similar to: Comparar variables fecha formato POSIXct

Hi all, For the R package bujar, the warnings below were generated on CRAN's Windows systems. The package uses some Fortran subroutines. I would appreciate any advice to eliminate the warnings. By the way, similar warnings were generated to some unrelated R packages as well: https://www.r-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/imputeTS-00check.html. Thanks in advance. Zhu

The anti_join from the package dplyr might also be handy. install.package("dplyr") library(dplyr) anti_join (x1, x2) You can get help on the different functions by ?function.name(), so ?anti_join() will bring you help - and examples - on the anti_join function. It might be worth testing your approach on a small subset of the data. That makes it easier for you to follow what happens

The diffobj package (https://cran.r-project.org/package=diffobj) is really helpful here. It provides "diff" functions diffPrint(), diffStr(), and diffChr() to compare two object 'x' and 'y' and provide neat colorized summary output. Example: > iris2 <- iris > iris2[122:125,4] <- iris2[122:125,4] + 0.1 > diffobj::diffPrint(iris2, iris) < iris2 >

Thanks, I think I've found the most succinct expression of differences in two data.frames... length(which( rowSums( x1 != x2 ) > 0)) gives a count of the # of records in two data.frames that do not match. // ________________________________________ From: Henrik Bengtsson [henrik.bengtsson at gmail.com] Sent: Sunday, January 28, 2018 11:12 AM To: Ulrik Stervbo Cc: Marsh Hardy ARA/RISK;

Hi everybody: Could anybody help how I solve the next problem?. I'm doing interpolation maps of tropospheric ozone of my region, and after create it using IDW, and kriging methods, I want from shapefiles (*.shx, *.shp, *.dbf, *.sbx & *.sbn ) create contour over the interpolation maps. Could anybody tell me how do it?. Thanks in advance. ###################################### Antonio

Buenos días, Estoy realizando un análisis de topic models con el método LDA. En principio, he quitado del análisis las palabras "stopwords" universales. A la hora de ver los topics y sus palabras más frecuentes encuentro que son muy similares y hay palabras que aparecen en todos los topics. Los textos que estoy analizando son opiniones de consumidores sobre una categoría concreta de

Buenas, Estoy analizando texto en R y no encuentro cómo eliminar los números y símbolos del texto como ",", "%", etc. Estoy pasando este código, text_data es donde está el texto en la variable "text". tidy_data <- text_data%>% unnest_tokens(word, text)%>% anti_join(stop_words) ¿Cómo podría añadirse a ese código? Muchas gracias

Hola, Acabo de calcular tf-idf y me surge una duda. ¿Habría un valor de idf o tf-idf que se considerara como umbral para establecer que una palabra es muy común o no? Los valores de idf en mis datos van entre 0 y 3.78 y los de tf-idf ente 0 y 0.07. Un saludo El Mar, 28 de Abril de 2020, 12:53, Carlos Ortega escribió: > Hola, > Yo de primeras los quitaría para qué otros topics aparecen.

Cool, looks like that'd do it, almost as if converting an entire record to a character string and comparing strings. -- M. B. Hardy, statistician work: Applied Research Associates, S. E. Div. 8537 Six Forks Rd., # 6000 / Raleigh, NC 27615-2963 (919) 582-3329, fax: 582-3301 home: 1020 W. South St. / Raleigh, NC 27603-2162 (919) 834-1245

Hi, I'll coded your example into R code: Table_A <- c('abc at gmail.com', 'John Chan', '0909') Table_A <- rbind(Table_A, c('bcd at yahoo.com', 'Tim Ma', '89089')) colnames(Table_A) <- c('Email', 'Name', 'Phone') Table_A Table_B <- c('abc at gmail.com', 'John Chan', 'M',

If your two objects have class "data.frame" (look at class(objectName)) and they both have the same number of columns and the same order of columns and the column types match closely enough (use all.equal(x1, x2) for that), then you can try which( rowSums( x1 != x2 ) > 0) E.g., > x1 <- data.frame(X=1:5, Y=rep(c("A","B"),c(3,2))) > x2 <-

GUYS, I NEED HELP WITH ERROR: library(MASS) > dados<-read.table("mediaRGinverno.txt",header=FALSE) > vento50<-fitdistr(dados[[1]],densfun="weibull") Erro em fitdistr(dados[[1]], densfun = "weibull") : Weibull values must be > 0 WHY RETURN THIS ERROR? WHAT CAN I DO? BEST REGARDS [[alternative HTML version deleted]]

Thanks - Peter, Eivind, Rui Sorry, I perhaps could not explain it properly in the first go. Trying to simplify it here with an example - Say I have two dataframes as below that are NOT equally-sized data frames (i.e., number of columns are different in each table): Table_A: Email Name Phone abc at gmail.com John Chan 0909 bcd at yahoo.com Tim Ma

Guys, I'm having an error when I use the command: library(MASS)> dados<-read.table("inverno.txt",header=FALSE)> vento50<-fitdistr(dados[[1]],densfun="weibull")Mensagens de aviso perdidas:1: In dweibull(x, shape, scale, log) : NaNs produzidos2: In dweibull(x, shape, scale, log) : NaNs produzidos3: In dweibull(x, shape, scale, log) : NaNs produzidos4: In

Hola a todos.... cordial saludo... Como se podran dar cuenta en contados segundos, soy completamente novato en R.. .asi que mis excusas por adelantado debido a lo simple del requerimiento... Tengo un archivo con datos, el cual adjunto.... la idea es ordenar los mismos por columna, una junto a la otra, estacion por estacion... esto es, los datos estan ordenados una estacion debajo de la otra,

Hi, I'm interpolating a list of syncronous accumulated precipitation observations collected over a number of raingauge stations sited over land, over a regular lat/lon grid using akima's interp(). Then, I plot and locate geographycally the resulting field with a filled.contour() and a call to map(). Everything is fine but I need to "blank" (in Golden Surfer nomenclature)

COD.EST VARIABLE AÑO DIA ENERO FEBRERO MARZO ABRIL MAYO JUNIO JULIO AGOSTO SEPBRE OCTUBRE NOVBRE DICBRE 1 2501001 PT 1986 1 NaN NaN NaN NaN 2.0 .0 .0 9.0 NaN NaN NaN NaN 2 2501001 PT 1986 2 NaN NaN NaN NaN .0 11.0 19.0 .0 NaN NaN NaN NaN 3 2501001 PT 1986 3 NaN NaN NaN NaN 11.0 3.0 .0 .0 NaN NaN

Hi everybody: I just generate interpolation maps with differents methods, like IDW and kriging, and now i want to compare the predict values versus real, and i don't who is the commant to do it. I want for example, if I pass from console the coordinates of a place, return me the predict value. Could anybody tell me how should do?. Thanks in advance --

Hi everybody: I just generate different maps of interpolation with different methods but with the same package -(gstat, i used the krige command). And now for evaluate the best method i want to compare the predict values versus experimental, but i don't know how do it. Could anybody tell me how should do it?. Thanks in advance. -- ######################################## Antoni Vi??dez

Hi all and thanks for your time in advance, I can't figure out why summary.lmrob complains when lmrob is used on a zooreg object. If the zooreg object is converted to vector before calling lmrob, no problems appear. Let me clarify this with an example: >library(robustbase) >library(zoo) >dad<-c(801.4625,527.2062,545.2250,608.2313,633.8875,575.9500,797.0500,706.4188,