Import Data

class: title-slide, center

# Import Data

## Tidy Data Science with the Tidyverse and Tidymodels

### W. Jake Thompson

#### [https://tidyds-2021.wjakethompson.com](https://tidyds-2021.wjakethompson.com) &#183; [https://bit.ly/tidyds-2021](https://bit.ly/tidyds-2021)

.footer-license[*Tidy Data Science with the Tidyverse and Tidymodels* is licensed under a [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).]

<div style = "position:fixed; visibility: hidden">
`$$\require{color}\definecolor{yellow}{rgb}{0.996078431372549, 0.843137254901961, 0.4}$$`
`$$\require{color}\definecolor{blue}{rgb}{0, 0.623529411764706, 0.717647058823529}$$`
</div>

---
background-image: url(images/import/bored.jpeg)
background-position: center middle
background-size: 100%

### **Incredibly boring, or...**

---
background-image: url(images/import/frustrated.jpeg)
background-position: center middle
background-size: 100%

### **absolutely infuriating.**

---
class: your-turn

# Your turn 1

.pull-left.big[
* Open the R Notebook **materials/exercises/05-import.Rmd**
* Run the setup chunk
]

.pull-right[
<img src="images/import/shock-emoji.png" width="80%" style="display: block; margin: auto;" />
]

---
class: center middle

---
# Be kind to your collaborators...

## including future you.

* Workflow

* Editor
    * Home directory
    * R code you ran before break
    
--

* Product
    * Raw data
    * R code someone else need to run to replicate results

* **Workflows should not be hardwired into the products**

---
# Projects

* Each analysis as a *project*
    * Folder on your computer with all relevant files

* R scripts written with assumption of:
    1. Clean session
    2. Working directory = project directory

* Creates everything it needs, touches nothing it didn't create.

???

Can move directory on computer, can move to different computer, can be used by other person (including future you!)

It’s like agreeing that we will all drive on the left or the right. A hallmark of civilization is following conventions that constrain your behavior a little, in the name of public safety.

---
background-image: url(images/import/here.png)
background-position: 75% 50%
background-size: 60%

.footnote[Artwork by [@allison_horst](https://twitter.com/allison_horst)]

---
# `here()`

.big[Find the project directory and build file paths.]

```r
library(here)

here()
#> [1] "/Users/jakethompson/Documents/GIT/courses/tidyds-2021"

here("materials", "data", "nimbus.csv")
#> [1] "/Users/jakethompson/Documents/GIT/courses/tidyds-2021/materials/data/nimbus.csv"
```

---
# `here()`

Where does **`here()`** start?

* Is a file named `.here` present?

* Is there a `.Rproj` file (e.g., `tidyds-2021.Rproj`)?

* Is there a `.git` or `.svn` directory?

```r
dr_here()
#> here() starts at /Users/jakethompson/Documents/GIT/courses/tidyds-2021.
#> - This directory contains a file matching "[.]Rproj$" with contents matching "^Version: " in the first line
#> - Initial working directory: /Users/jakethompson/Documents/GIT/courses/tidyds-2021/site/static/slides
#> - Current working directory: /Users/jakethompson/Documents/GIT/courses/tidyds-2021/site/static/slides
```

---
<div class="hex-book">
  <a href="https://readr.tidyverse.org">
    <img class="hex" src="images/hex/readr.png">
  </a>
  <a href="https://r4ds.had.co.nz/data-import.html">
    <img class="book" src="images/books/r4ds-data-import.png">
  </a>
</div>

---
background-image: url(images/import/applied-ds-import.png)
background-position: center 60%
background-size: 85%

# .nobold[(Applied)] Data Science

---
# `readr` functions

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]

---
# `readr` functions

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  text-transform: inherit;
  padding-top: 8px;
  padding-bottom: 8px;
  padding-left: 5px;
  padding-right: 5px;
}

#bqtuxreipy .gt_first_summary_row {
  padding-top: 8px;
  padding-bottom: 8px;
  padding-left: 5px;
  padding-right: 5px;
  border-top-style: solid;
  border-top-width: 2px;
  border-top-color: #D3D3D3;
}

