WEBVTT 00:00.670 --> 00:03.070 Welcome to the solution for coding exercise. 00:03.080 --> 00:08.450 Three and we have already imported pandas and also the list. 00:08.590 --> 00:09.820 CSB file. 00:10.600 --> 00:16.870 And here in question 19 we should select the numerical column last prize and create a copy and save 00:16.900 --> 00:20.720 the copy the panda series and the variable prize. 00:20.710 --> 00:22.300 And this is pretty simple. 00:22.300 --> 00:30.040 So we selected the last price column and we change the copy method to create an independent object and 00:30.310 --> 00:33.450 we save the independent object and the rabbit prize 00:37.460 --> 00:40.940 then next we should get some summary statistics on the prize. 00:41.090 --> 00:44.500 And of course we can do the service of the described method. 00:45.290 --> 00:50.150 And the question is here what is the price of the most expensive stock and therefore we have to look 00:50.150 --> 00:54.060 here at the maximum here in the next question. 00:54.060 --> 00:56.730 We should get the minimum value in our price. 00:56.740 --> 01:04.860 The panacea is by calling the respective method and of course the method as the main method. 01:04.860 --> 01:07.700 And the question is what is the cheapest stock price. 01:07.710 --> 01:16.710 And it's actually 0 point 0 0 3 dollars then in question 22 we have to get the frequency is in our price 01:16.890 --> 01:20.760 column and we can do this with the value counts method. 01:23.250 --> 01:26.370 And the question is here what are some of the most frequent price. 01:26.370 --> 01:30.790 And obviously it's a nine point seventy three and twenty five. 01:31.140 --> 01:39.770 So we have for both prices 9 occurrences so that were the absolute frequencies and we should also get 01:39.770 --> 01:47.060 the relative frequencies and uh we can simply do this by also using every value counts method and pass 01:47.230 --> 01:49.310 through to the normalized parameter 01:53.220 --> 02:03.420 and it's no surprise here that we get the pretty small numbers here so 0 point 1 3 percent actually. 02:03.530 --> 02:06.890 Here we have to sort of a price series from low to high. 02:07.310 --> 02:11.130 And we can do the service of the sort value method. 02:11.570 --> 02:19.640 And the second lowest price this year 0 point 0 for so that was the sorting from low to high. 02:20.010 --> 02:27.600 And now we have to sort the the price series from high to low and we have to pass the falls to the ascending 02:27.600 --> 02:30.770 power meter to get in descending order. 02:31.470 --> 02:36.630 And also we have to save for the changes by setting the in-place prior meter to true. 02:37.140 --> 02:41.430 So we pass your true to the in-place power meter and by doing so we actually. 02:41.450 --> 02:42.510 Oh right. 02:42.530 --> 02:49.730 Um the object that a start in the variable price with uh these starting here from high to low. 02:50.220 --> 02:53.390 And let's inspect our written object. 02:53.910 --> 02:57.120 So we are face starting from high to low. 02:57.120 --> 03:03.120 So these are the first five elements and obviously the second highest prices are two thousand nine hundred 03:03.150 --> 03:03.960 and ten 03:06.610 --> 03:13.450 and here we have to sort our pandas serious by the index in ascending order and we have to save for 03:13.480 --> 03:19.180 overwrite the changes and we can do this the rest of the thought index method and the default setting 03:19.180 --> 03:21.190 is an ascending order. 03:21.190 --> 03:26.920 And also here we have to pass through to the in-place power meter to save the change and to override 03:26.920 --> 03:35.870 the object here so again here we have our panacea series sorted by the arranged index from low to high 03:37.560 --> 03:39.770 then and the next step we shall select. 03:39.870 --> 03:47.250 The non numerical column sector and also here we create a copy and we save uh The Pen are serious and 03:47.250 --> 03:48.290 the variable sector. 03:48.600 --> 03:50.120 So let's have a look here. 03:50.220 --> 03:52.800 That's the first five elements here. 03:52.800 --> 03:58.570 For example capital got sloppy basic industries and then we have to use the described method. 03:58.580 --> 04:04.600 Also on the non numerical serious and the questionis the models are the most frequent. 04:04.590 --> 04:10.370 The value sector and obviously here it's the finance sector. 04:10.370 --> 04:16.430 Then next year in question 29 we should get all unique values in the serious sector. 04:16.430 --> 04:17.690 So let's have a look here. 04:19.960 --> 04:25.230 And last but not least we have to count the frequencies and uh the serious sector. 04:25.570 --> 04:29.910 And the question is how often does the value of the sector transportation appear. 04:30.040 --> 04:33.730 And of course we can U.S.A also the value accounts method 04:36.670 --> 04:44.380 so we we have the absolute frequencies for our sectors and we have in total 123 companies that are active 04:44.380 --> 04:46.930 in the transportation sector. 04:46.930 --> 04:47.320 All right. 04:47.320 --> 04:49.010 That was Exercise 3. 04:49.060 --> 04:53.320 I hope you had fun and looking forward to see you also on the next exercise by.