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POReplacing row values with the closest conditional values in R
 

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    <p>In R, I have a problem that is similar to the one presented here: <a href="https://stackoverflow.com/questions/10077415/replacing-nas-in-r-with-nearest-value">Replacing NAs in R with nearest value</a>. The differences however, are that the values that I want to change are not NAs but any value less than 0, and also that changing these values is dependent on values in another column (so a conditional statement would need to be added). I'm having trouble understanding how to adapt some of the solutions presented in that question to my problem. It's also important that this be speedy as I have a lot of data.</p> <p>sample data</p> <pre><code>pred_trip &lt;- c(0,0,0,0,0,1,1,1,1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1) locNumb &lt;- c(-1,-1,-1,-1,-1,2,2,2,2,3,3,0,0,0,4,4,4,4,-1,-1,-1,-1,-1,0,0,0,0,0,0,5,5,5,5) df &lt;- data.frame(pred_trip, locNumb) </code></pre> <p>So essentially if a value in the locNumb column is &lt;= 0 and there is a 0 in the pred_trip column then the value in the locNumb column gets reassigned to the closest value that is greater than 0. </p> <p>Desired output:</p> <pre><code> pred_trip locNumb 1 0 2 2 0 2 3 0 2 4 0 2 5 0 2 6 1 2 7 1 2 8 1 2 9 1 2 10 0 3 11 0 3 12 0 3 13 1 0 14 1 0 15 1 4 16 0 4 17 0 4 18 0 4 19 0 4 20 0 4 21 0 4 22 0 4 23 0 4 24 0 4 25 0 4 26 0 4 27 1 0 28 1 0 29 1 0 30 1 5 31 1 5 32 1 5 33 1 5 </code></pre> <p>I'm having trouble adapting the code in the similar solution as it relies a lot on is.na and doesn't include any of the other conditions that I need. But so in pseudo code something like: (not sure where to add in my other conditional statement of if pred_trip == 0.</p> <pre><code>f1 &lt;- function(df) { N &lt;- length(df) na.pos &lt;- which(df$locNumb &lt; 0 (df)) if (length(na.pos) %in% c(0, N)) { return(df) } non.na.pos &lt;- which(!df$locNumb &lt; 0(df)) intervals &lt;- findInterval(na.pos, non.na.pos, all.inside = TRUE) left.pos &lt;- non.na.pos[pmax(1, intervals)] right.pos &lt;- non.na.pos[pmin(N, intervals+1)] left.dist &lt;- na.pos - left.pos right.dist &lt;- right.pos - na.pos df[na.pos] &lt;- ifelse(left.dist &lt;= right.dist, df[left.pos], df[right.pos]) return(df) } </code></pre>
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    1. COWhat's desired output if there are 2 nearest values (before the negative number and after the negative numbers) that are greater than 0?
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    2. CO@geektrader, in that case the values before the negative numbers (numbers <= 0) should take precedence.
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    3. COWhat should happen if `locNumb` is <0, & `pre_trip` does not =0? I don't see any such cases in your example data. Are there none in your real application? If not, this becomes simpler.
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