#bqtuxreipy .gt_grand_summary_row {
  color: #333333;
  background-color: #F0F0F0;
  text-transform: inherit;
  padding-top: 8px;
  padding-bottom: 8px;
  padding-left: 5px;
  padding-right: 5px;
}

#bqtuxreipy .gt_first_grand_summary_row {
  padding-top: 8px;
  padding-bottom: 8px;
  padding-left: 5px;
  padding-right: 5px;
  border-top-style: double;
  border-top-width: 6px;
  border-top-color: #D3D3D3;
}

#bqtuxreipy .gt_striped {
  background-color: rgba(128, 128, 128, 0.05);
}

#bqtuxreipy .gt_table_body {
  border-top-style: solid;
  border-top-width: 2px;
  border-top-color: #D3D3D3;
  border-bottom-style: solid;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
}

#bqtuxreipy .gt_footnotes {
  color: #333333;
  background-color: #F0F0F0;
  border-bottom-style: none;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
  border-left-style: none;
  border-left-width: 2px;
  border-left-color: #D3D3D3;
  border-right-style: none;
  border-right-width: 2px;
  border-right-color: #D3D3D3;
}

#bqtuxreipy .gt_footnote {
  margin: 0px;
  font-size: 90%;
  padding: 4px;
}

#bqtuxreipy .gt_sourcenotes {
  color: #333333;
  background-color: #F0F0F0;
  border-bottom-style: none;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
  border-left-style: none;
  border-left-width: 0px;
  border-left-color: #D3D3D3;
  border-right-style: none;
  border-right-width: 0px;
  border-right-color: #D3D3D3;
}

#bqtuxreipy .gt_sourcenote {
  font-size: 12px;
  padding: 10px;
}

#bqtuxreipy .gt_left {
  text-align: left;
}

#bqtuxreipy .gt_center {
  text-align: center;
}

#bqtuxreipy .gt_right {
  text-align: right;
  font-variant-numeric: tabular-nums;
}

#bqtuxreipy .gt_font_normal {
  font-weight: normal;
}

#bqtuxreipy .gt_font_bold {
  font-weight: bold;
}

#bqtuxreipy .gt_font_italic {
  font-style: italic;
}

#bqtuxreipy .gt_super {
  font-size: 65%;
}

#bqtuxreipy .gt_footnote_marks {
  font-style: italic;
  font-size: 65%;
}
</style>
<div id="bqtuxreipy" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="gt_table" style="table-layout: fixed;; width: 0px">
  <colgroup>
    <col style="width:200px;"/>
    <col style="width:400px;"/>
  </colgroup>
  
  <thead class="gt_col_headings">
    <tr>
      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1" style="text-align: center; vertical-align: middle; font-weight: bold; border-bottom-width: 3px; border-bottom-style: solid; border-bottom-color: black;">function</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1" style="text-align: center; vertical-align: middle; font-weight: bold; border-bottom-width: 3px; border-bottom-style: solid; border-bottom-color: black;">extracts</th>
    </tr>
  </thead>
  <tbody class="gt_table_body">
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro'; font-weight: bold;">read_csv()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-weight: bold;">comma separated files</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">read_csv2()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">semi-colon separated files</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">read_delim()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">general delimited files</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">read_fwf()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">fixed width files</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">read_log()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">Apache log files</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">read_table()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">space separated files</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="border-bottom-width: 2px; border-bottom-style: solid; border-bottom-color: transparent; background-color: #F0F0F0; font-family: 'Source Code Pro';">read_tsv()</td>
      <td class="gt_row gt_center" style="border-bottom-width: 2px; border-bottom-style: solid; border-bottom-color: transparent; background-color: #F0F0F0;">tab separated files</td>
    </tr>
  </tbody>
  
  
</table></div>
]

---
# Example data: `nimbus`

```
#> date,longitude,latitude,ozone
#> 1985-10-01T00:00:00Z,-179.375,-73.5,302
#> 1985-10-01T00:00:00Z,-178.125,-73.5,302
#> 1985-10-01T00:00:00Z,-176.875,-73.5,302
#> 1985-10-01T00:00:00Z,-175.625,-73.5,302
#> 1985-10-01T00:00:00Z,-174.375,-73.5,304
#> 1985-10-01T00:00:00Z,-173.125,-73.5,304
#> 1985-10-01T00:00:00Z,-171.875,-73.5,304
#> 1985-10-01T00:00:00Z,-170.625,-73.5,304
#> 1985-10-01T00:00:00Z,-164.375,-73.5,287
```

