data-visualization

问题 I am using the R programming language. I am trying to arrange "plot1, plot2, plot3, plot4" on the same page: library(kohonen) #fitting SOMs library(ggplot2) #plots library(GGally) #plots library(RColorBrewer) #colors, using predefined palettes iris_complete <-iris[complete.cases(iris),] #only complete cases... the iris dataset floats around in the sky with diamonds. iris_unique <- unique(iris_complete) # Remove duplicates #scale data iris.sc = scale(iris_unique[, 1:4]) #build grid iris.grid =

问题 I am trying to learn how to combine different types of graphs together in the R programming language. Suppose I have the following data: library(dplyr) library(ggplot2) date= seq(as.Date("2014/1/1"), as.Date("2016/1/1"),by="day") var <- rnorm(731,10,10) group <- sample( LETTERS[1:4], 731, replace=TRUE, prob=c(0.25, 0.22, 0.25, 0.25) ) data = data.frame(date, var, group) data$year = as.numeric(format(data$date,'%Y')) data$year = as.factor(data$year) I summarized this data making different

问题 I am learning about the "kohonen" package in R for the purpose of making Self Organizing Maps (SOM, also called Kohonen Networks - a type of Machine Learning algorithm). I am following this R language tutorial over here: https://www.rpubs.com/loveb/som I tried to create my own data (this time with both "factor" and "numeric" variables) and run the SOM algorithm (this time using the "supersom()" function instead): #load libraries and adjust colors library(kohonen) #fitting SOMs library(ggplot2

问题 I am learning about the "kohonen" package in R for the purpose of making Self Organizing Maps (SOM, also called Kohonen Networks - a type of Machine Learning algorithm). I am following this R language tutorial over here: https://www.rpubs.com/loveb/som I tried to create my own data (this time with both "factor" and "numeric" variables) and run the SOM algorithm (this time using the "supersom()" function instead): #load libraries and adjust colors library(kohonen) #fitting SOMs library(ggplot2

问题 I am working with the R programming language. I am trying to save multiple HTML files together like this: library(plotly) library(shiny) #create widget_1 widget_1 = plot_ly(iris, x = ~Sepal.Length, type = "histogram", nbinsx = 20) #create_widget_2 widget_2 = plot_ly(iris, x = ~Sepal.Width, type = "histogram", nbinsx = 20) #create_widget_3 widget_3 = plot_ly(iris, x = ~Petal.Length, type = "histogram", nbinsx = 20) #create widget_4 widget_4 = plot_ly(iris, x = ~Petal.Width, type = "histogram",

问题 I'm trying to train a Linear Regression Model with Python via using Google Stock Prices that can be found here: https://www.kaggle.com/medharawat/google-stock-price And trying to predict future stocks by given features. After that I'm planning to plot it with the values in current dataset. First, I read dataframes with date values with date parser and concatted these 2 dataframes into one in order to split it myself: parser = lambda date: pd.datetime.strptime(date, '%m/%d/%Y') df_test=pd.read

问题 I am using the R programming language. I am trying to learn how to plot multiple time series on the same graph, as well as including their confidence intervals (in this case, their maximum and minimum values). Suppose I have two time series like this: library(xts) library(ggplot2) library(dplyr) library(plotly) library(lubridate) #time series 1 date_decision_made = seq(as.Date("2014/1/1"), as.Date("2016/1/1"),by="day") property_damages_in_dollars <- rnorm(731,100,10) final_data <- data.frame

问题 I have a netcdf with wind speed at model levels. On the same netcdf I have the altitude of each model level. I converted netcdf to a cube, so the altitude of each level became an auxiliary coordinate. I would like to plot a cross section (longitude x longitude) and would like the model levels to follow the topography. I tried using the Iris module documentation example (https://scitools.org.uk/iris/docs/latest/examples/General/cross_section.html), but it's not working. As I already have the

问题 I have the following code that produces an image but the labels are cut off. I edited the first value in each df column on purpose as my real data has really large labels. I tried the plt.tight_layout but it doesnt work. I also tried the solution from the following link, but was not successful. It only shifted the image to the left. I also tried increasing the width of the figsize and while it i make it large enough the whole label is shown, the image looks really tiny and stretched out. I

问题 I am new to python and am carrying out some little projects along side watching tutorials to enable me to learn. I have recently been working with some APIs to collect data - I save this data in a CSV file and then open the CSV file to show the data as a graph. I want the graph to show the data LIVE , but in doing so I only want 10 values on the screen at once, so when the 11th value is plotted, the 1st is no longer visible unless the scrolling function is used to look back at it.. I have