Individual

Column

H1

H2

42

H3

Column

H4

H5

H6

H7

Column

H8

H9

H10

Comparativo

Column

H11

H12

1

H13

Column

H14

H15

Column

H16

H17

Individual

Column

J1

J2

136

J3

Column

J4

J5

J6

J7

Column

J8

J9

J10

Comparativo

Column

J11

J12

Column

J13

J14

J15

68

J16

Column

J17

J18

Modeling

Column

M1

3.1415

M2

4673

M3

8

M4

0.0297

Column

M5

0.91

M6

427

M7

303

M8

0.07

Column

M9

M10

M11

M12

Column

M13

3.1415

M14

4673

M15

8

M16

0.0297

Column

M17

0.91

M18

427

M19

303

M20

0.07
---
title: "Data"
output: 
  flexdashboard::flex_dashboard:
    theme:
      bg: "#191b1d"
      fg: "#ebebeb" 
      primary: "#000000"
      base_font:
        google: Prompt
      code_font:
        google: JetBrains Mono
      storyboard: true
    orientation: columns
    vertical_layout: fill
    source_code: embed
    navbar:
        - { icon: "fab fa-google", href: "https://google.com", align: right }
        - { icon: "fab fa-jedi-order", href: "https://www.linux.org/", align: right}
        - { icon: "fa-github", href: "https://www.github.com/", align: right}
        - { icon: "fab fa-r-project", href: "https://rpubs.com/", align: right} 
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, warning = FALSE, message = FALSE, error = FALSE)
library(flexdashboard)
library(DT)
library(tidyverse)
library(plotly)
library(fontawesome)
library(data.table)
library(fs)
library(lubridate)
library(gganimate)
thematic::thematic_rmd(font = "auto")
```


Individual {data-navmenu="Horses" data-icon="fa-chess-knight"}
=======================================================================

Column {data-width=150}
-----------------------------------------------------------------------


### H1

```{r}
ggplotly(
  data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="purple")
)

```

### H2

```{r}
valueBox(
  value = 42,
  caption = "Texto...",
  icon = "fa-pie-chart",
  color = "cadetblue"
)
```

### H3

```{r}

ggplotly(
    data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="red")
)

```


Column {data-width=500 data-height=300 .tabset}
-----------------------------------------------------------------------

### H4

```{r}
ggplotly(
  data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="yellow")
)
```

### H5

```{r}
iris %>% 
  bind_cols(iris) %>% 
  mutate(across(where(is.numeric), round, digits = 2)) %>%
  datatable(
    rownames = FALSE,
    extensions = c('Buttons'),
    options = list(
      dom = 'Bfrtip',
      buttons = c('excel'),
      scrollX = TRUE
    )
  )

```


### H6


### H7


Column {data-width=150}
-----------------------------------------------------------------------


### H8

```{r}
ggplotly(
  data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="orange")
)

```

### H9

```{r}
gauge(
  value = 80, min = 0, max = 100,
  label = "Informativo", symbol = "m/s",
  gaugeSectors(
    success = c(80, 100),
    warning = c(40, 79),
    danger = c(0, 39)
  )
)
```

### H10

```{r}
ggplotly(
  data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="#33cccc")
)
```


Comparativo {data-navmenu="Horses" data-icon="fa-chess-knight"}
=======================================================================

Column {data-width=150}
-------------------------------------

### H11

```{r}
gauge(
  value = 60, min = 0, max = 100,
  label = "Informativo", symbol = "%",
  gaugeSectors(
    success = c(80, 100),
    warning = c(40, 79),
    danger = c(0, 39)
  )
)
```


### H12

```{r}
valueBox(
  value = 1,
  caption = "Posición",
  icon = "fa-medal",
  color = "primary"
)
```

### H13

```{r}
gauge(
  value = 39, min = 0, max = 100,
  label = "Informativo", symbol = "s",
  gaugeSectors(
    success = c(80, 100),
    warning = c(40, 79),
    danger = c(0, 39)
  )
)
```




Column {data-width=400}
-------------------------------------
    
### H14

```{r}

ggplotly(
  data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="#ebebeb")
)
```

### H15
    
```{r}

ggplotly(
  data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="red")
)
```
 
Column
-------------------------------------
   
### H16

