Day2RExercise_SrourMolly.Rmd

---
title: "R Day 2"
author: "Molly Srour"
date: "9/18/2018"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(here)
```

```{r}
gapminder <- read.csv('/Users/mollysrour/Documents/MSiA/bootcamp-2018/data/gapminder5.csv')
obs <- 1:nrow(gapminder)
for(i in obs) {
  gapminder[i, "gdp"] <- gapminder[i,"pop"] * gapminder[i, "gdpPercap"]
}
for(i in obs) {
  gapminder[i, "log_gdpPercap"] <- log(gapminder[i, "gdpPercap"])
  gapminder[i, "log_pop"] <- log(gapminder[i, "pop"])
}

years <- unique(gapminder$year)
for(i in years) {
  mean_le <- mean(gapminder$lifeExp[gapminder$year ==i], 
                  na.rm = T)
  print(paste0(i, ": ", mean_le))
}
```

```{r}
continents <- unique(gapminder$continent)
for(i in continents){
  mean_le <- mean(gapminder$lifeExp[gapminder$continent == i],
                na.rm = T)
  print(paste0(i, ": ", mean_le))
}
for(i in continents){
  print(paste0("Continent:", i))
  for(j in years) {
    sd_le <- sd(gapminder$lifeExp[gapminder$continent ==i & gapminder$year == j],
                na.rm=T)
  }
}
```

```{r}
  while(i <=2002 & i >=1987){
    sd_le <- sd(gapminder$lifeExp[gapminder$year == i],
                na.rm=T)
  }
```
```{r}
threshold <- 1987

for (i in unique(gapminder$year)) {
   tmp <- mean(gapminder$pop[gapminder$year==i])
   
   if (i < threshold) {
       print(paste("Sorry, your year is less than", threshold))
   } else {
       print(paste("Population in", i, ": ", tmp))
   }
}


```

```{r}
report <- 
  function(df, variable, continent) {
    var <- gapminder[[variable]][gapminder$continent == continent]
    m_le <- mean(var)
    med_le <- median(var)
    min_le <- min(var)
    max_le <- max(var)
    cat("Continent:", continent, 
        "\nMean Life Expectancy:", m_le,
        "\nMedian Life Expectancy:", med_le,
        "\nMin Life Expectancy:", min_le,
        "\nMax Life Expectancy:", max_le)
  }

report(gapminder, "lifeExp", "Asia")


```