graph

library(ggplot2)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ lubridate 1.9.3     ✔ tibble    3.2.1
## ✔ purrr     1.0.2     ✔ tidyr     1.3.1
## ✔ readr     2.1.5

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

mpg

## # A tibble: 234 × 11
##    manufacturer model      displ  year   cyl trans drv     cty   hwy fl    class
##    <chr>        <chr>      <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
##  1 audi         a4           1.8  1999     4 auto… f        18    29 p     comp…
##  2 audi         a4           1.8  1999     4 manu… f        21    29 p     comp…
##  3 audi         a4           2    2008     4 manu… f        20    31 p     comp…
##  4 audi         a4           2    2008     4 auto… f        21    30 p     comp…
##  5 audi         a4           2.8  1999     6 auto… f        16    26 p     comp…
##  6 audi         a4           2.8  1999     6 manu… f        18    26 p     comp…
##  7 audi         a4           3.1  2008     6 auto… f        18    27 p     comp…
##  8 audi         a4 quattro   1.8  1999     4 manu… 4        18    26 p     comp…
##  9 audi         a4 quattro   1.8  1999     4 auto… 4        16    25 p     comp…
## 10 audi         a4 quattro   2    2008     4 manu… 4        20    28 p     comp…
## # ℹ 224 more rows

#to plot the mpg

ggplot(data=mpg)+geom_point(mapping = aes(x=displ, y=cyl))

ggplot(data=mpg)+geom_point(mapping = aes(x=displ, y=hwy, color= class))

ggplot(data=mpg)+geom_point(mapping = aes(x=displ, y=hwy, size= class))

## Warning: Using size for a discrete variable is not advised.

ggplot(data=mpg)+geom_point(mapping = aes(x=displ, y=hwy, alpha= class))

## Warning: Using alpha for a discrete variable is not advised.

ggplot(data=mpg)+geom_point(mapping = aes(x=displ, y=hwy, shape= class))

## Warning: The shape palette can deal with a maximum of 6 discrete values because more
## than 6 becomes difficult to discriminate
## ℹ you have requested 7 values. Consider specifying shapes manually if you need
##   that many have them.

## Warning: Removed 62 rows containing missing values (`geom_point()`).

ggplot(data=mpg)+geom_point(mapping = aes(x=displ, y=cyl), color ="blue")

#for categorical data
#ggplot(data = mpg) + geom_point (mapping = aes(x-displ, y= hwy, color=class)) + facet_wrap(~ class, nrow =2)
#to facet your plot on the combination of two variables, add facet_grid() to plot
#ggplot(data = mpg) + geom_point (mapping = aes(x=displ, y= hwy)) + facet_grid(drv~cyl)

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