featurette

class: inverse, left, bottom
background-image: url(https://images.unsplash.com/photo-1542204165-65bf26472b9b?auto=format&fit=crop&q=80&w=1548&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D)
background-size: cover
# .Large[# My featurette]
## .small[featuring [{}]() ...]
#### .tiny[Gina Reynolds | 2023-10-25 |Image credit: Denise Jans, Upsplash]
???
Title

---

```r
library(tidyverse)
library(ggcirclepack)

# tidytuesday data
rladies_chapters_raw <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2023/2023-11-21/rladies_chapters.csv') %>% 
  mutate(chapter = str_remove(chapter, "rladies-") %>% 
           str_replace_all("-", " ") %>% str_to_title() %>% str_remove("\\s+$")) 
```

---

count: false

.panel1-feature-auto[

```r
*rladies_chapters_raw
```
]
 
.panel2-feature-auto[

```
## # A tibble: 4,268 × 6
##           id chapter   title                           date       location  year
##        <dbl> <chr>     <chr>                           <date>     <chr>    <dbl>
##  1 296275584 St Louis  "Save the date! Introduction t… 2023-11-30 online    2023
##  2 296277517 Coventry  "An basic introduction: Python… 2023-11-30 online    2023
##  3 295898711 Baltimore "Holiday graphics and animatio… 2023-11-28 inperson  2023
##  4 296346610 Philly    "TidyTuesday with R-Ladies Phi… 2023-11-14 online    2023
##  5 296275461 St Louis  "Save the date! Introduction t… 2023-11-08 online    2023
##  6 296424871 Kathmandu "4 days workshop"               2023-11-01 inperson  2023
##  7 296239571 Taipei    "旅遊服務銜接 AIGC 的各種坑"    2023-10-30 inperson  2023
##  8 296559481 Montreal  "RLadies October Meetup - \"R-… 2023-10-30 inperson  2023
##  9 296677321 Abuja     "R-Ladies Abuja and Abuja R us… 2023-10-28 inperson  2023
## 10 296720878 Sao Paulo "Meetup R-Ladies São Paulo - I… 2023-10-28 inperson  2023
## # ℹ 4,258 more rows
```
]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
* group_by(chapter)
```
]
 
.panel2-feature-auto[

```
## # A tibble: 4,268 × 6
## # Groups:   chapter [209]
##           id chapter   title                           date       location  year
##        <dbl> <chr>     <chr>                           <date>     <chr>    <dbl>
##  1 296275584 St Louis  "Save the date! Introduction t… 2023-11-30 online    2023
##  2 296277517 Coventry  "An basic introduction: Python… 2023-11-30 online    2023
##  3 295898711 Baltimore "Holiday graphics and animatio… 2023-11-28 inperson  2023
##  4 296346610 Philly    "TidyTuesday with R-Ladies Phi… 2023-11-14 online    2023
##  5 296275461 St Louis  "Save the date! Introduction t… 2023-11-08 online    2023
##  6 296424871 Kathmandu "4 days workshop"               2023-11-01 inperson  2023
##  7 296239571 Taipei    "旅遊服務銜接 AIGC 的各種坑"    2023-10-30 inperson  2023
##  8 296559481 Montreal  "RLadies October Meetup - \"R-… 2023-10-30 inperson  2023
##  9 296677321 Abuja     "R-Ladies Abuja and Abuja R us… 2023-10-28 inperson  2023
## 10 296720878 Sao Paulo "Meetup R-Ladies São Paulo - I… 2023-10-28 inperson  2023
## # ℹ 4,258 more rows
```
]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
* summarise(first_date = as.Date(min(date)),
*           last_date = as.Date(max(date)),
*           tot_meetings = n())
```
]
 
.panel2-feature-auto[

```
## # A tibble: 209 × 4
##    chapter        first_date last_date  tot_meetings
##    <chr>          <date>     <date>            <int>
##  1 Aarhus         2021-06-16 2021-06-16            1
##  2 Abuja          2020-03-21 2023-10-28           17
##  3 Addis Ababa    2018-03-28 2021-03-09           26
##  4 Adelaide       2017-03-08 2019-10-03            9
##  5 Aguascalientes 2020-08-13 2020-11-24            5
##  6 Algiers        2020-06-13 2020-11-24            3
##  7 Ames           2016-12-15 2021-07-07           86
##  8 Amsterdam      2018-04-12 2021-09-28           31
##  9 Ankara         2019-10-12 2021-03-23           16
## 10 Asuncion       2020-07-11 2020-07-11            1
## # ℹ 199 more rows
```
]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
  summarise(first_date = as.Date(min(date)),
            last_date = as.Date(max(date)),
            tot_meetings = n()) %>%
* arrange(first_date)
```
]
 
.panel2-feature-auto[

