diff --git a/AI_ASSIST.md b/AI_ASSIST.md index 07efd00..9af13ef 100644 --- a/AI_ASSIST.md +++ b/AI_ASSIST.md @@ -6,16 +6,66 @@ Document one session where you used an LLM to help with a query or a design deci ## The problem -TODO: What were you trying to solve? Paste the relevant SQL or schema fragment. +-- 3. Range validation: what are the min and max fare_amount? Are there negative values? +-- TODO: SELECT MIN(fare_amount), MAX(fare_amount), and a count of rows where fare_amount < 0. +select + MIN(rt.fare_amount), + MAX(rt.fare_amount), + COUNT(*) +where rt.fare_amount < 0, +from nyc_taxi.raw_trips rt; +Syntax error: ## The prompt - -TODO: What did you ask the AI? Include the context you provided. +why i got syntax error here and should i apply filter (where) ? ## The response +You got a syntax error because of how the SQL engine processes queries and where components must be placed. -TODO: What did it suggest? Did it work first try? +Here is exactly why your query failed and why using a **`FILTER`** clause is the best approach here: -## Reflection +--- + +### 1. Why you got a Syntax Error + +There are two structural mistakes in your original query: + +* **Placement of `FROM` and `WHERE`:** In SQL, the `FROM` clause must always come *before* the `WHERE` clause. You placed a comma after your `WHERE` condition and then wrote `FROM`, which completely confuses the database parser. +* **The comma inside `WHERE`:** You wrote `WHERE rt.fare_amount < 0,`. A `WHERE` clause cannot end with a comma. + +--- + +### 2. Should you apply a regular `WHERE` at the bottom? + +**No**, you shouldn't use a regular `WHERE` clause at the bottom of this query. + +If you put `WHERE rt.fare_amount < 0` at the end of the query, **the database will filter the entire table first**. This means your `MIN()` and `MAX()` functions would *only* look at the negative rows. + +* Your `MIN` would show the worst negative number. +* Your `MAX` would show the highest negative number (something close to `0`), **not** the true maximum fare paid by a real customer (which could be hundreds of dollars). -TODO: Did you understand *why* the suggestion worked, or did you accept it blindly? +--- + +### 3. The Solution: Use the `FILTER` clause + +To get the true minimum, the true maximum, and the count of bad rows all in a single pass, you must use the `FILTER` clause inside the `COUNT(*)` function. This acts as a mini-conditional statement just for that specific counter. + +Here is the correct way to write it: + +```sql +SELECT + MIN(rt.fare_amount) AS min_fare, + MAX(rt.fare_amount) AS max_fare, + COUNT(*) FILTER (WHERE rt.fare_amount < 0) AS negative_fares_count +FROM nyc_taxi.raw_trips rt; + +``` + +### Why this works perfectly: + +* `MIN(rt.fare_amount)` and `MAX(rt.fare_amount)` scan the **entire table** to find the absolute lowest and highest values. +* `COUNT(*) FILTER (WHERE rt.fare_amount < 0)` looks at every row but only increments the counter when the fare is negative. + +Run this updated query in your editor, and it will return a clean, one-row report without any errors! +## Reflection +Yes, I understand the response, and I noticed that the order of "where" before "from" is wrong, and also the comma, and using "filter" is better. diff --git a/assets/borough_count.png b/assets/borough_count.png new file mode 100644 index 0000000..bea86f7 Binary files /dev/null and b/assets/borough_count.png differ diff --git a/data_dictionary.md b/data_dictionary.md index 5e44612..00ffbb9 100644 --- a/data_dictionary.md +++ b/data_dictionary.md @@ -4,14 +4,14 @@ Document both views. State the grain in one sentence, identify the keys, and lis ## vw_fact_trips -- **Grain:** TODO (one sentence, e.g. "One row per ...") -- **Primary key:** TODO -- **Foreign keys:** TODO -- **Measures:** TODO (columns you would SUM or AVG) +- **Grain:** One row per individual valid taxi trip with a non-negative fare amount. +- **Primary key:** The raw data doesn't have a single primary key column, but we can use vendor_id and pickup_datetime together as a team (a composite key) to identify each unique row. +- **Foreign keys:** pickup_location_id, dropoff_location_id (both link to vw_dim_zones) +- **Measures:** fare_amount, tip_amount, total_amount,trip_distance ## vw_dim_zones -- **Grain:** TODO -- **Primary key:** TODO -- **Foreign keys:** TODO (or "none") -- **Measures:** TODO (or "none, descriptive attributes only") +- **Grain:** One row per unique taxi zone location ID +- **Primary key:** location_id +- **Foreign keys:** none +- **Measures:** none, "descriptive attributes only" diff --git a/schema_setup.sql b/schema_setup.sql index a7ae1ad..a91f381 100644 --- a/schema_setup.sql +++ b/schema_setup.sql @@ -5,7 +5,9 @@ -- TODO: complete the SELECT (location_id, zone, borough). CREATE OR REPLACE VIEW vw_dim_zones AS SELECT - -- TODO + rz.location_id, + rz.zone, + rz.borough FROM nyc_taxi.raw_zones; -- Fact: one row per taxi trip. @@ -15,12 +17,15 @@ FROM nyc_taxi.raw_zones; -- TODO: complete the SELECT and the WHERE. CREATE OR REPLACE VIEW vw_fact_trips AS SELECT - -- TODO + rt.