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These are the user uploaded subtitles that are being translated: 0 1 00:00:01,280 --> 00:00:04,352 The next and the last function is a string aggregator 1 2 00:00:05,632 --> 00:00:10,496 String aggregator will concatenate all the input values into a single string 2 3 00:00:10,752 --> 00:00:13,056 And all those values will be 3 4 00:00:13,312 --> 00:00:19,456 Separated by a delimiter delimiter is a symbol which you will mention and this symbol will segregate 4 5 00:00:19,712 --> 00:00:21,760 the input values of the string 5 6 00:00:24,320 --> 00:00:25,088 The syntax for 6 7 00:00:25,600 --> 00:00:27,904 String aggregation is string underscore 7 8 00:00:28,416 --> 00:00:29,440 agg 8 9 00:00:29,696 --> 00:00:31,744 and then you mention the expression 9 10 00:00:32,000 --> 00:00:36,352 This will contain the strings or it will contain the column name 10 11 00:00:37,632 --> 00:00:38,144 Comma 11 12 00:00:38,400 --> 00:00:41,984 The delimiter, delimiter usually is a comma 12 13 00:00:42,752 --> 00:00:44,032 You can have space 13 14 00:00:44,288 --> 00:00:47,360 We have tabs you can have any other special symbol 14 15 00:00:49,408 --> 00:00:50,176 Note that 15 16 00:00:50,688 --> 00:00:54,016 String aggregator is also concatenating strings 16 17 00:00:54,528 --> 00:00:59,136 But what is the difference between a string aggregator and the CONCAT operator 17 18 00:01:00,160 --> 00:01:01,440 When we used concat 18 19 00:01:01,952 --> 00:01:02,464 It 19 20 00:01:02,976 --> 00:01:04,512 Concatenated strings 20 21 00:01:05,280 --> 00:01:07,584 Of different column for a single record 21 22 00:01:09,120 --> 00:01:11,168 For example We concatenated 22 23 00:01:11,424 --> 00:01:15,264 City state and country for each customer 23 24 00:01:16,800 --> 00:01:19,360 Where as string aggregator will be used 24 25 00:01:19,616 --> 00:01:22,432 To concatenate all values in a column 25 26 00:01:22,944 --> 00:01:24,736 So for different records 26 27 00:01:25,504 --> 00:01:27,552 There will be different values in that column 27 28 00:01:27,808 --> 00:01:31,136 All those different values can be aggregated 28 29 00:01:31,904 --> 00:01:33,696 Using this string aggregate function 29 30 00:01:34,208 --> 00:01:36,512 Let us look at this using example 30 31 00:01:39,072 --> 00:01:40,864 If you remember from the sales table 31 32 00:01:41,376 --> 00:01:45,472 In the sales table there are different rows for each order 32 33 00:01:45,728 --> 00:01:48,032 And each order had different products 33 34 00:01:49,056 --> 00:01:50,848 So with the same order ID 34 35 00:01:51,104 --> 00:01:52,384 There'll be multiple rows 35 36 00:01:52,896 --> 00:01:59,040 And in these different rows there will be different product IDs. Basically the customer has ordered within a single order 36 37 00:01:59,296 --> 00:02:00,832 Different products 37 38 00:02:01,344 --> 00:02:02,880 If you want to find out 38 39 00:02:03,136 --> 00:02:07,232 What are the products in each order ID 39 40 00:02:08,000 --> 00:02:10,560 So we willl first group the order by order ID 40 41 00:02:10,816 --> 00:02:12,864 And within every order ID 41 42 00:02:13,120 --> 00:02:16,192 We will aggregate the different product IDs 42 43 00:02:16,704 --> 00:02:18,240 And we'll separate these with a 43 44 00:02:18,496 --> 00:02:19,008 Comma 44 45 00:02:20,032 --> 00:02:20,800 This is the 45 46 00:02:21,312 --> 00:02:24,384 Syntax select order ID, string aggregators 46 47 00:02:24,640 --> 00:02:28,736 The product ID separated by comma from sales table group by order ID 47 48 00:02:28,992 --> 00:02:35,136 Let's go and see in the pg Admin. Let us first do a select star on the sales table 48 49 00:02:35,392 --> 00:02:36,160 Just to 49 50 00:02:37,696 --> 00:02:43,840 So that I show you there are different order IDs and product IDs which 50 51 00:02:44,096 --> 00:02:47,168 are taking up different rows in the table 51 52 00:02:51,520 --> 00:02:52,544 You can see 52 53 00:02:55,616 --> 00:02:57,408 this second and third row 53 54 00:02:57,920 --> 00:02:59,712 The order ID is same 54 55 00:03:00,736 --> 00:03:04,064 But this row is different because the product ID is different 55 56 00:03:04,832 --> 00:03:06,624 So I want to find out 56 57 00:03:06,880 --> 00:03:08,416 For each order ID 57 58 00:03:08,672 --> 00:03:10,208 What are the products 58 59 00:03:10,464 --> 00:03:11,744 Ordered. To do that 59 60 00:03:12,000 --> 00:03:12,512 I'll group 60 61 00:03:12,768 --> 00:03:14,048 it by the order ID 61 62 00:03:14,304 --> 00:03:18,912 And against each order ID I'll have the product IDs concatenated 62 63 00:03:19,168 --> 00:03:24,032 Let's see. select order ID 63 64 00:03:27,616 --> 00:03:28,640 And 64 65 00:03:28,896 --> 00:03:32,480 String underscore agg 65 66 00:03:35,808 --> 00:03:38,624 This 66 67 00:03:38,880 --> 00:03:42,464 Column is to be aggregated separated by comma space 67 68 00:03:44,512 --> 00:03:46,816 Comma space 68 69 00:03:49,376 --> 00:03:53,728 From the sales table, grouped by 69 70 00:03:57,824 --> 00:03:59,104 The order ID 70 71 00:04:00,896 --> 00:04:07,040 Let's order it also by the order ID 71 72 00:04:07,296 --> 00:04:09,088 And run it 72 73 00:04:13,696 --> 00:04:17,791 You can see in the sales table there were multiple entries of the same order ID 73 74 00:04:18,047 --> 00:04:22,143 here we have grouped it so it will be a single entry for each order ID 74 75 00:04:22,399 --> 00:04:24,959 Add against that order ID you will see the different 75 76 00:04:25,471 --> 00:04:25,983 Products 76 77 00:04:26,239 --> 00:04:28,543 So this second order ID 77 78 00:04:29,055 --> 00:04:29,567 Has 78 79 00:04:29,823 --> 00:04:31,871 Two products separated by a comma 79 80 00:04:32,127 --> 00:04:33,663 If you go down you will find 80 81 00:04:33,919 --> 00:04:35,455 several order IDs with 81 82 00:04:35,711 --> 00:04:37,247 More than two products also 82 83 00:04:38,783 --> 00:04:42,623 So you can see we have concatenated values in different rows 83 84 00:04:42,879 --> 00:04:45,951 Of the same column the column was product ID 84 85 00:04:46,719 --> 00:04:49,791 So we have concatenated values in different rows 85 86 00:04:50,815 --> 00:04:53,375 So this is what string aggregator function does 86 87 00:04:53,887 --> 00:04:56,191 That is all for the string functions 87 88 00:04:57,215 --> 00:04:59,519 In the next section we will look at Mathematical functions 6841

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