```
## # A tibble: 209 × 4
##    chapter       first_date last_date  tot_meetings
##    <chr>         <date>     <date>            <int>
##  1 San Francisco 2012-10-31 2021-09-09           64
##  2 Tc            2015-04-26 2023-03-02           52
##  3 London        2016-03-04 2022-10-26           61
##  4 Rtp           2016-09-22 2023-08-22           74
##  5 Istanbul      2016-10-01 2021-03-08           36
##  6 Paris         2016-10-05 2023-10-19           25
##  7 Boston        2016-10-13 2021-07-29           44
##  8 La            2016-10-15 2020-07-29           32
##  9 Melbourne     2016-10-18 2022-11-30           81
## 10 Madrid        2016-10-24 2022-04-05           51
## # ℹ 199 more rows
```
]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
  summarise(first_date = as.Date(min(date)),
            last_date = as.Date(max(date)),
            tot_meetings = n()) %>%
  arrange(first_date) %>%
* mutate(chapter = fct_inorder(chapter))
```
]
 
.panel2-feature-auto[

```
## # A tibble: 209 × 4
##    chapter       first_date last_date  tot_meetings
##    <fct>         <date>     <date>            <int>
##  1 San Francisco 2012-10-31 2021-09-09           64
##  2 Tc            2015-04-26 2023-03-02           52
##  3 London        2016-03-04 2022-10-26           61
##  4 Rtp           2016-09-22 2023-08-22           74
##  5 Istanbul      2016-10-01 2021-03-08           36
##  6 Paris         2016-10-05 2023-10-19           25
##  7 Boston        2016-10-13 2021-07-29           44
##  8 La            2016-10-15 2020-07-29           32
##  9 Melbourne     2016-10-18 2022-11-30           81
## 10 Madrid        2016-10-24 2022-04-05           51
## # ℹ 199 more rows
```
]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
  summarise(first_date = as.Date(min(date)),
            last_date = as.Date(max(date)),
            tot_meetings = n()) %>%
  arrange(first_date) %>%
  mutate(chapter = fct_inorder(chapter)) ->
*rladies_chapter_df
```
]
 
.panel2-feature-auto[

]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
  summarise(first_date = as.Date(min(date)),
            last_date = as.Date(max(date)),
            tot_meetings = n()) %>%
  arrange(first_date) %>%
  mutate(chapter = fct_inorder(chapter)) ->
rladies_chapter_df

*rladies_chapters_raw
```
]
 
.panel2-feature-auto[

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
  summarise(first_date = as.Date(min(date)),
            last_date = as.Date(max(date)),
            tot_meetings = n()) %>%
  arrange(first_date) %>%
  mutate(chapter = fct_inorder(chapter)) ->
rladies_chapter_df

rladies_chapters_raw %>%
* mutate(chapter =
*          factor(chapter,
*                    levels =
*                   levels(rladies_chapter_df$chapter)))
```
]
 
.panel2-feature-auto[

```
## # A tibble: 4,268 × 6
##           id chapter   title                           date       location  year
##        <dbl> <fct>     <chr>                           <date>     <chr>    <dbl>
##  1 296275584 St Louis  "Save the date! Introduction t… 2023-11-30 online    2023
##  2 296277517 Coventry  "An basic introduction: Python… 2023-11-30 online    2023
##  3 295898711 Baltimore "Holiday graphics and animatio… 2023-11-28 inperson  2023
##  4 296346610 Philly    "TidyTuesday with R-Ladies Phi… 2023-11-14 online    2023
##  5 296275461 St Louis  "Save the date! Introduction t… 2023-11-08 online    2023
##  6 296424871 Kathmandu "4 days workshop"               2023-11-01 inperson  2023
##  7 296239571 Taipei    "旅遊服務銜接 AIGC 的各種坑"    2023-10-30 inperson  2023
##  8 296559481 Montreal  "RLadies October Meetup - \"R-… 2023-10-30 inperson  2023
##  9 296677321 Abuja     "R-Ladies Abuja and Abuja R us… 2023-10-28 inperson  2023
## 10 296720878 Sao Paulo "Meetup R-Ladies São Paulo - I… 2023-10-28 inperson  2023
## # ℹ 4,258 more rows
```
]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
  summarise(first_date = as.Date(min(date)),
            last_date = as.Date(max(date)),
            tot_meetings = n()) %>%
  arrange(first_date) %>%
  mutate(chapter = fct_inorder(chapter)) ->
rladies_chapter_df

rladies_chapters_raw %>%
  mutate(chapter =
           factor(chapter,
                     levels =
                    levels(rladies_chapter_df$chapter))) %>%
* group_by(chapter)
```
]
 
