1 00:00:05,600 --> 00:00:06,290 Hey everyone. 2 00:00:06,890 --> 00:00:10,180 So in this video we are going to do some time analyses on this data. 3 00:00:10,730 --> 00:00:18,050 So first of all if you move to the columns in the area you will find related to dates. 4 00:00:18,050 --> 00:00:23,650 We have some columns here that is project posted it detailed on which project is posted. 5 00:00:23,720 --> 00:00:29,650 Then we have this one project fully funded. 6 00:00:29,830 --> 00:00:34,450 This is the date when the project is completely funded by the donors. 7 00:00:34,450 --> 00:00:40,390 So we acquired these two former analyses right now because you just need that when the project posted 8 00:00:40,390 --> 00:00:42,050 in when it is fully funded. 9 00:00:42,330 --> 00:00:49,480 Duly denoted by any and the timing related to this would any analyses. 10 00:00:49,490 --> 00:00:51,170 So now we have these two columns. 11 00:00:51,170 --> 00:00:54,710 First of all we will check is there any empty value in these. 12 00:00:54,710 --> 00:01:01,280 Because like many posts something then it may be possible that every project has some data because every 13 00:01:01,280 --> 00:01:02,960 project is posted on a date. 14 00:01:03,080 --> 00:01:06,590 In case someone has left any like any column there. 15 00:01:07,280 --> 00:01:10,570 But it is not necessary that every project is fully funded. 16 00:01:10,610 --> 00:01:12,350 We have approx eleven million letters. 17 00:01:12,950 --> 00:01:16,210 So let we check that one. 18 00:01:16,280 --> 00:01:24,760 First of all here we have project posted date maybe over that one. 19 00:01:24,890 --> 00:01:29,420 After that we have project fully funded 20 00:01:36,350 --> 00:01:39,550 and we we use is no method for any vacancy. 21 00:01:40,640 --> 00:01:50,560 And then some so then we can have all dual use invalid system syntax fully I forget to add decodes here 22 00:01:53,230 --> 00:02:00,360 Neville now here we have project posted date that is zero because we have no project that is not posted 23 00:02:00,360 --> 00:02:01,210 on any date. 24 00:02:01,410 --> 00:02:03,540 Then we have project fully funded it. 25 00:02:03,570 --> 00:02:11,150 But here we have forty four like thirty seven thousand cases which are not completely funded so there's 26 00:02:11,160 --> 00:02:14,240 something acceptable because every project is not funded. 27 00:02:15,520 --> 00:02:24,310 Now we have this one and now we have a basic idea of these two columns copy this one. 28 00:02:24,480 --> 00:02:26,380 Come on see. 29 00:02:26,550 --> 00:02:27,060 Come on. 30 00:02:27,130 --> 00:02:28,120 Dot head. 31 00:02:28,940 --> 00:02:30,810 There we go with that one. 32 00:02:30,840 --> 00:02:32,900 So here we have the project both to date. 33 00:02:32,910 --> 00:02:34,670 And here we have defunded it. 34 00:02:35,190 --> 00:02:40,800 So as you can see here in three months first project is completely funded and this one is funded in 35 00:02:40,800 --> 00:02:42,970 just 12 days. 36 00:02:43,320 --> 00:02:46,020 And this one is just to one day. 37 00:02:46,020 --> 00:02:47,540 So there is depend on project. 38 00:02:47,550 --> 00:02:49,150 But let's not overlook. 39 00:02:50,340 --> 00:02:53,090 Nope one more thing here. 40 00:02:53,090 --> 00:02:56,240 You cannot apply directly or patient on these dates. 41 00:02:56,240 --> 00:03:02,390 Like if I want to calculate that how many days does this zero has taken then you can just noted this 42 00:03:02,390 --> 00:03:03,710 one like three months. 