Common Data Objects in R

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<div class="footer-small">https://github.com/mjfrigaard/ph-lacounty-r/</div>

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# Common Data Objects in R
#.fancy[Vectors, Lists, Data Frames and Tibbles]

.large[by Martin Frigaard]

Written: October 03 2022

Updated: December 02 2022

.footer-large[.right[.fira[
 [Created using the "λέξις" theme](https://jhelvy.github.io/lexis/index.html#what-does-%CE%BB%CE%AD%CE%BE%CE%B9%CF%82-mean)
]]]

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# Materials

The slides are in the `slides.pdf` file

The materials for this training are in the `worksheets` folder:

```
worksheets
├── import.Rmd
├── export.Rmd
├── objects.Rmd
├── rmd-basic.Rmd
├── rmd-tables.Rmd
└── rmd-visualizations.Rmd
```

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# Outline

.leftcol[

#### 1. Importing data

#### 2. .red[Common Data Objects]

#### 3. R Markdown

]

.rightcol[

#### 4. R Markdown Data Visualizations

#### 5. R Markdown Tables

#### 6. Exporting Data

]

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# .large[Common Data Objects]

.font90[.green[Open `objects.Rmd` to follow along]]

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# Data Objects: vector

#### Vectors are the fundamental data object in R

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# Data Objects: creating vectors

`c()` is used to combine (or concatenate) a variety of elements

`<-` is referred to as the assignment operator, and it’s used with `c()` to assign elements to a designated object

*Earlier we used `<-` to create the `medical` dataset*

.leftcol[

Create logical and integer vectors (`log_vec` and `int_vec`)

```r
log_vec <- c(TRUE, FALSE)
int_vec <- c(4L, 7L)
```

]

.rightcol[

Create double and character vectors (`dbl_vec` and `chr_vec`)

```r
dbl_vec <- c(2.2, 8.09)
chr_vec <- c("A", "D")
```

]

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# Data Objects: atomic vectors

.cols3[

.font80[Print Atomic Vectors]

.code60[

```r
log_vec
```

```
  [1]  TRUE FALSE
```

```r
int_vec
```

```
  [1] 4 7
```

```r
dbl_vec
```

```
  [1] 2.20 8.09
```

```r
chr_vec
```

```
  [1] "A" "D"
```

]

.cols3[

.font80[Check with `typeof()`]

.code60[

```r
typeof(log_vec)
```

```
  [1] "logical"
```

```r
typeof(int_vec)
```

```
  [1] "integer"
```

```r
typeof(dbl_vec)
```

```
  [1] "double"
```

```r
typeof(chr_vec)
```

```
  [1] "character"
```

]

.cols3[

.font80[Check `class()`]

.code60[

```r
class(log_vec)
```

```
  [1] "logical"
```

```r
class(int_vec)
```

```
  [1] "integer"
```

```r
*class(dbl_vec)
```

```
  [1] "numeric"
```

```r
class(chr_vec)
```

```
  [1] "character"
```

]

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# Data Objects: S3 vectors

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# Data Objects: S3 vectors

.leftcol[

.font80[Create S3 Vectors]

.code60[

```r
fct_vec <- factor(
 x = c("Medium", "Low", "High"), 
 levels = c("Low", "Medium", "High"))
date_vec <- c(Sys.Date(), Sys.Date() + 1)
dt_vec <- c(Sys.time(), Sys.time() + (86400*365))
difft_vec <- difftime(
 time1 = Sys.time(), 
 time2 = Sys.time() + (86400*365), 
 units = "days")
```

]

.rightcol[

.font80[View S3 vectors]

.code55[

```r
fct_vec
```

```
  [1] Medium Low    High  
  Levels: Low Medium High
```

```r
date_vec
```

```
  [1] "2022-12-02" "2022-12-03"
```

```r
dt_vec
```

```
  [1] "2022-12-02 09:33:48 PST" "2023-12-02 09:33:48 PST"
```

```r
difft_vec
```

```
  Time difference of -365 days
```

]
]

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# Data Objects: S3 vectors

.leftcol[

.font80[Check `typeof()`]

.code60[

```r
typeof(fct_vec)
```

```
  [1] "integer"
```

```r
typeof(date_vec)
```

```
  [1] "double"
```

```r
typeof(dt_vec)
```

```
  [1] "double"
```

```r
typeof(difft_vec)
```

```
  [1] "double"
```

]
]

.rightcol[

.font80[Check `class()`]

.code60[

```r
class(fct_vec)
```

```
  [1] "factor"
```

```r
class(date_vec)
```

```
  [1] "Date"
```

```r
class(dt_vec)
```

```
  [1] "POSIXct" "POSIXt"
```

```r
class(difft_vec)
```

```
  [1] "difftime"
```

]
]

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# Data Objects: S3 vectors

.font90[**S3 vectors have additional `attributes()`**]

.cols3[

.font80[Factor attributes]

.code60[

```r
attributes(fct_vec)
```

```
  $levels
  [1] "Low"    "Medium" "High"  
  
  $class
  [1] "factor"
```

]

.cols3[

.font80[Date/Datetime attributes]

