From 4cd4ec9fe97cc1fc2cf8e562050d9018b7ffbcff Mon Sep 17 00:00:00 2001 From: Subham Kumar <158332737+960Subhamsingh@users.noreply.github.com> Date: Wed, 25 Dec 2024 22:46:46 +0530 Subject: [PATCH] PosgreSQL Data Analysis --- Coffee/README.MD | 2 +- .../readme.md | 2 +- .../Music Store Analysis-Questions.pdf | Bin 106586 -> 0 bytes .../MusicDatabaseSchema.png | Bin 41653 -> 0 bytes .../Music_Store_Query.sql | 230 - .../Music_Store_database.sql | Bin 173473 -> 0 bytes SQL_Music_Store_Analysis/README.md | 13 - .../Raw-Music Store Analysis-SQL Project.zip | Bin 682064 -> 0 bytes .../Music Store Analysis-Questions.pdf | Bin 106586 -> 0 bytes .../Music Store- Create Tables Query.txt | 93 - .../MusicDatabaseSchema.png | Bin 41653 -> 0 bytes .../Music_Store_Query.sql | 230 - .../Music_Store_database.sql | Bin 173473 -> 0 bytes .../SQL Music Questions2.docx | Bin 19091 -> 0 bytes .../Music Playlist- SQL Project/album.csv | 348 - .../Music Playlist- SQL Project/artist.csv | 276 - .../Music Playlist- SQL Project/customer.csv | 60 - .../Music Playlist- SQL Project/employee.csv | 10 - .../Music Playlist- SQL Project/genre.csv | 26 - .../Music Playlist- SQL Project/invoice.csv | 615 -- .../invoice_line.csv | 4758 --------- .../media_type.csv | 6 - .../Music Playlist- SQL Project/playlist.csv | 19 - .../playlist_track.csv | 8716 ----------------- .../schema_diagram.png | Bin 211851 -> 0 bytes .../Music Playlist- SQL Project/track.csv | 3504 ------- SQL_Music_Store_Analysis/album2.csv | 348 - SQL_Music_Store_Analysis/music store data.zip | Bin 366995 -> 0 bytes club_member_info/README.md | 5 +- club_member_info/REAME.md | 4 +- 30 files changed, 5 insertions(+), 19260 deletions(-) delete mode 100644 SQL_Music_Store_Analysis/Music Store Analysis-Questions.pdf delete mode 100644 SQL_Music_Store_Analysis/MusicDatabaseSchema.png delete mode 100644 SQL_Music_Store_Analysis/Music_Store_Query.sql delete mode 100644 SQL_Music_Store_Analysis/Music_Store_database.sql delete mode 100644 SQL_Music_Store_Analysis/README.md delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project.zip delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/Music Store Analysis-Questions.pdf delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/Music Store- Create Tables Query.txt delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/MusicDatabaseSchema.png delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/Music_Store_Query.sql delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/Music_Store_database.sql delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/SQL Music Questions2.docx delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/album.csv delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/artist.csv delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/customer.csv delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/employee.csv delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/genre.csv delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/invoice.csv delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/invoice_line.csv delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/media_type.csv delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/playlist.csv delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/playlist_track.csv delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/schema_diagram.png delete mode 100644 SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project/Music Playlist- SQL Project/track.csv delete mode 100644 SQL_Music_Store_Analysis/album2.csv delete mode 100644 SQL_Music_Store_Analysis/music store data.zip diff --git a/Coffee/README.MD b/Coffee/README.MD index 922125e..b5a168a 100644 --- a/Coffee/README.MD +++ b/Coffee/README.MD @@ -1,6 +1,6 @@ # Monday Coffee Expansion SQL Project -![Company Logo](https://github.com/najirh/Monday-Coffee-Expansion-Project-P8/blob/main/1.png) +![Company Logo](./1.png) ## Objective The goal of this project is to analyze the sales data of Monday Coffee, a company that has been selling its products online since January 2023, and to recommend the top three major cities in India for opening new coffee shop locations based on consumer demand and sales performance. diff --git a/Digital-Music-Store-Analysis with PostgreSQL/readme.md b/Digital-Music-Store-Analysis with