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I am attempting to create an interactive plot of hexbins where a user can click on a given hexbin and receive a list of all observations of the original data frame that were grouped in that clicked hexbin. Below is a MWE that seems pretty close to my goal. I am using Shiny, hexbin(), and ggplotly. app.R library(shiny) library(plotly) library(data.table) library(GGally) library(reshape2) library(hexbin) ui <- fluidPage( plotlyOutput("plot"), verbatimTextOutput("click") ) server <- function(input, output, session) { #Create data set.seed(1) bindata <- data.frame(x=rnorm(100), y=rnorm(100)) h <-

While plotting normal distribution graph of data, how can we put labels like in image below for percentage of data in each bin where each band has a width of 1 standard deviation using matplotlib/seaborn or plotly ? Currently, im plotting like this: hmean = np.mean(data) hstd = np.std(data) pdf = stats.norm.pdf(data, hmean, hstd) plt.plot(data, pdf) Although I've labelled the percentages between the quartiles, this bit of code may be helpful to do the same for the standard deviations. import numpy as np import scipy import pandas as pd from scipy.stats import norm import matplotlib.pyplot as

A plot's width is less than half when using ggplotly vs plot_ly to generate a plotly in a shiny app. Why is that? Is there a way to fix it so that ggplotly produces the plot with the same width as plot_ly or ggplot2? I have tried using the width parameter but that doesn't fix it. Output from the shiny app: library(shiny) library(plotly) library(ggplot2) ui <- fluidPage( titlePanel("plotly with shiny"), mainPanel( h4("Using ggplotly:"), plotlyOutput("ggplotly", width = "200"), h4("Using native plotly:"), plotlyOutput("plotly"), h4("Using ggplot:"), plotOutput("ggplot") ) ) server <- function

I have XY data (a 2D tSNE embedding of high dimensional data) which I'd like to scatter plot . The data are assigned to several cluster s, so I'd like to color code the points by cluster and then add a single label for each cluster , that has the same color coding as the cluster s, and is located outside (as much as possible) from the cluster 's points. Any idea how to do this using R in either ggplot2 and ggrepel or plotly ? Here's the example data (the XY coordinates and cluster assignments are in df and the labels in label.df ) and the ggplot2 part of it: library(dplyr) library(ggplot2) set

Example code: from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot import plotly.graph_objs as go import numpy as np N = 30 random_x = np.random.randn(N) random_y = np.random.randn(N) # Create a trace trace = go.Scatter( x = random_x, y = random_y, mode = 'markers' ) data = [trace] # Plot and embed in ipython notebook! iplot(data, filename='basic-scatter') [ ] How do I get a copy of the x,y data, or the indices from the selection? So if you want to use javascript in Jupyter notebooks you have two options. Using the display(HTML()) method for rendering html inside