All language subtitles for 3. Import & manage data from Yahoo Finance

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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:12,300 --> 00:00:14,580 Hey, everyone, and welcome in this new video. 2 00:00:15,270 --> 00:00:23,430 In this video, we will import some data which come from without violence, and we will process the 3 00:00:23,430 --> 00:00:27,540 data to obtain exactly the same syntax. 4 00:00:27,720 --> 00:00:30,450 As for the data? 5 00:00:31,960 --> 00:00:33,760 Which come from Matis worldwide. 6 00:00:34,180 --> 00:00:34,550 OK. 7 00:00:34,900 --> 00:00:38,350 After the purpose of saying, of course, we're going to have. 8 00:00:39,800 --> 00:00:48,770 Always the same data after the preprocessing, first, we need to understand how to import some data 9 00:00:48,950 --> 00:00:51,170 using white finance, so. 10 00:00:54,320 --> 00:00:58,790 We will use the download function and then. 11 00:00:59,870 --> 00:01:05,290 You need to put the symbol of the assets that you import. 12 00:01:06,260 --> 00:01:11,780 OK, here I have put you used to find all the symbol. 13 00:01:12,200 --> 00:01:15,650 You just need to go on Yahoo Finance. 14 00:01:15,890 --> 00:01:18,380 You take, for example, one asset. 15 00:01:18,680 --> 00:01:25,030 And here you will see sorry, the symbol, OK? 16 00:01:25,460 --> 00:01:30,140 Two important using the way finance library. 17 00:01:32,970 --> 00:01:33,330 So. 18 00:01:34,420 --> 00:01:39,190 Then we need to create a preprocessing function. 19 00:01:40,250 --> 00:01:46,730 For the wife finance data, because as you can see here, we have. 20 00:01:48,840 --> 00:01:59,070 The name of the data of the column, which are different from the name, from the data on methods of 21 00:01:59,130 --> 00:01:59,520 fighting. 22 00:02:01,830 --> 00:02:04,590 We have an that close column. 23 00:02:05,250 --> 00:02:11,640 OK, so we need to make some modification, but some different modification. 24 00:02:11,830 --> 00:02:12,930 OK, so. 25 00:02:14,630 --> 00:02:15,980 I will take this. 26 00:02:17,890 --> 00:02:25,180 And in the preprocessing function for the yellow finance stater, I need to import that data. 27 00:02:25,970 --> 00:02:34,750 OK, then I will just apply that drop any to be sure that we don't have any missing value. 28 00:02:34,870 --> 00:02:41,500 So now forget to do it here, but we also can do it. 29 00:02:41,920 --> 00:02:42,310 OK. 30 00:02:48,970 --> 00:02:55,630 So now I have rename the columns OK and the index. 31 00:02:55,840 --> 00:03:02,800 So if I run the Senate like this, we will have the necessary things. 32 00:03:03,020 --> 00:03:12,040 OK, so the open Ilocos, would you name exactly the same as for the metadata of flight data officer 33 00:03:12,040 --> 00:03:12,730 preprocessing? 34 00:03:13,060 --> 00:03:21,640 And we can is really not mandatory, but I will just show you how to do it if you want to delete. 35 00:03:23,340 --> 00:03:33,710 The adjusted cross color in our case, the adjusted gross Karen, is not really important because usually 36 00:03:33,720 --> 00:03:35,850 with is forward data. 37 00:03:35,880 --> 00:03:40,590 So obviously the colors and the adjusted cross will be the same. 38 00:03:40,890 --> 00:03:45,000 But if you work with Stoke, for example, and that. 39 00:03:46,470 --> 00:03:48,120 You have a split. 40 00:03:49,560 --> 00:03:50,930 In your room. 41 00:03:52,300 --> 00:03:55,690 The split of the action price in your data, OK? 42 00:03:55,900 --> 00:04:02,380 The adjusted gross price will be very interesting, but in other hand, if you work with adjusted gross 43 00:04:02,380 --> 00:04:07,030 price, it will be very difficult to create your technical indicator. 44 00:04:07,470 --> 00:04:15,400 OK, if you have to use also the open and I price, for example, so. 45 00:04:16,990 --> 00:04:26,590 He the goal the the really the main goal of this chapter is to show you how to import some data. 46 00:04:26,830 --> 00:04:28,150 OK, so. 47 00:04:29,760 --> 00:04:36,210 That's not really the goal, because to import some data manually from meters for or. 48 00:04:36,750 --> 00:04:41,950 It's very simple to import some data for Yahoo Finance. 49 00:04:42,010 --> 00:04:43,450 It's very simple. 50 00:04:43,470 --> 00:04:43,860 OK. 51 00:04:44,370 --> 00:04:48,960 But the really interesting thing here is. 52 00:04:50,050 --> 00:04:51,610 To show you that. 53 00:04:54,020 --> 00:05:00,020 How we can process the data to obtain exactly the same. 54 00:05:01,550 --> 00:05:02,250 Doctor friend. 55 00:05:02,570 --> 00:05:10,760 OK, so the same Collins name exit that you're using a preprocessing function and then it will be very 56 00:05:10,760 --> 00:05:13,910 important in the next chapter. 57 00:05:14,010 --> 00:05:14,990 OK, so. 58 00:05:16,720 --> 00:05:21,640 I don't tell you more here, but you will have seen it in the next chapter. 59 00:05:22,270 --> 00:05:27,550 This preprocessing function will be very, very helpful. 5130

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