sapply is my new friend!

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I’ve written previously about how the apply function is a major workhorse in many of my work projects. What I didn’t know is how handy the sapply function can be!

There are a couple of cases so far where I’ve found that sapply really comes in handy for me:

1) If I want to quickly see some descriptive stats for multiple columns in my dataframe. For example,

sapply(mydf[,10:20], median, na.rm=true)

would show me the medians of columns 10 through 20, displaying the column names above each median value.

2) If I want to apply the same function to multiple vectors in my dataframe, modifying them in place. I oftentimes have count variables that have NA values in place of zeros. I made a “zerofy” function to add zeros into a vector that lacks them. So, if I want to use my function to modify these count columns, I can do the following:

mydf[,30:40] = sapply(mydf[,30:40], zerofy)

Which then replaces the original data in columns 30 through 40 with the modified data! Handy!

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