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add pdfs, update lab07

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Antoine Neuraz hace 5 años
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courses/01-dataviz-intro.pdf Ver fichero


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courses/02-perception-couleurs.pdf Ver fichero


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courses/03-design-tabulaire.pdf Ver fichero


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courses/04-interactivite.pdf Ver fichero


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courses/06_graphes.pdf Ver fichero


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courses/lab01-correction.Rmd Ver fichero

@@ -7,6 +7,7 @@ output: html_document

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(ggplot2)
```

## Ouvrir le dataset "mtcars"


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courses/lab01-correction.html
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courses/lab01-ggplot-intro.Rmd Ver fichero

@@ -13,9 +13,6 @@ output:
self-contained: true
beforeInit: "addons/macros.js"
highlightLines: true
pdf_document:
seal: false
---

```{r setup, include=FALSE}


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courses/lab01-ggplot-intro.pdf Ver fichero


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courses/lab02-perception-colors.Rmd Ver fichero

@@ -25,6 +25,18 @@ library(see)
library(RColorBrewer)
```

class: center, middle, title

# Lab 2: Perception et couleurs

### 2019-2020

## Dr. Antoine Neuraz

### AHU Informatique médicale
#### Hôpital Necker-Enfants malades, </br> Université de Paris


---
class: inverse, center, middle
# Perception des différentes marques dans ggplot2
@@ -240,6 +252,14 @@ class: full

#### changer la palette par défaut vers une autre palette disponible

---
```{r}
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
ggplot(dsamp, aes(carat, price)) +
geom_point(aes(colour = color)) +
scale_color_brewer(palette = "Set3") +
facet_wrap(~color)
```


---
@@ -254,17 +274,8 @@ class: full
#### Caler la palette sur le carat moyen

#### Annoter le plot avec une ligne désignant le carat moyen et un texte expliquant cette ligne



---
```{r}
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
ggplot(dsamp, aes(carat, price)) +
geom_point(aes(colour = color)) +
scale_color_brewer(palette = "Set3") +
facet_wrap(~color)
```


```{r}

@@ -273,7 +284,8 @@ ggplot(dsamp, aes(carat, price)) +
scale_color_distiller(palette="RdYlBu")
```

```{r}
---
```{r, eval = F}

#showtext_auto()
#font_add_google("Schoolbell", "bell")
@@ -307,7 +319,40 @@ ggplot(dsamp, aes(carat, price)) +
legend.position = "none")
```

---
```{r, echo = F}

#showtext_auto()
#font_add_google("Schoolbell", "bell")

font_family = "sans"
annotate_color = "grey50"

midpoint = (max(dsamp$carat)-min(dsamp$carat))/2

ggplot(dsamp, aes(carat, price)) +
geom_vline(xintercept = midpoint, color = annotate_color) +
geom_point(aes(colour = carat)) +
scale_color_gradient2(low = "#d8b365",
mid="#f5f5f5",
high="#5ab4ac",
midpoint = midpoint) +
annotate("text",
x=.78, y=15000, hjust=1, srt=40,
label ="this is the midpoint",
family=font_family,
color=annotate_color) +
annotate("curve",
x = .8, xend=midpoint-.01, y=15000, yend = 14000,
curvature = -.5,
color=annotate_color ,
arrow=arrow(length = unit(0.03, "npc") )) +

theme_elegant() +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
legend.position = "none")
```





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courses/lab02-perception-colors.html Ver fichero

@@ -13,6 +13,18 @@



class: center, middle, title

# Lab 2: Perception et couleurs

### 2019-2020

## Dr. Antoine Neuraz

### AHU Informatique médicale
#### Hôpital Necker-Enfants malades, &lt;/br&gt; Université de Paris


---
class: inverse, center, middle
# Perception des différentes marques dans ggplot2
@@ -236,6 +248,19 @@ class: full

#### changer la palette par défaut vers une autre palette disponible

---

```r
dsamp &lt;- diamonds[sample(nrow(diamonds), 1000), ]
ggplot(dsamp, aes(carat, price)) +
geom_point(aes(colour = color)) +
scale_color_brewer(palette = "Set3") +
facet_wrap(~color)
```

![](lab02-perception-colors_files/figure-html/unnamed-chunk-12-1.png)&lt;!-- --&gt;


