Lab done

Lab done agg and transform.sql

@@ -0,0 +1,117 @@
+use sakila;
+-- 1. You need to use SQL built-in functions to gain insights relating to the duration of movies:
+	--  1.1 Determine the **shortest and longest movie durations** and name the values as `max_duration` and `min_duration`.
+	-- 1.2. Express the **average movie duration in hours and minutes**. Don't use decimals.
+      -- *Hint: Look for floor and round functions.*
+
+select title, length from film;
+select max(length) as max_duration, min(length) as min_duration from film;
+
+select floor(avg(length)),
+floor(avg(length) / 60) as hours,
+floor(avg(length)) % 60 as minutes 
+from film;
+
+-- You need to gain insights related to rental dates:
+	-- 2.1 Calculate the **number of days that the company has been operating**.
+      -- *Hint: To do this, use the `rental` table, and the `DATEDIFF()` function to subtract the earliest date in the `rental_date` column from the latest date.*
+
+select DATEDIFF(max(rental_date), min(rental_date)) AS days_of_operation
+from rental;
+
+	-- 2.2 Retrieve rental information and add two additional columns to show the **month and weekday of the rental**. Return 20 rows of results.
+
+select *, month(rental_date) as rental_month,
+dayname(rental_date) as rental_weekday
+from rental
+limit 20;
+
+	-- 2.3 *Bonus: Retrieve rental information and add an additional column called `DAY_TYPE` with values **'weekend' or 'workday'**, depending on the day of the week.*
+      -- *Hint: use a conditional expression.*
+
+select *, month(rental_date) as rental_month,
+dayname(rental_date) as rental_weekday,
+case
+    when dayofweek(rental_date)= 1 then 'weekend'
+    when dayofweek(rental_date)= 7 then 'weekend'
+    else 'workday'
+end as 'DAY_TYPE'
+from rental;
+
+-- You need to ensure that customers can easily access information about the movie collection. 
+-- To achieve this, retrieve the **film titles and their rental duration**. 
+-- If any rental duration value is **NULL, replace** it with the string **'Not Available'**. Sort the results of the film title in ascending order.
+    -- *Please note that even if there are currently no null values in the rental duration column, 
+    -- the query should still be written to handle such cases in the future.*
+    -- *Hint: Look for the `IFNULL()` function.*
+
+select title, rental_duration,
+ifnull(rental_duration, 'Not Available') as rental_duration
+ from film
+ order by title asc;
+
+-- *Bonus: The marketing team for the movie rental company now needs to create a personalized email campaign for customers. 
+-- To achieve this, you need to retrieve the **concatenated first and last names of customers**, 
+-- along with the **first 3 characters of their email** address, so that you can address them by their first name 
+-- and use their email address to send personalized recommendations. 
+-- The results should be ordered by last name in ascending order to make it easier to use the data.*
+
+select concat(last_name, "  ", first_name) as customer, 
+left(email, 3) as email_prafix from customer
+order by last_name asc;
+
+-- Challenge 2
+
+-- 1. Next, you need to analyze the films in the collection to gain some more insights. Using the `film` table, determine:
+	-- 1.1 The **total number of films** that have been released.
+
+    select count(*)
+ from film
+ where release_year < 2025;
+
+	-- 1.2 The **number of films for each rating**.
+
+    select rating, count(*) as number_of_film
+    from film
+    group by rating;
+
+	-- 1.3 The **number of films for each rating, sorting** the results in descending order of the number of films.
+      select rating, count(*) as number_of_film
+    from film
+    group by rating
+    order by rating desc;
+
+	-- This will help you to better understand the popularity of different film ratings and adjust purchasing decisions accordingly.
+
+   -- Using the `film` table, determine:
+   -- 2.1 The **mean film duration for each rating**, and sort the results in descending order of the mean duration. 
+
+   select * from film;
+
+   select rating, avg(length) as mean_film_duration from film
+   group by rating
+   order by mean_film_duration desc;
+
+   -- Round off the average lengths to two decimal places. This will help identify popular movie lengths for each category.
+
+    select rating, round(avg(length), 2) as mean_film_duration
+    from film
+   group by rating
+   order by mean_film_duration desc;
+
+	-- 2.2 Identify **which ratings have a mean duration of over two hours** in order to help select films for customers who prefer longer movies.
+
+select rating, avg(length) as mean_film_duration
+from film
+group by rating
+having avg(length) > 120
+order by mean_film_duration desc;
+
+ -- *Bonus: determine which last names are not repeated in the table `actor`.*
+
+ select last_name from actor
+ group by last_name
+ having count(*) = 1;
+
+
+

