WEBVTT 00:00.090 --> 00:03.180 Hello and welcome back to this session about random numbers. 00:03.180 --> 00:08.750 So creating random numbers is a very helpful to you to assimilate and analyze the real world processes 00:08.790 --> 00:10.460 like playing the lottery. 00:10.500 --> 00:16.020 So if you are good and Massa so has six you can simply calculate the likelihood of winning a lottery. 00:16.020 --> 00:22.140 But if you don't have any clue about math and still has six yeah you can also assimilate this process 00:22.140 --> 00:29.760 by generating random numbers and analyze and the results of your simulation so first of all let's impart 00:29.760 --> 00:32.880 them the random module so it's not imparted by default. 00:33.450 --> 00:40.350 So we need to impart it with them the keyboard impart and then with the function random that random 00:40.800 --> 00:44.880 we can generate random floats in the interval 0 2 1. 00:44.880 --> 00:48.840 So if you press surf tab we can never look here. 00:48.990 --> 00:58.480 So it's in the interval a 0 2 1 until we get 0 point 5 to 3 something and the fear read around the cell 01:00.530 --> 01:02.460 we get another random float. 01:02.630 --> 01:04.730 Also on the Internet a 0 to 1. 01:04.730 --> 01:07.300 So it's 0 point 8 9. 01:07.640 --> 01:14.750 And every time we repeat this process we get another random float in the interval 0 to 1 and that's 01:14.810 --> 01:21.390 a very helpful tool called the random seed where you can pass within the brackets a number here it's 01:21.400 --> 01:21.990 one two three. 01:22.010 --> 01:23.540 But it can be any number. 01:23.900 --> 01:28.270 And when we create random numbers like here we need to set up the random seed before. 01:29.000 --> 01:33.670 And as long as we have the same random seed we get the same random numbers. 01:33.800 --> 01:40.250 So the random numbers are still random but we are so-called pseudo random because then they depend on 01:40.250 --> 01:41.360 the random seed. 01:41.540 --> 01:47.300 And this enables reproducibility so as long as you have the same seed as I have. 01:47.300 --> 01:54.540 So here in this case one two three we should get them the same random numbers so let's run here. 01:54.570 --> 01:56.790 The salad with the random seed one two three. 01:56.790 --> 02:04.590 So we still use the random generator random at random so we would expect a random float between 0 and 02:04.590 --> 02:06.580 1. 02:06.630 --> 02:09.080 So here we have 0 point 0 5 2. 02:09.510 --> 02:14.190 And uh if we repeat this process we should actually get the same random float 02:17.020 --> 02:22.800 and this is the case so when the feed change here the random seed to say let's take 10. 02:22.960 --> 02:29.770 So it can be any number here then we get a different random number hits or point five seven. 02:29.990 --> 02:34.760 And if we repeat this process we get the same number because we have the same seed as before 02:37.550 --> 02:43.940 and depending on the characteristics of our real world problem the different the random generating functions. 02:43.940 --> 02:51.190 So here we learn about the random that random function that creates floats in the interval 0 2 1. 02:51.330 --> 02:57.500 And that's also the function random dot rent in which creates random integers in an interview which 02:57.500 --> 02:58.880 we can determine actually. 02:58.880 --> 03:02.040 So let's press shift tap and have a look. 03:02.120 --> 03:07.380 So here return random integer and range a to b including both and points. 03:07.430 --> 03:14.540 So if you want to generate a random integer and Range 1 to 100 both ends including then our function 03:14.540 --> 03:18.680 here is random dot rent and from 1 to 100. 03:18.680 --> 03:21.200 So let's run the cell here. 03:21.400 --> 03:31.160 Here we get 55 and you can also repeated so without random CTF we get different integers and let's assume 03:31.160 --> 03:33.820 we have the problem of rolling the dice. 03:33.830 --> 03:43.210 Yeah we can simulate rolling the dice by creating random integers and the Range 1 2 6 so now first throw 03:43.300 --> 03:54.670 we get five and now a second throw one in our third throw two and so on and we can also create many 03:54.670 --> 03:58.060 random numbers with a for loop. 03:58.510 --> 04:05.620 So first of all we create an empty list and we set up the random C to 1 2 3 so we want to have the same 04:05.620 --> 04:06.330 random numbers. 04:06.340 --> 04:13.420 If we repeat the process here and then we say we want to have 10 random integers and Range 1 to 100. 04:13.420 --> 04:21.520 So we have a for loop with are 10 iterations so ten times we create a random in the 10 range. 04:21.510 --> 04:27.630 1 2 100 and each random integer We append to our list. 04:28.690 --> 04:31.980 So let's see what we get. 04:32.420 --> 04:35.830 And we can print out here. 04:35.940 --> 04:41.270 So here we have a list with 10 random integers and range one to one hundred and that. 04:41.280 --> 04:46.950 Also the length of added so of course we have 10 random integers and we can also simply change this. 04:46.980 --> 04:55.950 So let's assume that we want to simulate rolling the dice 10 times then we can say OK I want to create 04:55.950 --> 04:58.110 random in the just in range 1 to 6 05:01.600 --> 05:05.770 and here we have the result of simulating rolling the dice 10 times. 05:05.770 --> 05:10.510 So we have 1 3 1 4 3 1 1 4 5 5. 05:10.630 --> 05:15.640 And as I said depending on the characteristics of our real world problem there are many more random 05:15.940 --> 05:17.720 functions. 05:17.770 --> 05:22.090 So if you press your shift tap. 05:22.140 --> 05:27.380 So for example we can create like normal random numbers or normal random numbers. 05:27.390 --> 05:31.870 So there are a lot of options here. 05:31.990 --> 05:32.290 All right. 05:32.290 --> 05:35.410 So let's create some number distribute the numbers. 05:35.470 --> 05:42.470 Let's have a look at just tap so here we are creating normal distributed numbers. 05:42.530 --> 05:46.190 With the U.S. and the mean and seek mass the standard deviation. 05:46.190 --> 05:51.820 So let's assume we are we have a mean of 10 and a standard deviation of 5. 05:51.830 --> 05:58.280 Then we can create a random number from the normal distribution with the mean 10 and standard deviation 05:58.280 --> 05:59.210 5. 05:59.210 --> 06:02.120 So in this example 0 point to 6. 06:02.120 --> 06:02.480 All right. 06:02.480 --> 06:06.740 So we are finished now with the random module and later we can see that also name pi. 06:06.770 --> 06:12.720 There's a random module it's a uprights actually even more functionality and more options then than 06:12.740 --> 06:15.640 the adding module here in the past the standard library. 06:15.710 --> 06:18.660 So hope you enjoyed it and you we see us in the next lesson. 06:18.680 --> 06:18.890 But.