R编程 初学者 代码整理
Collecting of R Code (Noob)

R Packages

install commands like install.packages and install_github
do library function to load them

• dplyr: a grammar of data manipulation
• ggplot2: for data visualization

Basic

• Load Data: data() from data files or load()
• Dimensions of Data: dim(data_file_name)
• Names of variables: names(data_file_name)
• Single column of data: data_file_name$variable_name
• Data structure: str(data_file_name)
• Create new data from old: new_data_file_name <- data_file_name
• Descending order: desc
• If else: ifelse(test, yes, no)
• Counting streak lengths: calc_streak(data_file_name)
• Table: table(data)
• Search the names for a fragment of the name: grep("search_name", names(data_file_name), value = TRUE)

dplyr

dplyr

• data_file_name %>%
  • group_by(variable_name) %>%:grouped the data by origin
  • mutate(): adds new variables that are functions of existing variables

      data_file_name <- data_file_name %>%
        mutate(new_variable = variable_A simple_mathematical_operator variable_B)
    

  • select(): picks variables based on their names.
  • filter(): picks cases based on their values.

      new_data_file_name <- data_file_name %>%
        filter(variable_name logical_operator filter_condition)
    

    • find the one is na: filter(is.na(variable_name))
  • summarise(): reduces multiple values down to a single summary.

      data_file_name %>%
        summarise(mean_variable = mean(variable_name), sd_variable = sd(variable_name), n = n())
    

  • arrange(): changes the ordering of the rows.

      data_file_name %>%
        summarise(median_variable = median(variable_name)) %>%
        arrange(desc(median_variable))
    

    • desc: Descending order
  • distinct(): select distinct/unique rows
  • sample(): simulation, uses random numbers to generate an outcome

      data_outcomes <- c("variable_outcome_A", "variable_outcome_B")
      sample(data_outcomes, size = 100, replace = TRUE, prob = c( #variable_A_prob, #variable_B_prob ))
    

ggplot2

• Making graphics:

    ggplot(data = data_file_name, aes(x = x_aes_name, y = y_aes_name)) + 
    geom_line() +  
    geom_point()
  

• Making side-by-side box plots: geom_boxplot()

• Making segmented bar plot:

    ggplot(data = data_file_name, aes(x = x_aes_name, fill = variable_name)) + 
    geom_bar()
  

• Making histogram:

    ggplot(data = data_file_name, aes(x = x_aes_name)) + 
    geom_histogram(binwidth = #number )