1. Basic Scatterplot

plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, type = "scatter", mode = "markers")

2. Advanced Scatterplot with Colors and Tooltips

plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length,
        type = "scatter", mode = "markers",
        color = ~Species, text = ~paste("Sepal.Width:", Sepal.Width))

3. 3D Scatterplot

plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, z = ~Sepal.Width,
        color = ~Species, type = "scatter3d", mode = "markers")

4. Line Graph for Time Series Data

time <- seq.Date(from = as.Date("2023-01-01"), by = "month", length.out = 12)
values <- rnorm(12)

plot_ly(x = ~time, y = ~values, type = "scatter", mode = "lines+markers")

5. Histogram (Visualizing Data Distribution)

plot_ly(data = iris, x = ~Petal.Length, type = "histogram")

6. Boxplot (Comparing Distributions)

plot_ly(data = iris, y = ~Petal.Length, color = ~Species, type = "box")

7. Heatmap (2D Data Visualization)

z <- matrix(rnorm(100), nrow = 10)
plot_ly(z = ~z, type = "heatmap")

3D Surface Plot

z <- outer(seq(-2, 2, length.out = 30), seq(-2, 2, length.out = 30), function(x, y) x^2 + y^2)
plot_ly(z = ~z, type = "surface")

9. Choropleth Map (Geographic Visualization)

plot_ly(type = "choropleth",
        locations = c("USA", "CAN", "MEX"),
        locationmode = "country names",
        z = c(1000, 800, 600),
        colorscale = "Viridis")