.panel2-feature-auto[

```
## # A tibble: 4,268 × 6
## # Groups:   chapter [209]
##           id chapter   title                           date       location  year
##        <dbl> <fct>     <chr>                           <date>     <chr>    <dbl>
##  1 296275584 St Louis  "Save the date! Introduction t… 2023-11-30 online    2023
##  2 296277517 Coventry  "An basic introduction: Python… 2023-11-30 online    2023
##  3 295898711 Baltimore "Holiday graphics and animatio… 2023-11-28 inperson  2023
##  4 296346610 Philly    "TidyTuesday with R-Ladies Phi… 2023-11-14 online    2023
##  5 296275461 St Louis  "Save the date! Introduction t… 2023-11-08 online    2023
##  6 296424871 Kathmandu "4 days workshop"               2023-11-01 inperson  2023
##  7 296239571 Taipei    "旅遊服務銜接 AIGC 的各種坑"    2023-10-30 inperson  2023
##  8 296559481 Montreal  "RLadies October Meetup - \"R-… 2023-10-30 inperson  2023
##  9 296677321 Abuja     "R-Ladies Abuja and Abuja R us… 2023-10-28 inperson  2023
## 10 296720878 Sao Paulo "Meetup R-Ladies São Paulo - I… 2023-10-28 inperson  2023
## # ℹ 4,258 more rows
```
]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
  summarise(first_date = as.Date(min(date)),
            last_date = as.Date(max(date)),
            tot_meetings = n()) %>%
  arrange(first_date) %>%
  mutate(chapter = fct_inorder(chapter)) ->
rladies_chapter_df

rladies_chapters_raw %>%
  mutate(chapter =
           factor(chapter,
                     levels =
                    levels(rladies_chapter_df$chapter))) %>%
  group_by(chapter) %>%
* mutate(meeting_number = rank(date))
```
]
 
.panel2-feature-auto[

```
## # A tibble: 4,268 × 7
## # Groups:   chapter [209]
##           id chapter   title            date       location  year meeting_number
##        <dbl> <fct>     <chr>            <date>     <chr>    <dbl>          <dbl>
##  1 296275584 St Louis  "Save the date!… 2023-11-30 online    2023             41
##  2 296277517 Coventry  "An basic intro… 2023-11-30 online    2023             15
##  3 295898711 Baltimore "Holiday graphi… 2023-11-28 inperson  2023             34
##  4 296346610 Philly    "TidyTuesday wi… 2023-11-14 online    2023             83
##  5 296275461 St Louis  "Save the date!… 2023-11-08 online    2023             40
##  6 296424871 Kathmandu "4 days worksho… 2023-11-01 inperson  2023              6
##  7 296239571 Taipei    "旅遊服務銜接 A… 2023-10-30 inperson  2023             65
##  8 296559481 Montreal  "RLadies Octobe… 2023-10-30 inperson  2023             88
##  9 296677321 Abuja     "R-Ladies Abuja… 2023-10-28 inperson  2023             17
## 10 296720878 Sao Paulo "Meetup R-Ladie… 2023-10-28 inperson  2023             26
## # ℹ 4,258 more rows
```
]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
  summarise(first_date = as.Date(min(date)),
            last_date = as.Date(max(date)),
            tot_meetings = n()) %>%
  arrange(first_date) %>%
  mutate(chapter = fct_inorder(chapter)) ->
rladies_chapter_df

rladies_chapters_raw %>%
  mutate(chapter =
           factor(chapter,
                     levels =
                    levels(rladies_chapter_df$chapter))) %>%
  group_by(chapter) %>%
  mutate(meeting_number = rank(date)) ->
*meetings_df
```
]
 
.panel2-feature-auto[

]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
  summarise(first_date = as.Date(min(date)),
            last_date = as.Date(max(date)),
            tot_meetings = n()) %>%
  arrange(first_date) %>%
  mutate(chapter = fct_inorder(chapter)) ->
rladies_chapter_df

*make_ordinal <- function(x){

* ifelse(x == 1, "1st",
*        ifelse(x == 2, "2nd",
*               ifelse(x == 3, "3rd", paste0(x,"th"))))