---
# `read_csv()`

**`readr`** functions share a common syntax.

---
# `read_csv()`

**`readr`** functions share a common syntax.

???

object to save data to

---
# `read_csv()`

**`readr`** functions share a common syntax.

---
# `read_csv()`

**`readr`** functions share a common syntax.

???

build file path with `here()`

---
class: your-turn

# Your turn 2

.big[
* Find **`nimbus.csv`** in your project directory

* Read it into an object

* View the results
]

---
class: your-turn

.smallish[

```r
nimbus <- read_csv(here("materials", "data", "nimbus.csv"))
#> 
#> ── Column specification ────────────────────────────────────────────────────────
#> cols(
#>   date = col_datetime(format = ""),
#>   longitude = col_double(),
#>   latitude = col_double(),
#>   ozone = col_character()
#> )
nimbus
#> # A tibble: 18,963 x 4
#>    date                longitude latitude ozone
#>    <dttm>                  <dbl>    <dbl> <chr>
#>  1 1985-10-01 00:00:00     -179.    -73.5 302  
#>  2 1985-10-01 00:00:00     -178.    -73.5 302  
#>  3 1985-10-01 00:00:00     -177.    -73.5 302  
#>  4 1985-10-01 00:00:00     -176.    -73.5 302  
#>  5 1985-10-01 00:00:00     -174.    -73.5 304  
#>  6 1985-10-01 00:00:00     -173.    -73.5 304  
#>  7 1985-10-01 00:00:00     -172.    -73.5 304  
#>  8 1985-10-01 00:00:00     -171.    -73.5 304  
#>  9 1985-10-01 00:00:00     -164.    -73.5 287  
#> 10 1985-10-01 00:00:00     -163.    -73.5 287  
#> # … with 18,953 more rows
```
]

---
name: tibble
class: center middle

# tibbles

---
<div class="hex-book">
  <a href="https://tibble.tidyverse.org">
    <img class="hex" src="images/hex/tibble.png">
  </a>
  <a href="https://r4ds.had.co.nz/tibbles.html">
    <img class="book" src="images/books/r4ds-tibbles.png">
  </a>
</div>

---
# `read.csv()` vs. `read_csv()`

.pull-left.small[

```
#>                                            
#> 18939 1985-10-01T00:00:00Z 139.375 -0.5 270
#> 18940 1985-10-01T00:00:00Z 140.625 -0.5 275
#> 18941 1985-10-01T00:00:00Z 141.875 -0.5 270
#> 18942 1985-10-01T00:00:00Z 143.125 -0.5 266
#> 18943 1985-10-01T00:00:00Z 144.375 -0.5 267
#> 18944 1985-10-01T00:00:00Z 145.625 -0.5 263
#> 18945 1985-10-01T00:00:00Z 146.875 -0.5 261
#> 18946 1985-10-01T00:00:00Z 148.125 -0.5 262
#> 18947 1985-10-01T00:00:00Z 154.375 -0.5 271
#> 18948 1985-10-01T00:00:00Z 155.625 -0.5 272
#> 18949 1985-10-01T00:00:00Z 156.875 -0.5 268
#> 18950 1985-10-01T00:00:00Z 158.125 -0.5 276
#> 18951 1985-10-01T00:00:00Z 159.375 -0.5 273
#> 18952 1985-10-01T00:00:00Z 160.625 -0.5 272
#> 18953 1985-10-01T00:00:00Z 161.875 -0.5 271
#> 18954 1985-10-01T00:00:00Z 163.125 -0.5 272
#> 18955 1985-10-01T00:00:00Z 164.375 -0.5 275
#> 18956 1985-10-01T00:00:00Z 165.625 -0.5 271
#> 18957 1985-10-01T00:00:00Z 166.875 -0.5 271
#> 18958 1985-10-01T00:00:00Z 168.125 -0.5 273
#> 18959 1985-10-01T00:00:00Z 169.375 -0.5 273
#> 18960 1985-10-01T00:00:00Z 170.625 -0.5 271
#> 18961 1985-10-01T00:00:00Z 171.875 -0.5 270
#> 18962 1985-10-01T00:00:00Z 173.125 -0.5 268
#> 18963 1985-10-01T00:00:00Z 174.375 -0.5 265
```
]

