Mareh A.

.python-version

@@ -0,0 +1 @@
+3.12

.user.yml

@@ -0,0 +1 @@
+id: b7c01a20-043b-414e-9aec-8e45d62cec80

AI_ASSIST.md

@@ -8,27 +8,85 @@ Document one place you used an LLM during this assignment.
      Example: "My safe_divide macro compiled but returned NULL for all rows even
      when tip_amount and fare_amount were both non-zero." -->
 
-TODO
+dbt run --select +fct_daily_borough_stats
+17:45:39  Running with dbt=1.11.12
+17:45:39  Registered adapter: postgres=1.10.2
+17:45:41  Found 1 test, 3 models, 2 sources, 476 macros
+17:45:41  
+17:45:41  Concurrency: 1 threads (target='dev')
+17:45:41  
+17:45:43  1 of 3 START sql view model dev_mareh.stg_trips ................................ [RUN]
+17:45:45  1 of 3 OK created sql view model dev_mareh.stg_trips ........................... [CREATE VIEW in 1.34s]
+17:45:45  2 of 3 START sql view model dev_mareh.stg_zones ................................ [RUN]
+17:45:46  2 of 3 OK created sql view model dev_mareh.stg_zones ........................... [CREATE VIEW in 1.22s]
+17:45:46  3 of 3 START sql table model dev_mareh.fct_daily_borough_stats ................. [RUN]
+17:45:47  3 of 3 ERROR creating sql table model dev_mareh.fct_daily_borough_stats ........ [ERROR in 0.92s]
+17:45:48  
+17:45:48  Finished running 1 table model, 2 view models in 0 hours 0 minutes and 6.84 seconds (6.84s).
+17:45:48  
+17:45:48  Completed with 1 error, 0 partial successes, and 0 warnings:
+17:45:48  
+17:45:48  Failure in model fct_daily_borough_stats (models\marts\fct_daily_borough_stats.sql)
+17:45:48    Database Error in model fct_daily_borough_stats (models\marts\fct_daily_borough_stats.sql)
+  function avg(text) does not exist
+  LINE 44:     avg(t.tip_pct) AS avg_tip_pct,
+               ^
+  HINT:  No function matches the given name and argument types. You might need to add explicit type casts.
+  compiled code at target\run\nyc_taxi_borough_daily\models\marts\fct_daily_borough_stats.sql
+17:45:48  
+17:45:48    compiled code at target\compiled\nyc_taxi_borough_daily\models\marts\fct_daily_borough_stats.sql
+17:45:48  
+17:45:48  Done. PASS=2 WARN=0 ERROR=1 SKIP=0 NO-OP=0 TOTAL=3
+(c55-data-week-10) 
 
 ## The prompt
 
 <!-- TODO: paste the exact prompt you sent to the LLM. -->
 
-TODO
+Why i get an error here and is that error have a problem with type of the column?
 
 ## The response
 
 <!-- TODO: summarise or paste what the LLM returned. -->
 
-TODO
+Yes, your intuition is spot on! The error is 100% related to the data type of the column.
+🔍 Breaking Down the Error
+The key line in your error log is:
+
+function avg(text) does not exist
+
+In PostgreSQL, the avg() function calculates the mathematical average. Because of this, it expects a numeric data type (like integer, decimal, or numeric).
+
+The error tells us that the tip_pct column is currently being treated as a text (string) data type. PostgreSQL is essentially saying: "I don't know how to calculate a mathematical average of text words or characters."
+
+💡 Why is it text?
+When we used the macro {{ safe_divide('tip_amount', 'fare_amount') }} in your stg_trips.sql model, dbt compiled that division in a way that PostgreSQL returned it as a generic or text-like format, instead of a strict numeric type.
+
+🛠️ How to Fix It
+Just like the database hint suggested (You might need to add explicit type casts), you need to explicitly tell PostgreSQL to convert (cast) that column into a number before trying to calculate the average.
+
+Go to your fct_daily_borough_stats.sql file, look at line 44, and change this:
+
+SQL
+avg(t.tip_pct) AS avg_tip_pct,
+To this (adding ::numeric inside the brackets):
+
+SQL
+avg(t.tip_pct::numeric) AS avg_tip_pct,
+🚀 Try running it again!
+Save your file (Ctrl + S) and run your command once more in the terminal:
+
+Bash
+dbt run --select +fct_daily_borough_stats
+Let me know if it clears up and passes with that beautiful green success message!
 
 ## Reflection
 
 <!-- TODO: what did you change, keep, or discard after reviewing the LLM's answer?
      Be specific: "I kept the NULLIF suggestion but changed the column alias from
      'ratio' to 'tip_pct' to match the assignment schema." -->
 
-TODO
+I tried the solution that llm gives me and it's work.
 
