All language subtitles for 2. Import & manage data from Metatrader 5

af Afrikaans
ak Akan
sq Albanian
am Amharic
ar Arabic
hy Armenian
az Azerbaijani
eu Basque
be Belarusian
bem Bemba
bn Bengali
bh Bihari
bs Bosnian
br Breton
bg Bulgarian
km Cambodian
ca Catalan
chr Cherokee
ny Chichewa
zh-CN Chinese (Simplified)
zh-TW Chinese (Traditional)
co Corsican
hr Croatian
cs Czech
da Danish
nl Dutch
en English
eo Esperanto
et Estonian
ee Ewe
fo Faroese
tl Filipino
fi Finnish
fr French Download
fy Frisian
gaa Ga
gl Galician
ka Georgian
de German
el Greek
gn Guarani
gu Gujarati
ht Haitian Creole
ha Hausa
haw Hawaiian
iw Hebrew
hi Hindi
hu Hungarian
is Icelandic
ig Igbo
id Indonesian
ia Interlingua
ga Irish
it Italian
ja Japanese
jw Javanese
kn Kannada
kk Kazakh
rw Kinyarwanda
rn Kirundi
kg Kongo
ko Korean
kri Krio (Sierra Leone)
ku Kurdish
ckb Kurdish (Soranî)
ky Kyrgyz
lo Laothian
la Latin
lv Latvian
ln Lingala
lt Lithuanian
loz Lozi
lg Luganda
ach Luo
mk Macedonian
mg Malagasy
ms Malay
ml Malayalam
mt Maltese
mi Maori
mr Marathi
mfe Mauritian Creole
mo Moldavian
mn Mongolian
sr-ME Montenegrin
ne Nepali
pcm Nigerian Pidgin
nso Northern Sotho
no Norwegian
nn Norwegian (Nynorsk)
oc Occitan
or Oriya
om Oromo
ps Pashto
fa Persian
pl Polish
pt-BR Portuguese (Brazil)
pt-PT Portuguese (Portugal)
pa Punjabi
qu Quechua
ro Romanian
rm Romansh
nyn Runyakitara
ru Russian
gd Scots Gaelic
sr Serbian
sh Serbo-Croatian
st Sesotho
tn Setswana
crs Seychellois Creole
sn Shona
sd Sindhi
si Sinhalese
sk Slovak
sl Slovenian
so Somali
es Spanish
es-419 Spanish (Latin American)
su Sundanese
sw Swahili
sv Swedish
tg Tajik
ta Tamil
tt Tatar
te Telugu
th Thai
ti Tigrinya
to Tonga
lua Tshiluba
tum Tumbuka
tr Turkish
tk Turkmen
tw Twi
ug Uighur
uk Ukrainian
ur Urdu
uz Uzbek
vi Vietnamese
cy Welsh
wo Wolof
xh Xhosa
yi Yiddish
yo Yoruba
zu Zulu
Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:12,420 --> 00:00:20,490 Hi, everyone, and welcome in this new video and this video, we will begin to import and reprocess 2 00:00:20,640 --> 00:00:21,360 some data. 3 00:00:22,590 --> 00:00:29,220 First, we will pre-processed the data, which come from medicine to the front because it's the most 4 00:00:29,220 --> 00:00:29,820 important. 5 00:00:31,880 --> 00:00:39,500 So here we just have installed why plans to import that data from Yahoo Finance in the next video, 6 00:00:39,770 --> 00:00:47,810 then I have all on this site libraries and this code is not necessary in your case. 7 00:00:48,710 --> 00:00:52,550 So first, we need to import the data. 8 00:00:53,330 --> 00:00:59,510 In all, case, I have just input manually the data from makers all five. 9 00:00:59,690 --> 00:01:00,020 But. 10 00:01:01,100 --> 00:01:11,060 In the next chapter, I will show you how to import some data using Python and data which come from 11 00:01:11,060 --> 00:01:11,930 metaphor or frame. 12 00:01:12,230 --> 00:01:12,530 But. 13 00:01:13,590 --> 00:01:18,150 I think it's very important to begin by the easiest parts. 14 00:01:19,980 --> 00:01:28,170 So, for example, you can take the CSB, file it, so one of the things we find. 15 00:01:29,600 --> 00:01:39,800 Of the zip file attached to this video, this find contain nearly 10 currency data. 16 00:01:40,040 --> 00:01:40,420 OK. 17 00:01:40,520 --> 00:01:41,660 And you can take. 18 00:01:44,260 --> 00:01:50,260 The data that you'll then you just have to drag and drop here. 19 00:01:51,520 --> 00:01:52,000 In Google. 20 00:01:52,540 --> 00:01:52,880 OK. 21 00:01:53,110 --> 00:02:03,790 If you walk in Jupiter on a book, you need to have your notebooks and you see the file in the same 22 00:02:03,910 --> 00:02:04,390 folder. 