# setup data
mycountries <- c("India", "Iran", "Iraq", "Italy")
varnames <- c("lifeExp","pop","gdpPercap")
Df2 <- gapminder::gapminder %>%
  dplyr::filter(country %in% mycountries) %>%
  tidyr::pivot_longer(cols = varnames, names_to = "Ecoregion", values_to = "Tpoint") %>%
  dplyr::mutate(Time = year, Species = country)

Df2$Species <- factor(Df2$Species, levels = mycountries)

# build plot
p <- filter(Df2, Ecoregion == unique(Df2$Ecoregion)[1]) %>%
  plot_ly(
    x = ~Time, y = ~Tpoint, color = ~Species, type = "scatter", mode = "lines"
  ) %>%
  layout(
    title = "Ecoregion Line Plots",
    xaxis = list(title = "Time"),
    yaxis = list(title = "Tpoint"),
    updatemenus = list(
      list(
        buttons = list(
          list(
            method = "restyle",
            args = list(list(
              x = Df2[Df2$Ecoregion == "lifeExp", "Time"],
              y = Df2[Df2$Ecoregion == "lifeExp", "Tpoint"],
              color = Df2[Df2$Ecoregion == "lifeExp", "Species"],
              type = "scatter",
              mode = "lines"
            ), 0L),
            label = "lifeExp"),
          list(
            method = "restyle",
            args = list(list(
              x = Df2[Df2$Ecoregion == "pop", "Time"],
              y = Df2[Df2$Ecoregion == "pop", "Tpoint"],
              color = Df2[Df2$Ecoregion == "pop", "Species"],
              type = "scatter",
              mode = "lines"
            ), 1L),
            label = "pop"),
          list(
            method = "restyle",
            args = list(list(
              x = Df2[Df2$Ecoregion == "gdpPercap", "Time"],
              y = Df2[Df2$Ecoregion == "gdpPercap", "Tpoint"],
              color = Df2[Df2$Ecoregion == "gdpPerCap", "Species"],
              type = "scatter",
              mode = "lines"
            ), 2L),
            label = "gdpPercap")
        )
      )
    )
  )

# Show the interactive plot
p