 ---
 

macros/safe_divide.sql

@@ -6,5 +6,5 @@
     -- 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 %}

main.py

@@ -0,0 +1,6 @@
+def main():
+    print("Hello from c55-data-week-10!")
+
+
+if __name__ == "__main__":
+    main()

models/marts/_fct_daily_borough_stats.yml

@@ -3,22 +3,29 @@ 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).
+      The grain of this mart is one row per (pickup_borough, pickup_date). 
+      It is built from stg_trips and stg_zones. 
+      Note: Trips with invalid or unmatched zone IDs (such as location 999) 
+      were dropped during the staging/join process using an INNER JOIN, 
+      ensuring pickup_borough is never NULL.
     # 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.
+    tests:
+      - dbt_utils.unique_combination_of_columns:
+          combination_of_columns:
+            - pickup_borough
+            - pickup_date
     columns:
       - name: pickup_borough
-        description: "TODO: explain what this column contains and where it comes from"
+        description: "It is the name of the NYC borough where the trip started, It comes from the stg_zones table."
       - name: pickup_date
-        description: "TODO: explain units and how it is derived"
+        description: "It is the date of the trip, derived from the pickup_datetime column in stg_trips which is converted to date."
       - name: trip_count
-        description: "TODO: explain what is counted (unit: number of trips)"
+        description: "It is the total number of trips per borough per day."
       - name: total_fare
-        description: "TODO: explain units (USD) and what fare_amount represents"
+        description: "It is the sum of all fare_amount values for trips per borough per day in USD."
       - name: avg_tip_pct
-        description: "TODO: explain the ratio (tip_amount / fare_amount)"
+        description: "It is the average tip percentage,calculated as (tip_amount / fare_amount) * 100."
       - name: avg_trip_distance
-        description: "TODO: explain units (miles, from TLC source data)"
+        description: "The average distance traveled per trip, measured in miles from the source TLC data."

models/marts/fct_daily_borough_stats.sql

@@ -26,13 +26,13 @@ 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::numeric) AS avg_tip_pct,
+    avg(t.trip_distance) AS avg_trip_distance
 
 FROM trips t
--- TODO: add JOIN to zones here
--- TODO: add GROUP BY here
+    inner join zones z on t.pickup_location_id = z.location_id
+    GROUP BY pickup_borough, pickup_date

models/staging/_sources.yml

@@ -2,9 +2,9 @@ version: 2
 
 sources:
   - name: nyc_taxi
-    schema: nyc_taxi     # TODO: confirm this matches the schema where raw_trips and raw_zones live
+    schema: nyc_taxi
     tables:
       - name: raw_trips
-        description: "TODO: one sentence on what this table contains and its grain"
+        description: "Contains raw NYC taxi trip records, including timestamps, distances, fare amounts, and location IDs. The grain of this table is one row per individual taxi trip."
       - name: raw_zones
-        description: "TODO: one sentence on what this table contains"
+        description: "A lookup table that maps each unique location ID to its corresponding borough, zone name, and service zone."

models/staging/_stg_trips.yml

@@ -2,19 +2,21 @@ version: 2
 
 models:
   - name: stg_trips
-    description: "TODO: state the grain (one row per ___) and what source this reads from"
+    description: "One row per individual taxi trip is the grain of this model."
     columns:
       - name: pickup_datetime
-        description: "TODO"
-        # 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.
+        description: "It count the date and time when the trip started."
+        tests:
+          - not_null
       - name: pickup_location_id
-        description: "TODO"
+        description: "Its the location id of the pickup where the trip started."
+        tests:
+          - not_null
       - name: fare_amount
-        description: "TODO"
+        description: "It is the amount of money paid for the trip in USD. "
       - name: tip_amount
-        description: "TODO"
+        description: "It is the amount of money paid as a tip for the trip in USD."
       - name: trip_distance
-        description: "TODO"
+        description: "It is the distance of the trip in miles."
       - name: tip_pct
-        description: "TODO"
+        description: "It is percentage of the tip amount over the fare amount."

models/staging/_stg_zones.yml

@@ -2,11 +2,14 @@ version: 2
 
 models:
   - name: stg_zones
-    description: "TODO: state the grain and what source this reads from"
+    description: "One row per individual taxi zone is the grain of this model."
     columns:
       - name: location_id
-        description: "TODO"
+        description: "It is the unique identifier for each taxi zone."
         # TODO: Task 5 -- this column is the join key. Which two generic tests
         # guarantee a clean one-to-many join from stg_trips?
+        tests:
+          - not_null
+          - unique
       - name: borough
-        description: "TODO"
+        description: "It is the NYC borough where the taxi zone is located."

models/staging/stg_trips.sql

@@ -3,11 +3,11 @@
 -- Downstream: fct_daily_borough_stats joins this to stg_zones.
 
