1 00:00:05,870 --> 00:00:10,320 Here even now we will continue combining data frames in this video. 2 00:00:11,090 --> 00:00:17,390 So first we will consider the concatenated that thing like when you concatenate two strings. 3 00:00:17,390 --> 00:00:19,010 Just add one after DNA. 4 00:00:19,130 --> 00:00:20,780 Without any combining of anything. 5 00:00:21,590 --> 00:00:24,500 So for that again we need some examples. 6 00:00:24,500 --> 00:00:29,810 So here I have X fun a dictionary X to an endeavor on an x 3 and so on. 7 00:00:30,680 --> 00:00:41,680 And they will be something like here first a then I have 1 1 2 3 1 1 1. 8 00:00:41,750 --> 00:00:43,720 Like this one 5 elements in that. 9 00:00:44,650 --> 00:00:47,030 Now just come on see me dot com. 10 00:00:47,060 --> 00:01:00,950 So do and this one based this one five times the comma three four and five only change the column value 11 00:01:00,950 --> 00:01:05,320 here like this an e this one. 12 00:01:06,750 --> 00:01:10,890 This on C and this one B. 13 00:01:10,930 --> 00:01:12,020 Now again without. 14 00:01:12,120 --> 00:01:14,270 So time will not get wasted here. 15 00:01:14,280 --> 00:01:15,640 Just copy this one again. 16 00:01:15,840 --> 00:01:26,250 Based here and convert this one into doo doo doo doo doo again it could be the sun replace all the 17 00:01:29,760 --> 00:01:35,300 dissonant again and there we go with this fun. 18 00:01:36,300 --> 00:01:36,930 The 19 00:01:40,750 --> 00:01:49,060 and just e now change D also like after e we have f no no. 20 00:01:49,470 --> 00:01:56,570 Hey I also need e now F G. 21 00:01:57,040 --> 00:02:06,970 And this one edge and this one right now again could be this whole command see. 22 00:02:07,180 --> 00:02:12,080 And this time without changing the column value just change the indexes. 23 00:02:12,190 --> 00:02:20,130 That is this one not indexes what the values come on C here. 24 00:02:20,160 --> 00:02:20,940 This one 25 00:02:26,640 --> 00:02:27,870 individual go. 26 00:02:27,950 --> 00:02:31,250 Now we are done with the dictionaries cheaply done here. 27 00:02:31,250 --> 00:02:34,700 Now convert all of these into three data frames. 28 00:02:34,700 --> 00:02:36,750 That is DFA and the F two. 29 00:02:37,220 --> 00:02:49,580 And then the three here the first one will be equal to like Bebe dot de da frame and he'll invent his 30 00:02:49,580 --> 00:03:01,050 bus X1 and then the index and index value will be like one two three four and five. 31 00:03:01,400 --> 00:03:10,000 Just copy this complete one and pasted here and here also this one into x2 this one into equity. 32 00:03:10,220 --> 00:03:25,400 In this case we will not change the index material change the index that is 6 7 8 9 and 0 0 0 5 also. 33 00:03:25,530 --> 00:03:34,200 Now here if you noticed on the about I have X1 and X3 with the same column value here I have the one 34 00:03:34,210 --> 00:03:40,760 in DFT the different index value but the F1 and d F2 with same index value. 35 00:03:40,970 --> 00:03:42,540 That's what you will get here. 36 00:03:42,750 --> 00:03:44,160 I have done that one. 37 00:03:44,220 --> 00:03:53,440 Now if you print the one you will have this one the F2 this one and they have three this one now for 38 00:03:53,470 --> 00:03:55,490 concatenate and concatenation. 39 00:03:55,530 --> 00:03:59,740 We have syntax like Billy don't. 40 00:03:59,760 --> 00:04:06,190 And then we use gon get just gonna get and then pass dependencies. 41 00:04:06,200 --> 00:04:16,230 Now if you press shift return here you will get different objects like Xs join join Adios keys and then 42 00:04:16,290 --> 00:04:17,130 a lot more. 43 00:04:17,130 --> 00:04:19,290 You can have a look at all of them if you want to. 44 00:04:21,120 --> 00:04:27,380 Now here b did not concatenate the one we need to contact me like first I will try for B F1 and Def 45 00:04:27,380 --> 00:04:28,640 to here. 46 00:04:28,680 --> 00:04:30,840 You will get error avoid this happen. 47 00:04:32,310 --> 00:04:35,860 Oh that one required the brackets also. 48 00:04:37,290 --> 00:04:39,230 So here you will get this one. 49 00:04:39,630 --> 00:04:43,090 If you notice them we have only one. 50 00:04:43,410 --> 00:04:45,380 The index values are seen. 51 00:04:45,660 --> 00:04:47,060 That is one two three four five. 52 00:04:47,220 --> 00:04:50,050 And if you notice here we have lost one two three four five. 53 00:04:50,070 --> 00:04:51,660 Then again one two three four five. 54 00:04:52,020 --> 00:04:53,100 But they're separated. 55 00:04:53,940 --> 00:04:58,730 And then we have this one ABC and up to E and equal them. 56 00:04:58,890 --> 00:05:06,190 And that is common in both have this one now in the F2 in extra we have these things different. 57 00:05:06,400 --> 00:05:07,200 The column value. 58 00:05:07,200 --> 00:05:09,300 So here we have e f g h and I. 59 00:05:10,140 --> 00:05:17,370 So this is the concatenation of two data frames in which we have same index values but different column 60 00:05:17,370 --> 00:05:18,170 values. 61 00:05:18,210 --> 00:05:20,960 Now this one is an x is 0. 