---
## TODO: couleurs 2

@@ -248,20 +273,8 @@ class: full
#### Caler la palette sur le carat moyen

#### Annoter le plot avec une ligne désignant le carat moyen et un texte expliquant cette ligne



---

```r
dsamp &lt;- diamonds[sample(nrow(diamonds), 1000), ]
ggplot(dsamp, aes(carat, price)) +
geom_point(aes(colour = color)) +
scale_color_brewer(palette = "Set3") +
facet_wrap(~color)
```

![](lab02-perception-colors_files/figure-html/unnamed-chunk-12-1.png)&lt;!-- --&gt;


```r
@@ -272,6 +285,7 @@ ggplot(dsamp, aes(carat, price)) +

![](lab02-perception-colors_files/figure-html/unnamed-chunk-13-1.png)&lt;!-- --&gt;

---

```r
#showtext_auto()
@@ -306,7 +320,8 @@ ggplot(dsamp, aes(carat, price)) +
legend.position = "none")
```

![](lab02-perception-colors_files/figure-html/unnamed-chunk-14-1.png)&lt;!-- --&gt;
---
![](lab02-perception-colors_files/figure-html/unnamed-chunk-15-1.png)&lt;!-- --&gt;
</textarea>
<style data-target="print-only">@media screen {.remark-slide-container{display:block;}.remark-slide-scaler{box-shadow:none;}}</style>
<script src="https://remarkjs.com/downloads/remark-latest.min.js"></script>


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courses/lab03-tabulaire.html Ver fichero

@@ -44,8 +44,8 @@ class: center, middle, title
read_csv("lab03_data/notes.csv") -&gt; notes
```

<div id="htmlwidget-a9f909b507366e2763fd" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-a9f909b507366e2763fd">{"x":{"filter":"none","data":[["1/1/2019","1/15/2019","2/1/2019","2/15/2019","3/1/2019","3/15/2019","4/1/2019","4/15/2019","5/1/2019","5/15/2019"],[14,16,15,17,14,15,13,15,16,17],[10,11,11,10,15,13,12,12,13,11],[18,19,18,19,19,20,19,19,17,18],[9,10,12,11,14,13,14,15,14,15]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th>Date<\/th>\n <th>Alice<\/th>\n <th>Bob<\/th>\n <th>Claire<\/th>\n <th>David<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"paging":false,"info":false,"searching":false,"columnDefs":[{"className":"dt-right","targets":[1,2,3,4]}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
<div id="htmlwidget-94c0f5d1381e56fb5881" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-94c0f5d1381e56fb5881">{"x":{"filter":"none","data":[["1/1/2019","1/15/2019","2/1/2019","2/15/2019","3/1/2019","3/15/2019","4/1/2019","4/15/2019","5/1/2019","5/15/2019"],[14,16,15,17,14,15,13,15,16,17],[10,11,11,10,15,13,12,12,13,11],[18,19,18,19,19,20,19,19,17,18],[9,10,12,11,14,13,14,15,14,15]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th>Date<\/th>\n <th>Alice<\/th>\n <th>Bob<\/th>\n <th>Claire<\/th>\n <th>David<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"paging":false,"info":false,"searching":false,"columnDefs":[{"className":"dt-right","targets":[1,2,3,4]}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>