```{r}
iris %>% 
  bind_cols(iris) %>% 
  mutate(across(where(is.numeric), round, digits = 2)) %>%
  datatable(
    rownames = FALSE,
    extensions = c('Buttons'),
    options = list(
      dom = 'Btip',
      buttons = c('excel'),
      scrollX = TRUE
    )
  )

```   
 
### H17
    
```{r}
iris %>% 
  bind_cols(iris) %>% 
  mutate(across(where(is.numeric), round, digits = 2)) %>%
  datatable(
    rownames = FALSE,
    extensions = c('Buttons'),
    options = list(
      dom = 'Btip',
      buttons = c('excel'),
      scrollX = TRUE
    )
  )

```


Individual {data-navmenu="Jockeys" data-icon="fa-user-circle"}
=======================================================================

Column {data-width=150}
-----------------------------------------------------------------------
  
  
### J1
  
```{r}
ggplotly(
  data.frame(
    t = 1:20,
    y = rnorm(n = 20, mean = 2, sd = 20)
  ) %>% 
    ggplot(aes(x = t,  y = y))+
    geom_line(color="cyan")
)
```

### J2

```{r}
valueBox(
  value = 136,
  caption = "Info.",
  icon = "fa-first-aid",
  color = "#00674a"
)
```

### J3

```{r}
ggplotly(
  data.frame(
    t = 1:20,
    y = rnorm(n = 20, mean = 2, sd = 20)
  ) %>% 
    ggplot(aes(x = t,  y = y))+
    geom_line(color="#ff0066")
)
```


Column {data-width=500 data-height=300 .tabset}
-----------------------------------------------------------------------
  
### J4
  
```{r}
ggplotly(
  data.frame(
    t = 1:20,
    y = rnorm(n = 20, mean = 2, sd = 20)
  ) %>% 
    ggplot(aes(x = t,  y = y))+
    geom_line(color="#ffff00")
)
```

### J5

```{r}
iris %>% 
  bind_cols(iris) %>% 
  mutate(across(where(is.numeric), round, digits = 2)) %>%
  datatable(
    rownames = FALSE,
    extensions = c('Buttons'),
    options = list(
      dom = 'Bfrtip',
      buttons = c('excel'),
      scrollX = TRUE
    )
  )

```


### J6


### J7


Column {data-width=150}
-----------------------------------------------------------------------
  
  
### J8
  
```{r}
ggplotly(
  data.frame(
    t = 1:20,
    y = rnorm(n = 20, mean = 2, sd = 20)
  ) %>% 
    ggplot(aes(x = t,  y = y))+
    geom_line(color="#00ff00")
)
```

### J9

```{r}
gauge(
  value = 50, min = 0, max = 100,
  label = "Informativo", symbol = "K°",
  gaugeSectors(
    success = c(80, 100),
    warning = c(40, 79),
    danger = c(0, 39)
  )
)
```

### J10

```{r}
library(tidyverse)

ggplotly(
  data.frame(
    t = 1:20,
    y = rnorm(n = 20, mean = 2, sd = 20)
  ) %>% 
    ggplot(aes(x = t,  y = y))+
    geom_line(color="#9933ff")
)
```


Comparativo {data-navmenu="Jockeys" data-icon="fa-users"}
=======================================================================

Column {data-width=500}
-------------------------------------
    
### J11

```{r}
iris %>% 
  bind_cols(iris) %>% 
  mutate(across(where(is.numeric), round, digits = 2)) %>%
  datatable(
    rownames = FALSE,
    extensions = c('Buttons'),
    options = list(
      dom = 'Btip',
      buttons = c('excel'),
      scrollX = TRUE
    )
  )

```


### J12
    
```{r}

ggplotly(
  data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="white")
)
```


Column {data-width=150}
-------------------------------------

### J13

```{r}
gauge(
  value = 79, min = 0, max = 100,
  label = "", symbol = "mH",
  gaugeSectors(
    success = c(80, 100),
    warning = c(40, 79),
    danger = c(0, 39)
  )
)
```

### J14

