# tally

From dplyr v0.5.0
by Hadley Wickham

##### Counts/tally observations by group.

`tally`

is a convenient wrapper for summarise that will either call
`n`

or `sum(n)`

depending on whether you're tallying
for the first time, or re-tallying. `count()`

is similar, but also
does the `group_by`

for you.

##### Usage

`tally(x, wt, sort = FALSE)`count(x, ..., wt = NULL, sort = FALSE)

count_(x, vars, wt = NULL, sort = FALSE)

##### Arguments

- x
a

`tbl`

to tally/count.- wt
(Optional) If omitted, will count the number of rows. If specified, will perform a "weighted" tally by summing the (non-missing) values of variable

`wt`

.- sort
if

`TRUE`

will sort output in descending order of`n`

- ..., vars
Variables to group by.

##### Examples

`library(dplyr)`

```
if (require("Lahman")) {
batting_tbl <- tbl_df(Batting)
tally(group_by(batting_tbl, yearID))
tally(group_by(batting_tbl, yearID), sort = TRUE)
# Multiple tallys progressively roll up the groups
plays_by_year <- tally(group_by(batting_tbl, playerID, stint), sort = TRUE)
tally(plays_by_year, sort = TRUE)
tally(tally(plays_by_year))
# This looks a little nicer if you use the infix %>% operator
batting_tbl %>% group_by(playerID) %>% tally(sort = TRUE)
# count is even more succinct - it also does the grouping for you
batting_tbl %>% count(playerID)
batting_tbl %>% count(playerID, wt = G)
batting_tbl %>% count(playerID, wt = G, sort = TRUE)
}
```

*Documentation reproduced from package dplyr, version 0.5.0, License: MIT + file LICENSE*

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