Design of everyday functions

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The DESIGN   of EVERYDAY   FUNCTIONS Hadley Wickham  @hadleywickham 
RStudio September 2018

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Practitioner Programmer

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Interactive Easily detect & resolve problems Packaged In production You
hear your code Things break and people at you Practitioner Programmer

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Notebook IDE https://yihui.name/en/2018/09/notebook-war/ The First Notebook War Data analyst Engineer

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Me You Practitioner Programmer

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Code is a conversation Ambiguity can be tolerated early and
often Practitioner Programmer Implicit Explicit

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Practitioner Programmer Implicit Explicit

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What makes a good door? https://99percentinvisible.org/article/norman-doors

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None

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“When you have trouble with things—whether it’s ﬁguring out whether
to push or pull a door or the arbitrary vagaries of the modern computer and electronics industries—it’s not your fault. Don't blame yourself: blame the designer...” — Donald A. Norman

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https://twitter.com/irismwang/status/994349937944158208

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https://twitter.com/BrockTibert/status/1009543843690278920

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https://twitter.com/mattfrost/status/768078660200898560

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https://twitter.com/gshotwell/status/675344503566417921

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https://twitter.com/PetrelStation/status/1038043993387552768

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https://twitter.com/NateApathy/status/1030263775205707776

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https://twitter.com/scottmccain5/status/986275394692272129

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“Rule of thumb: if you think something is clever and
sophisticated, beware — it is probably self-indulgence.” — Donald A. Norman

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WAT makes a bad function? https://www.destroyallsoftware.com/talks/wat

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c(factor("a"), factor("b")) What happens when you combine two factors?

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c(factor("a"), factor("b")) #> [1] 1 1 What happens when you
combine two factors? WAT!

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today <- as.Date("2018-09-18") lunch <- as.POSIXct("2018-09-18 12:00", tz = "Europe/Belgrade")
c(today, lunch) What happens when you combine a date and a date-time?

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c(today, lunch) #> [1] "2018-09-18" #> [2] "4210927-01-24" What happens when you combine a date and a date time? WAT!

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c(lunch, today) What happens when you combine a date and a date-time?

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c(lunch, today) #> [1] "2018-09-18 12:00:00 CDT" #> [2] "1969-12-31 22:56:32 CST" What happens if you touch a date-time the wrong way? WAT!

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lunch <- as.POSIXct("2018-09-18 12:00", tz = "Europe/Belgrade") lunch #> [1]
"2018-09-18 12:00:00 CEST" c(lunch) c(NULL, lunch) What happens if you look at a date-time the wrong way?

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lunch <- as.POSIXct("2018-09-18 12:00", tz = "Europe/Belgrade") lunch #> [1]
"2018-09-18 12:00:00 CEST" c(lunch) #> [1] "2018-09-18 05:00:00 CDT" c(NULL, lunch) #> [1] 1537264800 What happens if you look at a date-time the wrong way? WAT! WAT!!

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What makes a good function? one aspect of ^

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c(<factor>, <factor>) -> <integer> c(<datetime<tz>>) -> <datetime> c(NULL, <datetime<tz>>) ->
<double> Types can give us a high-level overview of a function I’ll put types in angle brackets to make clear that this is not real R code

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To do that we need to review some foundations Atomic
Numeric Logical Integer Double Character

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c(<logical>, <logical>) -> <logical> c(<logical>, <integer>) -> <integer> c(<logical>, <double>)
-> <double> c(<logical>, <character>) -> <character> c(<integer>, <logical>) -> <logical> c(<integer>, <integer>) -> <integer> c(<integer>, <double>) -> <double> c(<integer>, <character>) -> <character> c(<double>, <logical>) -> <double> c(<double>, <integer>) -> <integer> c(<double>, <double>) -> <double> c(<double>, <character>) -> <character> For atomic vectors, the rules are simple

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For atomic vectors, the rules are simple Logical Integer Double
Character Logical logical integer double character Integer integer integer double character Double double double double character Character character character character character

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For atomic vectors, the rules are simple Logical Integer Double
Character Even if you’re never explicitly learned this, I think you internalise it quickly.

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Unfortunately c() breaks down when we get to S3 vectors
Atomic Numeric Logical Integer Double Character factor POSIXct Date S3 vectors

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Figuring out the rules is the goal of the vctrs
package http://vctrs.r-lib.org

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mutate(<data.frame>) -> <data.frame> filter(<data.frame>) -> <data.frame> select(<data.frame>) -> <data.frame> arrange(<data.frame>)
-> <data.frame> summarise(<data.frame>) -> <data.frame> group_by(<data.frame>) -> <grouped_df> The types of the primary dplyr functions are simple

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if_else(<logical>, <integer>, <integer>) -> <integer> if_else(<logical>, <double>, <double>) -> <double>
if_else(<logical>, <integer>, <logical>) -> ??? if_else(<logical>, <integer>, <double>) -> ??? if_else(<logical>, <factor>, <character>) -> ??? if_else(<logical>, <date>, <datetime>) -> ??? But there are a few that are more complex

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x <- runif(6) if_else(x > 0.5, x, NA) #> Error:
`false` must be type double, #> not logical Which leads to this annoyance

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x <- runif(6) if_else(x > 0.5, x, NA) #> Error:
`false` must be type double, #> not logical if_else(x > 5, x, NA_real_) #> [1] NA 0.700 0.557 NA NA NA Which leads to this annoyance You’re currently forced to learn about the “typed” NAs

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if_else(<logical>, <integer>, <logical>) -> vec_c(<integer>, <logical>) -> <integer> if_else(<logical>, <factor>,
<character>) -> vec_c(<factor>, <character>) -> <error> I think I'm starting to see the principles

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Fin

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Practitioner Programmer Implicit Explicit Interactive Easily detect & resolve problems
Packaged In production Code is a conversation Ambiguity can be tolerated early and often

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https://adv-r.hadley.nz/vectors-chap.html http://vctrs.r-lib.org https://www.destroyallsoftware.com/talks/wat https://99percentinvisible.org/article/norman-doors WAT! http://bit.ly/everyday-functions

Design of everyday functions

Design of everyday functions

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