*, + rt.pickup_datetime::TIMESTAMP AS pickup_datetime_clean FROM nyc_taxi.raw_trips --- TODO: WHERE fare_amount >= 0 -; +WHERE fare_amount >= 0; -- Join-readiness test (run after creating the views; it must run without error -- and return a count close to the vw_fact_trips row count): -- SELECT COUNT(*) FROM vw_fact_trips f -- JOIN vw_dim_zones d ON f.pickup_location_id = d.location_id; +SELECT COUNT(*) +FROM vw_fact_trips f +JOIN vw_dim_zones d ON f.pickup_location_id = d.location_id; \ No newline at end of file diff --git a/validation_queries.sql b/validation_queries.sql index 301b194..6f6934f 100644 --- a/validation_queries.sql +++ b/validation_queries.sql @@ -5,16 +5,30 @@ -- 1. Duplicate check: are there rows with the same vendor_id, pickup_datetime, dropoff_datetime? -- TODO: GROUP BY the three columns and keep only groups with HAVING COUNT(*) > 1. - - +select rt.vendor_id , rt.pickup_datetime , rt.dropoff_datetime , COUNT(*) AS copies +from nyc_taxi.raw_trips rt +group by rt.vendor_id , rt.pickup_datetime , rt.dropoff_datetime +having count(*)>1 +ORDER BY copies DESC; -- 2. Null integrity: how many rows have a NULL pickup_location_id or dropoff_location_id? -- TODO: count the NULLs (COUNT(*) FILTER (WHERE ... IS NULL) is handy for several columns at once). - +select + COUNT(*) filter(where rt.pickup_location_id is null) as null_pickup_location, + COUNT(*) filter(where rt.dropoff_location_id is null)as null_dropoff_location +from nyc_taxi.raw_trips rt; -- 3. Range validation: what are the min and max fare_amount? Are there negative values? -- TODO: SELECT MIN(fare_amount), MAX(fare_amount), and a count of rows where fare_amount < 0. - +select + MIN(rt.fare_amount) as min_fare_amount, + MAX(rt.fare_amount) as max_fare_amount, + COUNT(*) FILTER (WHERE rt.fare_amount < 0) AS negative_fares_count +from nyc_taxi.raw_trips rt; -- 4. Relationship check: which pickup_location_id values in nyc_taxi.raw_trips do NOT exist in nyc_taxi.raw_zones? -- TODO: LEFT JOIN nyc_taxi.raw_zones ... WHERE z.location_id IS NULL (or NOT EXISTS). -- Do NOT use NOT IN: a single NULL in the subquery hides every orphan. +select rt.pickup_location_id +from nyc_taxi.raw_trips rt +left join nyc_taxi.raw_zones rz on rt.pickup_location_id = rz.location_id +where rz.location_id is null; \ No newline at end of file diff --git a/verification_results.sql b/verification_results.sql index 68a8d26..527b4b0 100644 --- a/verification_results.sql +++ b/verification_results.sql @@ -6,17 +6,80 @@ -- What is the most common pickup/dropoff location combination? -- TODO -- (Take a screenshot of the per-borough counts and save it as assets/borough_count.png.) +SELECT COUNT(*) AS total_trips +FROM vw_fact_trips; + +SELECT + d.borough, + COUNT(*) AS trip_count +FROM vw_fact_trips f +JOIN vw_dim_zones d ON f.pickup_location_id = d.location_id +GROUP BY d.borough +ORDER BY trip_count DESC; + +SELECT + p.zone AS pickup_zone, + d.zone AS dropoff_zone, + COUNT(*) AS combination +FROM vw_fact_trips f +JOIN vw_dim_zones p ON f.pickup_location_id = p.location_id +JOIN vw_dim_zones d ON f.dropoff_location_id = d.location_id +GROUP BY p.zone, d.zone +ORDER BY combination DESC +LIMIT 1; -- 2. Revenue: which pickup zone (name, not ID) generated the highest total fare_amount? -- Which pickup zone collected the highest total fare_amount on any single day? -- TODO +SELECT + d.zone AS zone_name, + SUM(f.fare_amount) AS total_revenue +FROM vw_fact_trips f +INNER JOIN vw_dim_zones d + ON f.pickup_location_id = d.location_id +GROUP BY d.zone +ORDER BY total_revenue DESC +LIMIT 1; + +SELECT + d.zone AS zone_name, + DATE(f.pickup_datetime_clean) AS trip_date, + SUM(f.fare_amount) AS total_money +FROM vw_fact_trips f +JOIN vw_dim_zones d + ON f.pickup_location_id = d.location_id +GROUP BY d.zone, DATE(f.pickup_datetime_clean) +ORDER BY total_money DESC +LIMIT 1; -- 3. Geospatial: total number of trips and average trip_distance for each borough. -- TODO - +SELECT + d.borough, + COUNT(*) AS total_trips, + AVG(f.trip_distance) AS avg_distance +FROM vw_fact_trips f +JOIN vw_dim_zones d ON f.pickup_location_id = d.location_id +GROUP BY d.borough +ORDER BY total_trips DESC; -- 4. Time patterns: which day of the week had the highest total tip_amount? -- What hour of the day has the highest average tip? -- TODO +SELECT + EXTRACT(DOW FROM f.pickup_datetime_clean) AS day_number, + SUM(f.tip_amount) AS total_tips +FROM vw_fact_trips f +GROUP BY day_number +ORDER BY total_tips DESC +LIMIT 1; + +SELECT + EXTRACT(HOUR FROM f.pickup_datetime_clean) AS trip_hour, + ROUND(AVG(f.tip_amount)::numeric, 2) AS avg_tip +FROM vw_fact_trips f +GROUP BY trip_hour +ORDER BY avg_tip DESC +LIMIT 1;