---
title: "Covid-19 Cases in Nepal" 
author: "Krishna Kumar Shrestha"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    source_code: embed
    vertical_layout: fill
---

```{r setup, include=FALSE}
#------------------ Packages ------------------
library(flexdashboard)


library(tidyverse)
library(RColorBrewer)


confirmed_color <- "purple"
active_color <- "#1f77b4"
recovered_color <- "forestgreen"
death_color <- "red"
#------------------ Data ------------------
library(dplyr)
library(jsonlite)
library(lubridate)

df <- fromJSON("https://nepalcorona.info/api/v1/data/nepal") %>%
  as.data.frame() %>%
  select(1:9)

```


```{r}
x<- "2020-07-01"
x<-ymd(x)
df1<- fromJSON("https://data.nepalcorona.info/api/v1/covid/timeline") 
df1$date <- ymd(df1$date)

df1<- df1%>%
  
  filter(date <= Sys.Date() & date > x) 


```



Summary
=======================================================================

Row {data-width=400}
-----------------------------------------------------------------------

### confirmed {.value-box}

```{r}

valueBox(
  value = paste(format(sum(df$tested_positive), big.mark = ","), "", sep = " "),
  caption = "Total confirmed cases",
  icon = "fas fa-user-md",
  color = confirmed_color
)
```


### death {.value-box}

```{r}

valueBox(
  value = paste(format(sum(df$deaths, na.rm = TRUE), big.mark = ","), " (",
    round(100 * df$deaths / df$tested_positive,3),
    "%)",
    sep = ""
  ),
  caption = "Death cases (death rate)",
  icon = "fas fa-heart-broken",
  color = death_color
)
```


### recovered {.value-box}

```{r}

valueBox(
  value = paste(format(sum(df$recovered, na.rm = TRUE), big.mark = ","), " (",
    round(100 * df$recovered / df$tested_positive,3),
    "%)",
    sep = ""
  ),
  caption = "Recovered cases (recovered rate)",
  icon= "fas fa-heartbeat",
  
  color = "green"
)
```


### PCR testing {.value-box}

```{r}

valueBox(
  value = paste(format((df$tested_total), big.mark = ","), "", sep = " "),
  caption = "Total PCR testing",
  icon = "fas fa-user-md",
  color = "pink"
)
```

Row {data-width=400}
-----------------------------------------------------------------------
### New cases {.value-box}

```{r}
aa<-df1
aa <- aa %>% filter(date == Sys.Date()-1)
valueBox(
  value = paste(format((aa$newCases), big.mark = ","), "", sep = " "),
  caption = "New conformed cases",
  icon = "fas fa-user-md",
  color = confirmed_color
)
```



  
    
    

### New recover {.value-box}

```{r}

valueBox(
  value = paste(format((aa$newRecoveries), big.mark = ","), "", sep = " "),
  caption = "New recovered cases",
  icon = "fas fa-heartbeat",
  color = "green"
)
```







Daily cases
=======================================================================
  
  
  
-------------------------------------
```{r}
df1 %>%
  plotly::plot_ly() %>%
  plotly::add_trace(
    x = ~date,
    y = ~newCases,
    text = ~newCases,
    textposition = 'auto',
    type = "bar",
    name = "Confirmed") %>% 
  # plotly::add_trace(
  #   x = ~date,
  #   y = ~Malawi,
  #   type = "bar",
  #   name = "Recovered")%>% 
  #  plotly::add_trace(
  #   x = ~date,
  #   y = ~Malawi,
  #   type = "bar",
  #   name = "Deaths")%>% 
  plotly::layout(
    title = "",
    legend = list(x = 0.1, y = 0.9),
    yaxis = list(title = "New confirmed cases"),
    xaxis = list(title = "Date"))

```




 Trend
======================================================================



-------------------------------------

    
```{r}


df2<- fromJSON("https://data.nepalcorona.info/api/v1/covid/timeline")
df2$date <-ymd(df2$date)
df2 <- df2 %>% filter(date <= Sys.Date())
plotly::plot_ly(data = df2) %>%
  plotly::add_trace(
    x = ~date,
    y = ~totalCases,
    type = "scatter",
    mode = "lines+markers",
    name = "Confirmed",
    line = list(color = active_color),
    marker = list(color = active_color)
  ) %>%
  plotly::add_trace(
    x = ~date,
    y = ~totalDeaths,
    type = "scatter",
    mode = "lines+markers",
    name = "Death",
    line = list(color = death_color),
    marker = list(color = death_color)
  ) %>%
  
  plotly::add_trace(
    x = ~date,
    y = ~totalRecoveries,
    type = "scatter",
    mode = "lines+markers",
    name = "Recovered",
    line = list(color = "black"),
    marker = list(color ="black")
  ) %>%
  
  plotly::layout(
    title = "",
    yaxis = list(title = "Cumulative number of cases"),
    xaxis = list(title = "Date"),
    legend = list(x = 0.1, y = 0.9),
    hovermode = "compare"
  )
```









About
=======================================================================
  
  **The Covid-19 Dashboard for Nepal**
  
  This  provides an overview of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) pandemic. This dashboard is built with R using the R Markdown framework and was adapted from this [dashboard](https://ramikrispin.github.io/coronavirus_dashboard/){target="_blank"} by Rami Krispin.


**Data**
  
  The input data for this dashboard is available from the [`{coronavirus}`](https://nepalcorona.com/data/api){target="_blank"} .
  
 

The data and dashboard are refreshed on a daily basis.


**Update**
  
  The data is as of `r format(max(df1$date), "%A %B %d, %Y")` and the dashboard has been updated on `r format(Sys.time(), "%A %B %d, %Y")`.