Calendar-based graphics for visualizing people’s daily schedules

# Calendar-based graphics for visualizing people’s daily schedules
### Earo Wang
### 30 July 2018 slides at <a href="http://slides.earo.me/jsm18" class="uri">http://slides.earo.me/jsm18</a>

---

.pull-left[
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]
.pull-right[
## .blue[Melbourne pedestrian counting sensors]
 
<img src="img/sensor.png" height="450px">
]

---

.left-column[
 
 
 
 
 
 
## What is a typical working day like at Southern Cross Station?
]
.right-column[
 
 
![](img/day1.gif)
]

???

* One normal working day in last Jan
*

---

.left-column[
 
 
 
 
 
 
 
 
 
 
## More and more
]
.right-column[
 
 
 
<video autoplay loop controls>
 <source src="img/sx17.mp4" type="video/mp4">
</video>
]

---

<img src="figure/sx-wrap-1.svg" style="display: block; margin: auto;" />
]

---

##

---

---

---

### `sugrrants::frame_calendar()`

* Its name draws inspiration from `tibble::frame_data()`, but the origin has shifted to `tibble::tribble()`.

* It needs a better meaning: frame the series into the calendar canvas.
]
.pull-right[
 
 
 
 
<img src="figure/sx-oct-1.svg" style="display: block; margin: auto;" />
]

---

## Construction

.center[<img src="img/month.png" width=450>]
 
The grid position for any day in the month is given by

`$$\begin{align}
i &= \lceil (g \mod 35) / 7\rceil \\ j &= g \mod 7.
\end{align}$$`

Let `$h$` and `$c$` be the scaled hour and count, respectively, then the final
coordinates are given by:

`$$\begin{align}
x &= j + h \\ y &= i - c.
\end{align}$$`

---

## Map over each month

```r
*mday_x <- mday(x)
*month_x <- unique(x - mday_x + 1)
*if (sunday) { # Weekday starts with Sunday
* first_wday <- wday(month_x, week_start = 7) # k
*} else { # starts with Monday
* first_wday <- wday(month_x, week_start = 1) # k
*}
counter <- map2( # g
 .x = first_wday, .y = days_x, function(.x, .y) .x + 0:(.y - 1)
)
row_idx <- map( # i
 counter, 
 function(x) ifelse(x == ncells, max_wks, ceiling((x %% ncells) / ndays))
)
col_idx <- map( # j
 counter, 
 function(x) ifelse(x %% ndays == 0, ndays, x %% ndays)
)
```

---

```r
sx_cal <- sx %>%
 frame_calendar(x = Time, y = Count, date = Date)
sx_cal
```

```
#> # A tibble: 8,760 x 6
#> Date_Time Date Time Count .Time .Count
#> * <dttm> <date> <int> <int> <dbl> <dbl>
#> 1 2017-01-01 00:00:00 2017-01-01 0 1335 0.258 0.986
#> 2 2017-01-01 01:00:00 2017-01-01 1 463 0.260 0.972
#> 3 2017-01-01 02:00:00 2017-01-01 2 219 0.261 0.968
#> 4 2017-01-01 03:00:00 2017-01-01 3 122 0.263 0.967
#> 5 2017-01-01 04:00:00 2017-01-01 4 21 0.264 0.965
#> 6 2017-01-01 05:00:00 2017-01-01 5 28 0.266 0.965
#> # ... with 8,754 more rows
```
]

---

```r
p_sx <- ggplot(sx_cal, aes(.Time, .Count, group = Date)) +
 geom_line()
```
<img src="figure/sx-2-1.svg" style="display: block; margin: auto;" />
]

---

```r
prettify(p_sx)
```

<img src="figure/sx-3-1.svg" style="display: block; margin: auto;" />
]

---

.left-column[
## Easy to use
### - frame_calendar()
### - ggplot2
### - prettify()
### - plotly
]
.right-column[

```r
library(plotly)
pp_sx <- sx_cal %>%
 group_by(Date) %>%
 plot_ly(x = ~ .Time, y = ~ .Count) %>%
 add_lines()
prettify(pp_sx)
```

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]

---

## Options: calendar type

.pull-left[
`calendar = "weekly"`
 
 
<img src="figure/weekly-1.svg" style="display: block; margin: auto;" />
]
.pull-right[
`calendar = "daily"`
 
 
<img src="figure/daily-1.svg" style="display: block; margin: auto;" />
]

---

## Options: polar

.pull-left[
`polar = FALSE`
 
 
<img src="figure/linear-1.svg" style="display: block; margin: auto;" />
]
.pull-right[
`polar = TRUE`
 
 
<img src="figure/polar-1.svg" style="display: block; margin: auto;" />
]

---

## Multiple calendars

---

## Showcase

.pull-left[
Energy consumption
![elec](img/elec-consumption.png)
]
.pull-right[
Bus delay
 
 
 
 
 
![bus](img/bus-delay.jpg)
.red[.footnote[left: Roach, C (forthcoming 2018). Assessing the impact of building characteristics on energy consumption using semiparametric mixed models. right: [Tom Elliott's tweet](https://twitter.com/tomelliottnz/status/958887861943640064)]]
]

---

### The full range of plotting capabilities in ggplot2 is essentially available, from geom_line() to geom_ribbon().

### Patterns on special events, like Australian Day, or Australian Open, more easily pop out to the viewer as public holidays.

### Localize the calendar: other languages are supported for labels, like CJK.

.pull-left[
<img src="figure/chn-1.svg" style="display: block; margin: auto;" />
]
.pull-right[
<img src="figure/fr-1.svg" style="display: block; margin: auto;" />
]

---

### Joint work with [Di Cook](http://dicook.org) & [Rob J Hyndman](http://robjhyndman.com)

### More on sugrrants <http://pkg.earo.me/sugrrants>

### Slides created via xaringan <http://slides.earo.me/jsm18>

### Open source [earowang/jsm18](https://github.com/earowang/jsm18)

### This work is under licensed [ BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/).