.pull-right.small[

```
#> # A tibble: 18,963 x 4
#>    date                longitude latitude ozone
#>    <dttm>                  <dbl>    <dbl> <chr>
#>  1 1985-10-01 00:00:00     -179.    -73.5 302  
#>  2 1985-10-01 00:00:00     -178.    -73.5 302  
#>  3 1985-10-01 00:00:00     -177.    -73.5 302  
#>  4 1985-10-01 00:00:00     -176.    -73.5 302  
#>  5 1985-10-01 00:00:00     -174.    -73.5 304  
#>  6 1985-10-01 00:00:00     -173.    -73.5 304  
#>  7 1985-10-01 00:00:00     -172.    -73.5 304  
#>  8 1985-10-01 00:00:00     -171.    -73.5 304  
#>  9 1985-10-01 00:00:00     -164.    -73.5 287  
#> 10 1985-10-01 00:00:00     -163.    -73.5 287  
#> # … with 18,953 more rows
```
]

---
background-image: url(images/import/df-display.png)
background-position: center middle
background-size: 65%

---
background-image: url(images/import/tib-display.png)
background-position: center middle
background-size: 65%

---
background-image: url(images/import/cheatsheet-tibble.png)
background-position: center middle
background-size: 70%

---
name: parsing
class: center middle

# parsing

---
class: pop-quiz

# Consider

.big[
* Look at the **`nimbus`** data.

* What class (data type) is **`ozone`**?
]

```r
nimbus %>%
  pull(ozone) %>%
  class()
```

---
class: pop-quiz

```r
nimbus %>%
  pull(ozone) %>%
  class()
#> [1] "character"

nimbus %>%
  pull(ozone) %>%
  unique()
#>   [1] "302" "304" "287" "274" "264" "242" "211" "195" "197" "196" "198" "193"
#>  [13] "187" "190" "199" "194" "213" "218" "221" "229" "209" "186" "188" "191"
#>  [25] "189" "184" "180" "."   "215" "312" "319" "320" "311" "300" "290" "267"
#>  [37] "226" "210" "200" "203" "201" "192" "204" "206" "208" "205" "223" "232"
#>  [49] "238" "243" "220" "202" "185" "219" "222" "216" "324" "336" "333" "323"
#>  [61] "308" "295" "244" "212" "237" "248" "239" "241" "250" "249" "252" "234"
#>  [73] "318" "313" "326" "335" "337" "316" "266" "207" "227" "251" "253" "257"
#>  [85] "261" "214" "228" "273" "285" "288" "291" "270" "254" "317" "325" "332"
#>  [97] "340" "344" "338" "297" "247" "217" "225" "231" "235" "236" "262" "260"
#> [109] "265" "272" "278" "280" "279" "255" "245" "224" "181" "240" "269" "296"
#> [121] "307" "315" "321" "306" "299" "298" "283" "327" "322" "328" "331" "310"
#> [133] "275" "233" "258" "276" "281" "289" "330" "346" "305" "334" "359" "347"
#> [145] "314" "301" "256" "263" "277" "284"
#>  [ reached getOption("max.print") -- omitted 82 entries ]
```

---
# `NA` values

```r
nimbus %>%
  filter(ozone == ".")
#> # A tibble: 155 x 4
#>    date                longitude latitude ozone
#>    <dttm>                  <dbl>    <dbl> <chr>
#>  1 1985-10-01 00:00:00      70.6    -73.5 .    
#>  2 1985-10-01 00:00:00      71.9    -73.5 .    
#>  3 1985-10-01 00:00:00      73.1    -73.5 .    
#>  4 1985-10-01 00:00:00      74.4    -73.5 .    
#>  5 1985-10-01 00:00:00      75.6    -73.5 .    
#>  6 1985-10-01 00:00:00      76.9    -73.5 .    
#>  7 1985-10-01 00:00:00      78.1    -73.5 .    
#>  8 1985-10-01 00:00:00      79.4    -73.5 .    
#>  9 1985-10-01 00:00:00      65.6    -72.5 .    
#> 10 1985-10-01 00:00:00      66.9    -72.5 .    
#> # … with 145 more rows
```

---
# Define missing values

---
class: your-turn

# Your turn 3

.big[
* Read in **`nimbus.csv`** again.

