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Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.

library(help="datasets")
years<-c(1980,1980,1985,1990)
scores<-c(34,44,56,83)
df<-data.frame(years,scores)
df[,1]
## [1] 1980 1980 1985 1990
df$years
## [1] 1980 1980 1985 1990
df[,2]
## [1] 34 44 56 83
df[df$scores<50, "scores"]
## [1] 34 44
df[df$years==1980, "scores"]
## [1] 34 44
df$initial=c('d','b','s','u')
nrow(df)
## [1] 4
subject_name<-c("John Doe","Jane Doe","Steve Graves")
temperature<-c(98.1,98.6,101.4)
flu_status<-c(FALSE,FALSE,TRUE)
temperature[2]
## [1] 98.6
temperature[2:3]
## [1]  98.6 101.4
temperature[-2] #excluding patient 2
## [1]  98.1 101.4
subject_name[2]
## [1] "Jane Doe"
subject_name[-3]
## [1] "John Doe" "Jane Doe"
gender<-factor(c("MALE","FEMALE","MALE"))
gender
## [1] MALE   FEMALE MALE  
## Levels: FEMALE MALE
blood<-factor(c("O","AB","A"),levels = c("A","B","AB","O"))
blood
## [1] O  AB A 
## Levels: A B AB O
symptoms<-factor(c("SEVERE","MILD","MODERATE"),levels = c("MILD","MODERATE","SEVERE"),ordered = TRUE)
symptoms
## [1] SEVERE   MILD     MODERATE
## Levels: MILD < MODERATE < SEVERE
symptoms<-factor(c("SEVERE","MILD","MODERATE"),levels = c("MILD","MODERATE","SEVERE"),ordered = FALSE)
symptoms>"MODERATE"
## Warning in Ops.factor(symptoms, "MODERATE"): '>' not meaningful for factors
## [1] NA NA NA
pt_data<-data.frame(subject_name,temperature,flu_status,gender,blood,symptoms,stringsAsFactors = FALSE)
pt_data
##   subject_name temperature flu_status gender blood symptoms
## 1     John Doe        98.1      FALSE   MALE     O   SEVERE
## 2     Jane Doe        98.6      FALSE FEMALE    AB     MILD
## 3 Steve Graves       101.4       TRUE   MALE     A MODERATE
pt_data[1,2] #frst row scnd col
## [1] 98.1
pt_data[,2]
## [1]  98.1  98.6 101.4
pt_data[c(1,3),c(2,4)] #frst and 3rd row and 2nd and 4th col
##   temperature gender
## 1        98.1   MALE
## 3       101.4   MALE
pt_data[c(1,3),c("temperature","gender")]
##   temperature gender
## 1        98.1   MALE
## 3       101.4   MALE
pt_data[,]
##   subject_name temperature flu_status gender blood symptoms
## 1     John Doe        98.1      FALSE   MALE     O   SEVERE
## 2     Jane Doe        98.6      FALSE FEMALE    AB     MILD
## 3 Steve Graves       101.4       TRUE   MALE     A MODERATE
pt_data$temp_c<-(pt_data$temperature-32)*(5/9)
pt_data$temp_c
## [1] 36.72222 37.00000 38.55556
pt_data
##   subject_name temperature flu_status gender blood symptoms   temp_c
## 1     John Doe        98.1      FALSE   MALE     O   SEVERE 36.72222
## 2     Jane Doe        98.6      FALSE FEMALE    AB     MILD 37.00000
## 3 Steve Graves       101.4       TRUE   MALE     A MODERATE 38.55556
pt_data[c("temperature","temp_c")]
##   temperature   temp_c
## 1        98.1 36.72222
## 2        98.6 37.00000
## 3       101.4 38.55556
library(ggplot2)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ lubridate 1.9.3     ✔ tibble    3.2.1
## ✔ purrr     1.0.2     ✔ tidyr     1.3.1
## ── 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
library(dplyr)
?mpg
## starting httpd help server ... done
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
head(mpg)
## # A tibble: 6 × 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(l5)   f        18    29 p     compa…
## 2 audi         a4      1.8  1999     4 manual(m5) f        21    29 p     compa…
## 3 audi         a4      2    2008     4 manual(m6) f        20    31 p     compa…
## 4 audi         a4      2    2008     4 auto(av)   f        21    30 p     compa…
## 5 audi         a4      2.8  1999     6 auto(l5)   f        16    26 p     compa…
## 6 audi         a4      2.8  1999     6 manual(m5) f        18    26 p     compa…
ggplot(data=mpg)+geom_point(mapping = aes(x=displ,y=hwy))

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

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=hwy),color="blue")

ggplot(data=mpg)+geom_point(mapping = aes(x=displ,y=hwy))+facet_wrap(~class,nrow=2)

ggplot(data=mpg)+geom_point(mapping = aes(x=displ,y=hwy,shape=class))+facet_wrap(~class,nrow=2)
## 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.
## Removed 62 rows containing missing values (`geom_point()`).

ggplot(data=mpg)+geom_point(mapping = aes(x=displ,y=cyl))+facet_wrap(~class,nrow=3)

ggplot(data=mpg)+geom_point(mapping = aes(x=displ,y=hwy))+facet_wrap(~cyl,nrow=2)

ggplot(data=mpg)+geom_point(mapping = aes(x=displ,y=hwy))+facet_grid(drv~cyl)