---

@@ -61,8 +61,8 @@ pivot_longer(notes,
values_to = "Note") -&gt; notes_long
```

<div id="htmlwidget-744a3944844d231f7996" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-744a3944844d231f7996">{"x":{"filter":"none","data":[["1/1/2019","1/1/2019","1/1/2019","1/1/2019","1/15/2019","1/15/2019","1/15/2019","1/15/2019","2/1/2019","2/1/2019","2/1/2019","2/1/2019","2/15/2019","2/15/2019","2/15/2019","2/15/2019","3/1/2019","3/1/2019","3/1/2019","3/1/2019","3/15/2019","3/15/2019","3/15/2019","3/15/2019","4/1/2019","4/1/2019","4/1/2019","4/1/2019","4/15/2019","4/15/2019","4/15/2019","4/15/2019","5/1/2019","5/1/2019","5/1/2019","5/1/2019","5/15/2019","5/15/2019","5/15/2019","5/15/2019"],["Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David"],[14,10,18,9,16,11,19,10,15,11,18,12,17,10,19,11,14,15,19,14,15,13,20,13,13,12,19,14,15,12,19,15,16,13,17,14,17,11,18,15]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th>Date<\/th>\n <th>Prénom<\/th>\n <th>Note<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"paging":false,"info":false,"searching":false,"columnDefs":[{"className":"dt-right","targets":2}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
<div id="htmlwidget-3265d78dc11fed97ef02" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-3265d78dc11fed97ef02">{"x":{"filter":"none","data":[["1/1/2019","1/1/2019","1/1/2019","1/1/2019","1/15/2019","1/15/2019","1/15/2019","1/15/2019","2/1/2019","2/1/2019","2/1/2019","2/1/2019","2/15/2019","2/15/2019","2/15/2019","2/15/2019","3/1/2019","3/1/2019","3/1/2019","3/1/2019","3/15/2019","3/15/2019","3/15/2019","3/15/2019","4/1/2019","4/1/2019","4/1/2019","4/1/2019","4/15/2019","4/15/2019","4/15/2019","4/15/2019","5/1/2019","5/1/2019","5/1/2019","5/1/2019","5/15/2019","5/15/2019","5/15/2019","5/15/2019"],["Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David","Alice","Bob","Claire","David"],[14,10,18,9,16,11,19,10,15,11,18,12,17,10,19,11,14,15,19,14,15,13,20,13,13,12,19,14,15,12,19,15,16,13,17,14,17,11,18,15]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th>Date<\/th>\n <th>Prénom<\/th>\n <th>Note<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"paging":false,"info":false,"searching":false,"columnDefs":[{"className":"dt-right","targets":2}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>

---

@@ -77,8 +77,8 @@ pivot_wider(notes_long,
values_from = Note)
```

<div id="htmlwidget-206da931c15e14bd710f" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-206da931c15e14bd710f">{"x":{"filter":"none","data":[["1/1/2019","1/15/2019","2/1/2019","2/15/2019","3/1/2019","3/15/2019","4/1/2019","4/15/2019","5/1/2019","5/15/2019"],[14,16,15,17,14,15,13,15,16,17],[10,11,11,10,15,13,12,12,13,11],[18,19,18,19,19,20,19,19,17,18],[9,10,12,11,14,13,14,15,14,15]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th>Date<\/th>\n <th>Alice<\/th>\n <th>Bob<\/th>\n <th>Claire<\/th>\n <th>David<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"paging":false,"info":false,"searching":false,"columnDefs":[{"className":"dt-right","targets":[1,2,3,4]}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
<div id="htmlwidget-1496fd73ac98b39c4291" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-1496fd73ac98b39c4291">{"x":{"filter":"none","data":[["1/1/2019","1/15/2019","2/1/2019","2/15/2019","3/1/2019","3/15/2019","4/1/2019","4/15/2019","5/1/2019","5/15/2019"],[14,16,15,17,14,15,13,15,16,17],[10,11,11,10,15,13,12,12,13,11],[18,19,18,19,19,20,19,19,17,18],[9,10,12,11,14,13,14,15,14,15]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th>Date<\/th>\n <th>Alice<\/th>\n <th>Bob<\/th>\n <th>Claire<\/th>\n <th>David<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"paging":false,"info":false,"searching":false,"columnDefs":[{"className":"dt-right","targets":[1,2,3,4]}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>