* Set values of **`"."`** to **`NA`**.
]

---
class: your-turn

.panelset[
.panel[.panel-name[Original]
.smallish[

```r
read_csv(here("materials", "data", "nimbus.csv"))
#> 
#> ── Column specification ────────────────────────────────────────────────────────
#> cols(
#>   date = col_datetime(format = ""),
#>   longitude = col_double(),
#>   latitude = col_double(),
#>   ozone = col_character()
#> )
#> # A tibble: 18,963 x 4
#>    date                longitude latitude ozone
#>    <dttm>                  <dbl>    <dbl> <chr>
#>  1 1985-10-01 00:00:00     -179.    -73.5 302  
#>  2 1985-10-01 00:00:00     -178.    -73.5 302  
#>  3 1985-10-01 00:00:00     -177.    -73.5 302  
#>  4 1985-10-01 00:00:00     -176.    -73.5 302  
#>  5 1985-10-01 00:00:00     -174.    -73.5 304  
#>  6 1985-10-01 00:00:00     -173.    -73.5 304  
#>  7 1985-10-01 00:00:00     -172.    -73.5 304  
#>  8 1985-10-01 00:00:00     -171.    -73.5 304  
#>  9 1985-10-01 00:00:00     -164.    -73.5 287  
#> 10 1985-10-01 00:00:00     -163.    -73.5 287  
#> # … with 18,953 more rows
```
]
]

.panel[.panel-name[Solution]
.smallish[

```r
read_csv(here("materials", "data", "nimbus.csv"), na = ".")
#> 
#> ── Column specification ────────────────────────────────────────────────────────
#> cols(
#>   date = col_datetime(format = ""),
#>   longitude = col_double(),
#>   latitude = col_double(),
#>   ozone = col_double()
#> )
#> # A tibble: 18,963 x 4
#>    date                longitude latitude ozone
#>    <dttm>                  <dbl>    <dbl> <dbl>
#>  1 1985-10-01 00:00:00     -179.    -73.5   302
#>  2 1985-10-01 00:00:00     -178.    -73.5   302
#>  3 1985-10-01 00:00:00     -177.    -73.5   302
#>  4 1985-10-01 00:00:00     -176.    -73.5   302
#>  5 1985-10-01 00:00:00     -174.    -73.5   304
#>  6 1985-10-01 00:00:00     -173.    -73.5   304
#>  7 1985-10-01 00:00:00     -172.    -73.5   304
#>  8 1985-10-01 00:00:00     -171.    -73.5   304
#>  9 1985-10-01 00:00:00     -164.    -73.5   287
#> 10 1985-10-01 00:00:00     -163.    -73.5   287
#> # … with 18,953 more rows
```
]
]
]

---
# Specify column types

<code class ='r hljs remark-code'>dat <- read_csv(here("path", "to", "file.csv"), na = ".",<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span style="background-color:#FED766;color:#009FB7">col_types = cols(var_1 = col_number())</span>)</code>

---
# Column types

#hqnllhopzl .gt_table {
  display: table;
  border-collapse: collapse;
  margin-left: auto;
  margin-right: auto;
  color: #333333;
  font-size: 16px;
  font-weight: normal;
  font-style: normal;
  background-color: #F0F0F0;
  width: auto;
  border-top-style: solid;
  border-top-width: 1px;
  border-top-color: #A8A8A8;
  border-right-style: none;
  border-right-width: 2px;
  border-right-color: #D3D3D3;
  border-bottom-style: solid;
  border-bottom-width: 1px;
  border-bottom-color: #A8A8A8;
  border-left-style: none;
  border-left-width: 2px;
  border-left-color: #D3D3D3;
}

#hqnllhopzl .gt_heading {
  background-color: #F0F0F0;
  text-align: left;
  border-bottom-color: #F0F0F0;
  border-left-style: none;
  border-left-width: 1px;
  border-left-color: #D3D3D3;
  border-right-style: none;
  border-right-width: 1px;
  border-right-color: #D3D3D3;
}

