Greetings,

I am using your codes modified by Antoine Soetewey to create a New Dashboard for Haiti as this country lacks a good dashboard https://statsandr.com/blog/how-to-create-a-simple-coronavirus-dashboard-specific-to-your-country-in-r/

When knitting to flexdashboard I am getting the following error:

Quitting from lines 156-185 (Haiti-Coronavirus-Dashboard.Rmd) Error in validateCssUnit(sizeInfo$width) : CSS units must be a single-element numeric or character vector Calls: ... -> need_screenshot -> toHTML -> validateCssUnit In addition: Warning message: package 'flexdashboard' was built under R version 4.0.3 Execution halted

I am using RStudio Version 1.3.1093. Do you have an idea why I am getting this error message and how to fix it. I would be very grateful to you.

The codes are below:

Best,

Patrick

title: "Coronavirus in Haiti" author: "Patrick Stephenson" output: flexdashboard::flex_dashboard: orientation: rows

social: ["facebook", "twitter", "linkedin"]

source_code: embed
vertical_layout: fill

#------------------ Packages ------------------
library(flexdashboard)
# install.packages("devtools")
# devtools::install_github("RamiKrispin/coronavirus", force = TRUE)
library(coronavirus)
data(coronavirus)
# View(coronavirus)
# max(coronavirus$date)
`%>%` <- magrittr::`%>%`
#------------------ Parameters ------------------
# Set colors
# https://www.w3.org/TR/css-color-3/#svg-color
confirmed_color <- "purple"
active_color <- "#1f77b4"
recovered_color <- "forestgreen"
death_color <- "red"
#------------------ Data ------------------
df <- coronavirus %>%
  # dplyr::filter(date == max(date)) %>%
  dplyr::filter(country == "Haiti") %>%
  dplyr::group_by(country, type) %>%
  dplyr::summarise(total = sum(cases)) %>%
  tidyr::pivot_wider(
    names_from = type,
    values_from = total
  ) %>%
  # dplyr::mutate(unrecovered = confirmed - ifelse(is.na(recovered), 0, recovered) - ifelse(is.na(death), 0, death)) %>%
  dplyr::mutate(unrecovered = confirmed - ifelse(is.na(death), 0, death)) %>%
  dplyr::arrange(-confirmed) %>%
  dplyr::ungroup() %>%
  dplyr::mutate(country = dplyr::if_else(country == "United Arab Emirates", "UAE", country)) %>%
  dplyr::mutate(country = dplyr::if_else(country == "Mainland China", "China", country)) %>%
  dplyr::mutate(country = dplyr::if_else(country == "North Macedonia", "N.Macedonia", country)) %>%
  dplyr::mutate(country = trimws(country)) %>%
  dplyr::mutate(country = factor(country, levels = country))
df_daily <- coronavirus %>%
  dplyr::filter(country == "Haiti") %>%
  dplyr::group_by(date, type) %>%
  dplyr::summarise(total = sum(cases, na.rm = TRUE)) %>%
  tidyr::pivot_wider(
    names_from = type,
    values_from = total
  ) %>%
  dplyr::arrange(date) %>%
  dplyr::ungroup() %>%
  #dplyr::mutate(active = confirmed - death - recovered) %>%
  dplyr::mutate(active = confirmed - death) %>%
  dplyr::mutate(
    confirmed_cum = cumsum(confirmed),
    death_cum = cumsum(death),
    # recovered_cum = cumsum(recovered),
    active_cum = cumsum(active)
  )
df1 <- coronavirus %>% dplyr::filter(date == max(date))

Summary

Row {data-width=400}

confirmed {.value-box}

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

death {.value-box}

valueBox(
  value = paste(format(sum(df$death, na.rm = TRUE), big.mark = ","), " (",
    round(100 * sum(df$death, na.rm = TRUE) / sum(df$confirmed), 1),
    "%)",
    sep = ""
  ),
  caption = "Death cases (death rate)",
  icon = "fas fa-heart-broken",
  color = death_color
)

