WEBVTT 00:07.730 --> 00:08.210 All right. 00:08.210 --> 00:13.970 So in this video let me go ahead and look at the age function in PostgreSQL. 00:14.870 --> 00:15.230 All right. 00:15.260 --> 00:17.240 So we're going to deal with age function. 00:17.270 --> 00:20.300 And what we're going to run into the big problem. 00:20.330 --> 00:21.440 Yes. 00:21.470 --> 00:27.410 The big problem we're going to run is that when I was creating this I was creating this the enrolled 00:27.410 --> 00:31.760 date as from 2014 to 2015. 00:31.790 --> 00:34.550 This is the year that never existed before now. 00:35.060 --> 00:45.830 And, uh, I should have gone to, uh, actually in, uh, create in road dates from 1980 or 2000, 00:45.860 --> 00:50.450 anything maybe 2000 below 2020 and so on. 00:50.480 --> 00:54.590 What I want for us 2014 to 2015. 00:55.190 --> 00:55.610 All right. 00:55.640 --> 01:03.920 Now, if I were to get each of each of these people, maybe from the time they enrolled into the school 01:03.950 --> 01:08.680 to date, I should be getting negative date or negative age. 01:09.430 --> 01:16.060 What if I've done this from maybe 19 something, or now I should be getting the age? 01:16.240 --> 01:20.770 Let me say seven years ago, eight years ago or nine years ago. 01:20.800 --> 01:21.370 What now? 01:21.370 --> 01:29.200 If I should go ahead and do that from 2040, 2050, which never existed, is going to start from maybe 01:29.230 --> 01:34.600 minus seven years, -20 years, -18, -16 and so on. 01:34.630 --> 01:37.480 But I need to introduce us to these. 01:37.480 --> 01:41.080 That is why I want to make this video. 01:41.080 --> 01:48.580 So you can go ahead and are great in new, uh, data sets from macro. 01:48.610 --> 01:54.460 You can drop this table and uh, change it or enroll date to 19. 01:54.490 --> 01:58.330 Anything you understand so that this date can actually match. 01:58.330 --> 02:05.350 But for the sake of this course and for us having the knowledge, I want to actually explain this before 02:05.350 --> 02:09.160 we go ahead and check the age of the students. 02:09.190 --> 02:09.730 All right. 02:09.730 --> 02:10.990 Let me go ahead and see. 02:11.020 --> 02:20.550 I want to select all from students or acquire head and select maybe the first underscore name, and 02:20.550 --> 02:23.760 I will select the last underscore name. 02:23.760 --> 02:30.090 And uh I will also select the in row underscore. 02:30.120 --> 02:32.070 Did you understand. 02:32.100 --> 02:35.610 Now I will introduce an h function. 02:35.610 --> 02:39.720 And this h function accepts two arguments. 02:39.750 --> 02:42.330 The very first argument is a timestamp. 02:42.330 --> 02:51.300 We are going to start now where we are taking this lecture to the age 2042, to know the age that the 02:51.300 --> 02:52.260 students enrolled. 02:52.260 --> 02:55.950 And that is going to give us minus which is not proper. 02:55.950 --> 03:04.860 But if we have done enroll date to be something better off, maybe like 1960, 1970, 1989, 2000 and 03:04.860 --> 03:07.860 so on, it might be like 17 years ago. 03:07.890 --> 03:10.650 Now let's go ahead and introduce that H function. 03:10.650 --> 03:12.270 And I want to show us this. 03:12.270 --> 03:17.070 So the function, the very first the text, the timestamp, the very first one is noun. 03:17.070 --> 03:20.410 So starting from now we want to check out dates. 03:20.410 --> 03:26.050 And you insert the a row underscore date. 03:26.050 --> 03:29.920 So this is a quorum we want to actually check. 03:29.950 --> 03:35.620 And we're going to create a new quorum to actually give us the age of the student. 03:35.620 --> 03:44.650 And for us to do that we're going to create that new quorum as age or as students. 03:47.440 --> 03:49.420 Students underscore age. 03:50.020 --> 03:50.470 Okay. 03:50.500 --> 03:53.620 Now we can go ahead and execute this query and check it out. 03:53.650 --> 04:01.120 Now, just like I explained, you can see that our Macron alone enrolled on this. 04:01.120 --> 04:04.300 And that is -70 is a goal. 04:04.330 --> 04:11.290 And the negative term ones and the -20 days and the time the person enrolled. 04:11.290 --> 04:20.380 So this is the time stamp on the submit this to be like in 1920, 1989, 1960, 17 and so on. 04:20.410 --> 04:21.610 You might have something better. 04:21.610 --> 04:24.250 And that should be like 17 years, three months ago. 04:24.280 --> 04:27.790 2020, three days ago and so on. 04:28.120 --> 04:32.890 So I think I explained this sort of actually know why we are having negative e. 04:32.920 --> 04:33.400 Okay. 04:33.430 --> 04:38.200 So you can actually go ahead and add a create a new macro dataset. 04:38.230 --> 04:43.870 Then drop this table is set or you know new table right in here. 04:43.870 --> 04:49.210 And now actually create a new table called a student's age. 04:49.210 --> 04:59.020 Or students are vacation or the time they actually graduated or the graduation age. 05:00.190 --> 05:01.930 Okay, so I hope that is cool. 05:01.930 --> 05:03.370 So go ahead and check it out. 05:03.370 --> 05:04.600 I just want to introduce this. 05:04.600 --> 05:11.950 So can be able to know how to add or take in this function known as the age function is very important 05:11.950 --> 05:13.030 in PostgreSQL. 05:13.030 --> 05:14.380 So go ahead and check it out. 05:14.380 --> 05:17.410 And if you have any questions go ahead and use the question and answer section. 05:17.410 --> 05:19.840 And I'm going to get back to you as soon as possible. 05:19.870 --> 05:20.800 Thank you so much. 05:20.800 --> 05:24.070 And I'm going to see you in the next video lecture.