#hqnllhopzl .gt_title {
  color: #333333;
  font-size: 125%;
  font-weight: initial;
  padding-top: 4px;
  padding-bottom: 4px;
  border-bottom-color: #F0F0F0;
  border-bottom-width: 0;
}

#hqnllhopzl .gt_subtitle {
  color: #333333;
  font-size: 85%;
  font-weight: initial;
  padding-top: 0;
  padding-bottom: 4px;
  border-top-color: #F0F0F0;
  border-top-width: 0;
}

#hqnllhopzl .gt_bottom_border {
  border-bottom-style: solid;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
}

#hqnllhopzl .gt_col_headings {
  border-top-style: solid;
  border-top-width: 3px;
  border-top-color: #F0F0F0;
  border-bottom-style: solid;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
  border-left-style: none;
  border-left-width: 1px;
  border-left-color: #D3D3D3;
  border-right-style: none;
  border-right-width: 1px;
  border-right-color: #D3D3D3;
}

#hqnllhopzl .gt_col_heading {
  color: #333333;
  background-color: #F0F0F0;
  font-size: 80%;
  font-weight: bolder;
  text-transform: uppercase;
  border-left-style: none;
  border-left-width: 1px;
  border-left-color: #D3D3D3;
  border-right-style: none;
  border-right-width: 1px;
  border-right-color: #D3D3D3;
  vertical-align: bottom;
  padding-top: 5px;
  padding-bottom: 6px;
  padding-left: 5px;
  padding-right: 5px;
  overflow-x: hidden;
}

#hqnllhopzl .gt_column_spanner_outer {
  color: #333333;
  background-color: #F0F0F0;
  font-size: 80%;
  font-weight: bolder;
  text-transform: uppercase;
  padding-top: 0;
  padding-bottom: 0;
  padding-left: 4px;
  padding-right: 4px;
}

#hqnllhopzl .gt_column_spanner_outer:first-child {
  padding-left: 0;
}

#hqnllhopzl .gt_column_spanner_outer:last-child {
  padding-right: 0;
}

#hqnllhopzl .gt_column_spanner {
  border-bottom-style: solid;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
  vertical-align: bottom;
  padding-top: 5px;
  padding-bottom: 6px;
  overflow-x: hidden;
  display: inline-block;
  width: 100%;
}

#hqnllhopzl .gt_group_heading {
  padding: 8px;
  color: #333333;
  background-color: #F0F0F0;
  font-size: 80%;
  font-weight: bolder;
  text-transform: uppercase;
  border-top-style: solid;
  border-top-width: 2px;
  border-top-color: #D3D3D3;
  border-bottom-style: solid;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
  border-left-style: none;
  border-left-width: 1px;
  border-left-color: #D3D3D3;
  border-right-style: none;
  border-right-width: 1px;
  border-right-color: #D3D3D3;
  vertical-align: middle;
}

#hqnllhopzl .gt_empty_group_heading {
  padding: 0.5px;
  color: #333333;
  background-color: #F0F0F0;
  font-size: 80%;
  font-weight: bolder;
  border-top-style: solid;
  border-top-width: 2px;
  border-top-color: #D3D3D3;
  border-bottom-style: solid;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
  vertical-align: middle;
}

#hqnllhopzl .gt_from_md > :first-child {
  margin-top: 0;
}

#hqnllhopzl .gt_from_md > :last-child {
  margin-bottom: 0;
}

#hqnllhopzl .gt_row {
  padding-top: 3px;
  padding-bottom: 3px;
  padding-left: 5px;
  padding-right: 5px;
  margin: 10px;
  border-top-style: solid;
  border-top-width: 1px;
  border-top-color: #D3D3D3;
  border-left-style: none;
  border-left-width: 1px;
  border-left-color: #D3D3D3;
  border-right-style: none;
  border-right-width: 1px;
  border-right-color: #D3D3D3;
  vertical-align: middle;
  overflow-x: hidden;
}

#hqnllhopzl .gt_stub {
  color: #333333;
  background-color: #F0F0F0;
  font-size: 80%;
  font-weight: bolder;
  text-transform: uppercase;
  border-right-style: solid;
  border-right-width: 2px;
  border-right-color: #D3D3D3;
  padding-left: 12px;
}