43 00:03:03,710 --> 00:03:05,420 But how will you do that one here. 44 00:03:06,500 --> 00:03:13,040 So for that one we have included the liability date time if you remember this is the library which make 45 00:03:13,040 --> 00:03:17,400 us to calculate the dates by performing some mathematical operations on them. 46 00:03:18,290 --> 00:03:19,220 Let me show you that one. 47 00:03:19,220 --> 00:03:25,490 But first of all we need to convert these by using the date time so that we can make the calculation 48 00:03:25,490 --> 00:03:26,530 on them. 49 00:03:26,570 --> 00:03:30,780 So first of all here we have date for sort of doubtful. 50 00:03:30,890 --> 00:03:41,990 And first we will work with Project posted date and do hear something like hey we have beady note to 51 00:03:41,990 --> 00:03:54,660 underscore daytime and then simply pass this one come out and see in Pence's command VE Day we have 52 00:03:54,660 --> 00:03:57,110 this one shifted one. 53 00:03:57,150 --> 00:04:04,860 David go with that but never tried to bring this data with this one you will get the same result as 54 00:04:04,860 --> 00:04:05,840 this one. 55 00:04:05,940 --> 00:04:10,100 There's nothing different but now you can perform operations on that one. 56 00:04:10,590 --> 00:04:15,470 How I will show you just after this one so. 57 00:04:15,480 --> 00:04:17,010 Copy this one completely. 58 00:04:17,010 --> 00:04:18,290 Come on come on see. 59 00:04:18,300 --> 00:04:22,710 And here we have come on me and James that one with this column. 60 00:04:23,670 --> 00:04:36,730 So here we have this one here we have this one shifted on made for that one too processed so here we 61 00:04:36,730 --> 00:04:37,440 have this one. 62 00:04:37,720 --> 00:04:48,700 And now if I create another variable and that variable will be a column in data file with the name let's 63 00:04:48,700 --> 00:04:58,870 say funding time that really present the time in between these and now we can simply just do this one 64 00:05:00,640 --> 00:05:05,720 command see and here we have this one. 65 00:05:05,890 --> 00:05:12,080 And the difference will be project fully funded it minus the project posted it it will provide as the 66 00:05:12,080 --> 00:05:13,060 time between them. 67 00:05:13,330 --> 00:05:16,410 So here we have this one. 68 00:05:16,790 --> 00:05:23,800 So you copy and pasted before that one and put a minus sign in between them. 69 00:05:24,220 --> 00:05:32,950 Then we have shifted on this one and now we will have all these four. 70 00:05:32,940 --> 00:05:41,670 Like if I print all these here data for this one come on see. 71 00:05:41,840 --> 00:05:42,220 Come on. 72 00:05:42,230 --> 00:05:47,480 V and add funding time in this so funding time 73 00:05:49,990 --> 00:05:51,370 should return. 74 00:05:51,420 --> 00:05:52,530 Dave we have this fund now. 75 00:05:53,100 --> 00:05:58,860 So one hundred two days that is we cannot count right now but we can count this one as I have only this 76 00:05:58,860 --> 00:06:08,290 one can just take 12 days and this one takes just only a one day so we have no the difference in between 77 00:06:08,290 --> 00:06:09,910 these dates. 78 00:06:09,970 --> 00:06:13,170 That is something the daytime has done here. 79 00:06:13,510 --> 00:06:18,670 The date without the time you will get added in that one because you cannot subtract the days by just 80 00:06:18,670 --> 00:06:22,920 using simple mathematical patients. 81 00:06:23,380 --> 00:06:27,310 And now we will check is there any null value in these now. 82 00:06:27,700 --> 00:06:35,330 So just this one because we have checked only for both student and fully funded debt. 83 00:06:35,350 --> 00:06:38,790 But now we have funding time also. 84 00:06:38,950 --> 00:06:47,390 So is null and then not some shifted on David go the debt fund as expected. 85 00:06:47,500 --> 00:06:55,870 There must be same values these because as many number of we have posted it. 86 00:06:56,030 --> 00:07:02,030 We have as many number of funded except those which are not completely funded. 87 00:07:02,030 --> 00:07:08,660 And as in the model funding time but the values that are taken hit also the values that are vacant here 88 00:07:09,300 --> 00:07:09,990 in funding. 