23 00:02:04,450 --> 00:02:11,290 It's very important because a lot of you doesn't walk with Google Club and. 24 00:02:12,760 --> 00:02:19,990 So if you work with Jupyter Notebook, but you don't really muster it, you will have a problem then 25 00:02:19,990 --> 00:02:20,650 problem. 26 00:02:20,680 --> 00:02:28,510 OK, so if you or move very comfortable with Python and Jupiter on a book, I only advise you to work 27 00:02:28,510 --> 00:02:29,350 with Google. 28 00:02:31,950 --> 00:02:37,020 So first, we need to import the data to improve the data. 29 00:02:37,440 --> 00:02:40,410 I will create a new variable def for data. 30 00:02:41,670 --> 00:02:51,000 And I use the really as function from ponds to import the CSP file. 31 00:02:52,080 --> 00:02:55,740 So we need to put the name of the CSB find. 32 00:03:02,300 --> 00:03:08,000 And then we can enforce it and show what this fight is. 33 00:03:08,720 --> 00:03:12,690 OK, I have just four kids to run this, so. 34 00:03:18,490 --> 00:03:22,660 And now, as we can see, we have a little problem, OK? 35 00:03:23,200 --> 00:03:25,090 This problem is that. 36 00:03:26,220 --> 00:03:32,630 The three metre between each value is backslash T. 37 00:03:32,880 --> 00:03:36,090 OK, as we can see between each value we have. 38 00:03:36,260 --> 00:03:39,150 But that's OK because. 39 00:03:41,130 --> 00:03:44,490 The delimiter isn't a stone cold. 40 00:03:45,630 --> 00:03:50,400 And then and this is not able to. 41 00:03:51,770 --> 00:03:53,270 Find it automatically. 42 00:03:53,690 --> 00:03:59,960 Needed to specify the daily meter in the function as input. 43 00:04:00,170 --> 00:04:02,120 So backslash key. 44 00:04:03,370 --> 00:04:03,790 OK. 45 00:04:05,200 --> 00:04:07,750 I'll just put it here. 46 00:04:11,250 --> 00:04:16,410 And now, as we can see, we have a much better results. 47 00:04:17,880 --> 00:04:19,380 But we. 48 00:04:21,390 --> 00:04:24,420 Still wants to make some modification. 49 00:04:24,930 --> 00:04:31,680 First, we don't want the volume and spread color, so we needed to remove it. 50 00:04:31,980 --> 00:04:33,660 We need to remove sensory. 51 00:04:35,190 --> 00:04:36,540 And to do it. 52 00:04:37,880 --> 00:04:46,220 We will just create a little function to do all all necessary modification. 53 00:04:49,710 --> 00:04:57,750 So the input of the pension is the name of the CSB fight then. 54 00:05:00,110 --> 00:05:06,410 We want to remove this two columns, so to do it. 55 00:05:06,830 --> 00:05:07,460 We just. 56 00:05:11,830 --> 00:05:22,030 You, ADF, when you look, we take all the role and we take all of the rule from zero to minus two. 57 00:05:22,690 --> 00:05:27,790 So if you're not comfortable with this, I would advise you to read again. 58 00:05:28,060 --> 00:05:33,820 The BBB is talking about pandas in the chapter Python for that science. 59 00:05:35,360 --> 00:05:37,370 And then if. 60 00:05:46,660 --> 00:05:48,370 I use this function. 61 00:05:48,730 --> 00:05:49,630 I can see that. 62 00:05:51,270 --> 00:05:54,930 The last column as being removed. 63 00:05:56,250 --> 00:06:01,410 But we still want to make some modification. 64 00:06:01,800 --> 00:06:03,870 First, we want that dates. 65 00:06:05,050 --> 00:06:09,340 Is the index OK, because financial data? 66 00:06:11,560 --> 00:06:12,070 Or. 67 00:06:13,850 --> 00:06:19,010 Time series and soon we want the dates as index and to do it. 68 00:06:19,460 --> 00:06:24,380 We just need to put heat index quote equal. 69 00:06:27,930 --> 00:06:28,440 Date. 70 00:06:30,340 --> 00:06:37,240 So if we use like this, we will have dates as indexed, but pundits. 71 00:06:38,440 --> 00:06:42,130 Doesn't understand that this dates or date. 72 00:06:42,970 --> 00:06:43,360 OK. 73 00:06:43,600 --> 00:06:44,170 It will. 74 00:06:46,300 --> 00:06:50,020 Take this column as a story. 