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Isao Maruyama

COVID19 Tokyo per days of the week

Isao Maruyama, Fukuoka Institute of Technology

Posted 1 year ago

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MODERATOR NOTE: coronavirus resources & updates: https://wolfr.am/coronavirus

enter image description here

Seven curves represent number of confirmed COVID-19 cases in each day of the week through the year 2020, with top 4 points highlighted on each curve

(In Japanese)??????????????????????????????????????????????????????????????????????

COVID 19 : TOP4 visualization per days of the week

2020 - 12 - 21 (Mon) UPDATE : Today in Tokyo, daily confirmed case 392 is reported. This is a smaller value than the maximum value (822@2020 - 12 - 17), but is actually the maximum value on Mondays. Every day in the last week is breaking TOP1 record as shown in this "TOP4 visualization per days of the week".

(IN Japanese) 東京の新規感染者について、本日２１日（月曜日）は最高値（822人）の半数以下ですが、下記のように「曜日毎のＴＯＰ４」で図示すると、過去一週間の全曜日がＴＯＰ１更新、つまり「１週間連続記録更新」となっているのが分かります。

Everyday in Tokyo, daily confirmed case is being reported in the form like “highest value in Fridays” or “2nd highest value in Sundays” in the latest news, reflecting periodic peak structure with one-week period as shown below.

To avoid this periodic peak structure, one can plot the 7-day average line. However, for daily updates, alternative choice is to plot seven lines from Monday to Sunday with visualising TOP 4 ranking on each line. The following quick hack provides a TOP4 visualization per days of the week as shown below.

data import and save

First, one can obtain open data from the following url.

In[]:=

url="https://stopcovid19.metro.tokyo.lg.jp/data/130001_tokyo_covid19_patients.csv";import=Import[url];

Next, create a variable `d’ in the form : d={{ISODate1, number1},{ISODate2, number2},{ISODate3, number3}...} with using some tricks to create continuous date-list without empty data.

In[]:=

idtarget=5;lastday=import[[-1,idtarget]];zeroday=import[[2,idtarget]];dayrange=DateString[#,"ISODate"]&/@DayRange[zeroday,lastday];d={#[[1]],#[[2]]-1}&/@Tally[Join[dayrange,import[[2;;,idtarget]]]];

OPTIONAL: add new

One can add the newest data, because open data has one-day delay, as following;

AppendTo[d,{DateString["ISODate"],392}];(*392casesarereportedtoday(2020-12-21)*)

OPTIONAL: save and load

One can save the variable d.

In[]:=

SetDirectory[NotebookDirectory[]];Save["covid19data.m",d];

In[]:=

SetDirectory[NotebookDirectory[]];Get["covid19data.m"];

data plot

After defining the following title of plot,

In[]:=

title="confirmed cases in Tokyo; TOP4 per days of the week";

In[]:=

title="東京の新規感染者：曜日毎のＴＯＰ４";

one can use the following plot command `plt’.

In[]:=

Clear[plt];plt[iend_:1,top_:4]:=Block[{idtarget,today,lastday,zeroday,dayrange,w,c,r,dw,dws,txt,dco,larg,pm,dlp,d2,dlp0},lastday=d[[-1,1]];zeroday=d[[1,1]];w={Monday,Tuesday,Wednesday,Thursday,Friday,Saturday,Sunday};c=Table[Hue[i/7,1,1/2],{i,1,7}];r=(Rule@@#)&/@Transpose[{w,c}];dw[i_]:=Select[d2,(#[[1]]w[[i]])&][[;;,{2,3}]];dws[i_,topn_]:=Sort[dw[i],#1[[2]]>#2[[2]]&][[;;Min[topn,Length[d2]]]];txt[d_]:=Text[Style[ToString[d[[2]]]<>"@"<>ToString[d[[1]]]<>"\n("<>ToString[DayName[d[[1]]]]<>")",DayName[d[[1]]]/.r,Bold]];dco[i_]:=Callout[dw[i],txt[dw[i][[-1]]]];larg[txt_,n_]:=Nest[Style[#,Larger]&,txt,n];pm[max_,c_]:=Table[larg[Text[Style[n,Bold,White],Backgroundc],max-n],{n,1,max}];dlp[i_,topn_]:=DateListPlot[{#}&/@dws[i,topn],PlotMarkerspm[topn,c[[i]]]];d2={DayName[#[[1]]],#[[1]],#[[2]]}&/@d[[;;-iend]];dlp0=DateListPlot[dco/@Range[7],PlotLegendsPlaced[LineLegend[Table[txt[dws[i,1][[1]]],{i,1,7}],LegendLabel"Max. cases@date",LegendFunction(Framed[#,RoundingRadius5]&),LegendMargins5],{Left,Top}],GridLinesAll,PlotStylec,PlotRange{{zeroday,lastday},All},ImageSize1000];Show[dlp0,Table[dlp[i,top],{i,1,7}],PlotLabeltitle<>"@"<>d2[[-1,2]]]];

plt[]

Out[]=

DateListPlot[d]

Out[]=

The above code is little bit messy but works in the following animation. Note: I noticed this code generates wrong legend box on the wolfram cloud but I can see correct image on my local PC.

OPTIONAL: Animation

To make an animation, we use ParallelDo and the unix command `convert’.

save[days_]:=ParallelDo[Export[StringPadLeft[ToString[i],6,"0"]<>".gif",plt[i,4]],{i,1,days}]

save[260];

TIPS: the following convert command requires large memory. Please check or google.

convert -reverse -layers optimize -delay 2 -loop 0 0*.gif -delay 1000 000001.gif tokyo.gif

convert tokyo.gif -coalesce -scale 30% -deconstruct tokyo_small.gif

Of course, one can elaborate with Mathematica only (without convert).

In[]:=

SetDirectory[NotebookDirectory[]];

ListAnimate[Import["tokyo_small.gif"]]

Out[]=

The above “TOP4 per days of the week” animation visualizes that the 3rd wave is emerging in Tokyo and is bigger than the previous waves. One can use this code to check another periodic peak structure of other cities or countries.

UPDATED : v .3. 2020-12-21

POSTED BY: Isao Maruyama

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Moderation Team

Moderation Team, WOLFRAM

Posted 1 year ago

-- you have earned *Featured Contributor Badge* Your exceptional post has been selected for our editorial column *Staff Picks* http://wolfr.am/StaffPicks and Your Profile is now distinguished by a *Featured Contributor Badge* and is displayed on the Featured Contributor Board. Thank you!

POSTED BY: Moderation Team

Isao Maruyama

Isao Maruyama, Fukuoka Institute of Technology

Posted 1 year ago

Thank you for your selection and edition. I uploaded today's data with Japanese explanation. (But, my figure of plt[] becomes wrong again...)

POSTED BY: Isao Maruyama

Moderation Team

Moderation Team, WOLFRAM

Posted 1 year ago

Congratulations! Your post was highlighted on the Wolfram's official social media channels. Thank you for your contribution. We are looking forward to your future posts. Twitter Facebook Instagram

POSTED BY: Moderation Team

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