Analyze Temperature Variability at a Given Location

Use

WeatherData

to get the temperature data for the city of Seattle using quantity values and time series:

In[1]:=

data=WeatherData

Seattle

CITY

,"Temperature",{{2021,6,25},{2021,7,1}}

Out[1]=

TimeSeries

Time: 25 Jun 2021 GMT -5 to 01 Jul 2021 GMT -5
Data points: 161



Fill in missing data values in

TimeSeries

using linear interpolation:

In[2]:=

temps=TimeSeries[data,MissingDataMethod"Interpolation"]

Out[2]=

TimeSeries

Time: 25 Jun 2021 GMT -5 to 01 Jul 2021 GMT -5
Data points: 161



Visualize the temperature time series:

In[3]:=

DateListPlot[temps,PlotTheme"Detailed"]

Out[3]=

Look for basic properties:

In[4]:=

stats={Min,Max,Mean,Median,StandardDeviation};TableForm[{Map[#[temps]&,stats]},TableHeadings{None,stats}]

Out[4]//TableForm=

Min	Max	Mean	Median	StandardDeviation
16.7 °C	39.4 °C	25.7224 °C	25.6 °C	6.24384 °C

Convert temperatures to degrees Fahrenheit:

In[5]:=

tempsF=UnitConvert[temps,"DegreesFahrenheit"];TableForm[{Map[#[tempsF]&,stats]},TableHeadings{None,stats}]

Out[5]//TableForm=

Min	Max	Mean	Median	StandardDeviation
62.06 °F	102.92 °F	78.3002 °F	78.08 °F	11.2389 °F

Find the 6-hour moving average:

In[6]:=

avg=MovingMap[Mean,temps,{Quantity[6,"Hours"],Center}]

Out[6]=

TimeSeries

Time: 25 Jun 2021 GMT -5 to 01 Jul 2021 GMT -5
Data points: 155



Visualize the data together with the moving average:

In[7]:=

DateListPlot{temps,avg},



Out[7]=

	temperatures
	6-hour moving average

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