1 00:00:00,540 --> 00:00:01,350 Hello, welcome back. 2 00:00:01,660 --> 00:00:07,830 In the previous videos, we built this daily graph of average ratings and this video, we are going 3 00:00:07,830 --> 00:00:11,190 to be the same graph, but on a weekly basis. 4 00:00:11,460 --> 00:00:16,380 Now, this is going to be a short video because I'm not going to explain the code because I already 5 00:00:16,380 --> 00:00:16,860 did that. 6 00:00:16,860 --> 00:00:20,050 So you will be able to easily understand what I'm doing. 7 00:00:20,730 --> 00:00:23,520 So let me go back to Visual Studio Code. 8 00:00:24,970 --> 00:00:27,800 And I will create a new file. 9 00:00:28,960 --> 00:00:34,840 I'm going to name this av for average, rat for rating and week. 10 00:00:37,330 --> 00:00:44,920 So that is number two, and what I usually do when I build these graphs is I go to that template of 11 00:00:44,920 --> 00:00:49,810 JustPy and paste it here and then inside here 12 00:00:50,080 --> 00:00:52,570 then I create a new 13 00:00:56,930 --> 00:01:00,800 HighCharts component which which belongs to wp 14 00:01:02,650 --> 00:01:10,450 and as options, it has this chart_def variable, which is going to be a variable in here. 15 00:01:13,630 --> 00:01:23,200 It's going to be a multiline string enclosed in triple quotes, so here now I'm going to find an example 16 00:01:23,200 --> 00:01:24,640 from HighCharts. 17 00:01:25,240 --> 00:01:31,480 So I'm going to use a spline again for this weekly chart, because I think that's the most appropriate 18 00:01:31,480 --> 00:01:35,530 chart type for this kind of analysis, for this kind of visualizations. 19 00:01:36,220 --> 00:01:42,700 So I will click over to jsFiddle, and that will show me the JavaScript code, which is this one 20 00:01:42,700 --> 00:01:43,210 in here. 21 00:01:44,110 --> 00:01:52,690 I can copy all that and go to Python and paste it there and then, of course, delete that part. 22 00:01:53,140 --> 00:02:01,390 So it starts with the first curly bracket before chart and then it ends with a curly bracket. 23 00:02:01,400 --> 00:02:05,470 So I'll delete the semicolon and the parentheses. 24 00:02:06,130 --> 00:02:09,820 So Options points to that doc string. 25 00:02:11,170 --> 00:02:16,800 Before I apply my own data, I first try oout this code to see if it's working. 26 00:02:16,810 --> 00:02:17,800 But first I need to. 27 00:02:19,380 --> 00:02:22,950 Stop the current process with Control C and run. 28 00:02:26,700 --> 00:02:28,940 Go to justpy, reload. 29 00:02:29,670 --> 00:02:30,590 Yeah, it's working. 30 00:02:36,430 --> 00:02:43,030 Next, I want to import pandas, so since I was doing the analysis on Jupyter already, I can just copy 31 00:02:43,030 --> 00:02:44,680 and paste these lines. 32 00:02:48,750 --> 00:02:49,520 Paste them there. 33 00:02:49,680 --> 00:02:51,020 We don't need matplotlib. 34 00:02:51,150 --> 00:02:52,140 I can delete that. 35 00:02:52,800 --> 00:02:54,870 This is our data frame. 36 00:02:54,870 --> 00:02:58,070 Now we need to do some analysis on these data. 37 00:02:59,160 --> 00:03:03,830 So go back to Jupyter and find the weekly analysis. 38 00:03:03,840 --> 00:03:05,070 So that's one in there. 39 00:03:06,180 --> 00:03:08,460 Week average is the data we need. 40 00:03:09,660 --> 00:03:13,290 So paste them below the original data frame. 41 00:03:15,190 --> 00:03:22,080 And we should have this week average now, now week average is going to have as index column the weeks, 42 00:03:22,300 --> 00:03:26,310 so a year and a week that is going to be week average dot index. 43 00:03:26,590 --> 00:03:32,440 And there'll also be a rating column in the week average data frame. 44 00:03:32,590 --> 00:03:36,980 So let's use those those two columns to plot the data. 45 00:03:38,140 --> 00:03:41,290 So we should be accessing hc dot 46 00:03:43,350 --> 00:03:56,670 options dot x axis dot categories for categorical data such as dates, so that would be week average 47 00:03:56,670 --> 00:04:00,390 dot index but in a form of a list. 48 00:04:00,390 --> 00:04:10,140 So we have to convert it into a list for justpy to recognize it and then hc.options.series.data. 49 00:04:12,970 --> 00:04:21,070 So which means series zero gives us this first item, which is a dictionary, so we have 50 00:04:21,090 --> 00:04:25,430 a dictionary here and then we access the data key from that dictionary. 51 00:04:25,440 --> 00:04:29,730 So that will give us actually the value of that key, which is this list. 52 00:04:29,940 --> 00:04:38,880 And we replace that list with another list, which is a week average rating. That should do it. 53 00:04:39,510 --> 00:04:42,090 So stop control C? 54 00:04:44,510 --> 00:04:47,390 Rerun, reload. 55 00:04:48,370 --> 00:04:52,120 And this is a graph, it looks weird because we have to reverse it. 56 00:04:52,390 --> 00:05:02,490 Actually, it's originally reversed, so we should say false as the value of inverted, control C and 57 00:05:02,510 --> 00:05:03,370 rerun. 58 00:05:05,530 --> 00:05:08,540 Reload and this is it. 59 00:05:08,870 --> 00:05:14,890 I'm not going to waste your time and change all these labels as I did in the previous video, so I already 60 00:05:14,890 --> 00:05:15,370 did that. 61 00:05:15,640 --> 00:05:18,370 Therefore, this is enough for this video. 62 00:05:18,400 --> 00:05:19,130 Thanks for following. 63 00:05:19,150 --> 00:05:19,920 I'll talk to you later.