Row

Daily cumulative cases by type (Haiti only)

plotly::plot_ly(data = df_daily) %>%
  plotly::add_trace(
    x = ~date,
    # y = ~active_cum,
    y = ~confirmed_cum,
    type = "scatter",
    mode = "lines+markers",
    # name = "Active",
    name = "Confirmed",
    line = list(color = active_color),
    marker = list(color = active_color)
  ) %>%

  # plotly::add_annotations(
  #   x = as.Date("2020-02-04"),
  #   y = 1,
  #   text = paste("First case"),
  #   xref = "x",
  #   yref = "y",
  #   arrowhead = 5,
  #   arrowhead = 3,
  #   arrowsize = 1,
  #   showarrow = TRUE,
  #   ax = -10,
  #   ay = -90
  # ) %>%

  plotly::layout(
    title = "",
    yaxis = list(title = "Cumulative number of cases"),
    xaxis = list(title = "Date"),
    legend = list(x = 0.1, y = 0.9),
    hovermode = "compare"
  )

Comparison

Column {data-width=400}

Daily new confirmed cases

daily_confirmed <- coronavirus %>%
  dplyr::filter(type == "confirmed") %>%
  dplyr::filter(date >= "2020-02-29") %>%
  dplyr::mutate(country = country) %>%
  dplyr::group_by(date, country) %>%
  dplyr::summarise(total = sum(cases)) %>%
  dplyr::ungroup() %>%
  tidyr::pivot_wider(names_from = country, values_from = total)
#----------------------------------------
# Plotting the data
daily_confirmed %>%
  plotly::plot_ly() %>%
  plotly::add_trace(
    x = ~date,
    y = ~Haiti,
    type = "scatter",
    mode = "lines+markers",
    name = "Haiti"
  ) %>%
  # plotly::add_trace(
  #   x = ~date,
  #   y = ~France,
  #   type = "scatter",
  #   mode = "lines+markers",
  #   name = "France"
  # ) %>%
  # plotly::add_trace(
  #   x = ~date,
  #   y = ~Spain,
  #   type = "scatter",
  #   mode = "lines+markers",
  #   name = "Spain"
  # ) %>%
  plotly::add_trace(
    x = ~date,
    y = ~`Dominican Republic`,
    type = "scatter",
    mode = "lines+markers",
    name = "Dominican Republic"
  ) %>%
  plotly::add_trace(
    x = ~date,
    y = ~Jamaica,
    type = "scatter",
    mode = "lines+markers",
    name = "Jamaica"
  ) %>%
  plotly::add_trace(
    x = ~date,
    y = ~Cuba,
    type = "scatter",
    mode = "lines+markers",
    name = "Cuba"
  ) %>%
  plotly::layout(
    title = "",
    legend = list(x = 0.7, y = 0.9),
    yaxis = list(title = "New confirmed cases"),
    xaxis = list(title = "Date"),
    # paper_bgcolor = "black",
    # plot_bgcolor = "black",
    # font = list(color = 'white'),
    hovermode = "compare",
    margin = list(
      # l = 60,
      # r = 40,
      b = 10,
      t = 10,
      pad = 2
    )
  )

Cases distribution by type

df_EU <- coronavirus %>%
  # dplyr::filter(date == max(date)) %>%
  dplyr::filter(country == "Haiti" |
    country == "Dominican Republic " |
    country == "Jamaica" |
    country == "Cuba") %>%
  dplyr::group_by(country, type) %>%
  dplyr::summarise(total = sum(cases)) %>%
  tidyr::pivot_wider(
    names_from = type,
    values_from = total
  ) %>%
  # dplyr::mutate(unrecovered = confirmed - ifelse(is.na(recovered), 0, recovered) - ifelse(is.na(death), 0, death)) %>%
  dplyr::mutate(unrecovered = confirmed - ifelse(is.na(death), 0, death)) %>%
  dplyr::arrange(confirmed) %>%
  dplyr::ungroup() %>%
  dplyr::mutate(country = dplyr::if_else(country == "United Arab Emirates", "UAE", country)) %>%
  dplyr::mutate(country = dplyr::if_else(country == "Mainland China", "China", country)) %>%
  dplyr::mutate(country = dplyr::if_else(country == "North Macedonia", "N.Macedonia", country)) %>%
  dplyr::mutate(country = trimws(country)) %>%
  dplyr::mutate(country = factor(country, levels = country))
plotly::plot_ly(
  data = df_EU,
  x = ~country,
  # y = ~unrecovered,
  y = ~ confirmed,
  # text =  ~ confirmed,
  # textposition = 'auto',
  type = "bar",
  name = "Confirmed",
  marker = list(color = active_color)
) %>%
  plotly::add_trace(
    y = ~death,
    # text =  ~ death,
    # textposition = 'auto',
    name = "Death",
    marker = list(color = death_color)
  ) %>%
  plotly::layout(
    barmode = "stack",
    yaxis = list(title = "Total cases"),
    xaxis = list(title = ""),
    hovermode = "compare",
    margin = list(
      # l = 60,
      # r = 40,
      b = 10,
      t = 10,
      pad = 2
    )
  )