PostgreSQL/readme.md index 99220f3..318c22b 100644 --- a/Digital-Music-Store-Analysis with PostgreSQL/readme.md +++ b/Digital-Music-Store-Analysis with PostgreSQL/readme.md @@ -6,4 +6,4 @@ Data Analysis project to help **Chinook Digital Music Store** to help how they c + pgAdmin4 -![schema](https://raw.githubusercontent.com/ptyadana/data-analysis-digital-music-store/master/ChinookSchema.png) \ No newline at end of file +![schema](./ChinookSchema.png) \ No newline at end of file diff --git a/SQL_Music_Store_Analysis/Music Store Analysis-Questions.pdf b/SQL_Music_Store_Analysis/Music Store Analysis-Questions.pdf deleted file mode 100644 index dfae82ef18d1eb7fb996bcbdd4c03fe727077448..0000000000000000000000000000000000000000 GIT binary patch literal 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-/* Q1: Who is the senior most employee based on job title? */ - -SELECT title, last_name, first_name -FROM employee -ORDER BY levels DESC -LIMIT 1 - - -/* Q2: Which countries have the most Invoices? */ - -SELECT COUNT(*) AS c, billing_country -FROM invoice -GROUP BY billing_country -ORDER BY c DESC - - -/* Q3: What are top 3 values of total invoice? */ - -SELECT total -FROM invoice -ORDER BY total DESC - - -/* Q4: Which city has the best customers? We would like to throw a promotional Music Festival in the city we made the most money. -Write a query that returns one city that has the highest sum of invoice totals. -Return both the city name & sum of all invoice totals */ - -SELECT billing_city,SUM(total) AS InvoiceTotal -FROM invoice -GROUP BY billing_city -ORDER BY InvoiceTotal DESC -LIMIT 1; - - -/* Q5: Who is the best customer? The customer who has spent the most money will be declared the best customer. -Write a query that returns the person who has spent the most money.*/ - -SELECT customer.customer_id, first_name, last_name, SUM(total) AS total_spending -FROM customer -JOIN invoice ON customer.customer_id = invoice.customer_id -GROUP BY customer.customer_id -ORDER BY total_spending DESC -LIMIT 1; - - - - -/* Question Set 2 - Moderate */ - -/* Q1: Write query to return the email, first name, last name, & Genre of all Rock Music listeners. -Return your list ordered alphabetically by email starting with A. */ - -/*Method 1 */ - -SELECT DISTINCT email,first_name, last_name -FROM customer -JOIN invoice ON customer.customer_id = invoice.customer_id -JOIN invoiceline ON invoice.invoice_id = invoiceline.invoice_id -WHERE track_id IN( - SELECT track_id FROM track - JOIN genre ON track.genre_id = genre.genre_id - WHERE genre.name LIKE 'Rock' -) -ORDER BY email; - - -/* Method 2 */ - -SELECT DISTINCT email AS Email,first_name AS FirstName, last_name AS LastName, genre.name AS Name -FROM customer -JOIN invoice ON invoice.customer_id = customer.customer_id -JOIN invoiceline ON invoiceline.invoice_id = invoice.invoice_id -JOIN track ON track.track_id = invoiceline.track_id -JOIN genre ON genre.genre_id = track.genre_id -WHERE genre.name LIKE 'Rock' -ORDER BY email; - - -/* Q2: Let's invite the artists who have written the most rock music in our dataset. -Write a query that returns the Artist name and total track count of the top 10 rock bands. */ - -SELECT artist.artist_id, artist.name,COUNT(artist.artist_id) AS number_of_songs -FROM track -JOIN album ON album.album_id = track.album_id -JOIN artist ON artist.artist_id = album.artist_id -JOIN genre ON genre.genre_id = track.genre_id -WHERE genre.name LIKE 'Rock' -GROUP BY artist.artist_id -ORDER BY number_of_songs DESC -LIMIT 10; - - -/* Q3: Return all the track names that have a song length longer than the average song length. -Return the Name and Milliseconds for each track. Order by the song length with the longest songs listed first. */ - -SELECT name,miliseconds -FROM track -WHERE miliseconds > ( - SELECT AVG(miliseconds) AS avg_track_length - FROM track ) -ORDER BY miliseconds DESC; - - - - -/* Question Set 3 - Advance */ - -/* Q1: Find how much amount spent by each customer on artists? Write a query to return customer name, artist name and total spent */ - -/* Steps to Solve: First, find which artist has earned the most according to the InvoiceLines. Now use this artist to find -which customer spent the most on this artist. For this query, you will need to use the Invoice, InvoiceLine, Track, Customer, -Album, and