1 00:00:00,530 --> 00:00:08,300 In this video, we will learn about web scraping in power, so we will have to pass in total and today 2 00:00:08,300 --> 00:00:09,750 we will do the part parfum. 3 00:00:10,280 --> 00:00:13,690 For this, I need to show you one website, Wadlow meters dot info. 4 00:00:14,030 --> 00:00:17,120 And here we have different population collectivize. 5 00:00:17,390 --> 00:00:20,900 For example, if I click China, then we can see. 6 00:00:23,100 --> 00:00:24,960 The population of China. 7 00:00:25,250 --> 00:00:35,790 Right, so here we have different columns and then let me copy this link and if I want to see a population, 8 00:00:35,790 --> 00:00:37,530 for example, India. 9 00:00:38,400 --> 00:00:44,700 So, again, I need to play one by one to see different population in in different cities. 10 00:00:44,710 --> 00:00:49,990 So here you can see we have a population in different cities as well. 11 00:00:50,130 --> 00:00:53,160 So we are Indesit to fetch this information. 12 00:00:54,420 --> 00:00:59,490 And for this, I need to go to the power theory here first. 13 00:00:59,490 --> 00:01:01,620 I need to get data. 14 00:01:03,000 --> 00:01:10,800 And you have to click whip because we need to get the data from the Web and we need to be Stelling and 15 00:01:10,800 --> 00:01:11,380 click, OK? 16 00:01:12,570 --> 00:01:16,590 And now the paperback is extracting the data. 17 00:01:18,620 --> 00:01:22,840 And here you can see we have different data. 18 00:01:22,880 --> 00:01:31,730 Let me submit so here you can see the table one we have Colomban and table two, we have data and population. 19 00:01:33,350 --> 00:01:41,780 And then again, you can see different tables that are available on the website, Overbay has accepted 20 00:01:41,780 --> 00:01:42,770 all the information. 21 00:01:46,410 --> 00:01:51,570 So here you can see in the table six, we have a city name and population, so we are interested in 22 00:01:51,570 --> 00:01:54,030 this table for this. 23 00:01:54,030 --> 00:01:54,870 We need to click. 24 00:01:57,210 --> 00:02:01,500 And this statement, and then we have to transform later. 25 00:02:08,800 --> 00:02:14,860 So here we have data, 40 cities in China, two different cities and their populations. 26 00:02:18,430 --> 00:02:20,890 Let's go to the audience editor here. 27 00:02:23,790 --> 00:02:24,290 And. 28 00:02:26,280 --> 00:02:34,350 If I, um, let me show you the website, if I go to like India or maybe. 29 00:02:37,550 --> 00:02:49,610 So here you can see if I mouth over on India and you can see this is India dash population and the India 30 00:02:49,610 --> 00:02:50,250 hyperlink. 31 00:02:50,330 --> 00:02:50,690 Right. 32 00:02:51,470 --> 00:02:54,930 So if I click USA, then is the US population. 33 00:02:55,820 --> 00:02:59,830 So then what we have to do is let's call the power rate. 34 00:03:01,710 --> 00:03:06,570 And the advance editor and here we just need to replace China. 35 00:03:09,330 --> 00:03:19,710 Possibly want to see the population for the India so you can see India population and then we have a 36 00:03:19,710 --> 00:03:29,880 click then and you will see we are getting all the cities from India and in the same way we can quite 37 00:03:30,120 --> 00:03:34,350 different sitting here like a US based population. 38 00:03:34,360 --> 00:03:36,990 Then we will get the data from the US. 39 00:03:36,990 --> 00:03:37,230 Right. 40 00:03:37,740 --> 00:03:39,380 So let's light one function here. 41 00:03:47,750 --> 00:03:49,730 So it would be as simple. 42 00:03:53,780 --> 00:04:04,130 Country name is taxed because it's a tax information and we need as a table and then we have the right 43 00:04:04,660 --> 00:04:07,860 to say equal and greater, then. 44 00:04:08,930 --> 00:04:10,790 So this is the function, right? 45 00:04:13,970 --> 00:04:17,590 The name and we just need to click on. 46 00:04:19,470 --> 00:04:25,110 Before clicking, then, we just need to replace. 