Example: Group Data Frame Based On Multiple Columns Using dplyr Package This example explains how to group and summarize our data frame according to two variables using the functions of thedplyr package. In order to use the functions of the dplyr package, we first have to install and load dpl...
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group_by(col_A)%>%summarise(col_name = paste(col_A, collapse = "|")) 将一个string中的所有数字都去掉: str_remove_all("335436_dfg345fgh","\\d+") 将一个string中的所有非数字都去掉: str_remove_all("335436_dfg345fgh","\\D+") 提取一个string中的所有数字: string_extract_all("......
reactor internalsreac reactor loading reactor side-film coe reactor variablesreac reactorappurtenance reactorbehaviour reactor atomic reactor boiling cycle reactor carbon reactor gas-cooled reactor ground test reactor multiple-regi reactor nak-cooled reactor tamped reactor zero-energy read a few lines read...
ggscatterstats() scatterplots for correlation between two variables ggcorrmat() correlation matrices for correlations between multiple variables ggpiestats() pie charts for categorical data ggbarstats() bar charts for categorical data ggcoefstats() dot-and-whisker plots for regression models and meta...
(car$State),] # sort by a single column, State >>> ascending order 从小排列到大 new <- car[order(car$fm, car$Mileage),] # sort by multiple columns new # melt(): # suppose we want to keep only two vars as identifiers, vehicle and state # and combine all other vars into a ...
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 (...
Hi, I try to group by two variables in nPlot. I would like to get interactive Legend for both of this variables so I can filter on both variables. My code in R for single group variables looks as follows: require(devtools) install_github...
ggplot(my_summary, aes(LanguageGroup, n, fill = Hobbyist)) + geom_bar(stat = "identity") + facet_wrap(facets = vars(Gender), scales = "free_y") Now it’s easier to compare multiple variables by gender.For more R tips, head to the “Do More With R” page on InfoWorld or ch...
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