Tip 1: Avoid loops.
\nThey are generally slow – use a function instead. Even with the need of variable and fixed columns in a loop, a function may be constructed like
\napply(data,2,function(col2){table(col1,col2)<\/p>\n
Tip 2: Always show current state.
\nInclude options(warn=1) and show current state with cat(“message\\n”);flush.console();<\/p>\n
Tip 3: Avoid merging steps.
\nUse instead datasets in same order and with the same subset of the larger table before updating anew column with data from the second table.<\/p>\n\n
<\/p>\n
Tip 1: Avoid loops. They are generally slow – use a function instead. Even with the need of variable and fixed columns in a loop, a function may be constructed like apply(data,2,function(col2){table(col1,col2) Tip 2: Always show current state. Include options(warn=1) and show current state with cat(“message\\n”);flush.console(); Tip 3: Avoid merging steps. Use instead datasets in … Continue reading 3 R tips for loops<\/span>