75 00:06:50,200 --> 00:06:54,760 OK, so you need to specify porous. 76 00:06:56,220 --> 00:06:57,480 Date Eagle. 77 00:07:01,690 --> 00:07:12,880 So now the last thing that we need to do and is one of the most important is to rename the column and 78 00:07:12,880 --> 00:07:16,300 it's very, very important one because. 79 00:07:19,220 --> 00:07:25,760 And you have only two we can use data which come from several sources. 80 00:07:26,390 --> 00:07:34,430 And if I take data which come from Methods four or five manually, you will have opened with capital 81 00:07:34,430 --> 00:07:34,870 letter. 82 00:07:34,910 --> 00:07:35,270 OK. 83 00:07:36,280 --> 00:07:40,240 If I inputs the same data using pattern. 84 00:07:40,660 --> 00:07:43,900 OK, so the data which comes from is a little fun. 85 00:07:44,170 --> 00:07:44,470 OK. 86 00:07:45,010 --> 00:07:45,760 You will have. 87 00:07:47,610 --> 00:07:53,610 Open a local and te volume in knots in capital later. 88 00:07:53,820 --> 00:07:54,690 OK, so. 89 00:07:56,110 --> 00:07:57,460 The name of the killer. 90 00:07:58,760 --> 00:08:00,680 Can change very often. 91 00:08:00,920 --> 00:08:01,280 OK. 92 00:08:01,520 --> 00:08:09,640 And so if you create a trading system that demand the close price, for example, and you call growth 93 00:08:09,950 --> 00:08:14,930 in capitalism, OK, the next dataframe will have. 94 00:08:17,880 --> 00:08:19,500 One time close in. 95 00:08:20,960 --> 00:08:21,800 Capitalism. 96 00:08:22,040 --> 00:08:30,200 One thing close, for example, like this one time like this, one time like this, 97 00:08:33,220 --> 00:08:34,460 this execution. 98 00:08:34,580 --> 00:08:35,480 OK, so. 99 00:08:36,690 --> 00:08:45,870 If each time you had another notation, each time you will need to do some much of the modification 100 00:08:45,990 --> 00:08:47,220 in your trading strategy. 101 00:08:47,550 --> 00:08:57,720 And it's a really big problem because the goal of the ultimate ization is that we don't need it to. 102 00:08:59,340 --> 00:09:01,410 Modifying something every time. 103 00:09:01,470 --> 00:09:01,860 OK. 104 00:09:02,190 --> 00:09:04,650 So to avoid you have this problem. 105 00:09:05,220 --> 00:09:06,030 We will use. 106 00:09:07,380 --> 00:09:10,020 We will rename the column. 107 00:09:10,380 --> 00:09:18,780 So first, we need to rename the name of the column, so personally, I use this syntax. 108 00:09:19,020 --> 00:09:19,370 OK. 109 00:09:19,620 --> 00:09:23,880 But in your own protest, you can use the syntax that you want. 110 00:09:23,910 --> 00:09:24,210 OK. 111 00:09:24,450 --> 00:09:28,410 The only main point is to keep it all right. 112 00:09:30,730 --> 00:09:34,360 So open a close and the thick volume. 113 00:09:35,480 --> 00:09:43,910 OK will be named volume, but we know that is not really the volume, but you can take it to create 114 00:09:43,910 --> 00:09:47,240 some indicators that demand the volume. 115 00:09:47,570 --> 00:09:49,070 OK, but it's not. 116 00:09:52,100 --> 00:09:54,510 Really a good method to do it. 117 00:09:54,530 --> 00:10:01,280 OK, but sometimes if you don't have the volume and you want to try something using the volume, you 118 00:10:01,280 --> 00:10:03,950 can take this color OK. 119 00:10:04,250 --> 00:10:13,160 But I don't really advise you to do it if you don't really muster what you do. 120 00:10:14,570 --> 00:10:20,690 So and then I just rename the name of the index. 121 00:10:20,870 --> 00:10:24,110 This is not really mandatory, but. 122 00:10:25,670 --> 00:10:27,890 I think it's a good practice. 