WEBVTT 00:00.460 --> 00:06.790 Okay, So now we were able to get the company name and all we need to do now to get the contact column 00:06.790 --> 00:13.150 and the contact column is just to do the same thing we have here just with a different index instead. 00:13.420 --> 00:21.280 So let's just copy this line here and paste it down two times below and change the index to one and 00:21.280 --> 00:24.490 we change the variable name to be contact instead. 00:24.790 --> 00:30.910 And down here we change it to be two and change it to be country instead. 00:30.910 --> 00:32.830 So then it fits with the table. 00:32.830 --> 00:37.180 And now we need to put all of the results. 00:37.180 --> 00:45.550 For every row we have a object we create, let's call it const and let's call it scraped. 00:46.470 --> 00:47.040 Row. 00:47.820 --> 00:54.750 And let's say that it is this object here with the company contact and country. 00:57.570 --> 00:58.710 And we save that. 00:58.710 --> 01:05.130 And then we need to save it into an array that we declare up here before we begin the loop. 01:05.130 --> 01:13.350 So up here we can declare an array we call const scraped rows, just an empty array. 01:13.350 --> 01:19.350 And then for each row we just push this scraped object into the array. 01:19.380 --> 01:21.570 So scraped rows. 01:22.290 --> 01:23.610 Third push. 01:24.400 --> 01:26.620 Scrape row. 01:28.090 --> 01:34.930 Now, once the loop has finished, we can try to do a console log to see how the array is looking like. 01:35.650 --> 01:39.520 Console log scraped rows. 01:40.590 --> 01:45.240 Let's save that and let's try to run it inside Node JS. 01:45.690 --> 01:47.640 Node Index.js. 01:47.670 --> 01:48.720 And here we go. 01:48.720 --> 01:52.800 So now we can see all of the table data. 01:53.490 --> 02:01.110 You can see the first row here has empty data inside of it because it has the element instead. 02:01.110 --> 02:03.570 But we're going to fix that in just a moment. 02:03.720 --> 02:11.670 But as you can see, we have all the other rows here with the company, contact and country correctly 02:11.670 --> 02:12.750 declared. 02:12.780 --> 02:19.440 Let's try and skip the first row we have on top so we don't have this empty object here. 02:19.440 --> 02:25.470 So we can say if the index equals zero. 02:25.470 --> 02:30.210 So that's the first row we have up here with the elements. 02:30.360 --> 02:35.040 If that's is the case, if that's the case, then we just say return true. 02:35.040 --> 02:42.970 So then then we skip this this iteration of the each loop, this, this row. 02:43.000 --> 02:43.960 We skip that. 02:44.650 --> 02:49.270 So now let's try and run it again and see what happens here. 02:49.360 --> 02:55.090 So now we have all of the rows, but without the empty data at the first row. 02:56.400 --> 02:57.630 Okay, so that's it. 02:57.630 --> 03:04.920 That's how we we find out how to build a selector with chrome tools and how to make sure it works inside 03:04.920 --> 03:09.950 Chrome tools and then how to transfer that into NodeJS. 03:09.960 --> 03:16.860 So now that we have it inside of NodeJS, we can build an API, we can deploy a periodic scraper that 03:16.860 --> 03:25.140 we can make, so we can make it scrape a page at every hour, every day, every week or however however 03:25.140 --> 03:26.250 we want to do it. 03:26.610 --> 03:34.290 And so now we can scrape websites without having a browser open and pasting pasting in code every time. 03:34.800 --> 03:41.790 And we can save the data to a database in MongoDB or save it to a CSV file and so on. 03:42.090 --> 03:49.020 So I hope you enjoyed this section and if there's any questions or if you're stuck with anything, let 03:49.020 --> 03:49.710 me know.