---
title: "Corruption Perception Index 2017 : Corruption Perception Index trend worldwide and it's  representation with various factors "

output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    source_code: embed
---

```{r setup, include=FALSE}
library(flexdashboard)
library(ggplot2)
library(maps)
library(tidyverse)
library(ggiraph)
library(widgetframe)
library(ggthemes)
library(plotly)
library(viridis)
library(DT)
library(scales)
library(plotly)
setwd("C:/Study material/Data Visualisation/Assignment 3")
Plot1<-read.csv("Corruption_Spatial.csv")
All_data<-read.csv("All_vs.csv")
Fig2_data<-read.csv("Topclean.csv")
Fig3_data<-read.csv("Topcorrupt.csv")
```

Dashboard
=======================================================================

Row
-----------------------------------------------------------------------

### Global Corruption Perception Index with World Ranking. Scores are on a scale of 0-100, where 0 means that a country is recognized as highly corrupt.

```{r}
fig1 <- plot_ly(Plot1, locations = ~Code, z = ~CPI,
                  type='choropleth', color = ~CPI, colors = 'Purples',
                  text = ~paste("Country:", `Entity`,
                                '
CPI Rank:', `RANK`, 
                                '
Corruption Perception Index:', `CPI`))
  
  fig1 <- fig1 %>% colorbar(title = 'CPI Scale', x =-0.2, y =1) 
  
  fig1 <- fig1 %>% layout(title = 'Corruption Perception Index 2017',
                          height = 350, margin = list(t = 50),
                          geo = list(showframe = FALSE, showcoastlines = FALSE))
  fig1

```


### Representation of various indicators with Corruption Perception Index

```{r}

fig2 <- plot_ly(All_data) %>%
  
  add_markers(x = ~`HDI`,y = ~CPI,name = "HDI vs. CPI", text =
                ~paste("Country:", `Entity`, '
CPI Rank:', `RANK`)) %>%
  
  add_markers(x =~`Average_years_of_schooling`,y = ~CPI , name = "Avg yrs of schooling vs. CPI", text =
                ~paste("Country:", `Entity`, '
CPI rank:', `RANK`), visible =FALSE) %>%
  
 
  add_markers(x = ~`GDP`, name ="GDP per capita vs CPI",y = ~CPI, text =
                ~paste("Country:", `Entity`,'
CPI Rank:', `RANK`), visible = FALSE) %>%
  
  
  layout(
    title = "Corruption Perception Index vs. Various Indicators",
    xaxis = list( title ="Human Development Index", range=c(0.3,1)),
    yaxis = list(title = "Corruption Perception Index"),
    
    showlegend = FALSE,
    
    updatemenus = list(
      list(
        y = 1, x = -0.1,
        buttons = list(
          list(method = "update",
               args = list(list(visible = list(T, F, F)),
                           list(xaxis = list(title = "Human Development Index", range=c(0.3,1)))),
               label = "HDI" ),
          
          list(method = "update",
               args = list(list(visible = list(F, T, F)),
                           list(xaxis = list(title = "Average years of schooling"))),
               label = "Schooling"),
          
         list(method = "update",
               args = list(list(visible = list(F, F, T)),
                           list(xaxis = list(title = "GDP per capita", range=c(0,50000)))),
               label = "GDP")
          ))
    )
  )

fig2
```

Row
-----------------------------------------------------------------------

### Countries who are top CPI scorers are all Developed Nations

```{r}
Dev<- plot_ly(Fig2_data) %>%
  
  
  
  add_lines(x = ~Year, y = ~CPI, group = ~Entity,
            color = ~Entity) %>%
  
  layout( title = "CPI trend of 10 most Clean countries",
          yaxis = list(zeroline = FALSE, title = "CPI", range = c(78, 95)),
          xaxis = list(zeroline = FALSE, title = "Year"))


Dev
```

### Countries who are least scorers are all Developing or Underdeveloped Nations

```{r}
Undev<- plot_ly(Fig3_data) %>%
  
  
  
  add_lines(x = ~Year, y = ~CPI, group = ~Entity,
            color = ~Entity) %>%
  
  layout( title = "CPI trend of 10 most Corrupt countries",
          yaxis = list(zeroline = FALSE, title = "CPI", range = c(0, 30)),
          xaxis = list(zeroline = FALSE, title = "Year"))


Undev

```

References
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Row
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### References

* 2017 - CPI. Transparency.org. (2020). Retrieved 2 November 2020, from https://www.transparency.org/en/cpi/2017.

* Human Development Data (1990-2018) | Human Development Reports. Hdr.undp.org. (2020). Retrieved 2 November 2020, from http://hdr.undp.org/en/data.

* World Development Indicators (WDI) | Data Catalog. Datacatalog.worldbank.org. (2020). Retrieved 2 November 2020, from https://datacatalog.worldbank.org/dataset/world-development-indicators.