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POSplit dataframe and calculate averages for data subsets in R
 

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  1. POSplit dataframe and calculate averages for data subsets in R
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    <p>I have this data frame in R:</p> <pre><code>steps day month 4758 Tuesday December 9822 Wednesday December 10773 Thursday December </code></pre> <p>I want to iterate over the data frame and apply a function to the steps column based on the value in the month column. I'm trying to work out the average number of steps per weekday for each month.</p> <p>I want to output to a new data frame like so where the week days repeat but I only have the average values per day:</p> <pre><code>average.steps day month 4500 Tuesday December 9000 Wednesday December 1000 Thursday December </code></pre> <p>I can work out how to work out the averages for the data frame as a whole, but want to use a for loop to apply it just for step values from the same month.</p> <pre><code>avgsteps &lt;- ddply(DATA, "day", summarise, msteps = mean(steps)) </code></pre> <p>My basic idea for the for function was:</p> <pre><code>f &lt;- function(m in month) {ddply(DATA, "day", summarise, msteps = mean(steps))} </code></pre> <p>But it won't process it and throws the error:</p> <pre><code>Error: unexpected 'in' in "f &lt;- function(m in" </code></pre> <p>Any help would be greatly appreciated!</p> <p>EDIT:</p> <p>SO I've tried @agstudy's suggested fix (below) and it gets the right data structure (single value for each weekday for each month), but the value assigned to each day is identical. I'm a bit confused what could be going wrong.</p> <pre><code>steps.month.day.avg &lt;- ddply(steps.month.day, .(fitbit.day,fitbit.month), summarise, msteps = mean(steps)) </code></pre>
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