two-variables.Rmd

---
title: "two-variables"
author: "SasanGN"
date: "December 13, 2018"
output: html_document
editor_options: 
  chunk_output_type: console
---


## import libraries
```{r}
library(ggplot2)
library(dplyr)
```

## Reading in the tab separated file // read.csv or read.delim
```{r}
getwd()
setwd("D://Documents//GitHub//100-days-of-code-challenge/")
list.files()
inFile <- read.csv('pseudo_facebook.tsv', sep= '\t')
## inFile2 <- read.delim('pseudo_facebook.tsv')
names(inFile)
```

## qplot vs ggplot syntax
```{r}
qplot(data = inFile, x= age, y= friend_count)

ggplot(aes(age, friend_count), data=inFile) + geom_point() +
  xlim(13,90)
summary(inFile$age)
```

## coord_trans
```{r}
ggplot(aes(age, friend_count), data = inFile) +
  geom_point(alpha = 1/20, position = position_jitter(h=0)) +
  xlim (13, 90) +
  coord_trans(y= 'sqrt')
```

## the relationship between friends initiated (y) vs age (x)
```{r}
ggplot(aes(age, friendships_initiated), data = inFile) + 
  geom_point(alpha = 0.1, position = position_jitter(h=0)) +
  coord_trans(y= 'sqrt')
```

## conditional means, group data by age
```{r}
age_groups <- group_by(inFile, age)
inFile.fc_by_age <- summarise(age_groups,
          friend_count_mean = mean(friend_count),
          friend_count_median = median(friend_count),
          n = n())
inFile.fc_by_age 

head(inFile.fc_by_age)
```

## alt. way to do the same result
```{r}
inFile.fc_by_age <- inFile %>%
  group_by(age) %>%
  summarise(friend_count_mean = mean(friend_count),
            friend_count_median = median(friend_count),
            n = n()) %>%
  arrange(age)
head(inFile.fc_by_age, 20)
```

## plot average friend count vs age using a line graph
## using geom_line()
```{r}
ggplot(aes(age, friend_count_mean), data = inFile.fc_by_age) + 
  geom_line()
```

```{r}
inFile$age_with_months <- inFile$age + (1 - inFile$dob_month /12)
inFile$age_with_months
```

## age with months mean
```{r}
inFile$age_with_months <- inFile$age + (1 - inFile$dob_month /12)
age_groups_months <- group_by(inFile, inFile$age_with_months)

inFile.fc_by_age_months <- summarise(age_groups_months,
          friend_count_mean = mean(friend_count),
          friend_count_median = median(friend_count),
          n = n())
inFile.fc_by_age_months <- arrange(inFile.fc_by_age_months, age_with_months)
head(inFile.fc_by_age_months)
```
## alt way
```{r}
library(dplyr)
inFile$age_with_months <- inFile$age + (1 - inFile$dob_month /12)

inFile.fc_by_age_months2 <- inFile %>%
  group_by(age_with_months) %>%
  summarise(friend_count_mean = mean(friend_count),
            friend_count_median = median(friend_count),
            n = n()) %>%
              arrange(age_with_months)
head(inFile.fc_by_age_months2)
```

## plot friend_count_mean vs age_with_months
```{r}
ggplot(aes(x = age_with_months, y = friend_count_mean), 
       data = subset(inFile.fc_by_age_months2, age_with_months < 71)) +
  geom_line()
```

```{r}
p1 <- ggplot(aes(x=age, y= friend_count_mean),
             data = subset(inFile.fc_by_age, age< 71)) + 
  geom_line() +
  geom_smooth()

p2 <- ggplot(aes(x=age_with_months, y=friend_count_mean),
             data = subset(inFile.fc_by_age_months2, age_with_months < 71)) +
  geom_line() +
  geom_smooth()

p3 <- ggplot(aes(x=round(age/5)*5, y= friend_count),
             data = subset(inFile, age < 71)) +
  geom_line(stat = 'summary', fun.y = mean)
library(gridExtra)
grid.arrange(p2, p1, p3, ncol = 1)
```



## overlaying summaries with raw data!
```{r}
ggplot(aes(x= age, y = friend_count), data = inFile) +
  coord_cartesian(xlim=c(13, 60), ylim = c(0,1000))+
  geom_point(alpha = 0.05, position = position_jitter(h=0), color = 'red') +
  geom_line(stat = 'summary', fun.y = mean) +
  geom_line(stat = 'summary', fun.y = quantile, fun.args = list(probs = .1), linetype = 2, color = 'yellow') + 
  geom_line(stat = 'summary', fun.y = quantile, fun.args = list(probs = .5), color = 'green') + 
  geom_line(stat = 'summary', fun.y = quantile, fun.args  = list(probs = .9), linetype = 2, color = 'blue')
```

?cor.test

## correlation
```{r}
cor.test(inFile$age, inFile$friend_count, method = 'pearson')
## or
with(inFile, cor.test(age, friend_count, method = 'pearson'))
```

## correlation on subset data
```{r}
with(subset(inFile, age <= 70), cor.test(age, friend_count, method = 'spearman'))
```

## scatterplot of likes_received (y) vs. www_likes_received (x)
```{r}
names(inFile)
ggplot(aes(www_likes_received, likes_received), data = inFile) + 
  geom_point() +
  xlim(0, quantile(inFile$www_likes_received, 0.95)) +
  ylim(0, quantile(inFile$likes_received, 0.95)) +
  geom_smooth(method = 'lm', color = 'red')
```


## correlation between the above two variables
```{r}
with(inFile, cor.test(www_likes_received, likes_received))
```
## Mitchell soil temperature data set
```{r}
install.packages('alr3')
library(alr3)
data(Mitchell)
?Mitchell
names(Mitchell) 
```

```{r}
with(Mitchell, cor.test(Month, Temp))
range(Mitchell$Month)

ggplot(aes(Month, Temp), data = Mitchell) +
  geom_point() +
  scale_x_continuous(breaks = seq(0, 203, 12))

## creating sinusoidal
ggplot(aes(x=(Month%%12),y=Temp), data=Mitchell)+
  geom_point()
```