ggplot2 r tutorial

script and diagram for the Pareto diagram drawn with Ggplot2 are as follows: Library ( grid) library (VCD) library (GGPLOT2) library (scales) labels"","30-40","40-50","50-60","60-70",">=") Breaks1, -, +, -, -, -, -) MyTableTRUE) DF as. data.frame (Table (age=mytable), stringsasfactors=FALSE) DFprop.table (Freq)) DFTRUE),]rownames (DF)seq (nrow (DF)) Df$agedf$age) Df$cumratecumsum (df$freqrate) df$cumratel

default value is False, drawing an additional graph, connecting each elbow value, to show the difference between the various elbow values, to help identify the "elbow", suggesting "correct" number of clusters. The Sjc.elbow () function is used to draw the elbow value of the K-means cluster analysis, which calculates the K-means cluster analysis in the specified data frame, producing two graphs: one graph has different elbow values, and the other is the connection of each "step" on the y-ax

Label:According to the characteristics of various industries, a variety of clustering algorithms are proposed, which are divided into several categories: hierarchy, Division, density, graph theory, grid and model. Among them, the density-based clustering algorithm is the most representative in Dbscan. Assuming a set of data, the R code of the generated data is as follows X1 0, Pi,length. out= -) Y10.1*rnorm ( -) X21.5+ SEQ (0, Pi,length. out= -) Y20.1*rnorm ( -) DataData.frame (C (X1,X2), C (y1

source JavaScript Chart library.There are two ways to install:Install.packages ("plotly")OrDevtools::install_github ("ropensci/plotly")The plotly package uses the function Plot_ly function to draw the interaction graph.If you plot a scatter plot relative to the iris data set, you need to set the mode parameter to "markers".Library (plotly) P If you want to draw an interactive box line diagram, you need to set the type parameter to box.Library (plotly) Plot_ly (midwest, x = percollege, color = s

those who want to get the basic and thought of r language and data mining, they want to use r language in practice to solve problems in school students and in-service workers.Syllabus:First Lecture: The Essentials of R languageIn order to gradually and cover the R language important and useful basic content principles, this talk from the beginning of the introduction of the R language, with the previous data processing as the core, with the actual case as the carrier, including the R language v

0 reply: many good-looking PYTHON image libraries are developed and encapsulated based on matplotlib! I have used seaborn, bokeh, and ggplot databases! Seaborn is biased towards statistical plot, especially linear plot, which is easy to use and simple. The entire syntax layer of seaborn will also be much simpler, and it looks nice to draw a picture without any modification. However, the drawing method is limited and not flexible enough. Bokeh uses js. Therefore, it focuses on interactive plotti

A: R itself is single-threaded, how to let its multi-threaded run up, improve the speed of computing? Playing parallel computing with parallel and foreach packetsAfter reading the above article will be. Plainly, to load the parallel package, and then rewrite your own code is OK.#-----With a strength to demonstrate R how multithreaded computingFunc n = 1Raw while (x > 1) {X n = n + 1}Return (c (raw,n))}#----Library (parallel)# Use System.time to return the time required to calculateSystem.time ({

# sample Datad The figure 1a does isn't draw any lines, while the figure of 1b works well.The key concept is a "group" in AES.The rule is simple: Geom_line () tries to connect data points this belong to same group. Different levels of factor variable belong to different group. So, by specifying GROUP=G in AES, the lines appear in Figure 1b.Figure 1c would help to understand more.In Figure 1c, all data points belong to Group=1, hence all data points is connected.REF:http://www.m

The 5th Chapter regression model: Predicting Web page trafficRegression model: Predict another DataSet with a known dataset, known as an input, also called a predictor or feature, and the data you want to predict is called an output. The regression model differs from the classification model in that the output of the regression model is a meaningful value.Benchmark model: Using mean as a prediction#machine learing for Heckers#chapter 5Library (Ggplot2

table covers most of R's knowledge, and Rstudio also publishes some quick-look tables to make r easier to learn. When you want to show the results, it may be a good idea to use Ggplot2 to visualize the data.R Cheat Sheet (Google drive)R Functions for Regression analysisR Reference CardR Functions for TIME series analysisR Reference Card for Data MiningR Cheat SheetData Analysis The Data.tableInteractive Web Apps cheatsheet by R StudioData visualisati