Artist tables. Note, this one is tricky because the Total spent in the Invoice table might not be on a single product, -so you need to use the InvoiceLine table to find out how many of each product was purchased, and then multiply this by the price -for each artist. */ - -WITH best_selling_artist AS ( - SELECT artist.artist_id AS artist_id, artist.name AS artist_name, SUM(invoice_line.unit_price*invoice_line.quantity) AS total_sales - FROM invoice_line - JOIN track ON track.track_id = invoice_line.track_id - JOIN album ON album.album_id = track.album_id - JOIN artist ON artist.artist_id = album.artist_id - GROUP BY 1 - ORDER BY 3 DESC - LIMIT 1 -) -SELECT c.customer_id, c.first_name, c.last_name, bsa.artist_name, SUM(il.unit_price*il.quantity) AS amount_spent -FROM invoice i -JOIN customer c ON c.customer_id = i.customer_id -JOIN invoice_line il ON il.invoice_id = i.invoice_id -JOIN track t ON t.track_id = il.track_id -JOIN album alb ON alb.album_id = t.album_id -JOIN best_selling_artist bsa ON bsa.artist_id = alb.artist_id -GROUP BY 1,2,3,4 -ORDER BY 5 DESC; - - -/* Q2: We want to find out the most popular music Genre for each country. We determine the most popular genre as the genre -with the highest amount of purchases. Write a query that returns each country along with the top Genre. For countries where -the maximum number of purchases is shared return all Genres. */ - -/* Steps to Solve: There are two parts in question- first most popular music genre and second need data at country level. */ - -/* Method 1: Using CTE */ - -WITH popular_genre AS -( - SELECT COUNT(invoice_line.quantity) AS purchases, customer.country, genre.name, genre.genre_id, - ROW_NUMBER() OVER(PARTITION BY customer.country ORDER BY COUNT(invoice_line.quantity) DESC) AS RowNo - FROM invoice_line - JOIN invoice ON invoice.invoice_id = invoice_line.invoice_id - JOIN customer ON customer.customer_id = invoice.customer_id - JOIN track ON track.track_id = invoice_line.track_id - JOIN genre ON genre.genre_id = track.genre_id - GROUP BY 2,3,4 - ORDER BY 2 ASC, 1 DESC -) -SELECT * FROM popular_genre WHERE RowNo <= 1 - - -/* Method 2: : Using Recursive */ - -WITH RECURSIVE - sales_per_country AS( - SELECT COUNT(*) AS purchases_per_genre, customer.country, genre.name, genre.genre_id - FROM invoice_line - JOIN invoice ON invoice.invoice_id = invoice_line.invoice_id - JOIN customer ON customer.customer_id = invoice.customer_id - JOIN track ON track.track_id = invoice_line.track_id - JOIN genre ON genre.genre_id = track.genre_id - GROUP BY 2,3,4 - ORDER BY 2 - ), - max_genre_per_country AS (SELECT MAX(purchases_per_genre) AS max_genre_number, country - FROM sales_per_country - GROUP BY 2 - ORDER BY 2) - -SELECT sales_per_country.* -FROM sales_per_country -JOIN max_genre_per_country ON sales_per_country.country = max_genre_per_country.country -WHERE sales_per_country.purchases_per_genre = max_genre_per_country.max_genre_number; - - -/* Q3: Write a query that determines the customer that has spent the most on music for each country. -Write a query that returns the country along with the top customer and how much they spent. -For countries where the top amount spent is shared, provide all customers who spent this amount. */ - -/* Steps to Solve: Similar to the above question. There are two parts in question- -first find the most spent on music for each country and second filter the data for respective customers. */ - -/* Method 1: using CTE */ - -WITH Customter_with_country AS ( - SELECT customer.customer_id,first_name,last_name,billing_country,SUM(total) AS total_spending, - ROW_NUMBER() OVER(PARTITION BY billing_country ORDER BY SUM(total) DESC) AS RowNo - FROM invoice - JOIN customer ON customer.customer_id = invoice.customer_id - GROUP BY 1,2,3,4 - ORDER BY 4 ASC,5 DESC) -SELECT * FROM Customter_with_country WHERE RowNo <= 1 - - -/* Method 2: Using Recursive */ - -WITH RECURSIVE - customter_with_country AS ( - SELECT customer.customer_id,first_name,last_name,billing_country,SUM(total) AS total_spending - FROM invoice - JOIN customer ON customer.customer_id = invoice.customer_id - GROUP BY 1,2,3,4 - ORDER BY 2,3 DESC), - - country_max_spending AS( - SELECT billing_country,MAX(total_spending) AS max_spending - FROM customter_with_country - GROUP BY 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You