LIMIT 5
 ```
-
-**Result:** TODO
-
-**Interpretation:** TODO — note whether any avg_tip_pct > 1 rows appear and what causes them
+SELECT
+    pickup_borough,
+    pickup_date,
+    avg_tip_pct
+FROM dev_baraah.fct_daily_borough_stats
+ORDER BY avg_tip_pct DESC
+LIMIT 5;
+
+**Result:** 
+ pickup_borough | pickup_date |    avg_tip_pct     
+----------------+-------------+--------------------
+ Unknown        | 2024-01-30  |           2.500125
+ Unknown        | 2024-01-07  | 1.3396296296296295
+ Unknown        | 2024-01-11  | 1.1044956140350877
+ Unknown        | 2024-01-16  |                  1
+ Unknown        | 2024-01-18  |  0.611111111111111
+(5 rows)
+
+**Interpretation:** The highest average tip percentage occurred in Unknown on 2024-01-30 . 
 
 ---
 
@@ -51,7 +86,18 @@ Queries run against `dev_<your_name>.fct_daily_borough_stats`.
 ```sql
 -- TODO: use percentile_cont(0.5) WITHIN GROUP (ORDER BY trip_count) filtered by borough
 ```
+SELECT
+    pickup_borough,
+    percentile_cont(0.5) WITHIN GROUP (ORDER BY trip_count) AS median_trip_count
+FROM dev_baraah.fct_daily_borough_stats
+WHERE pickup_borough IN ('Manhattan', 'Brooklyn')
+GROUP BY pickup_borough;
 
 **Result:** TODO
+ pickup_borough | median_trip_count 
+----------------+-------------------
+ Brooklyn       |               248
+ Manhattan      |            1169.5
+(2 rows)
 
-**Interpretation:** TODO (one sentence on the ratio)
+**Interpretation:** Manhattan had a higher median daily trip count than Brooklyn. 

test-output.txt

@@ -0,0 +1 @@
+bash: test.sh: No such file or directory

tests/assert_avg_tip_pct_within_bounds.sql

@@ -12,8 +12,15 @@
 -- unique_combination primary-key tests, which you want to stay at ERROR.
 --
 -- The test passes (no WARN) when zero rows are returned; any returned rows are flagged.
+{{ config(severity='warn') }}
 
 -- TODO: write the SELECT here.
 -- Query {{ ref('fct_daily_borough_stats') }} and return rows where avg_tip_pct > 1.
-SELECT NULL AS pickup_borough, NULL AS pickup_date, NULL AS avg_tip_pct
-WHERE FALSE  -- TODO: replace with the real query
+SELECT
+    pickup_borough,
+    pickup_date,
+    avg_tip_pct
+
+FROM {{ ref('fct_daily_borough_stats') }}
+
+WHERE avg_tip_pct > 1