summary

问题 I am having trouble to prepare a summary table using dplyr based on the data set below: set.seed(1) df <- data.frame(rep(sample(c(2012,2016),10, replace = T)), sample(c('Treat','Control'),10,replace = T), runif(10,0,1), runif(10,0,1), runif(10,0,1)) colnames(df) <- c('Year','Group','V1','V2','V3') I want to calculate the mean, median, standard deviation and count the number of observations by each combination of Year and Group . I have successfully used this code to get mean , median and sd :

问题 I am having trouble to prepare a summary table using dplyr based on the data set below: set.seed(1) df <- data.frame(rep(sample(c(2012,2016),10, replace = T)), sample(c('Treat','Control'),10,replace = T), runif(10,0,1), runif(10,0,1), runif(10,0,1)) colnames(df) <- c('Year','Group','V1','V2','V3') I want to calculate the mean, median, standard deviation and count the number of observations by each combination of Year and Group . I have successfully used this code to get mean , median and sd :

问题 I am having trouble to prepare a summary table using dplyr based on the data set below: set.seed(1) df <- data.frame(rep(sample(c(2012,2016),10, replace = T)), sample(c('Treat','Control'),10,replace = T), runif(10,0,1), runif(10,0,1), runif(10,0,1)) colnames(df) <- c('Year','Group','V1','V2','V3') I want to calculate the mean, median, standard deviation and count the number of observations by each combination of Year and Group . I have successfully used this code to get mean , median and sd :

问题 I am having trouble to prepare a summary table using dplyr based on the data set below: set.seed(1) df <- data.frame(rep(sample(c(2012,2016),10, replace = T)), sample(c('Treat','Control'),10,replace = T), runif(10,0,1), runif(10,0,1), runif(10,0,1)) colnames(df) <- c('Year','Group','V1','V2','V3') I want to calculate the mean, median, standard deviation and count the number of observations by each combination of Year and Group . I have successfully used this code to get mean , median and sd :

问题 Number of Threads (users) : 10 Ramp-up Period (in seconds) : 1 Loop Count : 2 Result - When I ran the test it shows 40 samples rather expected count was 20 . I want to ask what could be the reason behind 40 samples . Number of Threads (users): 10 Ramp-up Period (in seconds): 1 Loop Count : 1 Result - When I ran the test it shows 20 samples rather expected count was 10 . Error - I tried to compute but I can't understand how it is doubling the user count every time 回答1: It just means that every

问题 I have a dataset of 500 trials per participant that I want to sample from in various quantities (i.e. I want to sample the same number of trials from each participant) and then compute the mean for each participant. Instead of doing so, it is creating a file with a one mean for each participant separately for each "num", e.g. if the mean for participant 1 with 125 trials is 426 that will be the whole file, then another file for participant 1 with 150 trials with a single value, and that is

问题 I'm trying to calculate some summary information to help me check for outliers in different groups in a dataset. I can get the sort of output I want using dplyr::group_by() and dplyr::summarise() - a dataframe with summary information for each group for a given variable. Something like this: Sepal.Length_outlier_check <- iris %>% dplyr::group_by(Species) %>% dplyr::summarise(min = min(Sepal.Length, na.rm = TRUE), max = max(Sepal.Length, na.rm = TRUE), median = median(Sepal.Length, na.rm =

问题 This question already has answers here : Apply several summary functions on several variables by group in one call (7 answers) Closed 4 years ago . I have a data.frame like this (example): product protein fat starch aaa 40 5 10 bbb 50 6 8 ccc 12 50 4 and I want to ask for a summary of this values (min,max,1stQ, 3rdQ..). When I run: aggregate(protein~product,summary,data=DATA4, na.rm = TRUE) I have this... product protein.Min. protein.1st Qu. protein.Median protein.Mean protein.3rd Qu. protein

问题 I am trying to run a beta regression model in R using the betareg package. However, I am surprisingly running into memory size issue. Let me explain why this surprises me. I am using Windows 7, 64 Bit, R-64, and have 32 GB in RAM. The betareg command I am running is:: br1 <- betareg(dfp ~ ago + evl + spe + low + poly(fpt, 4, raw = T), data = tt[tt$zero_one_ind == 1, ], model = T, y = F, x = F) The object size of the betareg model is: print(object.size(br1), units = "Mb") 46 Mb This is the

问题 I am trying to run a beta regression model in R using the betareg package. However, I am surprisingly running into memory size issue. Let me explain why this surprises me. I am using Windows 7, 64 Bit, R-64, and have 32 GB in RAM. The betareg command I am running is:: br1 <- betareg(dfp ~ ago + evl + spe + low + poly(fpt, 4, raw = T), data = tt[tt$zero_one_ind == 1, ], model = T, y = F, x = F) The object size of the betareg model is: print(object.size(br1), units = "Mb") 46 Mb This is the