1 00:00:05,800 --> 00:00:06,350 Here everyone. 2 00:00:06,560 --> 00:00:11,290 So in the last few days we have find the main period and more in this video we are going to do two smaller 3 00:00:11,290 --> 00:00:12,820 analyses. 4 00:00:13,300 --> 00:00:18,260 First in which percent is the data sports greater or smaller than the value shown excesses. 5 00:00:18,400 --> 00:00:23,950 And second is in which states they are more donations than by donor clustering is very easy one that 6 00:00:23,950 --> 00:00:27,090 is the one depends on the mean minute and more. 7 00:00:27,310 --> 00:00:32,290 If you have noticed we have mean sixty one and median quantified it means there's a great difference 8 00:00:32,320 --> 00:00:33,360 in between them. 9 00:00:33,490 --> 00:00:42,640 Also the 25 percent values fifteen and seventy five is 50 that denotes that we have some outliers causing 10 00:00:42,640 --> 00:00:49,700 men to rise and that is something shown here that on some values we have the values what we can see 11 00:00:49,700 --> 00:00:53,320 points greater or smaller than the values on x axis. 12 00:00:53,330 --> 00:01:00,050 So this is a little graph easy to understand after that that we move to a proper analysis. 13 00:01:00,050 --> 00:01:05,360 That is again based on the data in which states that are more donations than by donors. 14 00:01:05,960 --> 00:01:12,160 So we need to find here than that what are the states in this day donations are more that is judged 15 00:01:12,160 --> 00:01:13,480 by the donors. 16 00:01:13,520 --> 00:01:22,660 So how we get so different so lesbian just by creating a data and using data for. 17 00:01:22,890 --> 00:01:30,570 So what we require for disclosure look at the cushion in which states that are more donations than by 18 00:01:30,570 --> 00:01:31,050 the donor. 19 00:01:31,090 --> 00:01:38,120 So we require donors with states and then their donations that how many donations to have. 20 00:01:38,910 --> 00:01:44,790 So we will first group by the elements by donor states. 21 00:01:44,820 --> 00:01:55,230 If you look at the columns then we have a column here that is to donor state status of donor and we 22 00:01:55,230 --> 00:02:01,520 will group the elements according to Declan who will find particular state donors as in there. 23 00:02:02,040 --> 00:02:06,780 So we have here donor state and then they will use 24 00:02:09,780 --> 00:02:17,870 this buy up and sees because this is not the particular column of data for we just need to group by 25 00:02:17,870 --> 00:02:18,750 decision. 26 00:02:18,800 --> 00:02:24,700 So here very glad now the packets for the main column Vidic platform. 27 00:02:24,920 --> 00:02:33,460 So here we require donation I column that was offensive I that features the idea of donation and then 28 00:02:33,460 --> 00:02:37,220 we will count net how many are present state. 29 00:02:37,360 --> 00:02:38,370 So just count. 30 00:02:39,310 --> 00:02:43,690 And then so devalues according to their 31 00:02:46,170 --> 00:02:47,070 amplitude. 32 00:02:47,100 --> 00:02:57,550 So here we have salt values and ascending equal to False and we will print tier 15 values this time 33 00:02:58,210 --> 00:03:00,670 shifted on that region. 34 00:03:00,670 --> 00:03:09,960 David go and now been devalues as three so here we have 15 states in which we have these numbers of 35 00:03:09,960 --> 00:03:16,890 donors here we have sixty nine thousand six left ninety three thousand. 36 00:03:16,890 --> 00:03:26,500 Now we will just blow this data by using as three I bloat and then provide kind equal to bar. 37 00:03:26,980 --> 00:03:32,390 We had the sun ex title state 38 00:03:36,500 --> 00:03:39,780 then we have white title. 39 00:03:40,760 --> 00:03:49,020 This will be number of donations area design. 40 00:03:49,430 --> 00:03:59,580 Then we have titan that is donations count because we are counting the donations state and also polite 41 00:03:59,650 --> 00:04:00,550 gala scaled 42 00:04:03,990 --> 00:04:05,060 equal to be a 43 00:04:09,230 --> 00:04:10,490 shift return. 44 00:04:10,540 --> 00:04:11,580 David go with that. 45 00:04:12,000 --> 00:04:15,660 So here we have these 50 states with the number of donations in them. 46 00:04:15,930 --> 00:04:18,240 This one six up to 700. 47 00:04:18,250 --> 00:04:25,370 Kate just a few million is less than we had this one and then of course 10 values. 48 00:04:25,380 --> 00:04:29,210 So this is the number of donations by the state. 49 00:04:29,220 --> 00:04:34,800 We have also analyzed that plan and now we will move to some more advanced solutions that is in the 50 00:04:34,800 --> 00:04:35,600 next video. 51 00:04:36,300 --> 00:04:38,890 These are defining the relations between these values. 52 00:04:38,970 --> 00:04:39,840 So thanks for watching. 53 00:04:39,840 --> 00:04:41,280 See you then.