Map

World map of cases (use + and - icons to zoom in/out)

# map tab added by Art Steinmetz
library(leaflet)
library(leafpop)
library(purrr)
cv_data_for_plot <- coronavirus %>%
  # dplyr::filter(country == "Haiti") %>%
  dplyr::filter(cases > 0) %>%
  dplyr::group_by(country, province, lat, long, type) %>%
  dplyr::summarise(cases = sum(cases)) %>%
  dplyr::mutate(log_cases = 2 * log(cases)) %>%
  dplyr::ungroup()
cv_data_for_plot.split <- cv_data_for_plot %>% split(cv_data_for_plot$type)
pal <- colorFactor(c("orange", "red", "green"), domain = c("confirmed", "death", "recovered"))
map_object <- leaflet() %>% addProviderTiles(providers$Stamen.Toner)
names(cv_data_for_plot.split) %>%
  purrr::walk(function(df) {
    map_object <<- map_object %>%
      addCircleMarkers(
        data = cv_data_for_plot.split[[df]],
        lng = ~long, lat = ~lat,
        #                 label=~as.character(cases),
        color = ~ pal(type),
        stroke = FALSE,
        fillOpacity = 0.8,
        radius = ~log_cases,
        popup = leafpop::popupTable(cv_data_for_plot.split[[df]],
          feature.id = FALSE,
          row.numbers = FALSE,
          zcol = c("type", "cases", "country", "province")
        ),
        group = df,
        #                 clusterOptions = markerClusterOptions(removeOutsideVisibleBounds = F),
        labelOptions = labelOptions(
          noHide = F,
          direction = "auto"
        )
      )
  })
map_object %>%
  addLayersControl(
    overlayGroups = names(cv_data_for_plot.split),
    options = layersControlOptions(collapsed = FALSE)
  )

About

The Coronavirus Dashboard: the case of Haiti

This Coronavirus dashboard: the case of Haiti provides an overview of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic for Haiti. This dashboard is built with R using the R Makrdown framework and was adapted from this dashboard{target="_blank"} by Rami Krispin.

Code

The code behind this dashboard is available on GitHub{target="_blank"}.

Data

The input data for this dashboard is the dataset available from the {coronavirus}{target="_blank"} R package. Make sure to download the development version of the package to have the latest data:

install.packages("devtools")
devtools::install_github("RamiKrispin/coronavirus")

The raw data is pulled from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository{target="_blank"}.

Information

More information about this dashboard (and how to replicate it for your own country) can be found in this article.

Update

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

Go back to statsandr.com (blog) or antoinesoetewey.com (personal website).

I have circumvented part of the problem for the first plot, in Daily cumulative cases by type (Haiti only) I have replaced

plotly::plot_ly(data = df_daily) %>%

with: plotly::plot_ly(data = df_daily, height= 400, width=800 ) %>%

But this strategy does not work for the other plots

Hi @stepminer, could you please send me a link to the code on github?

Greetings Rami,

Thanks for the great codes in the coronavirus dashboard. Just for your information, in case you are asked the same question: The issue was with the old htmlwidgets package in RStudio. After a reinstall of the newest fixed version, everything is running smoothly (no error codes).

Thanks again for your time and codes. The dashboard is now public on Rpubs and I will be updating it almost daily (when you refresh the data). Have a look and please leave a comment, that will be appreciated.

https://rpubs.com/stepminer/709695

Best,

Pat

On Sat, Jan 9, 2021 at 12:27 AM Rami Krispin notifications@github.com wrote:

Hi @stepminer https://github.com/stepminer, could you please send me a link to the code on github?