---



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@@ -233,8 +233,8 @@ graph.star(n = 10, mode = "out")
read_csv("lab06_data/OMIM.csv") -&gt; OMIM
```

<div id="htmlwidget-47d834c4dcc97d74e7ee" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-47d834c4dcc97d74e7ee">{"x":{"filter":"none","data":[["ACYL-CoA DEHYDROGENASE, SHORT-CHAIN, DEFICIENCY OF","ADAMS-OLIVER SYNDROME 1","ADAMS-OLIVER SYNDROME 2","ADAMS-OLIVER SYNDROME 3","ADENINE PHOSPHORIBOSYLTRANSFERASE DEFICIENCY","LUNG CANCER","LUNG CANCER","LUNG CANCER","LUNG CANCER","LUNG CANCER","LUNG CANCER"],["ACADS","ARHGAP31","DOCK6","RBPJ","APRT","CYP2A6","EGFR","TNFSF6","IRF1","BRAF","ERBB2"]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th>Disease<\/th>\n <th>Gene<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"paging":false,"search":false,"info":false,"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
<div id="htmlwidget-e2536eee24b80cd7b4a4" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-e2536eee24b80cd7b4a4">{"x":{"filter":"none","data":[["ACYL-CoA DEHYDROGENASE, SHORT-CHAIN, DEFICIENCY OF","ADAMS-OLIVER SYNDROME 1","ADAMS-OLIVER SYNDROME 2","ADAMS-OLIVER SYNDROME 3","ADENINE PHOSPHORIBOSYLTRANSFERASE DEFICIENCY","LUNG CANCER","LUNG CANCER","LUNG CANCER","LUNG CANCER","LUNG CANCER","LUNG CANCER"],["ACADS","ARHGAP31","DOCK6","RBPJ","APRT","CYP2A6","EGFR","TNFSF6","IRF1","BRAF","ERBB2"]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th>Disease<\/th>\n <th>Gene<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"paging":false,"search":false,"info":false,"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>

---
# Chargement du graphe
@@ -246,9 +246,9 @@ graph.data.frame(OMIM, directed = F) -&gt; graphe


```
## IGRAPH 01bad3b UN-- 6288 4234 --
## IGRAPH d3876e8 UN-- 6288 4234 --
## + attr: name (v/c)
## + edges from 01bad3b (vertex names):
## + edges from d3876e8 (vertex names):
## [1] ADRENAL HYPERPLASIA, CONGENITAL, DUE TO 17-ALPHA-HYDROXYLASE DEFICIENCY--CYP17A1
## [2] 17-BETA-HYDROXYSTEROID DEHYDROGENASE X DEFICIENCY --HSD17B10
## [3] 2-METHYLBUTYRYL-CoA DEHYDROGENASE DEFICIENCY --ACADSB
@@ -304,7 +304,7 @@ neighbors(graphe, V(graphe)[2019])
```

```
## + 1/6288 vertex, named, from 01bad3b:
## + 1/6288 vertex, named, from d3876e8:
## [1] SLC25A3
```

@@ -333,9 +333,9 @@ HDN
```

```
## IGRAPH 8db9c9b UNW- 3512 2839 --
## IGRAPH 58fb0bd UNW- 3512 2839 --
## + attr: name (v/c), weight (e/n)
## + edges from 8db9c9b (vertex names):
## + edges from 58fb0bd (vertex names):
## [1] 17-BETA-HYDROXYSTEROID DEHYDROGENASE X DEFICIENCY--MENTAL RETARDATION, X-LINKED 17
## [2] 17-BETA-HYDROXYSTEROID DEHYDROGENASE X DEFICIENCY--MENTAL RETARDATION, X-LINKED, SYNDROMIC 10
## [3] 3-HYDROXYACYL-CoA DEHYDROGENASE DEFICIENCY --HYPERINSULINEMIC HYPOGLYCEMIA, FAMILIAL, 4
@@ -353,9 +353,9 @@ HGN
```

```
## IGRAPH 65dfdde UNW- 2776 2810 --
## IGRAPH f5f35d8 UNW- 2776 2810 --
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- 20
courses/lab7-temporal_data.Rmd Ver fichero

@@ -21,6 +21,8 @@ library(ggplot2)
library(gghighlight)
library(dplyr)
library(ggTimeSeries)
library(hrbrthemes)
library(gganimate)
```