 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

@@ -2,6 +2,6 @@
 -- Exposes location_id and borough for use as a lookup in the mart.
 
 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: 1.4.1
+sha1_hash: e6424ba9e5a22487e47f023803aa4f0411946808

packages.yml

@@ -2,4 +2,7 @@
 # `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: 1.4.1
+    version: [">=1.1.0", "<2.0.0"]

pyproject.toml

@@ -0,0 +1,9 @@
+[project]
+name = "c55-data-week-10"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+    "dbt-postgres>=1.10.2",
+]

reports/answers.md

@@ -7,12 +7,18 @@ Queries run against `dev_<your_name>.fct_daily_borough_stats`.
 **SQL:**
 
 ```sql
--- TODO: query fct_daily_borough_stats grouped by pickup_borough, sum total_fare, order DESC
+SELECT 
+    pickup_borough, 
+    SUM(total_fare) AS grand_total_fare
+FROM dev_mareh.fct_daily_borough_stats
+GROUP BY pickup_borough
+ORDER BY grand_total_fare DESC;
 ```
 
-**Result:** TODO
-
-**Interpretation:** TODO (one sentence)
+**Result:** 
+Manhattan: 493,955.62
+Queens: 274,214.90
+**Interpretation:** Manhattan has the highest total fare across the entire dataset, generating nearly double the revenue of the second-highest borough, Queens.
 
 ---
 
@@ -21,12 +27,18 @@ Queries run against `dev_<your_name>.fct_daily_borough_stats`.
 **SQL:**
 
 ```sql
--- TODO: query fct_daily_borough_stats grouped by pickup_date, sum trip_count, order DESC LIMIT 1
+SELECT 
+    pickup_date, 
+    SUM(trip_count) AS daily_trips
+FROM dev_mareh.fct_daily_borough_stats
+GROUP BY pickup_date
+ORDER BY daily_trips DESC
+LIMIT 1;
 ```
 
-**Result:** TODO
+**Result:** pickup_date:2024-01-17 daily_trips: 2,221
 
-**Interpretation:** TODO (one sentence)
+**Interpretation:** January 17, 2024, was the busiest day in the dataset, recording the highest overall trip volume with 2,221 trips.
 
 ---
 
@@ -35,12 +47,23 @@ Queries run against `dev_<your_name>.fct_daily_borough_stats`.
 **SQL:**
 
 ```sql
--- TODO: query fct_daily_borough_stats order by avg_tip_pct DESC LIMIT 5
+SELECT 
+    pickup_borough,
+    pickup_date,
+    avg_tip_pct
+FROM dev_mareh.fct_daily_borough_stats
+ORDER BY avg_tip_pct DESC
+LIMIT 5;
 ```
 
-**Result:** TODO
+**Result:** 
+Unknown (2024-01-30): 2.500125
+Unknown (2024-01-07): 1.339630
+Unknown (2024-01-11): 1.104496
+Unknown (2024-01-16): 1.000000
+Unknown (2024-01-18): 0.611111
 
-**Interpretation:** TODO — note whether any avg_tip_pct > 1 rows appear and what causes them
+**Interpretation:** Yes, there are rows where avg_tip_pct > 1 (specifically on Jan 30, Jan 7, and Jan 11, all in the "Unknown" borough). This occurs because the "Unknown" borough represents a very small-sample bucket where a few outlier trips with exceptionally high tips easily skew and dominate the daily average.
 
 ---
 
@@ -49,9 +72,16 @@ Queries run against `dev_<your_name>.fct_daily_borough_stats`.
 **SQL:**
 
 ```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_mareh.fct_daily_borough_stats
+WHERE pickup_borough IN ('Manhattan', 'Brooklyn')
+GROUP BY pickup_borough;
 ```
 
-**Result:** TODO
+**Result:** 
+Brooklyn: 248
+Manhattan: 1,169.5
 
-**Interpretation:** TODO (one sentence on the ratio)
+**Interpretation:** Manhattan has a significantly higher median daily trip count compared to Brooklyn, outperforming it by nearly 4.7 times.

tests/assert_avg_tip_pct_within_bounds.sql

@@ -15,5 +15,10 @@
 
 -- 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
+{{ config(severity='warn') }}
+SELECT 
+    pickup_borough,
+    pickup_date,
+    avg_tip_pct
+FROM {{ ref('fct_daily_borough_stats') }}
+WHERE avg_tip_pct > 1