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POReplace last NA of a segment of NAs in a column with last valid value
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  1. POReplace last NA of a segment of NAs in a column with last valid value
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    copied!<p>Here is a sample data frame:</p> <pre><code>&gt; df = data.frame(rep(seq(0, 120, length.out=6), times = 2), c(sample(1:50, 4), + NA, NA, NA, sample(1:50, 5))) &gt; colnames(df) = c("Time", "Pat1") &gt; df Time Pat1 1 0 33 2 24 48 3 48 7 4 72 8 5 96 NA 6 120 NA 7 0 NA 8 24 1 9 48 6 10 72 28 11 96 31 12 120 32 </code></pre> <p>NAs which have to be replaced are identified by <code>which</code> and logical operators:</p> <pre><code>x = which(is.na(df$Pat1) &amp; df$Time == 0) </code></pre> <p>I know the <code>locf()</code> command, but it's replacing all NAs. How can I replace only the NAs at position x in a multi-column df?</p> <hr> <p>EDIT: Here is a link to my original dataset: <a href="https://www.dropbox.com/s/o9qdkorjnozvwmh/pad_88.csv" rel="nofollow">link</a></p> <p>And thats how far I get: </p> <pre><code>require(reshape2) require(zoo) pad.88 &lt;- read.csv2("pad_88.csv") colnames(pad.88) = c("Time", "Increment", "Side", 4:length(pad.88)-3) attach(pad.88) x = which(Time == 240 &amp; Increment != 5) pad.88 = pad.88[c(1:x[1], x[1]:x[2], x[2]:x[3], x[3]:x[4], x[4]:x[5], x[5]:x[6],x[6]:x[7], x[7]:x[8], x[8]:nrow(pad.88)),] y = which(duplicated(pad.88)) pad.88$Time[y] = 0 pad.88$Increment[y] = Increment[x] + 1 z = which(is.na(pad.88[4:ncol(pad.88)] &amp; pad.88$Time == 0), arr.ind=T) a = na.locf(pad.88[4:ncol(pad.88)]) </code></pre> <p>My next step is something like <code>pat.cols[z] = a[z]</code>, which doesn't work.</p> <hr> <p>That's how the result should look like:</p> <pre><code>Time Increment Side 1 2 3 4 5 ... 150 4 0 27,478 24,076 27,862 20,001 25,261 165 4 0 27,053 24,838 27,231 20,001 NA 180 4 0 27,599 24,166 27,862 20,687 NA 195 4 0 27,114 23,403 27,862 20,001 NA 210 4 0 26,993 24,076 27,189 19,716 NA 225 4 0 26,629 24,21 26,221 19,887 NA 240 4 0 26,811 26,228 26,431 20,001 NA 0 5 1 26,811 26,228 26,431 20,001 25,261 15 5 1 .... </code></pre> <p>The last valid value in col 5 is 25,261. This value replaces the NA at Time 0/Col 5.</p>
 

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