#hqnllhopzl .gt_summary_row {
  color: #333333;
  background-color: #F0F0F0;
  text-transform: inherit;
  padding-top: 8px;
  padding-bottom: 8px;
  padding-left: 5px;
  padding-right: 5px;
}

#hqnllhopzl .gt_first_summary_row {
  padding-top: 8px;
  padding-bottom: 8px;
  padding-left: 5px;
  padding-right: 5px;
  border-top-style: solid;
  border-top-width: 2px;
  border-top-color: #D3D3D3;
}

#hqnllhopzl .gt_grand_summary_row {
  color: #333333;
  background-color: #F0F0F0;
  text-transform: inherit;
  padding-top: 8px;
  padding-bottom: 8px;
  padding-left: 5px;
  padding-right: 5px;
}

#hqnllhopzl .gt_first_grand_summary_row {
  padding-top: 8px;
  padding-bottom: 8px;
  padding-left: 5px;
  padding-right: 5px;
  border-top-style: double;
  border-top-width: 6px;
  border-top-color: #D3D3D3;
}

#hqnllhopzl .gt_striped {
  background-color: rgba(128, 128, 128, 0.05);
}

#hqnllhopzl .gt_table_body {
  border-top-style: solid;
  border-top-width: 2px;
  border-top-color: #D3D3D3;
  border-bottom-style: solid;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
}

#hqnllhopzl .gt_footnotes {
  color: #333333;
  background-color: #F0F0F0;
  border-bottom-style: none;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
  border-left-style: none;
  border-left-width: 2px;
  border-left-color: #D3D3D3;
  border-right-style: none;
  border-right-width: 2px;
  border-right-color: #D3D3D3;
}

#hqnllhopzl .gt_footnote {
  margin: 0px;
  font-size: 90%;
  padding: 4px;
}

#hqnllhopzl .gt_sourcenotes {
  color: #333333;
  background-color: #F0F0F0;
  border-bottom-style: none;
  border-bottom-width: 2px;
  border-bottom-color: #D3D3D3;
  border-left-style: none;
  border-left-width: 0px;
  border-left-color: #D3D3D3;
  border-right-style: none;
  border-right-width: 0px;
  border-right-color: #D3D3D3;
}

#hqnllhopzl .gt_sourcenote {
  font-size: 12px;
  padding: 10px;
}

#hqnllhopzl .gt_left {
  text-align: left;
}

#hqnllhopzl .gt_center {
  text-align: center;
}

#hqnllhopzl .gt_right {
  text-align: right;
  font-variant-numeric: tabular-nums;
}

#hqnllhopzl .gt_font_normal {
  font-weight: normal;
}

#hqnllhopzl .gt_font_bold {
  font-weight: bold;
}

#hqnllhopzl .gt_font_italic {
  font-style: italic;
}

#hqnllhopzl .gt_super {
  font-size: 65%;
}

#hqnllhopzl .gt_footnote_marks {
  font-style: italic;
  font-size: 65%;
}
</style>
<div id="hqnllhopzl" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="gt_table" style="table-layout: fixed;; width: 0px">
  <colgroup>
    <col style="width:220px;"/>
    <col style="width:500px;"/>
  </colgroup>
  
  <thead class="gt_col_headings">
    <tr>
      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1" style="text-align: center; vertical-align: middle; font-weight: bold; border-bottom-width: 3px; border-bottom-style: solid; border-bottom-color: black;">function</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1" style="text-align: center; vertical-align: middle; font-weight: bold; border-bottom-width: 3px; border-bottom-style: solid; border-bottom-color: black;">data type</th>
    </tr>
  </thead>
  <tbody class="gt_table_body">
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_character()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">characters</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_date()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">dates</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_datetime()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">POSIXct (date-time)</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_double()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">double (decimal number)</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_factor()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">factors</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_guess()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">let readr guess (default)</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_integer()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">integers</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_logical()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">logicals</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_number()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">numbers mixed with non-number characters</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_numeric()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">double or integer</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="background-color: #F0F0F0; font-family: 'Source Code Pro';">col_skip()</td>
      <td class="gt_row gt_center" style="background-color: #F0F0F0;">do not read</td>
    </tr>
    <tr>
      <td class="gt_row gt_center" style="border-bottom-width: 2px; border-bottom-style: solid; border-bottom-color: transparent; background-color: #F0F0F0; font-family: 'Source Code Pro';">col_time()</td>
      <td class="gt_row gt_center" style="border-bottom-width: 2px; border-bottom-style: solid; border-bottom-color: transparent; background-color: #F0F0F0;">time</td>
    </tr>
  </tbody>
  
  
</table></div>

---
class: your-turn

# Your turn 4

.big[
* Read in **`nimbus.csv`** again.

