lab resolved v1

labs_SQL_Data_Aggregation.sql

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+use Sakila ;
+
+-- Challenge 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.
+-- 1.1 Shortest and longest movie durations (max_duration and min_duration)
+
+select max(length) as max_duration, min(length) as min_duration
+from sakila.film;
+
+-- 1.2. Express the average movie duration in hours and minutes. Don't use decimals.
+-- Hint: Look for floor and round functions.
+select floor(avg(length) / 60) as hours, 
+  floor(avg(length) % 60) as minutes
+FROM sakila.film;
+
+-- 2 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((select max(rental_date) from sakila.rental), (select min(rental_date) from sakila.rental)) as operating_days;
+
+-- 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 rental_id, rental_date, inventory_id, customer_id, return_date, staff_id, last_update,
+date(rental_date) as rental_date_only, 
+month(rental_date) as rental_month,
+dayname(rental_date) as weekday
+from sakila.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 rental_id, rental_date, inventory_id, customer_id, return_date, staff_id, last_update,
+case
+when dayname(rental_date) in ("Monday", "Tuesday", "Wednesday", "Thursday", "Friday") then 'weekday' 
+when dayname(rental_date) in ("Saturday", "Sunday") then 'weekend'
+end as DAY_TYPE
+from sakila.rental;
+
+-- 3. 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,
+ifnull(cast(rental_duration as char), 'Not Available') as rental_duration
+from sakila.film 
+order by title asc;
+
+-- 4. 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(first_name, ' ', last_name, ' ', left(email, 3)) as email_prefix
+from sakila.customer
+order by last_name asc;
+
+-- Challenge 2
+-- 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(*) as total_films from sakila.film;
+
+ -- 1.2 The number of films for each rating.
+
+select rating, count(film_id) as Number_of_films
+from film
+group by rating
+order by rating;
+
+-- 1.3 The number of films for each rating, sorting the results in descending order of the number of films. 
+-- This will help you to better understand the popularity of different film ratings and adjust purchasing decisions accordingly.
+
+select rating, count(film_id) as Number_of_films
+from film
+group by rating
+order by Number_of_films desc;
+
+-- 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. 
+-- 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 average_lenght
+from sakila.film
+group by rating
+order by average_lenght 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, round(avg(length), 2) as average_lenght
+from sakila.film
+group by rating
+having avg(length) > 120;
+
+-- 3. Bonus: determine which last names are not repeated in the table actor.
+
+select last_name, count(*) as repetead
+from sakila.actor
+group by last_name
+having count(*) = 1;
+
+
+