.code60[

```r
attributes(date_vec)
```

```
  $class
  [1] "Date"
```

```r
attributes(dt_vec)
```

```
  $class
  [1] "POSIXct" "POSIXt" 
  
  $tzone
  [1] ""
```

]
]

.cols3[

.font80[Difftime attributes]

.code60[

```r
attributes(difft_vec)
```

```
  $class
  [1] "difftime"
  
  $units
  [1] "days"
```

]
]

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# Data Objects: lists

.font90[**Vectors have to be the same type, or `class`**]

.font90[**Lists can contain objects of different `class`es**]

.leftcol40[

```r
atomic_list <- list(
 'logical vector' = log_vec,
 'integer vector' = int_vec,
 'double vector' = dbl_vec,
 'character vector' = chr_vec
)
```

]

.rightcol60[

```r
atomic_list
```

```
  $`logical vector`
  [1]  TRUE FALSE
  
  $`integer vector`
  [1] 4 7
  
  $`double vector`
  [1] 2.20 8.09
  
  $`character vector`
  [1] "A" "D"
```

]

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# Data Objects: lists

.font90[**Lists can even contain other lists!**]

.leftcol[

.font80[Create list of date vectors]

.code60[

```r
s3_list <- list(
 'date vector' = date_vec,
 'datetime vector' = dt_vec,
 'difftime vector' = difft_vec
)
```
]

.font80[Create list of lists]

.code60[

```r
vector_list <- list(
 'S3 list' = s3_list,
 'Atomic list' = atomic_list
)
```
]

]

.rightcol[

.code50[

```r
vector_list
```

```
  $`S3 list`
  $`S3 list`$`date vector`
  [1] "2022-12-02" "2022-12-03"
  
  $`S3 list`$`datetime vector`
  [1] "2022-12-02 09:33:48 PST" "2023-12-02 09:33:48 PST"
  
  $`S3 list`$`difftime vector`
  Time difference of -365 days
  
  
  $`Atomic list`
  $`Atomic list`$`logical vector`
  [1]  TRUE FALSE
  
  $`Atomic list`$`integer vector`
  [1] 4 7
  
  $`Atomic list`$`double vector`
  [1] 2.20 8.09
  
  $`Atomic list`$`character vector`
  [1] "A" "D"
```

]
]

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# Data Objects: data.frames

.font120[**A `data.frame` is a rectangular list**]

.leftcol30[

.font80[Create `data.frame`]

.code60[

```r
my_df <- data.frame(
 log_col = log_vec,
 int_col = int_vec,
 dbl_col = dbl_vec,
 chr_col = chr_vec,
 date_col = date_vec,
 dt_col = dt_vec
)
```

]

.rightcol70[

.font80[View `data.frame`]

.code60[

```r
my_df
```

```
    log_col int_col dbl_col chr_col   date_col              dt_col
  1    TRUE       4    2.20       A 2022-12-02 2022-12-02 09:33:48
  2   FALSE       7    8.09       D 2022-12-03 2023-12-02 09:33:48
```

]

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# Data Objects: data.frames

.font90[**Check the structure of the `data.frame`**]

.code60[

```r
str(my_df)
```

```
  'data.frame':	2 obs. of  6 variables:
   $ log_col : logi  TRUE FALSE
   $ int_col : int  4 7
   $ dbl_col : num  2.2 8.09
   $ chr_col : chr  "A" "D"
   $ date_col: Date, format: "2022-12-02" "2022-12-03"
   $ dt_col  : POSIXct, format: "2022-12-02 09:33:48" "2023-12-02 09:33:48"
```

]

.font90[**Check the `class` and `typeof()` for the a `data.frame`**]

.leftcol[

.code60[

```r
class(my_df)
```

```
  [1] "data.frame"
```
]

]

.rightcol[

.code60[

```r
typeof(my_df)
```

```
  [1] "list"
```

]

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# Data Objects: tibbles

.font90[**A tibble is a [modern reimagining](https://tibble.tidyverse.org/) of the `data.frame`**]

.font90[They are created just like `data.frame`s]

.leftcol30[

.font80[Create `tibble`]

.code60[

```r
my_tbl <- tibble(
 log_col = log_vec,
 int_col = int_vec,
 dbl_col = dbl_vec,
 chr_col = chr_vec,
 date_col = date_vec,
 dt_col = dt_vec
)
```

]

.rightcol70[

.font80[View `tibble`]

.code60[

```r
my_tbl
```

```
 # A tibble: 2 × 6
 log_col int_col dbl_col chr_col date_col dt_col 
 <lgl> <int> <dbl> <chr> <date> <dttm> 
 1 TRUE 4 2.2 A 2022-12-02 2022-12-02 09:33:48
 2 FALSE 7 8.09 D 2022-12-03 2023-12-02 09:33:48
```

]

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# Data Objects: data.frames & tibbles

.font90[`tibble`s print a little nicer than `data.frame`s, and we'll primarily be using them because they work well with other functions for tables and visualizations.]

.code80[

```r
my_df
```

]

.code80[

```r
my_tbl
```

]