123 00:10:31,050 --> 00:10:34,890 And then we have the same. 124 00:10:36,870 --> 00:10:41,160 Data from OK, so we are speaking with. 125 00:10:45,060 --> 00:10:47,520 This data, OK? 126 00:10:49,480 --> 00:10:56,800 And we have this data, so we I think we have very much. 127 00:10:58,720 --> 00:11:07,510 Preprocessing, well, the data now I will show you how to process the data, which comes from why finance? 128 00:11:07,840 --> 00:11:08,200 OK? 129 00:11:08,470 --> 00:11:20,890 To show you the importance to process the data using the same syntax for data which come from several 130 00:11:21,010 --> 00:11:21,640 sources. 131 00:11:23,560 --> 00:11:29,440 Now I will show you how to import some data, which come from make a total of five manually. 132 00:11:29,710 --> 00:11:31,000 OK, so. 133 00:11:32,570 --> 00:11:37,760 I don't have show you how to do it automatically. 134 00:11:38,060 --> 00:11:45,670 OK at this step, because for both of you which have a map, it's a little bit more complicated for 135 00:11:45,670 --> 00:11:53,210 all you colleagues which work with Windows because you need to have a Windows device to use the Method 136 00:11:53,220 --> 00:11:56,180 four or five library in Python. 137 00:11:56,210 --> 00:11:56,540 OK. 138 00:11:56,930 --> 00:12:07,640 But I will show you how to install Windows on your Mac using camp or an application like Perl Desktop 139 00:12:07,940 --> 00:12:08,450 or. 140 00:12:09,560 --> 00:12:11,760 It's a VP's Exeter. 141 00:12:11,810 --> 00:12:15,260 OK, so I will give you some. 142 00:12:16,930 --> 00:12:18,220 Possibility, OK. 143 00:12:18,430 --> 00:12:19,810 To fix this issue. 144 00:12:20,050 --> 00:12:21,040 So don't worry. 145 00:12:21,280 --> 00:12:25,930 But I think is not the time to fix this issue because. 146 00:12:27,670 --> 00:12:33,440 Were puts your algorithm in life, shooting is the last thing to do. 147 00:12:33,460 --> 00:12:33,880 OK. 148 00:12:34,090 --> 00:12:41,650 After before that, you needed to have a profitable strategy, and all the work is to find the profitable 149 00:12:41,650 --> 00:12:42,160 strategy. 150 00:12:42,400 --> 00:12:50,770 Once you have most profitable strategy, put it in life, writing is really the last of your. 151 00:12:52,660 --> 00:12:53,770 Issues, OK. 152 00:12:54,910 --> 00:12:58,270 So to import some data, it's very simple. 153 00:12:58,690 --> 00:13:02,610 OK, you need to install the metal frame. 154 00:13:03,590 --> 00:13:04,760 Application, OK. 155 00:13:04,790 --> 00:13:07,520 It's available for Mac and Windows. 156 00:13:07,970 --> 00:13:12,650 Then you give him her you. 157 00:13:14,400 --> 00:13:20,620 Go him on bomb or ticks and you imports the assets that you want. 158 00:13:20,700 --> 00:13:21,090 OK. 159 00:13:21,300 --> 00:13:24,780 You can go check for some crypto exit to exit two. 160 00:13:24,780 --> 00:13:26,070 If you choose one. 161 00:13:26,220 --> 00:13:27,960 You choose the time frame. 162 00:13:28,550 --> 00:13:33,930 OK, you choose the date and then you do you make your request? 163 00:13:35,510 --> 00:13:37,250 I just want to. 164 00:13:39,030 --> 00:13:45,930 I like that point is that in my case, I have to put just one time on request. 165 00:13:46,170 --> 00:13:49,070 Sometimes you need to put several time. 166 00:13:49,240 --> 00:13:51,090 Okay, so for example. 167 00:13:52,380 --> 00:13:58,020 If I put daily, OK, it's possible that I need to. 168 00:13:59,170 --> 00:14:04,990 Puts multiple time on request, so not this time, but if you have to put multiple time on request, 169 00:14:05,410 --> 00:14:07,290 don't worry, it's normal, OK? 170 00:14:07,690 --> 00:14:17,830 And then you export the raw, all the chips and you will have your data, so it's very easy to do it. 13796

Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.