Rikolto_dashboard.Rmd

---
title: "RIKOLTO"
output: flexdashboard::flex_dashboard
---


```{r setup, include=FALSE}
library(flexdashboard)
source("color.R")
source("map.R")
source("Demographics.R")
source("ProductionCommercialization.R")
source("PlanningInvestment.R")
source("Resilience.R")
source("Inclusion.R")
library(DT)
```
<style>                     
.navbar {
  background-color:#b6bf00;
  border-color:white;
}
.navbar-brand {
color:black!important;
}
</style> 
Map
=====================================  
 
### Rikolto Participants
    
```{r}
map
```

Demographics 
=====================================     
    
Column {data-width=600}
-------------------------------------
    
### Number of farmers using intensive, intercropping, monocrop and non-intensive rice system (only 1 rice season per year) production type by commodity
    
```{r}
ggplotly(prod_org) %>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```
   
Column {data-width=400}
-------------------------------------
   
### Gender counts and ratio by commodity

```{r}
counts %>% 
    DT::datatable()
```   
 
### Number of farmers less than or equal to 35 years old and number of farmers over 35 years old by commodity

    
```{r}
ggplotly(age) %>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```


Production & Commercialization {data-orientation=rows}
=====================================     
   
Row 
-------------------------------------

### Distribution of sizes of the farmland dedicated to cultivation by commodity

```{r}
farmland_plot
```

### Distribution of how many tons of commodity farmers produced last year by commodity

```{r}
ggplotly(p)%>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```

Row 
-------------------------------------
   
### Relationaship between tonnes of commodity produced and sold by commodity (click on the commodity on the legend to single it out)

```{r}
ggplotly(commercialization_plot)%>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```   
    
### Average response to a question "How many tons of your commodity did you produce last year?" by farmer organization 

```{r}
ggplotly(l)%>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```

Planning & Investment {data-orientation=rows}
=====================================     
   
Row 
-------------------------------------

### Percentage of farmers planning production of their focus crop based on the following aspects (hover over color segments to see the aspects)

```{r}
ggplotly(drivers_plot)%>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```

### Distribution of sources of access to credits or loans

```{r}
access_plot
```

Row 
-------------------------------------
   
### Number and proportion of farmers listing specific reason for why they did not have access to credits or loans

```{r}
why_no_acess %>% 
    DT::datatable()
```   
    
### Number of farmers listing the following aspects that motivate any new investments to improve production of the focus crop

```{r}
ggplotly(k)%>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```

Inclusiveness & Gender 
=====================================     
   
Column
-------------------------------------

### Participation in the value chain: Who typically represents the household when trainings are offered by farmer organisation

```{r}
ggplotly(training_plot)%>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```

### Participation in the value chain - opinion by age and sex: Compared with other members, is your opinion respected/taken into account within your farmer organisation?

```{r}
opinion_plot
```

Column
-------------------------------------
   
### Average degree of control of decision making on how the income from the focus crop is used by organisation and respondent's gender

```{r}
ggplotly(decisions_plot)%>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```

Resilience 
=====================================     
   
Column 
-------------------------------------

###  Average frequency of access to various information by commodity (from 0:I have no access to this information to 3:I can access this information any time I want)

```{r}
ggplotly(info_plot)%>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```

### Distribution of the popularity of shock copying strategies by commodity

```{r}
ggplotly(strategy)%>% 
  config(autosizable=TRUE, fillFrame=TRUE, displayModeBar=FALSE)
```

Column
-------------------------------------
   
### Intensity and frequency of shocks by organisation and commodity

```{r}
shock %>% 
    DT::datatable(options = list(
  pageLength = 25))
```