---
title: "Evolution CA"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    horizontal_layout: fill
---

```{r setup, include=FALSE}
library(flexdashboard)
load("../donnees/ca/ca.RData") # Attention, chemin spécifique dans mon organisation de fichiers
colDpt = "orange"
colPrv = "rosybrown"
colMois = "turquoise"
conv <- function(v) return(iconv(as.character(v), from = "UTF-8", to = "UTF-8"))
```

# Synthèse

## Column {data-width=650}

### Evolution mois par mois

```{r}
d = setNames(aggregate(ca / 1000000 ~ mois_no, ca_tout, sum), c("mois", "ca"))
par(mar = c(4, 4, 0, 0) + .1)
plot(ca ~ mois, d, type = "b",
     xlab = "Mois", ylab = "Chiffre d'affaires (M€)")
abline(h = mean(d$ca), lty = 3, col = "gray50")
```

## Column {data-width=350}

### Comparaison mois par mois (en k€)

```{r}
d = aggregate(cbind(ca2003, ca2004, evolution) ~ mois + mois_numero,
              ca_evol,
              sum)
d = subset(d, select = -mois_numero)
names(d) = c("Mois", "2003", "2004", "Evolution")
d$Mois = conv(d$Mois)
knitr::kable(d, digits = 0)
```

### Augmentation entre 2003 et 2004

```{r}
d = aggregate(ca ~ annee, ca_tout, sum)
v = paste(round((d$ca[2] / d$ca[1] - 1) * 100, 2), "%")
valueBox(v, 
         icon = "fa-arrow-circle-up", 
         color = "green")
```

# Détails {data-orientation=rows}

## Ligne 1

### Départements

```{r}
evol.dpt = aggregate(cbind(ca2003, ca2004, evolution) / 1000 ~ departement, ca_evol, sum)
names(evol.dpt) = c("Département", "2003", "2004", "Evolution")
evol.dpt$Département = conv(evol.dpt$Département)
knitr::kable(evol.dpt, digits = 0)
```

### Provenance

```{r}
evol.prov = aggregate(cbind(ca2003, ca2004, evolution) / 1000 ~ provenance, 
                      ca_evol, sum)
names(evol.prov) = c("Provenance", "2003", "2004", "Evolution")
evol.prov$Provenance = conv(evol.prov$Provenance)
knitr::kable(evol.prov, digits = 0)
```

## Ligne 2

### Nombre de département en hausse

```{r}
gauge(sum(evol.dpt$Evolution > 0), 0, 
      nrow(evol.dpt),
      sectors = gaugeSectors(colors = colDpt))
```

### Département avec la plus grosse évolution

```{r}
valueBox(evol.dpt$Département[which.max(evol.dpt$Evolution)], 
         icon = "fa-level-up",
         color = colDpt)
```

### Nombre de provenance en hausse

```{r}
gauge(sum(evol.prov$Evolution > 0), 0,
      nrow(evol.prov),
      sectors = gaugeSectors(colors = colPrv))
```

### Provenance avec la plus grosse évolution

```{r}
valueBox(evol.prov$Provenance[which.max(evol.prov$Evolution)], 
         icon = "fa-level-up",
         color = colPrv)
```


# Performance {data-orientation=rows}

## Ligne Département {data-height=200}

### Meilleur département

```{r}
dpt = aggregate(ca ~ departement, ca_tout, sum)
dpt.tri = dpt[order(dpt$ca, decreasing = TRUE),]
dpt.tri$departement = conv(dpt.tri$departement)
valueBox(dpt.tri$departement[1],
         icon = "ion-podium",
         color = colDpt)
```

### Part de `r dpt.tri$departement[1]`

```{r}
gauge(dpt.tri$ca[1], 0, sum(dpt.tri$ca),
      sectors = gaugeSectors(colors = colDpt),
      abbreviateDecimals = 0,
      symbol = "€")
```

### TOP 3

```{r}
knitr::kable(head(dpt.tri, 3), row.names = FALSE)
```


## Ligne Provenance {data-height=200}

### Meilleure provenance 

```{r}
prv = aggregate(ca ~ provenance, ca_tout, sum)
prv.tri = prv[order(prv$ca, decreasing = TRUE),]
prv.tri$provenance = conv(prv.tri$provenance)
valueBox(prv.tri$provenance[1],
         color = colPrv,
         icon = "ion-podium")
```

### Part de `r prv.tri$provenance[1]`

```{r}
gauge(prv.tri$ca[1], 0, sum(prv.tri$ca),
      sectors = gaugeSectors(colors = colPrv),
      abbreviateDecimals = 0,
      symbol = "€")
```

### TOP 3

```{r}
knitr::kable(head(prv.tri, 3), row.names = FALSE)
```


## Ligne Mois {data-height=200}


### Meilleur mois

```{r}
mois = aggregate(ca ~ mois + mois_numero + annee, ca_tout, sum)
mois.tri = mois[order(mois$ca, decreasing = TRUE),]
mois.tri$mois = conv(mois.tri$mois)
valueBox(paste(mois.tri$mois[1], mois.tri$annee[1]),
         icon = "ion-podium",
         color = colMois)
```

### Part de `r paste(mois.tri$mois[1], mois.tri$annee[1])`

```{r}
gauge(mois.tri$ca[1], 0, sum(mois.tri$ca),
      sectors = gaugeSectors(colors = colMois),
      abbreviateDecimals = 0,
      symbol = "€")
```

### TOP3

```{r}
knitr::kable(head(mois.tri[-2], 3), row.names = FALSE)
```