## TODO
@@ -47,27 +49,16 @@ library(ggTimeSeries)
---

```{r}

data("us_city_populations")

n_cities = 5

# top_cities <-
# us_city_populations %>%
# filter(Rank <= n_cities) %>%
# select(City, State, Region) %>%
# distinct()
#
# to_plot <- filter(us_city_populations, City %in% top_cities$City)

#to_plot <- us_city_populations

last_ranks <- us_city_populations %>%
filter(Year == max(Year)) %>%
mutate(last_rank = Rank) %>%
select(City, last_rank)

to_plot <- left_join(us_city_populations, last_ranks, by= 'City')
to_plot <- left_join(us_city_populations, last_ranks, by= 'City')

right_axis <- to_plot %>%
group_by(City) %>%
@@ -85,14 +76,16 @@ labels <- right_axis %>%

---
class: full
```{r, echo = FALSE}
ggplot(to_plot, aes(x=Year, y = Population, group = City, color = City)) +
```{r, echo = TRUE}
p <- ggplot(to_plot, aes(x=Year, y = Population,
group = City, color = City)) +
geom_line(size=1) +
#geom_text(data = subset(to_plot, Year == 2010), aes(x=Inf, y = Population, label=City), hjust = 1) +
scale_x_continuous("", expand=c(0,0))+
scale_y_continuous("",
labels=scales::comma_format(big.mark = " "),
sec.axis = sec_axis(~ ., breaks = ends, labels = labels ))+
sec.axis = sec_axis(~ .,
breaks = ends,
labels = labels ))+
scale_color_viridis_d()+
theme_elegant_dark()+
theme(legend.position = "none",
@@ -101,14 +94,23 @@ ggplot(to_plot, aes(x=Year, y = Population, group = City, color = City)) +
axis.line.x = element_blank(),
axis.ticks.x = element_line(),
panel.grid.major.y = element_line(color= 'grey30', size = .2) ) +
gghighlight(max(last_rank) <= n_cities, use_direct_label = FALSE, label_key = City,unhighlighted_colour = "grey20")
gghighlight(max(last_rank) <= n_cities,
use_direct_label = FALSE,
label_key = City,
unhighlighted_colour = "grey20")
```
---
class: full
```{r, echo = FALSE}
```{r, echo = TRUE}
p
```
---

class: full
```{r, echo = TRUE}
library(ggTimeSeries)
to_plot %>% filter(City %in% labels) %>%
p <- to_plot %>% filter(City %in% labels) %>%
ggplot(aes(x = Year, y = Population, group = City, fill = City)) +
scale_y_continuous("", labels = scales::comma_format(big.mark = " "))+
stat_steamgraph() +
@@ -121,7 +123,122 @@ to_plot %>% filter(City %in% labels) %>%
panel.grid.major.y = element_line(color= 'grey30', size = .2) )

```

---
class: full
```{r}
p
```
---
class: inverse, center, middle
# Barchart race

---
## Load data
```{r load_data}
data("us_city_populations")

n_cities = 10
top_cities <-us_city_populations %>% filter(Rank <= n_cities) %>%
select(City, State, Region) %>% distinct()

```

---
## Create all missing dates
```{r, combine_dates}
# create a data frame with all the years between min and max Year
all_years <- data.frame(Year = seq(min(us_city_populations$Year),
max(us_city_populations$Year), 1))

# combine top_cities and all_years
all_combos <- merge(top_cities, all_years, all = T)

# combine all_combos with the original dataset
res_interp <- merge(us_city_populations, all_combos, all.y = T)
```

## Interpolate the Populations when missing (linear interpolation here)
```{r, interpolate}
res_interp <- res_interp %>%
group_by(City) %>%
mutate(Population=approx(Year,Population,Year)$y)
```

---
## Filter data
```{r, filter_for_plot}
to_plot <- res_interp %>%
group_by(Year) %>%
arrange(-Population) %>%
mutate(Rank=row_number()) %>%
filter(Rank<=n_cities)

```

---
## Ease transitions