*} 
```
]
 
.panel2-feature-auto[

]

---
count: false

.panel1-feature-auto[

```r
rladies_chapters_raw %>%
  group_by(chapter) %>%
  summarise(first_date = as.Date(min(date)),
            last_date = as.Date(max(date)),
            tot_meetings = n()) %>%
  arrange(first_date) %>%
  mutate(chapter = fct_inorder(chapter)) ->
rladies_chapter_df

make_ordinal <- function(x){

ifelse(x == 1, "1st",
         ifelse(x == 2, "2nd",
                ifelse(x == 3, "3rd", paste0(x,"th"))))

}

# test
*make_ordinal(x = 1:10)
```
]
 
.panel2-feature-auto[

```
##  [1] "1st"  "2nd"  "3rd"  "4th"  "5th"  "6th"  "7th"  "8th"  "9th"  "10th"
```
]

---

count: false

.panel1-feature2-auto[

```r
*meetings_df
```
]
 
.panel2-feature2-auto[

---
count: false

.panel1-feature2-auto[

```r
meetings_df %>%
* ggplot()
```
]
 
.panel2-feature2-auto[
![](rladies-on-a-wire_files/figure-html/feature2_auto_02_output-1.png)
]

---
count: false

.panel1-feature2-auto[

```r
meetings_df %>%
  ggplot() +
* aes(y = as.numeric(chapter), x = date)
```
]
 
.panel2-feature2-auto[
![](rladies-on-a-wire_files/figure-html/feature2_auto_03_output-1.png)
]

---
count: false

.panel1-feature2-auto[

```r
meetings_df %>%
  ggplot() +
  aes(y = as.numeric(chapter), x = date) +
* geom_point(alpha = .6)
```
]
 
.panel2-feature2-auto[
![](rladies-on-a-wire_files/figure-html/feature2_auto_04_output-1.png)
]

---
count: false

.panel1-feature2-auto[

```r
meetings_df %>%
  ggplot() +
  aes(y = as.numeric(chapter), x = date) +
  geom_point(alpha = .6) +
* aes(color = meeting_number)
```
]
 
.panel2-feature2-auto[
![](rladies-on-a-wire_files/figure-html/feature2_auto_05_output-1.png)
]

---
count: false

.panel1-feature2-auto[

```r
meetings_df %>%
  ggplot() +
  aes(y = as.numeric(chapter), x = date) +
  geom_point(alpha = .6) +
  aes(color = meeting_number) +
* geom_text(data = rladies_chapter_df,
*           aes(x = first_date-days(120),
*               label = ifelse(chapter == "San Francisco",
*                              "San         \nFrancisco",
*                              as.character(chapter))),
*           color = "grey20",
*           hjust = 1,
*           size = 4.5,
*           lineheight = .7)
```
]
 
.panel2-feature2-auto[
![](rladies-on-a-wire_files/figure-html/feature2_auto_06_output-1.png)
]

---
count: false

.panel1-feature2-auto[

---
count: false

.panel1-feature2-auto[

```r
meetings_df %>%
  ggplot() +
  aes(y = as.numeric(chapter), x = date) +
  geom_point(alpha = .6) +
  aes(color = meeting_number) +
  geom_text(data = rladies_chapter_df,
            aes(x = first_date-days(120),
                label = ifelse(chapter == "San Francisco",
                               "San         \nFrancisco",
                               as.character(chapter))),
            color = "grey20",
            hjust = 1,
            size = 4.5,
            lineheight = .7) +
  geom_text(data = rladies_chapter_df,
            aes(x = last_date,
                label = make_ordinal(tot_meetings)),
            color = "grey20",
            hjust = -.3,
            size = 4.5) +
* theme(axis.text.y = element_blank())
```
]
 
.panel2-feature2-auto[
![](rladies-on-a-wire_files/figure-html/feature2_auto_08_output-1.png)
]

---
count: false

.panel1-feature2-auto[

```r
meetings_df %>%
  ggplot() +
  aes(y = as.numeric(chapter), x = date) +
  geom_point(alpha = .6) +
  aes(color = meeting_number) +
  geom_text(data = rladies_chapter_df,
            aes(x = first_date-days(120),
                label = ifelse(chapter == "San Francisco",
                               "San         \nFrancisco",
                               as.character(chapter))),
            color = "grey20",
            hjust = 1,
            size = 4.5,
            lineheight = .7) +
  geom_text(data = rladies_chapter_df,
            aes(x = last_date,
                label = make_ordinal(tot_meetings)),
            color = "grey20",
            hjust = -.3,
            size = 4.5) +
  theme(axis.text.y = element_blank()) +
* scale_color_viridis_c(option = "magma", breaks = c(1, 50, 100),
*                       labels = c("1st", "50th", "100th"))
```
]
 
.panel2-feature2-auto[
![](rladies-on-a-wire_files/figure-html/feature2_auto_09_output-1.png)
]

---
count: false

.panel1-feature2-auto[