```{r}
gauge(
  value = 39, min = 0, max = 100,
  label = "Por completar", symbol = "%",
  gaugeSectors(
    success = c(80, 100),
    warning = c(40, 79),
    danger = c(0, 39)
  )
)
```

### J15

```{r}
valueBox(
  value = 68,
  caption = "Unidades",
  icon = "fa-sun",
  color = "#8c1aff"
)
```

### J16

```{r}
gauge(
  value = 40, min = 0, max = 100,
  label = "Nivel", symbol = "%",
  gaugeSectors(
    success = c(80, 100),
    warning = c(40, 79),
    danger = c(0, 39)
  )
)
```
   
Column 
-------------------------------------
   
### J17

```{r}
ggplotly(
  data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="#eb1f27")
)
```  
 
### J18
    
```{r}
ggplotly(
  data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="#0e674b")
)
```

Modeling {data-icon="fa-infinity"}
=====================================

Column {data-width=100}
-----------------------------------------------------------------------


### M1

```{r}
valueBox(
  value = 3.1415,
  caption = "Potencia",
  icon = "fa-area-chart",
  color = "orange"
)
```


### M2

```{r}
valueBox(
  value = 4673,
  caption = "Libras",
  icon = "fa-bar-chart",
  color = "#00674a"
)
```

### M3

```{r}
valueBox(
  value = 8,
  caption = "Metros",
  icon = "fa-line-chart",
  color = "cadetblue"
)
```

### M4

```{r}
valueBox(
  value = 0.0297,
  caption = "Ampere",
  icon = " fa-divide",
  color = "#00b300"
)
```


Column {data-width=100}
-----------------------------------------------------------------------


### M5

```{r}
valueBox(
  value = 0.91,
  caption = "mol/l",
  icon = "fa-square-root-alt",
  color = "#ff3333"
)
```


### M6

```{r}
valueBox(
  value = 427,
  caption = "segundos",
  icon = "fa-subscript",
  color = "#003366"
)
```

### M7

```{r}
valueBox(
  value = 303,
  caption = "W",
  icon = "fa-calculator",
  color = "#751aff"
)
```

### M8

```{r}
valueBox(
  value = 0.07,
  caption = "N",
  icon = "fa-calculator",
  color = "#c2c2a3"
)
```

Column {data-width=600 .tabset}
-----------------------------------------------------------------------

### M9

```{r}
ggplotly(
  data.frame(
  t = 1:20,
  y = rnorm(n = 20, mean = 2, sd = 20)
) %>% 
  ggplot(aes(x = t,  y = y))+
  geom_line(color="cyan")
)
```

### M10

```{r}
iris %>% 
  bind_cols(iris) %>% 
  mutate(across(where(is.numeric), round, digits = 2)) %>%
  datatable(
    rownames = FALSE,
    extensions = c('Buttons'),
    options = list(
      dom = 'Bfrtip',
      buttons = c('excel'),
      scrollX = TRUE
    )
  )

```


### M11


### M12

Column {data-width=100}
-----------------------------------------------------------------------


### M13

```{r}
valueBox(
  value = 3.1415,
  caption = "Potencia",
  icon = "fa-area-chart",
  color = "orange"
)
```


### M14

```{r}
valueBox(
  value = 4673,
  caption = "Libras",
  icon = "fa-bar-chart",
  color = "#00674a"
)
```

### M15

```{r}
valueBox(
  value = 8,
  caption = "Metros",
  icon = "fa-line-chart",
  color = "cadetblue"
)
```

### M16

```{r}
valueBox(
  value = 0.0297,
  caption = "Ampere",
  icon = " fa-divide",
  color = "#00b300"
)
```


Column {data-width=100}
-----------------------------------------------------------------------


### M17

```{r}
valueBox(
  value = 0.91,
  caption = "mol/l",
  icon = "fa-not-equal",
  color = "#ff3333"
)
```


### M18

```{r}
valueBox(
  value = 427,
  caption = "segundos",
  icon = "fa-subscript",
  color = "#003366"
)
```

### M19

```{r}
valueBox(
  value = 303,
  caption = "W",
  icon = "fa-calculator",
  color = "#751aff"
)
```

### M20

```{r}
valueBox(
  value = 0.07,
  caption = "N",
  icon = "fa-calculator",
  color = "#c2c2a3"
)
```