```{r}
to_plot_trans <- to_plot %>%
group_by(City) %>%
arrange(Year) %>%
mutate(lag_rank = lag(Rank, 1),
change = ifelse(Rank > lag(Rank, 1), 1, 0),
change = ifelse(Rank < lag(Rank, 1), -1, 0)) %>%
mutate(transition = ifelse(lead(change, 1) == -1, -.9, 0),
transition = ifelse(lead(change,2) == -1, -.5, transition),
transition = ifelse(lead(change,3) == -1, -.3, transition),
transition = ifelse(lead(change, 1) == 1, .9, transition),
transition = ifelse(lead(change,2) == 1, .5, transition),
transition = ifelse(lead(change,3) == 1, .3, transition)) %>%
mutate(trans_rank = Rank + transition)
```


---
## Make the plot
.small[
```{r, make_plot}
p <- to_plot_trans %>%
ggplot(aes(x = -trans_rank,y = Population, group =City)) +
geom_tile(aes(y = Population / 2, height = Population, fill = Region),
width = 0.9) +
geom_text(aes(label = City),
hjust = "right", colour = "white",
fontface="bold", nudge_y = -100000) +
geom_text(aes(label = scales::comma(Population,big.mark = ' ')),
hjust = "left", nudge_y = 100000, colour = "grey90") +
coord_flip(clip="off") +
hrbrthemes::scale_fill_ipsum() +
scale_x_discrete("") +
scale_y_continuous("",labels=scales::comma_format(big.mark = " ")) +
theme_elegant_dark(base_size = 20) +
theme(
panel.grid.minor.x=element_blank(),
axis.line = element_blank(),
panel.grid.major= element_line(color='lightgrey', size=.2),
legend.position = c(0.6, 0.2),
plot.margin = margin(1,1,1,2,"cm"),
plot.title = element_text(hjust = 0),
axis.text.y=element_blank(),
legend.text = element_text(size = 15),
legend.background = element_blank()) +
# gganimate code to transition by year:
transition_time(Year) +
ease_aes('cubic-in-out') +
labs(title='Evolution des plus grandes villes US',
subtitle='Population en {round(frame_time,0)}')

```
]
---
```{r, animate, eval = FALSE}
animate(p, nframes = 400, fps = 25, end_pause = 30, width = 1200)
anim_save("bar_race.gif", animation = last_animation())
```

![](bar_race.gif)
![:scale 80%](bar_race.gif)


+ 219
- 19
courses/lab7-temporal_data.html Ver fichero

@@ -1,8 +1,8 @@
<!DOCTYPE html>
<html>
<html xmlns="http://www.w3.org/1999/xhtml" lang="" xml:lang="">
<head>
<title>Lab 07 - Données temporelles et textuelles</title>
<meta charset="utf-8">
<meta charset="utf-8" />
<meta name="author" content="Antoine Neuraz" />
<link href="libs/remark-css-0.0.1/default.css" rel="stylesheet" />
<link rel="stylesheet" href="css/my_style.css" type="text/css" />
@@ -42,22 +42,12 @@ data("us_city_populations")

n_cities = 5

# top_cities &lt;-
# us_city_populations %&gt;%
# filter(Rank &lt;= n_cities) %&gt;%
# select(City, State, Region) %&gt;%
# distinct()
#
# to_plot &lt;- filter(us_city_populations, City %in% top_cities$City)

#to_plot &lt;- us_city_populations

last_ranks &lt;- us_city_populations %&gt;%
filter(Year == max(Year)) %&gt;%
mutate(last_rank = Rank) %&gt;%
select(City, last_rank)

to_plot &lt;- left_join(us_city_populations, last_ranks, by= 'City')
to_plot &lt;- left_join(us_city_populations, last_ranks, by= 'City')

right_axis &lt;- to_plot %&gt;%
group_by(City) %&gt;%
@@ -74,14 +64,182 @@ labels &lt;- right_axis %&gt;%

---
class: full
![](lab7-temporal_data_files/figure-html/unnamed-chunk-2-1.png)&lt;!-- --&gt;

```r
p &lt;- ggplot(to_plot, aes(x=Year, y = Population,
group = City, color = City)) +
geom_line(size=1) +
scale_x_continuous("", expand=c(0,0))+
scale_y_continuous("",
labels=scales::comma_format(big.mark = " "),
sec.axis = sec_axis(~ .,
breaks = ends,
labels = labels ))+
scale_color_viridis_d()+
theme_elegant_dark()+
theme(legend.position = "none",
plot.margin = unit(c(1,3,1,1), "lines"),
axis.line.y = element_blank(),
axis.line.x = element_blank(),
axis.ticks.x = element_line(),
panel.grid.major.y = element_line(color= 'grey30', size = .2) ) +
gghighlight(max(last_rank) &lt;= n_cities,
use_direct_label = FALSE,
label_key = City,
unhighlighted_colour = "grey20")
```
---
class: full

```r
p
```

![](lab7-temporal_data_files/figure-html/unnamed-chunk-3-1.png)&lt;!-- --&gt;
---

![](bar_race.gif)
class: full

```r
library(ggTimeSeries)
p &lt;- to_plot %&gt;% filter(City %in% labels) %&gt;%
ggplot(aes(x = Year, y = Population, group = City, fill = City)) +
scale_y_continuous("", labels = scales::comma_format(big.mark = " "))+
stat_steamgraph() +
theme_elegant_dark() +
scale_fill_viridis_d() +
theme(plot.margin = unit(c(1,3,1,1), "lines"),
axis.line.y = element_blank(),
axis.line.x = element_blank(),
axis.ticks.x = element_line(),
panel.grid.major.y = element_line(color= 'grey30', size = .2) )
```

---
class: full

