R-Data-Exercises

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##Ex 1: Recreate the following dataframe by creating vectors and 
##using the data.frame function:
## I did 2 methods: a and df
 Age <- c(22,25,26)
 Weight <- c(150, 165, 120)
 Sex <- c("M", "M", "F")
 Name <- c("Sam", "Frank", "Ami")

 a <- cbind.data.frame( Age, Weight, Sex)
 row.names(a)<- c("Sam", "Frank", "Ami")
 a
 d <- data.frame(row.names =Name, Age, Weight, Sex )
 d
##Ex2.Check if mtcars is a dataframe using is.data.frame()
 is.data.frame(mtcars)
##Ex3.Use as.data.frame() to convert a matrix into a dataframe:
 mat <- matrix(1:25, nrow=5)
 mat <- as.data.frame(mat)
 mat
## Ex 4: Set the built-in data frame mtcars as a variable df. 
## We'll use this df variable for the rest of the exercises.
   df <- mtcars
## Ex 5: Display the first 6 rows of df
  head(mtcars)
## Ex 6: What is the average mpg value for all the cars?
  avg <- mean(df$mpg)
  avg
##Ex 7: Select the rows where all cars have 6 cylinders (cyl column)
  mtcars[mtcars$cyl==6, ]
##Ex 8: Select the columns am,gear, and carb.
  df(df$am, df$gear, df$carb)
  df[ , c("am", "gear", "carb")]
##Ex 9: Create a new column called performance, which is calculated by hp/wt.
  perfomence <- c(df$hp/df$wt)
  cbind(df, perfomence) 
##or method 2 
  df$perfomence <- df$hp/df$wt
##Ex 9: Your performance column will have several decimal place precision.
##Figure out how to use round() (check help(round)) to reduce this accuracy to only 
##2 decimal places.
##round(x, digits = 0)
 df$perfomence <- round(df$perfomence, digits = 2)
 head(df)
##Ex 10: What is the average mpg for cars that have more than 100 hp 
##AND a wt value of more than 2.5.
  avg.mpg <- mean(df$mpg[ (df$hp>100) & (df$wt>2.5)])
  avg.mpg
##method 2
  mean(subset( df, df$hp>100 & df$wt>2.5)$mpg)

##Ex 11: What is the mpg of the Hornet Sportabout?
  df[["Hornet Sportabout","mpg"]]

Work with ggplot2 package

##install.packages('ggplot2')
#install.packages('ggplot2movies')
library(ggplot2)
library(ggplot2movies)

# Data & Aesthetics
colnames(movies)
head(movies)
## will use rating for Aestethis to make first plot
pl <-ggplot(movies,aes(x=rating))
print(pl+ geom_histogram())  # will give you the base histogram plot1

 print(pl+ geom_histogram(binwidth = 0.1)) ## will show mor precise solution plot2

 print(pl+ geom_histogram(binwidth = 0.1, color = "red")) # and add red countor plot3

Now we need to use Geometry

pl2 <- pl + geom_histogram(binwidth = 0.1, color = 'red', fill= "pink", alpha = 0.4)
print(pl2) ## plot 4

pl3 <- pl + geom_histogram(binwidth = 0.1, color = 'red', fill= "pink", alpha = 0)
print(pl3) ## plot 5  alfa shows the trancparancy

pl4 <-pl2 + xlab('Movie Rating') + ylab('Count')
print(pl4) ## plot6 with adding x and y names

pl5 <- pl + geom_histogram(binwidth = 0.1, aes(fill = ..count..))
pl7 <-pl5 + xlab('Movie Rating') + ylab('Count') 
print(pl7) ##plot7

pl8 <-pl7 + xlab('Movie Rating') + ylab('Count') +theme(legend.position = "bottom")
print(pl8 + ggtitle("MY TITLE")) ##plot8 with TITLE and lables

SCATERPLOTS

library(ggplot2)
df <- mtcars

Data and aesthics

pl_sc <- ggplot(df,aes(x=wt,y=mpg))

GEOMETRY

print(pl_sc + geom_point( alpha = 0.5, size = 5))    # alpha shows clarity 0:1, plot10

 print(pl_sc + geom_point(aes(size=hp)))    ## by horse power, plot11

 print(pl_sc + geom_point(aes(size = cyl)))  ## by cylinders, plot12

 print(pl_sc + geom_point(aes(size = factor(cyl))))  ## plot13

 print(pl_sc + geom_point(aes(shape = factor(cyl)), size = 5))  ## plot14

 print(pl_sc + geom_point(aes(shape = factor(cyl)), size = 5, color = "#8470ff")) ##plot15

Hex color picker, you can use any code to pick any color www.color-hex.com

pl_sc2 <- pl_sc + geom_point(aes(color = hp, size=hp))
print(pl_sc2)  ## plot16

pl_sc3 <-  pl_sc2 + scale_color_gradient(low = 'black', high = 'green')
print(pl_sc3) ## plot17

Barplots

df <- mpg
pl.b <- ggplot(df, aes(x=class))  # class is a catigorical data in DF
print(pl.b + geom_bar())
print(pl.b + geom_bar(color="red", fill="blue"))  # color shows the line around, you  not nessasary 
print(pl.b + geom_bar(aes(fill=drv))) # will classify by color of class dvr 
#  "dodge" will show staking = classify bars next to each other for easy to compare
print(pl.b + geom_bar(aes(fill=drv), position = "dodge"))
# "fill will show percentage% 
print(pl.b + geom_bar(aes(fill=drv), position = "fill"))

Boxplots

df <- mtcars
pl.box <- ggplot(df, aes(x=cyl,y=mpg))
print(pl.box + geom_boxplot())
# but cyl a catigorical value, so we need to use as a factor for x
pl.box1 <- ggplot(df, aes(x=factor(cyl),y=mpg))
# add fill with color
print(pl.box1 + geom_boxplot(fill="blue"))
#we can also flip coordinates and make baxplot horizontal
pl.box1 <- ggplot(df, aes(x=factor(cyl),y=mpg))
print(pl.box1 + geom_boxplot()+ coord_flip())
#and we can add more color by group of factor cyl and theme as background
pl.box1 <- ggplot(df, aes(x=factor(cyl),y=mpg))
print(pl.box1 + geom_boxplot(aes(fill=factor(cyl)))+ theme_dark())

2 Variables plot

library(ggplot2)
library(ggplot2movies)
library(dplyr)

pl <- ggplot(movies, aes(x=year,y=rating))
pl2 <- pl + geom_bin2d()  ## pl1
pl2 %>%print()
#  pl1 <-( pl + geom_bin2d()) %>% print()  can work like this also

pl3 <- pl2+ scale_fill_gradient(high='red', low = 'green')
print(pl3)

pl4 <- pl3 + geom_bin2d(binwidth=c(3,1))
print(pl4)

pl5 <- pl4+ scale_fill_gradient(high='red', low = 'blue')
print(pl5)
install.packages('hexbin')

##install.packages('stat_binhex')
require('hexbin')
pl <- ggplot(movies, aes(x=year, y=rating))
pl6 <- pl + geom_hex()
pl7 <- pl6+ scale_fill_gradient(high='red', low = 'blue')
print(pl7)

pl8 <- pl+ geom_density2d()
print(pl8)
gqplot(x=years, y=rating, data = df, geom = "density2d")

IrinaMax / R-Data-Frames-Exercises

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