block011_write-your-own-function-CHALLENGE-SEGUE.rmd

### challenge

```{r}
gDat <- read.delim("gapminderDataFiveYear.txt")
str(gDat)
## or do this if the file isn't lying around already
## gd_url <- "http://tiny.cc/gapminder"
## gDat <- read.delim(gd_url)

## let's write a function that takes a data.frame
## like the Gapminder data
## or just the data for one country or continent or ...
## fits a linear model of lifeExp on year
## and returns the estimated intercept and slope

fit <- lm(lifeExp ~ year, data = gDat)
summary(fit)

## what's up with that crazy intercept?
## good time for a figure

library(ggplot2)
ggplot(gDat, aes(x = year, y = lifeExp)) + geom_point()
ggplot(gDat, aes(x = year, y = lifeExp)) + geom_point() +
  geom_smooth(method = "lm")

## intercept = estimate life exp in year 0
## let's re-fit so intercept = est life exp in 1952 = earliest year in dataset
fit <- lm( lifeExp ~ I(year - 1952), data=gDat)
summary(fit) # much better

class(fit) ## read up on `lm` ... learn about coef()
(fit.coef <- coef(fit))
names(fit.coef) <- c("intercept","slope")
fit.coef 

## package that into a function
## input: a data.frame
## output: a numeric vector of length two
##        first element = estimated intercept
##        second element = estimate slope
##        names are "intercept" and "slope"
## GO!

jFun <- function(x) {
  fit <- lm( lifeExp ~ I(year - 1952), data = x)
  fit.coef <- coef(fit)
  names(fit.coef) <- c("intercept","slope")
  return(fit.coef)
}

jFun(gDat)

## depending on time and interest, we could talk about better approaches to the
## "subtract 1952 from the year" problem

## what if we flexibility re: the shift?
## create a formal argument for the shift, but give it default value of 1952
jFun <- function(x, shift = 1952) {
  fit <- lm( lifeExp ~ I(year - shift), data = x)
  fit.coef <- coef(fit)
  names(fit.coef) <- c("intercept","slope")
  return(fit.coef)
}

jFun(gDat)
jFun(gDat, shift = 0) ## can still get this if you really want
jFun(gDat, shift = 2007) ## check against fitted line at 2007

## what if we don't want to hard-wire 1952? another approach
jFun <- function(x, shift = NULL) {
  if(is.null(shift)){
    shift <- min(x$year)
  }
  fit <- lm( lifeExp ~ I(year - shift), data = x)
  fit.coef <- coef(fit)
  names(fit.coef) <- c("intercept","slope")
  return(fit.coef)
}

jFun(gDat)
jFun(gDat, shift = 0)
jFun(gDat, shift = 2007)

## exercise:

## create a subset of the data
## eg just one continent or one country

## plot the lifeExp against year and superpose a line
## use jFun() to get intercept and slope
## sanity check numbers against plot

x <- subset(gDat, continent == "Asia")
jFun(x)
ggplot(x, aes(x = year, y = lifeExp)) +
  geom_point() + geom_smooth(method = "lm")

x <- subset(gDat, country == "Rwanda")
jFun(x)
ggplot(x, aes(x = year, y = lifeExp)) +
  geom_point() + geom_smooth(method = "lm")
```