62 00:05:20,970 --> 00:05:28,530 If you convert this one with x is 1 and this is that is in really by the backwards here because if we 63 00:05:28,530 --> 00:05:34,560 do not require the brackets the Biden will understand this one as X because that then becomes the second 64 00:05:34,560 --> 00:05:35,670 parameter. 65 00:05:35,670 --> 00:05:40,110 So we declare the brackets says all this will assumes to be a 1. 66 00:05:40,110 --> 00:05:43,060 Now if you do that one the energy and the Xs. 67 00:05:43,080 --> 00:05:48,720 So here the elements are contaminated with these y axes or we can see that column x. 68 00:05:48,740 --> 00:05:52,090 So here we have same index one two three four five. 69 00:05:52,170 --> 00:05:53,690 And here we have all the values. 70 00:05:53,700 --> 00:06:01,110 But if you notice here we have this one E and E we are both e are different. 71 00:06:01,200 --> 00:06:03,690 Here we have a large one here there too. 72 00:06:03,750 --> 00:06:07,290 So it's supposed to be three there with single e. 73 00:06:07,680 --> 00:06:11,660 But this thing is concatenation and concatenation is done on strings. 74 00:06:11,670 --> 00:06:12,500 If you remember. 75 00:06:12,870 --> 00:06:18,500 So if you try to add two strings like B plus E you will get the E. 76 00:06:18,780 --> 00:06:24,390 And if you do something like one plus two you will get well instead of three. 77 00:06:24,390 --> 00:06:30,390 So that's what's happening here in concatenation David we be some that by joining concatenation and 78 00:06:30,390 --> 00:06:36,350 merging are all different from each other and their three concepts are not what it seems to be their 79 00:06:36,360 --> 00:06:40,580 working is just like combining the the difference but they're a little different. 80 00:06:40,620 --> 00:06:48,810 So if you do hear now three with is one you will get this one that is five here that the index that 81 00:06:48,810 --> 00:06:55,800 is same on both that I have taken that's why I have taken same index here one only one index and are 82 00:06:55,800 --> 00:06:57,970 only one column seem to show that one. 83 00:06:59,280 --> 00:07:00,620 Now here we have this one. 84 00:07:00,810 --> 00:07:08,670 And if you know geez the access to zero you will get the one like this one the indexes will be in middle 85 00:07:08,910 --> 00:07:13,010 and ABC each just those are common because these columns are common. 86 00:07:13,140 --> 00:07:15,950 So X is zero means we are then doing with this one. 87 00:07:15,960 --> 00:07:21,200 And these are common X is one which means nothing will be common. 88 00:07:21,210 --> 00:07:22,410 All will be separated. 89 00:07:23,520 --> 00:07:27,230 So this is when we have index values different. 90 00:07:27,720 --> 00:07:33,450 So when we have index values different multi columns value will be same billion or divide any X as one 91 00:07:33,540 --> 00:07:39,950 we will get this one without any empty space but with index is zero. 92 00:07:39,960 --> 00:07:45,840 If we have different same indexes but different column values we have this thing. 93 00:07:45,840 --> 00:07:48,580 So that should be focused here. 94 00:07:48,900 --> 00:07:55,530 That's how these things are working so that you will not get confused them if you mode look out at this 95 00:07:55,530 --> 00:07:57,470 one here. 96 00:07:57,480 --> 00:07:59,250 We do not have how in this one 97 00:08:02,040 --> 00:08:09,250 so we are not done with the concatenation and the how that we have done indeed before that is in joining 98 00:08:09,720 --> 00:08:14,420 in that outer left and right are not in this one because the elements would not combine here. 99 00:08:14,940 --> 00:08:22,980 So concatenation is just simple have two or more data frames and you can add that one like this. 100 00:08:23,340 --> 00:08:33,690 And if you do something like this one the F three you will have all the trees concatenated here that 101 00:08:33,690 --> 00:08:41,850 is now if you notice when we have different indexes but same column value the columns will be shared 102 00:08:42,000 --> 00:08:45,220 like here this one is D7 be a tree. 103 00:08:45,300 --> 00:08:52,100 The columns are shared but not with those who have different column value but same indexes. 104 00:08:52,100 --> 00:08:59,180 And if you done the X is equal to one you will get something like this one. 105 00:08:59,270 --> 00:09:07,750 Now the same indexes will be shared but not the columns. 106 00:09:07,850 --> 00:09:09,750 So that's what all about concatenation. 107 00:09:09,800 --> 00:09:15,960 I hope you understand that one and I know you will get a little confused here because of these indexes 108 00:09:15,980 --> 00:09:23,510 different seem different to him but if you focus on this video only once you will get that all properly 109 00:09:23,640 --> 00:09:33,170 just of one concept that is the Xs and index variation or column variation just focus on that one according 110 00:09:33,170 --> 00:09:37,990 to the condition you need to concatenate the data frames and the rest will be very easy. 111 00:09:38,600 --> 00:09:42,220 So thanks for watching and we will continue with merging in the next video.