data_group <- data %>% # Group data group_by(gr1, gr2) %>% dplyr::summarize(gr_sum = sum(values)) %>% as.data.frame() data_group # Print grouped dataBy executing the previous R code we have created Table 2, i.e.
sample_n_by(): sample n rows by group from a table convert_as_factor(), set_ref_level(), reorder_levels(): Provides pipe-friendly functions to convert simultaneously multiple variables into a factor variable. make_clean_names(): Pipe-friendly function to make syntactically valid column names...
The group_by() function in R is from the dplyr package that is used to group rows by column values in the DataFrame, It is similar to the GROUP BY clause in SQL. R dplyr groupby is used to collect identical data into groups on DataFrame and perform aggregate functions on the grouped d...
sample_n_by(): sample n rows by group from a table convert_as_factor(),set_ref_level(),reorder_levels(): Provides pipe-friendly functions to convert simultaneously multiple variables into a factor variable. make_clean_names(): Pipe-friendly function to make syntactically valid column names (...
利用psych包中的describeBy()分组计算概述统计量: psych中的describeBy(data,by),其中data为目标数据框,by为分组依据的数据: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 > library(psych) > describeBy(iris[,-5],iris$Species) Descriptive statistics by group group: setosa vars n mean sd median...
To illustrate the GBTM technique, we will use a simulated dataset that represents the scores of individuals on a hypothetical variable measured at multiple time points. The dataset consists of three variables: ID, Time, and Score. # Simulating dataset.seed(123)n<-1000# Number of individualst<...
group=T则输出分组标记(abc),否则输出差异值。 Study: . ~ "Species" Duncan's new multiple range test for Sepal.Length Mean Square Error: 0.2650082 Species, means Sepal.Length std r Min Max setosa 5.006 0.3524897 50 4.3 5.8 versicolor 5.936 0.5161711 50 4.9 7.0 ...
extra by group # t = -1.8608, df = 17.776, p-value = 0.07939 # alternative hypothesis: true difference in means between group 1 and group 2 is not equal to 0 # 95 percent confidence interval: # -3.3654832 0.2054832 # sample estimates: # mean in group 1 mean in group 2 # 0.75 2.33...
sample_n_by(): sample n rows by group from a table convert_as_factor(), set_ref_level(), reorder_levels(): Provides pipe-friendly functions to convert simultaneously multiple variables into a factor variable. make_clean_names(): Pipe-friendly function to make syntactically valid column names...
Because of the limitations of single-level analytic techniques (e.g., multiple regression), researchers had to either choose individuals or groups as the unit of analysis. Data were then disaggregated to the individual level, or aggregated to the group level, in order to maintain a single-level...