47 00:04:29,710 --> 00:04:38,760 Here they are, the population we have to replace the name, the parameter name, like the word for 48 00:04:38,760 --> 00:04:38,840 the. 49 00:04:39,700 --> 00:04:42,880 What was what is the name of the pyramid of this country name? 50 00:04:42,940 --> 00:04:53,160 I just need to copy and then I have to, because every time this thing is being changed in the adult 51 00:04:53,170 --> 00:04:53,800 population. 52 00:04:53,800 --> 00:04:59,050 So what I have to do is for this, I need to write and ampersand. 53 00:05:00,310 --> 00:05:11,590 And then I have to write the name of the perimeter escorting continent and then again and sign and hear 54 00:05:12,340 --> 00:05:13,930 the wind, right. 55 00:05:17,480 --> 00:05:22,000 OK, so this is the stuff that we need to right here. 56 00:05:25,580 --> 00:05:32,780 And so it is taking we are putting country name as a barometer to the to the you are it. 57 00:05:33,000 --> 00:05:33,460 Right? 58 00:05:34,130 --> 00:05:35,840 So let's click done. 59 00:05:37,610 --> 00:05:41,020 And here you can see we are getting one convenient barometer. 60 00:05:41,780 --> 00:05:50,430 So here I have to, for example, if I want to get data from the U.S. So I just see right here is the 61 00:05:50,690 --> 00:05:51,410 population. 62 00:05:59,690 --> 00:06:02,120 And then I need to click, OK, invoke. 63 00:06:04,930 --> 00:06:15,850 So here you can see this is the population from us and the same like if I was in Pakistan, click, 64 00:06:15,850 --> 00:06:19,990 OK, and here you can see the population of all the different cities. 65 00:06:20,500 --> 00:06:22,330 How many more? 66 00:06:22,360 --> 00:06:27,080 So this is how we can get data from different countries. 67 00:06:27,100 --> 00:06:28,410 So let's do one more thing. 68 00:06:28,960 --> 00:06:34,560 We we just need to delete this invert function cable. 69 00:06:36,390 --> 00:06:37,890 And the latest. 70 00:06:40,430 --> 00:06:49,790 And we need to write one BlackBerry here, too, because we don't need to right every time different 71 00:06:49,790 --> 00:06:54,210 countries or we will make a table that will have different countries inside. 72 00:06:55,220 --> 00:06:58,360 So we need right here like BlackBerry. 73 00:07:00,860 --> 00:07:02,630 And today it was Ed. 74 00:07:04,250 --> 00:07:05,510 And here we have two. 75 00:07:08,630 --> 00:07:10,100 Delete this one. 76 00:07:15,210 --> 00:07:21,330 And then we have right here, for example, one table hash table. 77 00:07:25,500 --> 00:07:29,400 And then when it right died, David. 78 00:07:31,960 --> 00:07:32,860 And they had some. 79 00:07:36,220 --> 00:07:41,110 The Blackhawks and the heroic and write country name. 80 00:07:48,500 --> 00:07:50,360 And then when you tried Koma. 81 00:07:56,330 --> 00:08:00,820 It and then one more calibrated because we need a couple of values here. 82 00:08:01,740 --> 00:08:06,320 So here we have to write the name of the the curious thing. 83 00:08:07,050 --> 00:08:09,510 So it is India. 84 00:08:11,830 --> 00:08:12,970 This population. 85 00:08:18,530 --> 00:08:20,180 So I just need to copy 86 00:08:23,360 --> 00:08:27,650 and then I need to create another. 87 00:08:33,200 --> 00:08:34,070 So this is. 88 00:08:37,070 --> 00:08:43,470 US population and we can create more for Ssempa. 89 00:08:51,290 --> 00:08:52,950 Pakistan population, right? 90 00:08:53,780 --> 00:08:59,790 So here we have created one table that contain three the to India. 91 00:09:00,200 --> 00:09:05,840 India population, the US and Pakistan, and then we just need to click 10. 92 00:09:08,650 --> 00:09:13,750 And the name of the stable we can right here 93 00:09:17,020 --> 00:09:27,220 country list, this is the name of the table and what we can do now, we just need to click Ed column 94 00:09:27,850 --> 00:09:32,560 and here we have to invoke custom function. 95 00:09:35,980 --> 00:09:37,960 And in the custom function. 96 00:09:39,160 --> 00:09:44,210 We need to listen to one one one more thing here. 97 00:09:44,770 --> 00:09:46,400 This is the name of a function, right? 