ggplot2 boxplot

Getting Started video tutorialsBasic R Language Course (1)-Quick Start for R language http://cos.name/videos/intro-2-r/Code#对象1 +1*3c (1,2,3,4,5) C (' HelloWorld ', ' I am a R user ') C ("hehe", "haha") 1:66:1exp (1:4) log (1:3) aRun results> #对象 > 1+1*3[1] 4> C (1,2,3,4,5) [1] 1 2 3 4 5> C (' HelloWorld ', ' I am a R user ') [1] "HelloWorld" "I am a R use R "> C (" hehe "," haha ") [1]" hehe "" haha "> 1:6[1] 1 2 3 4 5 6> 6:1[1] 6 5 4 3 2 1> exp (1:4) [1] 2.718282 7.389056 20.085537 54.598150>

machine Learning course), and the syntax of the R language is pretty good in formula settings.2. Furthermore, it is the corresponding Python library of the static graphics library Ggplot2 and the interactive graphics library D3. The Matplotlib library is not easy to install, it is difficult to use, and it is not easily built for interactive graphics for the web.3. The third is the scalability of the numpy and pandas libraries when dealing with large

#-*-Coding:utf-8-*-"""Created on Sat 18 11:08:38 2018@author: Acadsoc"""Import Pandas as PDImport NumPy as NPImport MatplotlibImport Matplotlib.pyplot as PltFrom pyecharts import Bar, line, Page, overlapImport Statsmodels.api as SMFrom sklearn.preprocessing import Standardscaler# import PymssqlFrom Dateutil Import ParserImport CopyImport OSImport SysFrom featureselection import featureselectionPlt.style.use (' Ggplot ') # set GGPLOT2 paint style# Set

learn, R, lucky to meet Lu Wenjun teacher, he is the great God of economic college, but also learned some learning methods, I belong to the kind of anxious character, the result. You know.. Is a tragedy, just no heroine, think Ha, have studied what, I am not easy to get started, oh right, now do not know how to get started, 罒 Omega 罒 steal laughter.The books are as follows : | | (time or double, forget almost)| | "R Language Beginner's Guide", "R language Combat", "multivariate statistical anal

Using Ggplot2 to draw a box line chart######*****绘制箱线图代码*****#######data1$学区房 R Language Drawing: Box-line diagram

In general, this book covers a lot of r language knowledge, but the content of the relatively trivial, it is difficult to string the whole book chapters, if it as a knowledge dictionary of the R language is very good. This book mainly covers the following, but it does not carry out in-depth discussion of these contents.the next thing to doThe output of the R detection function needs to be thoroughly understoodCombining real-life case practice with the contents of this bookR Language Programming

This function is a function under the Stringr package, it is useful to do data cleaning, presumably use to extract a string under a certain content, according to some of the rules you want, the specific use of the following: x Str_extract_all (x, "[F0-9]")[[1]][1] "F" "1" "2" > Str_extract_all (x, "[f0-9]{1,3}")[[1]][1] "F12" > Str_extract_all (x, "[f0-9]{1,2}")[[1]][1] "F1" "2" Attach some code written in peacetime Library (GGPLOT2) library (rmysql)

In the recent internship need R language analysis, for the final result needs to be shown below the diagram to show (sample image in the paper interception) Because of contact with R language soon, just start is a variety of Meng, think directly with R is not drawing such pictures, and then asked the classmate said with R language Ggplot2 expansion package, so found some tutorials on the internet to find this kind of picture can be painted, but its

packages covered in this article are: In [3]: Set.seed (1680) # Set a random seed, making the results of this article a reproducible library (DPLYR) library (ISLR) library ( cluster) library (Rtsne ) Library (GGPLOT2) Attaching package: ' Dplyr ' The following objects is masked from ' package:stats ': filter, lag the following O Bjects is masked from ' package:base ': intersect, Setdiff, setequal, union Before building a clustering mod

(y~x1*x2), y = a*x1+b*x2+c*x1*x2+d Lm (Y~X1*X2*X3) Y =a*x1+b*x2+c*x3+d*x1*x2+e*x1*x2+f*x2*x3+g*x1*x2*x3+h Lm (Y~X1+X2+X3+X1:X2:X3) y = a*x1+b*x2+c*x3+d*x1*x2*x3+e SETP stepwise regression, you can remove the meaningless variable backwards, you can add a new variable to the forward regression Lm (y~x1, subset=1:100) selects only the first 100 data for regression Lm (Y~i (X1+X2)) to (X1+X2) regression Lm (Y~ploy (x,3,raw=true)) Y is the three-quadratic polynomial regression of x Lm (log (y) ~ x1