data-visualization

问题 I have obtained a dictionary mapping words to their vectors in python, and I am trying to scatter plot the n most similar words since TSNE on huge number of words is taking forever. The best option is to convert the dictionary to a w2v object to deal with it. 回答1: I had the same issue and I finaly found the solution So, I assume that your dictionary looks like mine d = {} d['1'] = np.random.randn(300) d['2'] = np.random.randn(300) Basically, the keys are the users' ids and each of them has a

问题 This is a follow up from a previous question for wich I built a test case in a (hopefully now public) notebook and noticed the following behavior: At the end of the notebook, in the section bugs you will notice that y-axis of the max_precipitation of the layered chart using is clamped to 10. I tried changing the domain but the bars do not go above 10. Here the code example in vega-lite's editor reproduced below: { "$schema": "https://vega.github.io/schema/vega-lite/v4.json", "title": "Top

问题 I want to plot boxplot using only summary statistics ( INPUT is summary statistics for each ID ). plot1 is what I want, but when I convert it to a plotly object something goes wrong (ie., plotly flips boxplot ). However, if I plot boxplot the usual way (not using stat = "identity" ) everything works fine. Question: Why plotly "flips" summarised ggplot2 boxplot and how to avoid this? library(broom) library(plotly) library(tidyverse) # Generate random data # Calculate statistics INPUT <- rnorm

问题 I want to plot boxplot using only summary statistics ( INPUT is summary statistics for each ID ). plot1 is what I want, but when I convert it to a plotly object something goes wrong (ie., plotly flips boxplot ). However, if I plot boxplot the usual way (not using stat = "identity" ) everything works fine. Question: Why plotly "flips" summarised ggplot2 boxplot and how to avoid this? library(broom) library(plotly) library(tidyverse) # Generate random data # Calculate statistics INPUT <- rnorm

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

问题 I have d-dimensional hyperrectangles defined by a minimum point and a maximum points. I have weights on theese rectangles and they form a partition of [0,1]^d. How can i plot a facetted geom_tiles that would show me every 2 dimensional projection of this partition ? x = list(minimum_points = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0, 0, 0, 0, 0

问题 I have d-dimensional hyperrectangles defined by a minimum point and a maximum points. I have weights on theese rectangles and they form a partition of [0,1]^d. How can i plot a facetted geom_tiles that would show me every 2 dimensional projection of this partition ? x = list(minimum_points = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0.419352004803182, 0, 0, 0, 0, 0

问题 I'm having trouble extracting and graphing a Tukey test that I did. I did a fairly basic one on an ANOVA but I only want to plot the significant mean differences. When I use the plain Tukey <- TukeyHSD(x=aov.out, 'Species', conf.level=0.95) plot(Tukey) The result is Is there any way to remove all the insignificant mean levels? When I attempted to, I was forced to turn it into a dataframe, which then could not be plotted in the same way. Tukey <- Tukey[[1]][row_to_keep,] NOTE: No packages were

问题 I'm having trouble extracting and graphing a Tukey test that I did. I did a fairly basic one on an ANOVA but I only want to plot the significant mean differences. When I use the plain Tukey <- TukeyHSD(x=aov.out, 'Species', conf.level=0.95) plot(Tukey) The result is Is there any way to remove all the insignificant mean levels? When I attempted to, I was forced to turn it into a dataframe, which then could not be plotted in the same way. Tukey <- Tukey[[1]][row_to_keep,] NOTE: No packages were