dataframe - Creating a seven day, average-by-week-of-year (or moving average?) in R -
I have data of a ton that I am feeding through R to make an average. Relevant data includes date and temperature readings, often there are many temperature readings for the same day. Dates are approximately 6 months.
Researchers requested by researchers were described as two for the following:
The average weekly a ???? 7 days rolling average (not calendar week) Average max 7 days rolling max
Therefore, if my data has begun on 1/1/13, then give me 1/1/13 and 1/7/13 All temperature readings should be average between, and then do this for the 1/8/13 item - 1/15/13 and so on. I have been told somewhere on the stack that it is actually called " average-by-year-by-year ", although I believe that I do not get enough that this is not how much the average is moving is . I have done some research, but overall it is that I am, I have great difficulty in understanding how the attitude of this problem is. For the visual between you, it's essentially the way I'm dealing with the data (actual I am looking at the XTS Library: It looks promising, but I can not understand it very much and the documentation is not helping too much. xts (x = mydf, order.by = date (x), frequency = 7 ...? thoughts? Thank you. Duplicate head here Is a small sample of information: This two does not sound like a moving average data.frame looks very different (given below) Look at the defect head) and several thousand records are long, but these are the two proper names for the relevant columns):
DATE | TEMP ----------------- 1/2/13 34.4 1/2/13 36.4 1/2/13 34.3 1/4/13 45.6 1/4/13 33.5 1 / 5/13 45.2 1/6/13 53.9 1/7/13 34.6 1/7/13 36.2 1/8/13 22.4 1 / 9/13 30.8 1 / 9/13 33.2
xts (x = null, order.by = index (x), frequency = null, unique = TRUE, tzone = Sys.getenv ("TZ "), ...)
structure (list (5701 = 57 9: 584, site = C (101l, 101l, 101l, 101l, 101l, 101l ), Menthe = C (6 L, 6 L, 6 L, 6 L, 6 L, 6 L), Day = C (7 L, 7 L, 7 L, 7 L, 7 L, 7 L), Date = Structure (C (34 L, 34 L, 34 L, 34 L, 34 L, 34 L). LABEL = C ("10/1/2013", "10/10/2013", "10/11/2013" , "10/12/2013", "10/2/2013", "10/3/2013", "10/4/2013", "10/5/2013", "10/6/2013", " 10/8/2013 "," 10/8/2013 "," 10/9/2013 "," 6/10/2013 "," 6/11/2016 3 "," 9/9/2013 "), class = "Factor") , TIMESTAMP = Structure (784: 789, .label = C ("10/1/2013 0:00", "10/1/2013 1: 00", "10/1/2013 10:00", "10 / 1/2013 11:00 "," 10/1/2013 12:00 "," 10/1/2013 13:00 "," 10 / 1/2013 14:00 "," 10/1/2013 15: 00 "," 10/1/2013 16:00 "," 10/1/2013 17:00 "," 10/1/2013 18: 00 "," 10/1/2013 1 9:00 "," 10 "CECTI", "MINAT", "DEA", "DATE", "T" = "23" (23.376, 23.376, 23.833, 24.146, 24.219, 24.05), "CECTI", "MINAT", "DEA", "DATE" "Timestamp", "TEP", "XC"), line.Name = C (NA, 6L), class = "data.frame")
sampled = 'DATE of 1/2/13 34.4 1/2/13 36.4 1/2/13 34.3 1/4/13 45.6 1 / 4/13 33.5 1/5 / 13 45.2 1/6/13 53.9 1/7/13 34.6 1/7/13 36.2 1/8/13 22.4 1 / 9/13 30.8 1 / 9/13 33.2 'Extra = Readable (Text = Sample, Header = T) Library (XTS) EX1 $ DATE = as.Date (ex1 $ date, format ='% m /% d /% y ') ex2 = xts (ex1 $ temp, order.by = ex1 $ DATE) xts:: Apply. Weekly (x2, mean)
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