```r
meetings_df %>%
  ggplot() +
  aes(y = as.numeric(chapter), x = date) +
  geom_point(alpha = .6) +
  aes(color = meeting_number) +
  geom_text(data = rladies_chapter_df,
            aes(x = first_date-days(120),
                label = ifelse(chapter == "San Francisco",
                               "San         \nFrancisco",
                               as.character(chapter))),
            color = "grey20",
            hjust = 1,
            size = 4.5,
            lineheight = .7) +
  geom_text(data = rladies_chapter_df,
            aes(x = last_date,
                label = make_ordinal(tot_meetings)),
            color = "grey20",
            hjust = -.3,
            size = 4.5) +
  theme(axis.text.y = element_blank()) +
  scale_color_viridis_c(option = "magma", breaks = c(1, 50, 100),
                        labels = c("1st", "50th", "100th")) +
* facet_wrap( ~ cut_interval(
*   as.numeric(chapter),
*   n = 4),
*   scales = "free_y",
*   ncol = 4)
```
]
 
.panel2-feature2-auto[
![](rladies-on-a-wire_files/figure-html/feature2_auto_10_output-1.png)
]

---
count: false

.panel1-feature2-auto[

```r
meetings_df %>%
  ggplot() +
  aes(y = as.numeric(chapter), x = date) +
  geom_point(alpha = .6) +
  aes(color = meeting_number) +
  geom_text(data = rladies_chapter_df,
            aes(x = first_date-days(120),
                label = ifelse(chapter == "San Francisco",
                               "San         \nFrancisco",
                               as.character(chapter))),
            color = "grey20",
            hjust = 1,
            size = 4.5,
            lineheight = .7) +
  geom_text(data = rladies_chapter_df,
            aes(x = last_date,
                label = make_ordinal(tot_meetings)),
            color = "grey20",
            hjust = -.3,
            size = 4.5) +
  theme(axis.text.y = element_blank()) +
  scale_color_viridis_c(option = "magma", breaks = c(1, 50, 100),
                        labels = c("1st", "50th", "100th")) +
  facet_wrap( ~ cut_interval(
    as.numeric(chapter),
    n = 4),
    scales = "free_y",
    ncol = 4) +
* labs(color = "Meeting\nnumber")
```
]
 
.panel2-feature2-auto[
![](rladies-on-a-wire_files/figure-html/feature2_auto_11_output-1.png)
]

---
count: false

.panel1-feature2-auto[

```r
meetings_df %>%
  ggplot() +
  aes(y = as.numeric(chapter), x = date) +
  geom_point(alpha = .6) +
  aes(color = meeting_number) +
  geom_text(data = rladies_chapter_df,
            aes(x = first_date-days(120),
                label = ifelse(chapter == "San Francisco",
                               "San         \nFrancisco",
                               as.character(chapter))),
            color = "grey20",
            hjust = 1,
            size = 4.5,
            lineheight = .7) +
  geom_text(data = rladies_chapter_df,
            aes(x = last_date,
                label = make_ordinal(tot_meetings)),
            color = "grey20",
            hjust = -.3,
            size = 4.5) +
  theme(axis.text.y = element_blank()) +
  scale_color_viridis_c(option = "magma", breaks = c(1, 50, 100),
                        labels = c("1st", "50th", "100th")) +
  facet_wrap( ~ cut_interval(
    as.numeric(chapter),
    n = 4),
    scales = "free_y",
    ncol = 4) +
  labs(color = "Meeting\nnumber") +
* scale_x_date(expand = expansion(c(.3,.2)))
```
]
 
.panel2-feature2-auto[
![](rladies-on-a-wire_files/figure-html/feature2_auto_12_output-1.png)
]

---

![](rladies-on-a-wire_files/figure-html/feature2-1.png)

---

### Contribute

- https://github.com/EvaMaeRey/ggcirclepack

---

### Check out {packcircles} which does the computation in ggcirclepack

- https://github.com/mbedward/packcircles

---

### Check out flipbookr, used to build this featurette

- https://github.com/EvaMaeRey/flipbookr
- discussion: https://github.com/EvaMaeRey/flipbookr/blob/master/docs/draft_jasa_submission.pdf

---

### Check out more featurettes

- https://EvaMaeRey.github.io/featurette