R Resources - selmling/Analytics-and-Data-Exploration GitHub Wiki

Five main verbs for data manipulation:
- filter(): pick observation based on their values
- arrange(): reorder rows
- mutate(): create new variables as a function of existing variables
- summarize(): collapse many values down to a single summary
These can all be used as a function of the entire dataframe / tibble OR group-wise:
- group_by(): changes the scope of following function from operating on the entire dataset to operating on it group-by-group.
Each of these functions work similarly:
- First argument of the function is always the data frame.
- Subsequent arguments describe what to do with the data frame, using the variable names without quotes
- Result in a new data frame
Useful creation functions:
- x / sum(x): proportion of the total
- y - mean(y): difference from the mean
- (n()): to count, or (sum(!is.na(x))): to count nonmissing values
- quantile(x, 0.25): find value of x that is greater than 25% of the values (and less than 75%)
Useful wrangling functions:
- na.rm = TRUE: drop NA rows
Useful operators:
- %>% pipe operator, hotkey: command+shift+M: use this instead of creating intermediate-step variables, useful to read this symbol as “then”