89 00:07:10,010 --> 00:07:12,170 Diane deep study. 90 00:07:12,170 --> 00:07:18,320 So there is something I hope you get that that why they are saying now here we have done this one. 91 00:07:18,320 --> 00:07:29,280 And let me create a and in the data there that will be data for and here I will provide BD or not none 92 00:07:30,330 --> 00:07:34,080 the values that are not empty in funding. 93 00:07:35,220 --> 00:07:41,220 So I'm just creating a variable here that contains all the values of funding type expect the known values 94 00:07:41,460 --> 00:07:42,300 that are empty. 95 00:07:43,140 --> 00:07:48,750 So here I would just provide data for and in that one funding type. 96 00:07:50,390 --> 00:07:51,200 Come on see. 97 00:07:51,870 --> 00:07:52,890 And there we have come on. 98 00:07:52,920 --> 00:08:02,520 We shifted on day we have the data for variable now and it pushes them until late we add another syntax 99 00:08:02,550 --> 00:08:02,980 here. 100 00:08:06,460 --> 00:08:12,460 That is now check these values that is there any value null of note. 101 00:08:12,730 --> 00:08:24,420 So just copy this one from this to this commodity and pasted here that one is still processing. 102 00:08:24,420 --> 00:08:31,380 So here it is done and now should return that man it's again processing. 103 00:08:31,430 --> 00:08:38,410 Let me add and underline here until Dedmon that is import the time as duty. 104 00:08:39,050 --> 00:08:44,030 We have also done this one before but again added this one with this set in which you will add this 105 00:08:44,030 --> 00:08:45,810 length that is date 5. 106 00:08:46,560 --> 00:09:00,610 So data type capability have the funding time is that is simply this one come on see Come on V and then 107 00:09:00,640 --> 00:09:02,980 equal to data. 108 00:09:02,990 --> 00:09:06,610 5 David go Dedmon. 109 00:09:06,730 --> 00:09:13,150 So this is what I need to show you here that now when we have removed all the null values but not have 110 00:09:13,150 --> 00:09:19,210 any empty value in funding time project posted and project fully funded it all are zero in this case. 111 00:09:19,210 --> 00:09:28,490 Now now here we have this one and we will use those deeply doe base metal shifted in there we have this 112 00:09:28,490 --> 00:09:34,040 one in days form now we have already that one in the days form but you need to add this line here I 113 00:09:34,040 --> 00:09:46,020 know after this one if you paint all the data that is data 5 and these all currency come on we note 114 00:09:46,260 --> 00:09:46,530 had 115 00:09:49,560 --> 00:09:57,380 shifted in here we have dismantled old that is defunding time project posted date and budget fully funded 116 00:09:57,380 --> 00:10:06,600 it we do not have any string here no that is what then here the days are already but this one is now 117 00:10:06,600 --> 00:10:10,740 in days so you do not have to add this here. 118 00:10:10,880 --> 00:10:17,270 So now we have our complete data frame in which you have funding time project both to date project fully 119 00:10:17,270 --> 00:10:26,150 funded till now we do not have done any analyses we have just created the data in funding time for we 120 00:10:26,150 --> 00:10:31,930 have budget posted date project fully funded it that we have done in different data types all we can 121 00:10:31,930 --> 00:10:37,910 see in different forms so that we can make calculations there by using the underscore data then we have 122 00:10:38,540 --> 00:10:42,170 calculated the funding time and now we are here with this one. 123 00:10:43,250 --> 00:10:50,400 So this is about creating the daytime objects in the next video we will do analyses on this one. 124 00:10:50,630 --> 00:10:51,640 So thanks for watching. 125 00:10:51,680 --> 00:10:52,730 See in the next video.