98 00:09:47,390 --> 00:09:50,780 So we have to write a name like a fine 99 00:09:53,390 --> 00:10:00,020 country, and then we just have to click then and again to the country list. 100 00:10:00,860 --> 00:10:07,270 OK, so here we have all the three values and now we need to click invoked function, invoked custom 101 00:10:07,280 --> 00:10:07,760 function. 102 00:10:09,270 --> 00:10:14,040 So here you can write any any name of the column, for example, 103 00:10:17,310 --> 00:10:27,100 combine data and the function query, this is the name of the curious country and then the country name. 104 00:10:27,840 --> 00:10:30,320 This is the table like the country name table. 105 00:10:31,800 --> 00:10:32,860 So that's all. 106 00:10:34,020 --> 00:10:36,170 So let's click, OK? 107 00:10:39,280 --> 00:10:43,120 And here is the information is required to get approval to continue. 108 00:10:44,880 --> 00:10:47,070 And ignore privacy level checks. 109 00:10:48,110 --> 00:10:48,680 Save. 110 00:10:50,900 --> 00:10:54,410 And then we need to wait and here you can see. 111 00:10:55,730 --> 00:11:04,880 They bailed out Ed column country list and we will get one one table that will have one column, the 112 00:11:04,880 --> 00:11:09,160 color name will be continuous and it will contain the information. 113 00:11:09,560 --> 00:11:18,470 And here you can see each so this function F and country will execute for each curious thing. 114 00:11:19,010 --> 00:11:19,780 I see. 115 00:11:20,570 --> 00:11:27,890 So this function has been executed for the Indian population, U.S. population and Pakistan population 116 00:11:27,890 --> 00:11:34,610 and fetch this record city name and some other for every country. 117 00:11:35,900 --> 00:11:39,980 It has received different messages depending on the country. 118 00:11:40,650 --> 00:11:44,090 We need to just need to combine data for the India, US and Pakistan. 119 00:11:45,560 --> 00:11:50,360 We just need to click here and you can click, OK? 120 00:11:53,020 --> 00:12:03,000 So here you can see we are getting data like a country name, and this is a city name and city population, 121 00:12:03,340 --> 00:12:09,510 and here you can see this in India and these are the different cities in India and their population. 122 00:12:09,940 --> 00:12:12,490 And then you can see us. 123 00:12:13,000 --> 00:12:21,430 And here it is the same I mean, different cities in the US and the population in the same way in Pakistan. 124 00:12:21,430 --> 00:12:21,700 Right. 125 00:12:22,330 --> 00:12:32,350 So what we have done here, we have just created one one table that holds all the recorded data that 126 00:12:32,350 --> 00:12:34,930 we need to scrap for Zimbabwe. 127 00:12:35,110 --> 00:12:44,500 We wanted to separate our two countries, Pakistan, US and India, and we don't need to go every time 128 00:12:44,500 --> 00:12:52,870 to the website to change the U.N. And I mean, then we just need to if we need to combine all the data 129 00:12:52,870 --> 00:13:03,100 in in one column, like a country name or the population of Sydney, then we don't need to go to like 130 00:13:04,840 --> 00:13:12,640 for example, here you can say we have different is so far has been used to get data from the US and 131 00:13:12,640 --> 00:13:18,460 then we need to get data from in India, like India and Pakistan in three different tables. 132 00:13:18,820 --> 00:13:25,830 And then we have to apply Mouskouri to to match all the data in the single destination. 133 00:13:25,840 --> 00:13:26,120 Right. 134 00:13:26,590 --> 00:13:34,280 So with the help of some function in poverty, we have to all the stuff in one step. 135 00:13:35,050 --> 00:13:41,770 So this is how we can use custom function to retrieve the data very quickly. 136 00:13:42,640 --> 00:13:44,350 So this is this was the first part. 137 00:13:44,590 --> 00:13:47,770 We will continue to enhance the web scrapping in poverty. 138 00:13:49,150 --> 00:13:50,050 In the next part.