WEBVTT 00:01.110 --> 00:05.530 In this video you will learn how to change one or many elements in a data frame. 00:05.580 --> 00:08.320 And this is actually pretty straightforward. 00:08.340 --> 00:12.820 So first of all you have to select the elements you want to change with Loke. 00:12.930 --> 00:19.020 I log our filtering techniques and then you have to set a new value on new values. 00:19.050 --> 00:25.250 So first of all we import pen us and also here we are working with the Titanic dataset. 00:25.260 --> 00:29.920 Now let's have a look at the female passenger with the index label 1. 00:30.240 --> 00:35.770 She is the 38 year old and it assumed that her correct age was 40. 00:35.940 --> 00:42.960 Then we can simply change this element here in the data frame by first before selecting the element 00:43.380 --> 00:51.060 and we can do the same with the lock operator so we select the passenger within next label 1 and tier 00:51.090 --> 00:56.690 the element and the H column 38 and then we actually set or we determine a new value. 00:56.700 --> 00:58.740 And in this case c a 40. 00:58.830 --> 01:03.440 So let's do this here and let's have a look here at our data frame. 01:03.660 --> 01:11.310 And here we have 40 and the same we can do actually also with the ILO operator and position based indexing 01:11.820 --> 01:18.240 and we select the passenger at the next position one and we want to change the element in the column 01:18.240 --> 01:20.100 with the next position 3. 01:20.460 --> 01:32.320 So that's the H column and we set to the value of 41 then we fear 41 and we can also change or manipulate 01:32.440 --> 01:33.810 many elements. 01:33.880 --> 01:42.070 So let's assume that the passengers with the index labels are 1 2 and 3 actually 42 years old. 01:42.070 --> 01:49.570 Then we can do this here with the label based indexing so we select these three elements here and we 01:49.570 --> 01:51.700 set the new value forty two. 01:52.300 --> 01:53.610 So let's have a look here. 01:54.990 --> 01:57.450 And here we have a three times forty two. 01:58.060 --> 02:01.740 And let's assume that the peasants with the next label one is forty two. 02:01.980 --> 02:07.260 Then the next passengers 43 and the next one forty four. 02:07.260 --> 02:13.120 Then we can also simply do this and instead of passing here only one value forty two we can pass you 02:13.200 --> 02:17.810 a list with three elements 42 43 and 44. 02:17.820 --> 02:20.340 So that's no problem at all here. 02:20.550 --> 02:22.890 And let's go to the next example. 02:22.920 --> 02:25.600 So he and the H column we have the H. 02:25.620 --> 02:26.560 And yes. 02:26.730 --> 02:34.770 And let's assume we want to convert the H and yes to the H and month then we can simply do this by selecting 02:34.770 --> 02:41.820 here the H column so we select all rows and the H column and then we multiply each and every element 02:41.820 --> 02:49.710 in the H column with 12 so that that's the new values and then we need to override the H column and 02:49.800 --> 02:55.110 therefore we also have select the H column and we set here the new value. 02:55.110 --> 02:56.070 So let's have a look 02:58.820 --> 03:02.370 and here we have now the H month and set off years. 03:02.540 --> 03:08.090 And of course we can also convert this back two years by dividing each and every element he and the 03:08.090 --> 03:17.790 H column by 12 and then we assign the new values here for the H column and again here we have for the 03:17.790 --> 03:18.180 H. 03:18.180 --> 03:25.510 And yes and now let's go to a filtering and let's assume that we want to set for all babies that are 03:25.650 --> 03:28.580 less than 1 year old the value of 1. 03:28.650 --> 03:37.470 So first of all we select all rows all passengers where the H S below 1 and we actually select the index 03:37.470 --> 03:45.670 labels and we start the index labels of the babies and the variable index babies and let's also slice 03:45.670 --> 03:48.820 for these rows of these passengers here. 03:48.940 --> 03:53.250 So that's the baby passengers with an H below 1. 03:53.530 --> 03:57.720 And now for all of these passengers we want to set the new age of 1. 03:57.730 --> 04:05.740 So we want to around up actually and we can do this uh by selecting the H column for passengers where 04:05.740 --> 04:07.440 the H is below 1. 04:07.450 --> 04:12.370 So instead of passing the Titanic that s a smaller one we could also pass here. 04:12.490 --> 04:13.930 Index babies. 04:14.080 --> 04:16.490 But here that's a more explicit. 04:16.490 --> 04:23.210 And then we set the new value 1 and let's again select all babies here. 04:23.710 --> 04:31.840 And here we have successfully changed the age of all babies to 1 so these are a few examples how to 04:31.840 --> 04:35.200 change one or many elements in the data frame. 04:35.200 --> 04:40.450 And there are many more ways to do it but for the time being we are finished here and I hope to see 04:40.450 --> 04:41.980 also in the next video by.