* Set values of **`"."`** to **`NA`**.

* Specify **`ozone`** as integer values.
]

---
class: your-turn

.panelset[
.panel[.panel-name[Solution]

```r
read_csv(here("materials", "data", "nimbus.csv"), na = ".",
         col_types = cols(ozone = col_integer()))
#> # A tibble: 18,963 x 4
#>    date                longitude latitude ozone
#>    <dttm>                  <dbl>    <dbl> <int>
#>  1 1985-10-01 00:00:00     -179.    -73.5   302
#>  2 1985-10-01 00:00:00     -178.    -73.5   302
#>  3 1985-10-01 00:00:00     -177.    -73.5   302
#>  4 1985-10-01 00:00:00     -176.    -73.5   302
#>  5 1985-10-01 00:00:00     -174.    -73.5   304
#>  6 1985-10-01 00:00:00     -173.    -73.5   304
#>  7 1985-10-01 00:00:00     -172.    -73.5   304
#>  8 1985-10-01 00:00:00     -171.    -73.5   304
#>  9 1985-10-01 00:00:00     -164.    -73.5   287
#> 10 1985-10-01 00:00:00     -163.    -73.5   287
#> # … with 18,953 more rows
```

]

.panel[.panel-name[Bonus Map]

```r
library(rnaturalearth)
library(sf)

world <- ne_countries(scale = "medium", returnclass = "sf")

ortho <- "+proj=ortho +lat_0=-78 +lon_0=166 +x_0=0 +y_0=0 +a=6371000 +b=6371000 +units=m +no_defs"

ggplot(data = nimbus) +
  geom_point(mapping = aes(x = longitude, y = latitude, color = ozone)) +
  geom_sf(data = world, fill = NA, color = "black") +
  scale_color_viridis_c(option = "viridis") +
  coord_sf(crs = ortho)
```
]

.panel[.panel-name[Map]
<img src="images/import/plots/bonus-map-1.png" width="80%" style="display: block; margin: auto;" />
]
]

---
name: misc
class: center middle

# other data files

---
class: center middle

.large-left-multi[
# Excel files (`.xls` and `.xlsx`)
]

.small-right[
<img src="images/hex/readxl.png" width="100%" style="display: block; margin: auto;" />
]

---
class: center middle

.large-left-multi[
# Data from other statistical software (SPSS, Stata, and SAS)
]

.small-right[
<img src="images/hex/haven.png" width="100%" style="display: block; margin: auto;" />
]

---
class: center middle

.large-left-multi[
# Google Sheets and other files from Google Drive
]

.small-right[
<img src="images/import/google.png" width="100%" style="display: block; margin: auto;" />
]

---
class: center middle

.large-left-multi[
# Efficient data sharing between R and Python
]

.small-right[
<img src="images/hex/feather.png" width="100%" style="display: block; margin: auto;" />
]

---
class: center middle

.large-left-multi[
# Web pages (web scraping)
]

.small-right[
<img src="images/hex/rvest.png" width="100%" style="display: block; margin: auto;" />
]

---
background-image: url(images/import/other-pkgs.png)
background-position: center middle
background-size: 50%

???

jsonlite -> json
xml2 -> xml
httr -> web APIs
DBI -> databases

---
class: title-slide, center

# Import Data

## Tidy Data Science with the Tidyverse and Tidymodels

### W. Jake Thompson

#### [https://tidyds-2021.wjakethompson.com](https://tidyds-2021.wjakethompson.com) &#183; [https://bit.ly/tidyds-2021](https://bit.ly/tidyds-2021)

.footer-license[*Tidy Data Science with the Tidyverse and Tidymodels* is licensed under a [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).]