A line chart is a way to reflect a change in the trend, and its input data is generally a matrix.Single line DiagramSuppose there is such a matrix, the first column of the transcription starting site and its upstream and downstream 5 KB area, the second column h3k27ac decorated in these areas of abundance, want to draw a line chart display.Profile= "Pos; h3k27ac-5000;8.7-4000;8.4-3000;8.3-2000;7.2-1000;3.60;3.61000;7.12000;8.23000;8.44000;8.55000;8.5 "Read in DataProfile_text And then start draw

(), and Dcast (), but they can "knead" the data into various shapes. Melt itself means dissolution, decomposition, and its role in a data set is actually split data, its object can be an array, a data frame or a list. > Library (RESHAPE2) > Data (airquality) > str (airquality) ' Data.frame ': 153obs. of 6 variables: $Ozone: int 41 36 12 Na 8 na ... $ solar.r:int 118 149 313 na Na 299 ... $Wind: num 7.4 8 12.6 11.5 14.3 14.9 8.6 13.8 20.1 8.6 ... $Temp: int .... $Month: int 5 5 5 5 5 5 5 5 5 5 .

talk.3. Drawing and VisualizationAristotle said, "Humans prefer to watch more than other senses." As a result, drawing and visualization are a lot of people's attention and attention. So how do you learn R-drawing and data visualization? How to draw a histogram? How do I add a density curve to the histogram? I'd like to finish reading the following books and you'll get the general idea.First of all, the introduction of drawing can read the "R Graphics", personally think this is a more classic,

scientific computing use Networkx-is an efficient software used for complex networks. pandas-This library provides high-performance, easy-to-use data structures and data analysis tools. The Business Intelligence tool (Pandas Web interface) in Open Mining-python. PYMC-MCMC Sampling Toolkit. Zipline-python's algorithmic Trading library. pydy-full name Python dynamics, assisting with dynamic modeling workflows based on NumPy, SciPy, Ipython, and Matplotlib. sympy-symbol

Watervoles data from the HSAUR2 package for example. This data is a similarity matrix, which indicates the similarity of paddy rats in different regions. Load the data first and then analyze it with cmdscales.Library (GGPLOT2) data (watervoles, package = "HSAUR2") data (Watervoles) Voles.mds=cmdscale (watervoles,k=13,eig=t)The following calculates the proportions of the first two eigenvalues in all eigenvalues, in order to detect whether the distance

Plotnine Csdn's edit and upload picture experience is too bad, more examples to plot-example to see. Https://github.com/has2k1/plotnine-examples Installation website: https://plotnine.readthedocs.io/en/stable/index.html Github:https://github.com/has2k1/plotnine Ggplot2 official website: http://ggplot2.tidyverse.org/reference/index.html#section-plot-basics Conda install-c conda-forge Plotnine # # Use Import

very popular language for data science, originally built by/for statisticians and now very widely used. Htmlwidgets-previously discussed in the post, htmlwidgets for Rich Data visualizations in R. allows for tons of interact Ion and great for the web. Ggplot2-a very popular plotting system for R. It is widely used and can create just about every type of graph.However, the plots is not interactive. R Visualization is a sample application

package. Numba-Python's low-level Virtual Machine JIT compiler, compiled by cython and numpy developers for scientific computing Networkx-efficient software for complex networks. Pandas-This database provides high-performance, easy-to-use data structures and data analysis tools. Open Mining-the pandas web interface in Python ). Pymc-MCMC sampling toolkit. Zipline-Python algorithm trading library. Pydy-Full name: Python dynamics, which assists in Dynamic Modeling workflows Based on numpy,

database provides high-performance, easy-to-use data structures and data analysis tools. Open Mining-the pandas web interface in Python ). Pymc-MCMC sampling toolkit. Zipline-Python algorithm trading library. Pydy-Full name: Python dynamics, which assists in Dynamic Modeling workflows Based on numpy, scipy, ipython, and matplotlib. Sympy-Python library for symbolic mathematics. Statsmodels-Python statistical modeling and library of metered economics. Astropy-Python astronomy library, com

work Ggvis, Lattice, and ggplot2 for data visualization Caret Machine Learning How does python work? If your data Analysis task requires the use of a Web application, or code statistics need to be incorporated into the production database for integration, you can use Python as a fully fledged programming language, which is a great tool for implementing algorithms. Although Python packages have been in the early stages of data analysis in the past,