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/RamiKrispin/coronavirus_dashboard/issues/21#issuecomment-757099730, or unsubscribe https://github.com/notifications/unsubscribe-auth/AQ3O6KUQ72ZAIDL6NPSF6QDSY7SMJANCNFSM4VPLGXCQ .

Thanks Pat,

Happy to see that you were able to solve and deploy the dashboard. Nice dashboard!

Stay safe, Rami

Hello Rami,

Hope you are doing well. Sorry to bother you again, I am trying to add a new panel to the Haiti dashboard for Active cases. I am getting a logic error using your codes or an alternative one:

The added code after line 139 is below is as per your codes template:

active {.value-box}

valueBox(
    value = paste(format(sum(df$unrecovered, na.rm = TRUE), big.mark =
","), "
 (",
                  round(100 * sum(df$unrecovered, na.rm = TRUE) /
sum(df$confirmed), 1),"%)",
                  sep = "" ),
    caption = "Active cases (% of total cases)", icon = "fas fa-ambulance",

    color = active_color
)

Alternatively I have tried:

active {.value-box}

valueBox(
    value = paste(format(sum(df$active, na.rm = TRUE), big.mark = ","), "
 (",
                  round(100 * sum(df$active, na.rm = TRUE) /
sum(df$confirmed), 1),"%)",
                  sep = "" ),
    caption = "Active cases (% of total cases)", icon = "fas fa-ambulance",

    color = active_color
)

I am getting either a high number (with your codes) or zero with the alternative codes.

I would be grateful for your advice. I am attaching the .Rmd file as well as a picture of the resulting codes.

Best,

Pat

On Mon, Jan 18, 2021 at 4:21 PM Rami Krispin notifications@github.com wrote:

Closed #21 https://github.com/RamiKrispin/coronavirus_dashboard/issues/21.

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/RamiKrispin/coronavirus_dashboard/issues/21#event-4219866230, or unsubscribe https://github.com/notifications/unsubscribe-auth/AQ3O6KUSVXTHKDDTO6STF7TS2SQ4PANCNFSM4VPLGXCQ .

Forget about it Rami,

I just modified line 47 of Antoine's codes and it works and is accurate

dplyr::mutate(unrecovered = confirmed - recovered - death , ifelse(is.na(death), 0, death)) %>%

Thanks again,

Best,

Pat

https://rpubs.com/stepminer/709695

On Tue, Jan 19, 2021 at 5:37 AM Pat Stephenson stepminer@gmail.com wrote:

Hello Rami,

Hope you are doing well. Sorry to bother you again, I am trying to add a new panel to the Haiti dashboard for Active cases. I am getting a logic error using your codes or an alternative one:

The added code after line 139 is below is as per your codes template:

active {.value-box}
valueBox(
    value = paste(format(sum(df$unrecovered, na.rm = TRUE), big.mark =
","), "
 (",
                  round(100 * sum(df$unrecovered, na.rm = TRUE) /
sum(df$confirmed), 1),"%)",
                  sep = "" ),
    caption = "Active cases (% of total cases)", icon = "fas fa-ambulance",

    color = active_color
)
Alternatively I have tried:

active {.value-box}
valueBox(
    value = paste(format(sum(df$active, na.rm = TRUE), big.mark = ","), "
 (",
                  round(100 * sum(df$active, na.rm = TRUE) /
sum(df$confirmed), 1),"%)",
                  sep = "" ),
    caption = "Active cases (% of total cases)", icon = "fas fa-ambulance",

    color = active_color
)
I am getting either a high number (with your codes) or zero with the alternative codes.

I would be grateful for your advice. I am attaching the .Rmd file as well as a picture of the resulting codes.

Best,

Pat

On Mon, Jan 18, 2021 at 4:21 PM Rami Krispin notifications@github.com wrote:

Closed #21 https://github.com/RamiKrispin/coronavirus_dashboard/issues/21.

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/RamiKrispin/coronavirus_dashboard/issues/21#event-4219866230, or unsubscribe https://github.com/notifications/unsubscribe-auth/AQ3O6KUSVXTHKDDTO6STF7TS2SQ4PANCNFSM4VPLGXCQ .

