summarize.Rmd

---
title: "Summarize_verb"
author: "Amit"
date: "5/28/2018"
output: html_document
---

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

## R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see <http://rmarkdown.rstudio.com>.

When you click the **Knit** button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

```{r cars}
#step 1
library(ggplot2)
library(tidyverse)
library(gapminder)
```

## summarizing into multiple columns and finding mean life expectancy from the gapminder dataset

```{r pressure, echo=FALSE}
gapminder %>%
   filter(year==2007) %>%
   summarize(meanLifeExp=mean(lifeExp),totalPop=sum(pop))
```
## summarizing into multiple columns
finding median life expectancy from the gapminder dataset

You can also embed plots, for example:

```{r pressure, echo=FALSE}
gapminder %>%
   filter(year==2007) %>%
   summarize(medianLifeExp=median(lifeExp) ,totalPop=sum(pop))

# Filter for 1957 then summarize the median life expectancy and the maximum GDP per capita
gapminder %>%
filter(year==1957)%>%
summarize(medianLifeExp=median(lifeExp),maxGdpPercap=max(gdpPercap))
```
## summarizing into multiple columns

performing summary withing each year

```{r pressure, echo=FALSE}
# Find median life expectancy and maximum GDP per capita in each year
gapminder %>%
  group_by(year) %>%
  summarize(medianLifeExp = median(lifeExp),
            maxGdpPercap = max(gdpPercap),maxpop=max(pop))

```

```{r pressure, echo=FALSE}
library(gapminder)
library(dplyr)
library(ggplot2)

# Find median life expectancy and maximum GDP per capita in each year/continent combination
gapminder %>%
  group_by(continent,year) %>%
  summarize(medianLifeExp = median(lifeExp),
            maxGdpPercap = max(gdpPercap))
```
```{r pressure, echo=FALSE}


# Summarize medianGdpPercap within each continent within each year: by_year_continent
by_year_continent<-gapminder %>%
group_by(continent,year)%>%
summarize(medianGdpPercap=median(gdpPercap))


# Plot the change in medianGdpPercap in each continent over time
ggplot(by_year_continent,aes(x=year,y=medianGdpPercap,color=continent)) + geom_point() + expand_limits(y=0)

```
```{r pressure, echo=FALSE}
library(gapminder)
library(dplyr)
library(ggplot2)

# Summarize the median GDP and median life expectancy per continent in 2007
by_continent_2007 <- gapminder %>%
  filter(year == 2007) %>%
  group_by(continent) %>%
  summarize(medianGdpPercap = median(gdpPercap),
            medianLifeExp = median(lifeExp))

# Use a scatter plot to compare the median GDP and median life expectancy
ggplot(by_continent_2007, aes(x = medianGdpPercap, y = medianLifeExp, color = continent)) +
  geom_point()
```