Second row as column headers using DT datatable in R shiny

[snt]

I have an output to be rendered in a shiny app using DT::datatable.

The output which currently looks like this and I want to use the second row as the column headers:

tab1:
          V1	  V2	  V3	  V4	  V5	  V6	  V7	  V8	
Month	Apr-17	May-17	Jun-17	Jul-17	Aug-17	Sep-17	Oct-17	Nov-17	
aaa	    116.719	120.404	120.26	123.431	117.327	110.742	114.811	117.34	
bbb	    76.118	75.976	76.215	76.134	77.19	78.519	78.258	74.522	

So when I want to use the row month as column headers I do the following:

   app1 <-reactive({ tab1()%>% .[-1,]})

And then I render it using datatable

 output$op1 <-renderDataTable({
    app1()
  })

I get the following output :

        V1	  V2	  V3	  V4	  V5	  V6	  V7	  V8	
aaa	    116.719	120.404	120.26	123.431	117.327	110.742	114.811	117.34	
bbb	    76.118	75.976	76.215	76.134	77.19	78.519	78.258	74.522	

How do I replace the v1,v2 by month names .Thank you.

[cderv]

I think you should prepare you data.frame before DT::datatable

• Add the first row as names for the DF
• delete the first row

With base R

df <- data.frame(V1 = c("Letter", "A", "B"), V2 = c("Number", "1", "2"), stringsAsFactors = FALSE)
names(df) <- df[1, ]
df <- df[-1, ]
df
#>   Letter Number
#> 2      A      1
#> 3      B      2

Created on 2018-08-13 by the reprex package (v0.2.0).

with tidyverse

library(tidyverse)
df <- tibble(V1 = c("Letter", "A", "B"), V2 = c("Number", "1", "2"))
df %>%
  # rename with first row
  set_names(df[1, ]) %>%
  # delete the first row
  slice(-1)
#> # A tibble: 2 x 2
#>   Letter Number
#>   <chr>  <chr> 
#> 1 A      1     
#> 2 B      2

Created on 2018-08-13 by the reprex package (v0.2.0).

[snt]

I get this error when I do this nm must be NULL or a character vector the same length as x

[cderv]

This error comes from set_names but I get no error on my side.
This pipe workflow should work. Are you sure the pipe executes correcly ?
Without pipe

library(tidyverse)
df <- set_names(df, nm = df[1, ])
df <- slice(df, -1)

Does it works ?
It is the same as df %>% set_names(df[1, ]) %>% slice(-1)

[snt]

I am pretty much sure the solution you provided is correct. A pre build up to what I am doing to get this point is

 intrc_pattern <-reactive({MyData %>%
      filter(Tab == "Interaction pattern" & Classification_Level ==  input$selected_class  &  Primary_family == input$selected_product &
               Metric_name == input$selected_metric ) %>%
      mutate(`pct` = as.numeric(as.character(Metric_Value))) %>%
          mutate(`Month` =  as.yearmon(Month_considered, "%b-%y")) %>%
      select(Month,`pct`,Secondary_family)%>%
      group_by(Month) %>% na.omit()
})


    intrc_pattern_reshape <-reactive({ dcast(intrc_pattern(), Month ~ Secondary_family, value.var="pct", fill=0)%>% t() %>% .[-1,]})

If i do use .[-1.] then my output is like this

And if I dont do it its like this

I am not sure if this is helpful without the data.