Hello Rami,

Sorry to bother you again. Did you change something in the coronavirus data structure? I am getting an error at line 215 Error: Column 1 must be named.


daily_confirmed <- coronavirus %>%
  dplyr::filter(type == "confirmed") %>%
  dplyr::filter(date >= "2020-02-29") %>%
  dplyr::mutate(country = country) %>%
  dplyr::group_by(date, country) %>%
  dplyr::summarise(total = sum(cases)) %>%
  dplyr::ungroup() %>%
  tidyr::pivot_wider(names_from = country, values_from = total)

I am attaching a screenshot as well as the Rmd file.

Thanks for your advice.

Pat

On Tue, Jan 19, 2021 at 7:39 AM Pat Stephenson <stepminer@gmail.com> wrote:

> Forget about it Rami,
>
>   I just modified line 47 of Antoine's codes and it works and is accurate
>
>   dplyr::mutate(unrecovered = confirmed - recovered - death , ifelse(is.na(death),
> 0, death)) %>%
>
> Thanks again,
>
> Best,
>
> Pat
>
> https://rpubs.com/stepminer/709695
>
> On Tue, Jan 19, 2021 at 5:37 AM Pat Stephenson <stepminer@gmail.com>
> wrote:
>
>> Hello Rami,
>>
>> Hope you are doing well. Sorry to bother you again, I am trying to add a
>> new panel to the Haiti dashboard for Active cases. I am getting a logic
>> error using your codes or an alternative one:
>>
>>
>> The added code after line 139 is below is as per your codes template:
>>
>> ### active {.value-box}
>>
>> ```{r}
>> valueBox(
>>     value = paste(format(sum(df$unrecovered, na.rm = TRUE), big.mark =
>> ","), "
>>  (",
>>                   round(100 * sum(df$unrecovered, na.rm = TRUE) /
>> sum(df$confirmed), 1),"%)",
>>                   sep = "" ),
>>     caption = "Active cases (% of total cases)", icon = "fas
>> fa-ambulance",
>>
>>     color = active_color
>> )
>> ```
>>
>> Alternatively I have tried:
>>
>> ### active {.value-box}
>>
>> ```{r}
>> valueBox(
>>     value = paste(format(sum(df$active, na.rm = TRUE), big.mark = ","), "
>>  (",
>>                   round(100 * sum(df$active, na.rm = TRUE) /
>> sum(df$confirmed), 1),"%)",
>>                   sep = "" ),
>>     caption = "Active cases (% of total cases)", icon = "fas
>> fa-ambulance",
>>
>>     color = active_color
>> )
>> ```
>> I am getting either a high number (with your codes) or zero with the
>> alternative codes.
>>
>> I would be grateful for your advice. I am attaching the .Rmd file as well
>> as a picture of the resulting codes.
>>
>> Best,
>>
>> Pat
>>
>> On Mon, Jan 18, 2021 at 4:21 PM Rami Krispin <notifications@github.com>
>> wrote:
>>
>>> Closed #21
>>> <https://github.com/RamiKrispin/coronavirus_dashboard/issues/21>.
>>>
>>> —
>>> You are receiving this because you were mentioned.
>>> Reply to this email directly, view it on GitHub
>>> <https://github.com/RamiKrispin/coronavirus_dashboard/issues/21#event-4219866230>,
>>> or unsubscribe
>>> <https://github.com/notifications/unsubscribe-auth/AQ3O6KUSVXTHKDDTO6STF7TS2SQ4PANCNFSM4VPLGXCQ>
>>> .
>>>
>>

RamiKrispin / coronavirus_dashboard

Error in validateCssUnit(sizeInfo$width) : #21

social: ["facebook", "twitter", "linkedin"]

Summary

Row {data-width=400}

confirmed {.value-box}

death {.value-box}

Row

Daily cumulative cases by type (Haiti only)

Comparison

Column {data-width=400}

Daily new confirmed cases

Cases distribution by type

Map

World map of cases (use + and - icons to zoom in/out)

About

active {.value-box}

active {.value-box}

active {.value-box}

active {.value-box}