In[]:=
ds=ResourceData["Epidemic Data for Novel Coronavirus 2019-nCoV from Wuhan, China"];
In[]:=
ds[1]
Out[]=
In[]:=
ts=ds[1,"ConfirmedCases"]
Out[]=
TimeSeries
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DateListPlot[ts]
Out[]=
In[]:=
DateListPlot[ds[1,"RecoveredCases"],PlotRangeAll]
Out[]=
In[]:=
DateListPlot[ds[1,"Deaths"],PlotRangeAll]
Out[]=
In[]:=
ds[1,"ConfirmedCases"]
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TimeSeries
In[]:=
ds[1,"ConfirmedCases"]["Values"]
Out[]=
{270,444,444,549,549,729,761,1052,1058,1423,1423,1423,2714,2714,3554,3554,3554,3554,4586,4903,5806,7153,7153,11177}
In[]:=
ds[1,"ConfirmedCases"]["Times"]
Out[]=
{3788632800,3788683200,3788769600,3788812800,3788856000,3788899200,3788942400,3788978400,3789025200,3789068400,3789104400,3789140400,3789145800,3789205200,3789223200,3789241200,3789293400,3789297000,3789320400,3789370800,3789468000,3789486000,3789540000,3789666000}
In[]:=
ds[1,"ConfirmedCases"]["Dates"]
Out[]=
,,,,,,,,,,,,,,,,,,,,,,,
In[]:=
UnixTime[]
Out[]=
1580935583
In[]:=
AbsoluteTime[]//Round
Out[]=
3789902796
In[]:=
FindFit[ds[1,"ConfirmedCases"],ax+b,{a,b},x]
Out[]=
{a0.00912366,b-3.45678×}
7
10
analysis #1 -- quadratic fit
analysis #1 -- quadratic fit
In[]:=
FindFit[ds[1,"ConfirmedCases"],ax^2+bx+c,{a,b,c},x]
Out[]=
{a1.26536×,b-95.8828,c1.81639×}
-8
10
11
10
In[]:=
eqn=ax^2+bx+c/.{a1.2653553653937558`*^-8,b-95.88279818931666`,c1.816389146070655`*^11}
Out[]=
1.81639×-95.8828x+1.26536×
11
10
-8
10
2
x
In[]:=
p1=Plot[eqn,{x,3788632800,3789666000}]
Out[]=
In[]:=
p2=ListPlot[Transpose[ds[1,"ConfirmedCases"][#]&/@{"Times","Values"}]]
Out[]=
In[]:=
Show[p1,p2]
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analysis #2 -- exponential fit
analysis #2 -- exponential fit
In[]:=
24×60×60
Out[]=
86400
In[]:=
times=(ds[1,"ConfirmedCases"]["Times"]-3788632800)/86400.
Out[]=
{0.,0.583333,1.58333,2.08333,2.58333,3.08333,3.58333,4.,4.54167,5.04167,5.45833,5.875,5.9375,6.625,6.83333,7.04167,7.64583,7.6875,7.95833,8.54167,9.66667,9.875,10.5,11.9583}
In[]:=
{min,max}=MinMax[times]