can examine the dataset with SQL and help the store understand its business growth by answering simple questions. - -> Complete project explained on YouTube: https://www.youtube.com/watch?v=VFIuIjswMKM - -## Database and Tools -* Postgre SQL -* PgAdmin4 - -Schema- Music Store Database -![MusicDatabaseSchema](https://user-images.githubusercontent.com/112153548/213707717-bfc9f479-52d9-407b-99e1-e94db7ae10a3.png) diff --git a/SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project.zip b/SQL_Music_Store_Analysis/Raw-Music Store Analysis-SQL Project.zip deleted file mode 100644 index 8b72b435bb31793c3b126d323ac1953d40fc811b..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 682064 zcmagFLwF@j)Tp~-+qP{x>Daby+eXJWI<{>a9ox>1)zSIRKe*@4{y|M@R_m#%Rqwl2 zDanF?qXPf{XaIWywFaaPL@yX70FX}y08solEAQ@VZAz?UXY6ff?drxrtg0+WtmNWo zV{YokWNc^RZqI1y>XD{1?SjXXzQZ^46SP`vCn*ej8p>o(Db;H)pj9k$X(KrbJ`yI? zk_@9ENUqwgJ!k3mWHJ=1{XApQ_OFo#YJ!|5t;*KopaE5wG}w2(_Z2^gwzu~5#|Bk9 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-GROUP BY billing_country -ORDER BY c DESC - - -/* Q3: What are top 3 values of total invoice? */ - -SELECT total -FROM invoice -ORDER BY total DESC - - -/* Q4: Which city has the best customers? We would like to throw a promotional Music Festival in the city we made the most money. -Write a query that returns one city that has the highest sum of invoice totals. -Return both the city name & sum of all invoice totals */ - -SELECT billing_city,SUM(total) AS InvoiceTotal -FROM invoice -GROUP BY billing_city -ORDER BY InvoiceTotal DESC -LIMIT 1; - - -/* Q5: Who is the best customer? The customer who has spent the most money will be declared the best customer. -Write a query that returns the person who has spent the most money.*/ - -SELECT customer.customer_id, first_name, last_name, SUM(total) AS total_spending -FROM customer -JOIN invoice ON customer.customer_id = invoice.customer_id -GROUP BY customer.customer_id -ORDER BY total_spending DESC -LIMIT 1; - - - - -/* Question Set 2 - Moderate */ - -/* Q1: Write query to return the email, first name, last name, & Genre of all Rock Music listeners. -Return your list ordered alphabetically by email starting with A. */ - -/*Method 1 */ - -SELECT DISTINCT email,first_name, last_name -FROM customer -JOIN invoice ON customer.customer_id = invoice.customer_id -JOIN invoiceline ON invoice.invoice_id = invoiceline.invoice_id -WHERE track_id IN( - SELECT track_id FROM track - JOIN genre ON track.genre_id = genre.genre_id - WHERE genre.name LIKE 'Rock' -) -ORDER BY email; - - -/* Method 2 */ - -SELECT DISTINCT email AS Email,first_name AS FirstName, last_name AS LastName, genre.name AS Name -FROM customer -JOIN invoice ON invoice.customer_id = customer.customer_id -JOIN invoiceline ON invoiceline.invoice_id = invoice.invoice_id -JOIN track ON track.track_id = invoiceline.track_id -JOIN genre ON genre.genre_id = track.genre_id -WHERE genre.name LIKE 'Rock' -ORDER BY email; - - -/* Q2: Let's invite the artists who have written the most rock music in our dataset. -Write a query that returns the Artist name and total track count of the top 10 rock bands. */ - -SELECT artist.artist_id, artist.name,COUNT(artist.artist_id) AS number_of_songs -FROM track -JOIN album ON album.album_id = track.album_id -JOIN artist ON artist.artist_id = album.artist_id -JOIN genre ON genre.genre_id = track.genre_id -WHERE genre.name LIKE 'Rock' -GROUP BY artist.artist_id -ORDER BY number_of_songs DESC -LIMIT 10; - - -/* Q3: Return all the track names that have a song length longer than the average song length. -Return the Name and Milliseconds for each track. Order by the song length with the longest songs listed first. */ - -SELECT name,miliseconds -FROM track -WHERE miliseconds > ( - SELECT AVG(miliseconds) AS avg_track_length - FROM track ) -ORDER BY miliseconds DESC; - - - - -/* Question Set 3 - Advance */ - -/* Q1: Find how much amount spent by each customer on artists? Write a query to return customer name, artist name and total spent */ - -/* Steps to Solve: First, find which artist has earned the most according to the InvoiceLines. Now use this artist to find -which customer spent the most on this artist. For this query, you will need to use the Invoice, InvoiceLine, Track, Customer, -Album, and Artist