날짜가 지정된 시계열의 필터 적용
WeatherData를 사용하여 지정된 날짜의 기온을 얻을 수 있습니다. MissingDataMethod를 지정하여 결손 데이터를 보간하는 새로운 시계열을 생성합니다.
In[1]:=
![Click for copyable input](assets.ko/filter-time-series-with-dates/In_93.png)
data = TimeSeries[
WeatherData["Chicago",
"Temperature", {{2015, 1, 1}, {2015, 12, 31}}],
MissingDataMethod -> "Interpolation"]
Out[1]=
![](assets.ko/filter-time-series-with-dates/O_49.png)
In[2]:=
![Click for copyable input](assets.ko/filter-time-series-with-dates/In_94.png)
DateListPlot[data, FrameLabel -> Automatic]
Out[2]=
![](assets.ko/filter-time-series-with-dates/O_50.png)
MinFilter를 사용하여 주어진 해의 처음과 마지막 결빙 시기를 분석합니다.
In[3]:=
![Click for copyable input](assets.ko/filter-time-series-with-dates/In_95.png)
minF = MinFilter[data, Quantity[1, "Month"]];
전체 Wolfram 언어 입력 표시하기
Out[5]=
![](assets.ko/filter-time-series-with-dates/O_51.png)
봄의 마지막 결빙일의 다음날을 알아봅니다.
In[6]:=
![Click for copyable input](assets.ko/filter-time-series-with-dates/In_98.png)
spring = TimeSeriesWindow[minF, {"15 April 2015", "15 May 2015"}];
In[7]:=
![Click for copyable input](assets.ko/filter-time-series-with-dates/In_99.png)
DateObject[
First@FirstCase[
spring["Path"], _?(#[[2]] > Quantity[0, "DegreesCelsius"] &)]]
Out[7]=
![](assets.ko/filter-time-series-with-dates/O_52.png)
가을의 첫 결빙일을 알아봅니다.
In[8]:=
![Click for copyable input](assets.ko/filter-time-series-with-dates/In_100.png)
fall = TimeSeriesWindow[minF, {"1 Oct 2015", "31 Oct 2015"}];
In[9]:=
![Click for copyable input](assets.ko/filter-time-series-with-dates/In_101.png)
DateObject[
First@FirstCase[
fall["Path"], _?(#[[2]] <= Quantity[0, "DegreesCelsius"] &)]]
Out[9]=
![](assets.ko/filter-time-series-with-dates/O_53.png)