```r
p
```

![](lab7-temporal_data_files/figure-html/unnamed-chunk-5-1.png)&lt;!-- --&gt;
---
class: inverse, center, middle
# Barchart race

---
## Load data

```r
data("us_city_populations")

n_cities = 10
top_cities &lt;-us_city_populations %&gt;% filter(Rank &lt;= n_cities) %&gt;%
select(City, State, Region) %&gt;% distinct()
```

---
## Create all missing dates

```r
# create a data frame with all the years between min and max Year
all_years &lt;- data.frame(Year = seq(min(us_city_populations$Year),
max(us_city_populations$Year), 1))

# combine top_cities and all_years
all_combos &lt;- merge(top_cities, all_years, all = T)

# combine all_combos with the original dataset
res_interp &lt;- merge(us_city_populations, all_combos, all.y = T)
```

## Interpolate the Populations when missing (linear interpolation here)

```r
res_interp &lt;- res_interp %&gt;%
group_by(City) %&gt;%
mutate(Population=approx(Year,Population,Year)$y)
```

---
## Filter data

```r
to_plot &lt;- res_interp %&gt;%
group_by(Year) %&gt;%
arrange(-Population) %&gt;%
mutate(Rank=row_number()) %&gt;%
filter(Rank&lt;=n_cities)
```

---
## Ease transitions


```r
to_plot_trans &lt;- to_plot %&gt;%
group_by(City) %&gt;%
arrange(Year) %&gt;%
mutate(lag_rank = lag(Rank, 1),
change = ifelse(Rank &gt; lag(Rank, 1), 1, 0),
change = ifelse(Rank &lt; lag(Rank, 1), -1, 0)) %&gt;%
mutate(transition = ifelse(lead(change, 1) == -1, -.9, 0),
transition = ifelse(lead(change,2) == -1, -.5, transition),
transition = ifelse(lead(change,3) == -1, -.3, transition),
transition = ifelse(lead(change, 1) == 1, .9, transition),
transition = ifelse(lead(change,2) == 1, .5, transition),
transition = ifelse(lead(change,3) == 1, .3, transition)) %&gt;%
mutate(trans_rank = Rank + transition)
```


---
## Make the plot
.small[

```r
p &lt;- to_plot_trans %&gt;%
ggplot(aes(x = -trans_rank,y = Population, group =City)) +
geom_tile(aes(y = Population / 2, height = Population, fill = Region),
width = 0.9) +
geom_text(aes(label = City),
hjust = "right", colour = "white",
fontface="bold", nudge_y = -100000) +
geom_text(aes(label = scales::comma(Population,big.mark = ' ')),
hjust = "left", nudge_y = 100000, colour = "grey90") +
coord_flip(clip="off") +
hrbrthemes::scale_fill_ipsum() +
scale_x_discrete("") +
scale_y_continuous("",labels=scales::comma_format(big.mark = " ")) +
theme_elegant_dark(base_size = 20) +
theme(
panel.grid.minor.x=element_blank(),
axis.line = element_blank(),
panel.grid.major= element_line(color='lightgrey', size=.2),
legend.position = c(0.6, 0.2),
plot.margin = margin(1,1,1,2,"cm"),
plot.title = element_text(hjust = 0),
axis.text.y=element_blank(),
legend.text = element_text(size = 15),
legend.background = element_blank()) +
# gganimate code to transition by year:
transition_time(Year) +
ease_aes('cubic-in-out') +
labs(title='Evolution des plus grandes villes US',
subtitle='Population en {round(frame_time,0)}')
```
]
---

```r
animate(p, nframes = 400, fps = 25, end_pause = 30, width = 1200)
anim_save("bar_race.gif", animation = last_animation())
```

![:scale 80%](bar_race.gif)
</textarea>
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@@ -92,16 +250,57 @@ class: full
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d.head.appendChild(s);
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@@ -115,7 +314,8 @@ if (window.HTMLWidgets) slideshow.on('afterShowSlide', function (slide) {
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