data-visualization

I'm developing a 2D plane finite element tool. One of the features is the ability to visualize the stresses on a particular object. This tool creates a quadrilateral mesh using the following data: nodes : numpy array [[x1 y1], [x2 y2], etc] -> x and y coordinates of every node in the mesh elements : numpy array [[1 2 3 4], [2 3 5 6]] -> every line of the array corresponds to the 4 points of one particular element of the mesh. I was able to implement a method that plots the mesh: import matplotlib.pyplot as plt import matplotlib.collections import matplotlib.cm as cm import numpy as np def

Given the data frame below: import pandas as pd df = pd.DataFrame({ "n_index": list(range(5)) * 2, "logic": [True] * 5 + [False] * 5, "value": list(range(5)) + list(range(5, 10)) }) I'd like to use color and only color to distinguish logic in a line plot, and mark points on value s. Specifically, this is my desired output (plotted by R ggplot2 ): ggplot(aes(x = n_index, y = value, color = logic), data = df) + geom_line() + geom_point() I tried to do the same thing with seaborn.lineplot , and I specified markers=True but there was no marker: import seaborn as sns sns.set() sns.lineplot(x="n

Given a data frame as following: v1 v2 v3 v4 v5 tom A pinky A 3 ben B hugo C 2 lily A tom A 1 ... Which denotes that v1 from group v2 has mentioned v3 from group v4 for v5 times. For instance, tom from group A has mentioned pinky from group A for 3 times. Now I'd like to plot a social network, each user denoted by a point and its size is proportional to the times he or she has been mentioned totally. And there is a line linkage two points if they have mentioned each other mutually or unilaterally. As I look into the ggplot document, I can not find any function to do it. Do you have any idea?

I've tried to search for an answer, but can't seem to find the right one that does the job for me. I have a dataset ( data ) with two variables: people's ages ( age ) and number of awards ( awards ) My objective is to plot the number of awards against age in R. FYI, a person can have multiple awards and people can have the same age. I tried to plot a histogram and barplot, but the problem with that is that it counts the number of observations instead of summing the number of awards. A sample dataset: age <- c(21,22,22,25,30,34,45,26,37,46,49,21) awards <- c(0,3,2,1,0,0,1,3,1,1,1,1) data <-

Problem: I would like to produce a scatter plot with highcharter::hchart , where y is a factor , and x is a date . Apparently, highcharter::hchart "scatter" does not accept factor variables as y. Is there any workaround? Or is "scatter" just the wrong charttype? (Comment: I know ggplotly would be a good alternative, but I actually need a highcharter solution) Example: Let's suppose I want to produce a timeline of publications by type . I want a scatterplot with d$type (=y-axis) and d$date (=x-axis) and the highcharter tooltip should show me d$title , d$type and d$date (properly formatted).

Is there any way to change the title sizes of a ctree plot? Use the following variables to quickly set up a ctree plot a<-c(41, 45, 50, 50, 38, 42, 50, 43, 37, 22, 42, 48, 47, 48, 50, 47, 41, 50, 45, 45, 39, 45, 46, 48, 50, 47, 50, 21, 48, 50, 48, 48, 48, 46, 36, 38, 50, 39, 44, 44, 50, 49, 40, 48, 48, 45, 39, 40, 44, 39, 40, 44, 42, 39, 49, 50, 50, 48, 48, 47, 48, 47, 44, 41, 50, 47, 50, 41, 50, 44, 47, 50, 24, 40, 43, 37, 44, 32, 43, 42, 44, 38, 42, 45, 50, 47, 46, 43, 37, 47, 37, 45, 41, 50, 42, 32, 43, 48, 45, 45, 28, 44,38, 41, 45, 48, 48, 47 ,49, 16, 45, 50, 47, 50, 43, 49, 50) X1<-c(NA