tables. Note, this one is tricky because the Total spent in the Invoice table might not be on a single product, -so you need to use the InvoiceLine table to find out how many of each product was purchased, and then multiply this by the price -for each artist. */ - -WITH best_selling_artist AS ( - SELECT artist.artist_id AS artist_id, artist.name AS artist_name, SUM(invoice_line.unit_price*invoice_line.quantity) AS total_sales - FROM invoice_line - JOIN track ON track.track_id = invoice_line.track_id - JOIN album ON album.album_id = track.album_id - JOIN artist ON artist.artist_id = album.artist_id - GROUP BY 1 - ORDER BY 3 DESC - LIMIT 1 -) -SELECT c.customer_id, c.first_name, c.last_name, bsa.artist_name, SUM(il.unit_price*il.quantity) AS amount_spent -FROM invoice i -JOIN customer c ON c.customer_id = i.customer_id -JOIN invoice_line il ON il.invoice_id = i.invoice_id -JOIN track t ON t.track_id = il.track_id -JOIN album alb ON alb.album_id = t.album_id -JOIN best_selling_artist bsa ON bsa.artist_id = alb.artist_id -GROUP BY 1,2,3,4 -ORDER BY 5 DESC; - - -/* Q2: We want to find out the most popular music Genre for each country. We determine the most popular genre as the genre -with the highest amount of purchases. Write a query that returns each country along with the top Genre. For countries where -the maximum number of purchases is shared return all Genres. */ - -/* Steps to Solve: There are two parts in question- first most popular music genre and second need data at country level. */ - -/* Method 1: Using CTE */ - -WITH popular_genre AS -( - SELECT COUNT(invoice_line.quantity) AS purchases, customer.country, genre.name, genre.genre_id, - ROW_NUMBER() OVER(PARTITION BY customer.country ORDER BY COUNT(invoice_line.quantity) DESC) AS RowNo - FROM invoice_line - JOIN invoice ON invoice.invoice_id = invoice_line.invoice_id - JOIN customer ON customer.customer_id = invoice.customer_id - JOIN track ON track.track_id = invoice_line.track_id - JOIN genre ON genre.genre_id = track.genre_id - GROUP BY 2,3,4 - ORDER BY 2 ASC, 1 DESC -) -SELECT * FROM popular_genre WHERE RowNo <= 1 - - -/* Method 2: : Using Recursive */ - -WITH RECURSIVE - sales_per_country AS( - SELECT COUNT(*) AS purchases_per_genre, customer.country, genre.name, genre.genre_id - FROM invoice_line - JOIN invoice ON invoice.invoice_id = invoice_line.invoice_id - JOIN customer ON customer.customer_id = invoice.customer_id - JOIN track ON track.track_id = invoice_line.track_id - JOIN genre ON genre.genre_id = track.genre_id - GROUP BY 2,3,4 - ORDER BY 2 - ), - max_genre_per_country AS (SELECT MAX(purchases_per_genre) AS max_genre_number, country - FROM sales_per_country - GROUP BY 2 - ORDER BY 2) - -SELECT sales_per_country.* -FROM sales_per_country -JOIN max_genre_per_country ON sales_per_country.country = max_genre_per_country.country -WHERE sales_per_country.purchases_per_genre = max_genre_per_country.max_genre_number; - - -/* Q3: Write a query that determines the customer that has spent the most on music for each country. -Write a query that returns the country along with the top customer and how much they spent. -For countries where the top amount spent is shared, provide all customers who spent this amount. */ - -/* Steps to Solve: Similar to the above question. There are two parts in question- -first find the most spent on music for each country and second filter the data for respective customers. */ - -/* Method 1: using CTE */ - -WITH Customter_with_country AS ( - SELECT customer.customer_id,first_name,last_name,billing_country,SUM(total) AS total_spending, - ROW_NUMBER() OVER(PARTITION BY billing_country ORDER BY SUM(total) DESC) AS RowNo - FROM invoice - JOIN customer ON customer.customer_id = invoice.customer_id - GROUP BY 1,2,3,4 - ORDER BY 4 ASC,5 DESC) -SELECT * FROM Customter_with_country WHERE RowNo <= 1 - - -/* Method 2: Using Recursive */ - -WITH RECURSIVE - customter_with_country AS ( - SELECT customer.customer_id,first_name,last_name,billing_country,SUM(total) AS total_spending - FROM invoice - JOIN customer ON customer.customer_id = invoice.customer_id - GROUP BY 1,2,3,4 - ORDER BY 2,3 DESC), - - country_max_spending AS( - SELECT billing_country,MAX(total_spending) AS max_spending - FROM customter_with_country - GROUP BY 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