WEBVTT 00:00.380 --> 00:06.880 To come to the solution for coding exercise 10 and impart the pandas and plop lip. 00:06.870 --> 00:14.400 And then we import a CSB file with historical stock price data for Apple and Facebook and we can do 00:14.400 --> 00:23.860 the service of the CSB method and we pass the the column data to the pass data parameter to get um a 00:23.880 --> 00:32.250 daytime format and also we pass the date column to the index called parameter to create a date time 00:32.280 --> 00:32.840 index. 00:32.850 --> 00:40.370 So that's a common workflow here when working with time serious and pandas and be safe. 00:40.410 --> 00:46.590 The resulting data frame and the rabbit stocks and the Christmas year how many timestamps does the stocks 00:46.590 --> 00:57.410 contain so let's have a look here with the info method and we can see that we have 1000 and 5 timestamps 00:57.440 --> 01:04.800 or days and the second question is what was the minimum stock price for Facebook in that period. 01:05.030 --> 01:09.770 And we can determine this of a study described method. 01:09.770 --> 01:16.240 So here we are Facebook and the maximum value is two hundred seventeen point five dollars. 01:16.310 --> 01:23.710 Then we can also visualize that the evolution of stock prices over time with a line plot and we can 01:23.710 --> 01:26.070 simply do the service of the plot method. 01:27.890 --> 01:34.910 So here we have on the x axis the daytime index and on the y axis the stock prices and Apple and blue 01:34.910 --> 01:37.940 and Facebook and green. 01:37.980 --> 01:44.410 Here we have to select one single timestamp but the 13th of May 2016. 01:44.580 --> 01:47.290 And the question is what is the price for Apple. 01:47.400 --> 01:51.660 And we have to pass the date in a string format to the local operator. 01:51.990 --> 01:59.370 So there are many string formats that actually work here and this is probably of the most commonly used 01:59.370 --> 02:00.030 format. 02:00.060 --> 02:04.700 So here we have the 13th of May 2016. 02:04.860 --> 02:10.800 And on that day the Apple stock price was ninety point five two. 02:11.040 --> 02:15.090 Next we have to select our stock prices in September 2017. 02:15.090 --> 02:24.060 So far trading days and calculate the mean over those days for both stocks and also here we can pass 02:24.120 --> 02:33.350 September to 17 as a string to the local operator and then we change the mean method so airports I mean 02:33.380 --> 02:41.060 price in September to 17 was one hundred fifty seven point six one in the next question we have to create 02:41.090 --> 02:42.320 a single timestamp. 02:42.380 --> 02:49.640 So the 10th of August 2019 and we we've learned that there are many alternatives and options so we can 02:49.640 --> 02:53.150 pass a date in a different string formats. 02:53.210 --> 02:54.630 And here are two alternatives. 02:54.650 --> 03:02.770 So we have the 10th of August to 19 or we can use the 10th of August to 19 and both alternatives works 03:02.790 --> 03:04.760 uh in the same way. 03:04.760 --> 03:10.460 So here we get the timestamp tenths of August to 19 at midnight. 03:10.610 --> 03:12.200 Then he can exercise ninety five. 03:12.230 --> 03:17.060 We have to create a daytime indexed service for 31 days of July to 19. 03:17.270 --> 03:23.210 And essentially here we have uh three alternatives how to do this because we have uh three parameters 03:23.660 --> 03:26.150 and we have to use two of them. 03:26.150 --> 03:33.370 So we have start and and the periods parameter and not turn it off when we use the start parameter. 03:33.400 --> 03:40.670 So the start date is uh the first of July to nineteen and you want to have 31 periods and the frequency 03:40.670 --> 03:42.390 is daily. 03:42.770 --> 03:47.290 So here we have a daytime index with all days in July. 03:47.570 --> 03:51.370 Then next we can also use the combination of start and end. 03:51.500 --> 03:59.850 So status of the first of July and so the thirty first of July and finally we can also use the combination 03:59.850 --> 04:02.110 of end and periods. 04:02.130 --> 04:06.850 So this gives us the same date time index. 04:06.900 --> 04:11.370 Now we are getting to the more special cases and we should credit daytime in next starting from the 04:11.370 --> 04:20.520 17th of May to 19 and including the following nine Fridays so the 17th of May 219 as of Friday and we 04:20.520 --> 04:24.910 want to have also the following nine Fridays so in total ten Fridays. 04:25.230 --> 04:32.820 And uh we can do this here again with the the date range method and we set the start date to the 17th 04:32.820 --> 04:34.050 of May 219. 04:34.170 --> 04:40.170 We want to have 10 periods and as a frequency want to have weekly Friday 04:42.840 --> 04:48.730 A.B. F. The 10 Fridays next we have to create a daytime indexed service for the 12th of November for 04:48.730 --> 04:58.030 the Yes to 19 to 223 and we can do this again with the PD that date range method and we pass the tests 04:58.030 --> 05:06.530 of November to 9 into the start parameter we have 5 periods and this frequency we pass uh The Pen the 05:06.550 --> 05:10.380 start date offset method and thus increment. 05:10.450 --> 05:12.280 We have one year. 05:12.280 --> 05:17.310 So let's have a look here and we have uh five times. 05:17.410 --> 05:19.420 The 12th of November. 05:19.620 --> 05:21.420 So that was coding exercise 10. 05:21.420 --> 05:25.620 I hope you had fun and I see you also in the next exercise by.