| library(ggplot2) | |
| yDistribution <- function(x) { return(1/x) } | |
| xSampleDistribution <- function(x) { return((2 ^ x) * 10) } | |
| x <- c() | |
| y <- c() | |
| for (i in 0:8) { | |
| sampleCount <- xSampleDistribution(i) | |
| x <- c(x, rep(i, sampleCount)) |
This simple bar chart is constructed from a TSV file storing the frequency of letters in the English language. The chart employs conventional margins and a number of D3 features:
| install.packages('Cairo') | |
| install.packages('data.table') | |
| install.packages('extrafont') | |
| install.packages('ggplot2') | |
| install.packages('lubridate') | |
| install.packages('plyr') | |
| install.packages('dplyr') | |
| install.packages('rjson') | |
| install.packages('stringr') | |
| install.packages('XML') |
| Year,Make,Model,Length | |
| 1997,Ford,E350,2.34 | |
| 2000,Mercury,Cougar,2.38 |
| import struct | |
| import numpy as np | |
| import os | |
| def parseNPY(path, fileJustName): | |
| # load from the file | |
| inputFile = os.path.join(path, fileJustName + ".npy") | |
| matrices = np.load(inputFile) | |
| outputfile = os.path.join(path, fileJustName) |
| // Randomly samples an element from an array and prevents the same element | |
| // from being returned twice unless separated by some number of samples | |
| // | |
| // Constructor parameters | |
| // array: the original array to shuffle and use | |
| // proximityLimit: minimum number of samples between returning the same element (max: array.length/2) | |
| // Methods | |
| // Next(): get the next item | |
| // | |
| // sample use: |
| library(reshape2) | |
| library(plyr) | |
| library(ggplot2) | |
| library(grid) | |
| anscombe2 = melt(anscombe, measure.vars=c('x1', 'x2', 'x3', 'x4'), variable.name='number', value.name='x') | |
| anscombe2$number = substring(anscombe2$number, 2) | |
| anscombe2 = adply(anscombe2, 1, function(r){ | |
| r['y'] = r[paste0('y', r['number'])] | |
| return(r) |
| library(ggplot2) | |
| library(grid) | |
| library(doParallel) | |
| library(itertools) | |
| resolution = 1000 | |
| iterations = 100 | |
| threshold = 10 | |
| # image range |
I'm just adding a little color to Mike Bostock's demo.
Mario Klingemann has made some beautiful Voronoi diagrams. This is my attempt to recreate them using D3. To achieve the curved cells, each side of the Voronoi polygon is subdivided into three equal-length segments and then joined using the "basis-closed" line interpolator. There are some discontinuities in the animation when the sides of a polygon approach zero which could likely be avoided by adding a minimum-length threshold to the subdivision.
If you’d like to see other instances of this pattern, Mario describes the algorithm on Flickr.
| # Multiple plot function | |
| # from http://www.cookbook-r.com/Graphs/Multiple_graphs_on_one_page_(ggplot2)/ | |
| # | |
| # ggplot objects can be passed in ..., or to plotlist (as a list of ggplot objects) | |
| # - cols: Number of columns in layout | |
| # - layout: A matrix specifying the layout. If present, 'cols' is ignored. | |
| # | |
| # If the layout is something like matrix(c(1,2,3,3), nrow=2, byrow=TRUE), | |
| # then plot 1 will go in the upper left, 2 will go in the upper right, and | |
| # 3 will go all the way across the bottom. |