R Resources  selmling/AnalyticsandDataExploration Wiki
dplyr
:

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 groupwise:
group_by()
: changes the scope of following function from operating on the entire dataset to operating on it groupbygroup.

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 intermediatestep variables, useful to read this symbol as “then”
R techniques:

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