README.md

@@ -111,3 +111,122 @@ git push origin master
 ```
 
 - Paste the link of your lab in Student Portal.
+
+
+
+
+
+use sakila;
+-- 1. You need to use SQL built-in functions to gain insights relating to the duration of movies:
+	--  1.1 Determine the **shortest and longest movie durations** and name the values as `max_duration` and `min_duration`.
+	-- 1.2. Express the **average movie duration in hours and minutes**. Don't use decimals.
+      -- *Hint: Look for floor and round functions.*
+
+select title, length from film;
+select max(length) as max_duration, min(length) as min_duration from film;
+
+select floor(avg(length)),
+floor(avg(length) / 60) as hours,
+floor(avg(length)) % 60 as minutes 
+from film;
+
+-- You need to gain insights related to rental dates:
+	-- 2.1 Calculate the **number of days that the company has been operating**.
+      -- *Hint: To do this, use the `rental` table, and the `DATEDIFF()` function to subtract the earliest date in the `rental_date` column from the latest date.*
+
+select DATEDIFF(max(rental_date), min(rental_date)) AS days_of_operation
+from rental;
+
+	-- 2.2 Retrieve rental information and add two additional columns to show the **month and weekday of the rental**. Return 20 rows of results.
+
+select *, month(rental_date) as rental_month,
+dayname(rental_date) as rental_weekday
+from rental
+limit 20;
+
+	-- 2.3 *Bonus: Retrieve rental information and add an additional column called `DAY_TYPE` with values **'weekend' or 'workday'**, depending on the day of the week.*
+      -- *Hint: use a conditional expression.*
+
+select *, month(rental_date) as rental_month,
+dayname(rental_date) as rental_weekday,
+case
+    when dayofweek(rental_date)= 1 then 'weekend'
+    when dayofweek(rental_date)= 7 then 'weekend'
+    else 'workday'
+end as 'DAY_TYPE'
+from rental;
+
+-- You need to ensure that customers can easily access information about the movie collection. 
+-- To achieve this, retrieve the **film titles and their rental duration**. 
+-- If any rental duration value is **NULL, replace** it with the string **'Not Available'**. Sort the results of the film title in ascending order.
+    -- *Please note that even if there are currently no null values in the rental duration column, 
+    -- the query should still be written to handle such cases in the future.*
+    -- *Hint: Look for the `IFNULL()` function.*
+
+select title, rental_duration,
+ifnull(rental_duration, 'Not Available') as rental_duration
+ from film
+ order by title asc;
+
+-- *Bonus: The marketing team for the movie rental company now needs to create a personalized email campaign for customers. 
+-- To achieve this, you need to retrieve the **concatenated first and last names of customers**, 
+-- along with the **first 3 characters of their email** address, so that you can address them by their first name 
+-- and use their email address to send personalized recommendations. 
+-- The results should be ordered by last name in ascending order to make it easier to use the data.*
+
+select concat(last_name, "  ", first_name) as customer, 
+left(email, 3) as email_prafix from customer
+order by last_name asc;
+
+-- Challenge 2
+
+-- 1. Next, you need to analyze the films in the collection to gain some more insights. Using the `film` table, determine:
+	-- 1.1 The **total number of films** that have been released.
+
+    select count(*)
+ from film
+ where release_year < 2025;
+
+	-- 1.2 The **number of films for each rating**.
+
+    select rating, count(*) as number_of_film
+    from film
+    group by rating;
+
+	-- 1.3 The **number of films for each rating, sorting** the results in descending order of the number of films.
+      select rating, count(*) as number_of_film
+    from film
+    group by rating
+    order by rating desc;
+
+	-- This will help you to better understand the popularity of different film ratings and adjust purchasing decisions accordingly.
+
+   -- Using the `film` table, determine:
+   -- 2.1 The **mean film duration for each rating**, and sort the results in descending order of the mean duration. 
+
+   select * from film;
+
+   select rating, avg(length) as mean_film_duration from film
+   group by rating
+   order by mean_film_duration desc;
+
+   -- Round off the average lengths to two decimal places. This will help identify popular movie lengths for each category.
+
+    select rating, round(avg(length), 2) as mean_film_duration
+    from film
+   group by rating
+   order by mean_film_duration desc;
+
+	-- 2.2 Identify **which ratings have a mean duration of over two hours** in order to help select films for customers who prefer longer movies.
+
+select rating, avg(length) as mean_film_duration
+from film
+group by rating
+having avg(length) > 120
+order by mean_film_duration desc;
+
+ -- *Bonus: determine which last names are not repeated in the table `actor`.*
+
+ select last_name from actor
+ group by last_name
+ having count(*) = 1;