visualization

问题 Is there a way to increase the reltive sizes of hexagons in pyplot.hexbin based on their frequency? I can only see binsize for the keyword arguments, which affects the number of hexes, but not their size. But in this article (around 2/3 in under the heading 'Multivariate Hexagonal Binning'), it discusses drawing hexagons with size proportional to count in order to more clearly observe trends (see following image taken from that article) Have I missed a keyword argument that allows this?

问题 I want to add labels as percentages to the individual bars of my Likert chart. Is there an easy way to do this? I've tried using geom_text, adjusting ordering commands, and enabling "plot.percents = TRUE." None of these things seem to work. My code, data, and current plot below. library(ggplot2) library(reshape) library(likert) library(dplyr) setwd("~/Desktop/") df <- read.csv("Likert_Test.csv") df[2] <- lapply(df[2], as.factor) colnames(df)[2] <- c("cake?") df[2] <- lapply(df[2], factor,

问题 I want to create a Column Chart , using Google Visualization API , I can send the data to populate the chart's DataTable in array form. But I need to generate the chart with variable number of columns/rows , depending on what my arrays contain and i don`t know how to correctly iterate them and add them to the DataTable. Here is an example for parsing STATIC data to generate the chart : (all this is in javascript) var data = google.visualization.arrayToDataTable([ ['Year', 'Sales', 'Expenses']

问题 I am running into some labels issue when using rpart in R. Here's my situation. I'm working on a dataset with categorical variables, here's an extract of my data head(Dataset) Entity IL CP TD Budget 2 1 3 2 250 5 2 2 1 663 6 1 2 3 526 2 3 1 2 522 when I plot my decision tree adding the labels, using plot(tree) text(tree) I get wrong labels : for Entity, I get "abcd" Why do I get that and how can I fix that ? Thank you for your help 回答1: By default plot.rpart will just label the levels of

问题 I am using matplotlib to plot a serie of values per week. The dataframe I create (see code below) looks like this: Dataframe: df_dates | Name_Of_index | | |------------ |---- | | 2017-01-22 | 13 | | 2017-01-29 | 0 | | 2017-02-05 | 5 | | 2017-02-12 | 37 | Freq: W-SUN, dtype: int64 My code is supposed to draw a bar plot for number per week/timestamp. def plot_contact_with_waters_per_week(dataframe, target_name,contact_with_water_value='contact_with_water', date_col='TBL_DAT'): df_contact_with

问题 Often when solving a recursive or dynamic programming problem, I find myself drawing a recursion tree to help simplify the question for me. However, for some questions which are complicated I have access to the solution but no idea how to draw the tree. What I have tried so far is printing out the calling function and it's parameters, and this has proved helpful in some examples. However, I saw this tree for fibonacci(5) here generated by mathematica in this answer: https://mathematica

问题 I am unable to add a segment to a D3.js pie chart. I know I need to use .enter() and .append() to stage the new data -- but I am not sure how to apply that when I have the arcs grouped (which I need for the labels). Here is my update function: var updateChart = function(dataset) { arcs.data(donut(dataset)); arcs.transition() .duration(duration) .attrTween("d", arcTween); sliceLabel.data(donut(dataset)); sliceLabel.transition() .duration(duration) .attr("transform", function(d) { return

问题 I am unable to add a segment to a D3.js pie chart. I know I need to use .enter() and .append() to stage the new data -- but I am not sure how to apply that when I have the arcs grouped (which I need for the labels). Here is my update function: var updateChart = function(dataset) { arcs.data(donut(dataset)); arcs.transition() .duration(duration) .attrTween("d", arcTween); sliceLabel.data(donut(dataset)); sliceLabel.transition() .duration(duration) .attr("transform", function(d) { return

问题 I'm building a visualization with Python. There I'd like to visualize fuel stops and the fuel costs of my car. Furthermore, car washes and their costs should be visualized as well as repairs. The fuel costs and laundry costs should have a higher bar depending on the costs. I created the visualization below to describe the concepts. How to create such a visualization with matplotlib? This is the visualization being built: 回答1: Yes, this kind of visualization is perfectly possible with

问题 I'm building a visualization with Python. There I'd like to visualize fuel stops and the fuel costs of my car. Furthermore, car washes and their costs should be visualized as well as repairs. The fuel costs and laundry costs should have a higher bar depending on the costs. I created the visualization below to describe the concepts. How to create such a visualization with matplotlib? This is the visualization being built: 回答1: Yes, this kind of visualization is perfectly possible with