Is this what you were after? require(plotly) df <- data.frame(x = runif(200), y = runif(200), z = runif(200)) p <- plot_ly(df, x = ~x, y = ~y, mode = “markers”, name = “A”, visible = T) %>% layout( title = “Drop down menus – Styling”, xaxis = list(domain = c(0.1, 1)), yaxis = list(title = … Read more
plotly version 4.x As of version 4, plotly renderers know about Colab, so the following is sufficient to display a figure in both Colab and Jupyter (and other notebooks like Kaggle, Azure, nteract): import plotly.graph_objects as go fig = go.Figure( go.Scatter(x=[1,2,3], y=[1,3,2] ) ) fig.show() plotly version 3.x Here’s an example showing the use of … Read more
There are two main ways to do this (using either data or ‘paper’ coordinates). Assuming data coordinates, the easiest current way is via add_segments(): plot_ly() %>% add_segments(x = 4, xend = 4, y = 0, yend = 10) %>% add_segments(x = 3, xend = 5, y = 5, yend = 5) Notice how we’ve hard … Read more
First, if an explanation of the broader differences between go and px is required, please take a look here and here. And if absolutely no explanations are needed, you’ll find a complete code snippet at the very end of the answer which will reveal many of the powers with colors in plotly.express Part 1: The … Read more
The answer: In many situations, using an approach with df.to_dict() will do the job perfectly! Here are two cases that come to mind: Case 1: You’ve got a dataframe built or loaded in Python from a local source Case 2: You’ve got a table in another application (like Excel) The details: Case 1: You’ve got … Read more