data-visualization

问题 Time series data is data over time. I am trying to animate a line plot of time series data in python. In my code below this translates to plotting xtraj as they and trange as the x. The plot does not seem to be working though. I have found similar questions on Stack overflow but none of the solutions provided here seem to work. Some similar questions are matplotlib animated line plot stays empty, Matplotlib FuncAnimation not animating line plot and a tutorial referencing the help file

问题 I simulated some graph network data (~10,000 observations) in R and tried to visualize it using the visNetwork library in R. However, the data is very cluttered and is very difficult to analyze visually (I understand that in real life, network data is meant to be analyzed using graph query language). For the time being, is there anything I can do to improve the visualization of the graph network I created (so I can explore some of the linkages and nodes that are all piled on top of each other

问题 I simulated some graph network data (~10,000 observations) in R and tried to visualize it using the visNetwork library in R. However, the data is very cluttered and is very difficult to analyze visually (I understand that in real life, network data is meant to be analyzed using graph query language). For the time being, is there anything I can do to improve the visualization of the graph network I created (so I can explore some of the linkages and nodes that are all piled on top of each other

问题 I am trying to work with plotly, specifically ploty express, to build a few visualizations. One of the things I am building is a scatterplot I have some code below, that produces a nice scatterplot: import plotly.graph_objs as go, pandas as pd, plotly.express as px df = pd.read_csv('iris.csv') fig = px.scatter(df, x='sepal_length', y='sepal_width', color='species', marker_colorscale=px.colors.sequential.Viridis) fig.show() However, I want to try and change the colorscheme, i.e., the colors

问题 I am trying to work with plotly, specifically ploty express, to build a few visualizations. One of the things I am building is a scatterplot I have some code below, that produces a nice scatterplot: import plotly.graph_objs as go, pandas as pd, plotly.express as px df = pd.read_csv('iris.csv') fig = px.scatter(df, x='sepal_length', y='sepal_width', color='species', marker_colorscale=px.colors.sequential.Viridis) fig.show() However, I want to try and change the colorscheme, i.e., the colors

问题 I am trying to follow a tutorial in R (https://rviews.rstudio.com/2017/09/25/survival-analysis-with-r/).The computer I am using for work does not have a USB port or internet connection - it only has R with a few libraries installed. My work computer has "survival, ranger, ggplot2 and dplyr". However, it does not have "ggfortify". I am trying to figure out how to plot the graphs from the tutorial without 'ggfortify'. Here is the code I am using below: #load libraries library(survival) library

问题 I am trying to figure out how to easily access and manipulate graphs created in R. If I start with the following data. I create a graph, run some graph clustering and then plot the first cluster: #libraries library(igraph) library(igraphdata) data(karate) #cluster cfg <- cluster_fast_greedy(karate) plot(cfg, karate) cfg IGRAPH clustering fast greedy, groups: 3, mod: 0.43 + groups: $`1` [1] "Actor 9" "Actor 10" "Actor 15" "Actor 16" "Actor 19" "Actor 21" "Actor 23" "Actor 24" "Actor 25" "Actor

问题 I am using R and the igraph library to learn about network graph data. In particular, I am trying to understand the concept of a "weighted graph" - from what I have read, the "weights" are generally associated with the "Edges" in the graph. But can the "weights" ever be associated with the "nodes"? (sometimes, I see that "nodes" are also referred to as "vertexes") Suppose I have two datasets : one for the nodes and one for the edges. library(igraph) library(visNetwork) Nodes <-data.frame(

问题 I am using R and the igraph library to learn about network graph data. In particular, I am trying to understand the concept of a "weighted graph" - from what I have read, the "weights" are generally associated with the "Edges" in the graph. But can the "weights" ever be associated with the "nodes"? (sometimes, I see that "nodes" are also referred to as "vertexes") Suppose I have two datasets : one for the nodes and one for the edges. library(igraph) library(visNetwork) Nodes <-data.frame(

来源： https://stackoverflow.com/questions/64350898/plotting-dictionary-of-list-topic-word-embeddings-in-python3-x