similar to: ggplot2 Pareto plot (Barplot in decreasing frequency)

Hi all, I have a large data frame and would like to make a barplot of a categorical variable with the bars sorted in order of decreasing frequency. # Example: v1 = c(1.2, 1.4, 0.9, 1.0, 1.1, 1.0) v2 = c("aa", "cc", "bb", "bb", "cc", "bb") v3 = c(8, 10, 11, 9, 9, 10) df = data.frame(v1=v1, v2=v2, v3=v3) # How can I tell ggplot to sort

Gracias. Alguna idea de que usar para calcular los porcentajes y almacenarlos. Se puede usar flat table? El 18/06/2017 4:50 p. m., "Carlos J. Gil Bellosta" <cgb en datanalytics.com> escribió: > Los porcentajes que obtienes con tu código son sobre todas las facetas, no > país a país. > > Calcula los porcentajes previamente a por país y representa esa columna en >

Estimados Soy un nuevo usario de R, y estoy usando como base de datos el European Social Survey, que tiene datos de 40,000 individuos, y alrededor de 23 países europeos. Lo que he seleccionado es la útima ola, el round 7, para el año 2014. He leido los datos, desde SPSS y aquí tienen la base de datos y que tipo de objetos se han generado, y tambíen la distribución por pais de la muestra. No he

Hello Well I am relatively new so some of these issues may not fall under the subject that I have used. 1. How do I do a Pareto. Following is the approach I took. My data looks like this df2_9 Reaason.for.failure Frequency 1 Phy Conn 1 2 Power failure 3 3 Server software 29 4 Server hardware 2 5 Server out of mem 32

Hi All, Just hoping some one can give me a hand with a problem... I have a dataframe (DF) with about 5 million entries that looks something like the following: >DF ID Cl Co Brd Ind A AB AB 1 S-3 IND A BR_F BR_F01 1 0 0 2 S-3 IND A BR_F BR_F01 1 0 0 3 S-3 IND A BR_F BR_F01 1 0 0 4 S-3 IND A BR_F BR_F01 1 0 0 5 S-3 IND A BR_F BR_F01 1 0 0 6 S-3 IND A BR_F

Hello all, I would like to plot the emperical CDF, normal CDF and pareto CDF in the same graph and I amusing the following codes. "z" is a vector and I just need the part when z between 1.6 and 3. plot(ecdf(z), do.points=FALSE, verticals=TRUE, xlim=c(1.6,3),ylim=c(1-sum(z>1.6)/length(z), 1)) x <- seq(1.6, 3, 0.1) lines(x,pgpd(x, 1.544,0.4373,-0.2398), col="red") y

Hi, guys, I need to simulate Pareto distribution. But I found 'rpareto' didn't exist in R. And it seems that Pareto distribution don't have mathematical relationships with other distributions. What can I do? Thanks a lot. Ni --------------------------------- [[alternative HTML version deleted]]

Dear all, I am trying to simulate from truncated Pareto distribution. I know there is a package called PtProcess for Pareto distribution...but it is not for truncated one. Can anyone please help me with this? Thanks in advance. Cassie [[alternative HTML version deleted]]

In https://en.wikipedia.org/wiki/Pareto_distribution, it is clear what the parameters are for the pareto distribution: *xmin *the scale parameter and *a* the shape parameter. I am using rmutil to generate random deviates from a pareto distribution. It says in the documentation that the probabilty density of the pareto distribution The Pareto distribution has density f(y) = s (1 + y/(m

Hi, I would like to use the following codes to plot the CDF for pareto distribution. Before doing this, I have plot the emperical one. x <- seq(1.6, 3, 0.1) lines(x,pgpd(x, 1.544,0.4477557,), col="red") Could anyone give me some advice whether the above codes are correct? Many thanks. -- View this message in context:

#Simple table con frecuencias absolutas y crear relativas count =table(ess$stflife) percent = 100* (count)/sum(count) Carlos he creado a esto a nivel general en vez de usar prop.table. Según lo que dices o entiendo, debo de usar la función ddply para hacerlo a nivel de todos los paises, y entiendo que ddply (, c(""), debo de indicar los paises? Saludos 2017-06-18 17:37 GMT-05:00

Hi- Is there a quick way to plot a Pareto diagram? I couldn't find one. I'm being forced to do some pretty weird stuff, with awk and all, to extract data in order to plot the frequency of qualitative data from a larger set. Perhaps it's just my GNUrance. I mean, one day, if I have time, I might even write a generic Perl script, but right now, it doesn't look too good on the

Dear R helpers, I have a bimodal dataset dealing with loss amounts. I have divided this dataset into two with the bounds for the first dataset i.e. dataset-A being 5,000$ to 100,000$ and the dataset-B deals with the losses exceeding 100,000$ i.e. dataset-B is left truncated. I need to fit truncated normal disribution to dataset - I having lower bound of 5000 and upper bound of 100,000. While I

I would like to fit a Pareto Distribution and I am using the following codes. I thought the fitted (fit1) should be the fitted value for the data, is it correct? As the result of the "fitted" turns out to be a single value for all. fit=vglm(ycf1 ~ 1, pareto1(location=alpha), trace=TRUE, crit="c") fitted(fit) The result is fitted(fit) [,1] [1,] 0.07752694

I would like to fit a Pareto Distribution and I am using the following codes fit=vglm(ycf1 ~ 1, pareto1(location=alpha), trace=TRUE, crit="c") fitted(fit) But the fitted values turn out to be the same for each observation. I guess the problem is with "ycf1 ~ 1", I would be grateful if anyone can give me some advice on how to define the formula. Many thanks -- View this

Dear R users, Could you please help me out. I am in trouble as I am unable to model graphs to explain the GARCH (1 , 1) model, the Hill estimator (of alpha), and the Pareto estimator. I just got introduce to R. I am working on a paper which must be worked from R. You look at the difficulty I had from the text below. [1] "DAX" "DAX_CAC" "DAX_CAC40"

Dear R helpers, I need to use KS and AD test for Generalized Pareto and Generalized extreme value. E.g. if I need to use KS for Weibull, I have teh syntax ks.test(x.wei,"pweibull", shape=2,scale=1) Similarly, for AD I use ad.test(x, distr.fun, ...) My problem is fir given data, I have estimated the parameters of GPD and GEV using lmom. But I am not able to find out the distribution

Creo que esto me da para DK, y luego veré como aplicar el barplot ess %>% filter(cntry %in% c("DK")) %>% count (stflife) %>% mutate (freq = (n /sum(n)*100))%>% print 2017-06-18 19:01 GMT-05:00 Antonio Rodriguez Andres < antoniorodriguezandres70 en gmail.com>: > He conseguido el total para un país, pero no me deja usar percent = > count() /sum(count),

Hi R helpers, Is there any function in R, which generates random numbers in case of (1) Generalized Extreme Value distribution and (2) Generalized PAreto distribution for the respective given set of parameters? Regards Maithili

Hello My dataset is as follows: jobno recruits 1100 18 1200 1 1850 5 2100 190 2789 25 3000 1 . . . . the dataset has 130 rows I want to plot barplot from left side and cumulative curve from right side in one graph itself using layers in ggplot2. I sorted the recruits 1st in decreasing order