Function Reference

Function	Description
%within%	Test interval membership
abs	Absolute value
acos	Inverse cosine
acosh	Inverse hyperbolic cosine
add_diagnostics	Add Model Diagnostics
all_of	Select an explicit set of columns
am	Check whether a time is before noon
anova	Analysis of Variance (ANOVA)
anti_join	Filter rows lacking matches
any_of	Select columns that exist
apropos	Search for functions by keyword
args	Get function arguments and their types
arrange	Arrange rows
arrange_node	Arrange Pipeline Nodes
as_date	Convert values to Date
as_datetime	Convert values to Datetime
as_factor	Coerce values to factors
asin	Inverse sine
asinh	Inverse hyperbolic sine
assert	Assert Condition
atan	Inverse tangent
atan2	Two-argument arctangent
atanh	Inverse hyperbolic tangent
augment	Augment Data with Model Calculations
bind_cols	Combine DataFrames by columns
bind_rows	Stack DataFrames by rows
body	Get function body
build_pipeline	Build Pipeline Artifacts
build_pipeline_internal	Build Pipeline Internally
case_when	Vectorized Case-When
casewhen	Vectorized case-when
cat	Print values without escaping
cbind	Column bind matrices
ceil	Ceiling alias
ceiling	Ceiling function
ceiling_date	Round dates up
chain	Chain Two Pipelines
char_at	Get character at index
clean_colnames	Clean DataFrame Column Names
coef	Model Coefficients
col_lens	Create a Column Lens
colnames	Get column names
compare	Compare Models
complete	Complete a data frame
compose	Compose Lenses
conf_int	Confidence Intervals for Model Coefficients
contains	Check if string contains substring
cor	Correlation
cos	Cosine
cosh	Hyperbolic cosine
count	Count rows by group
cov	Covariance
crossing	Create a data frame from all combinations of inputs
cumall	Cumulative All
cumany	Cumulative Any
cume_dist	Cumulative Distribution
cummax	Cumulative Maximum
cummean	Cumulative Mean
cummin	Cumulative Minimum
cumsum	Cumulative Sum
cut	Discretize numeric vector
cv	Coefficient of variation
dataframe	Create a DataFrame
day	Extract the day of month
days_in_month	Get the number of days in a month
dense_rank	Dense Rank
deserialize	Deserialize Value
df_residual	Residual Degrees of Freedom
diag	Create or extract diagonal
difference	Subtract one pipeline from another
dir_exists	Check if directory exists
dispersion	Dispersion Parameter
distinct	Keep unique rows
downstream_of	Extract Downstream Subgraph
drop_na	Remove rows with missing values
ends_with	Check if string ends with suffix
enquo	Capture a function argument’s expression (non-standard evaluation)
enquos	Capture variadic argument expressions (non-standard evaluation)
env	Get environment variable
env_var_lens	Pipeline Env Var Lens
error	Raise Error
error_code	Get error code
error_context	Get error context
error_message	Get error message
eval	Evaluate a quoted expression or quosure
everything	Select every column
exit	Exit the interpreter
exp	Exponential function
expand	Create all combinations of values
explain	Explain Value
explain_json	Explain Value as JSON
expr	Capture an expression
exprs
factor	Create factor values
fct	Create factors in first-seen order
fct_c	Concatenate factor vectors
fct_collapse	Collapse multiple levels
fct_drop	Drop unused factor levels
fct_expand	Add explicit factor levels
fct_infreq	Order factor levels by frequency
fct_lump_min	Lump factor levels below a minimum count
fct_lump_n	Keep the most frequent factor levels
fct_lump_prop	Lump factor levels below a minimum proportion
fct_other	Replace unlisted levels with Other
fct_recode	Rename factor levels
fct_relevel	Move selected levels to the front
fct_reorder	Order factor levels by another vector
fct_rev	Reverse factor levels
file_exists	Check if file exists
fill	Fill missing values
filter	Filter rows
filter_lens	Filter Lens
filter_node	Filter Pipeline Nodes
fit_stats	Model Goodness-of-Fit Statistics
fivenum	Five-number summary
floor	Floor function
floor_date	Round dates down
force_tz	Retag a datetime with a timezone
format_date	Format dates as strings
format_datetime	Format datetimes as strings
full_join	Join all rows from both tables
get	Get Value via Lens
getwd	Get current working directory
glimpse	Glimpse DataFrame
greet	Greet someone
group_by	Group by columns
head	Get the first n rows/items
help	Display documentation for a function
hour	Extract the hour
huber_loss	Huber loss
idx_lens	Index Lens
ifelse	Vectorized If-Else
index_of	Find index of substring
inner_join	Join matching rows
inspect_node	Inspect Pipeline Node Metadata
inspect_pipeline	Inspect Pipeline Logs
intent_fields	Get All Intent Fields
intent_get	Get Intent Field
intersect	Keep shared pipeline nodes
interval	Create an interval
inv	Matrix inverse
iota	Create a vector of ones
iqr	Interquartile range
is_character	Check for character columns
is_empty	Check if string is empty
is_error	Check if a value is an Error
is_factor	Check for factor columns
is_leap_year	Check for leap years
is_logical	Check for logical columns
is_na	Check for NA
is_numeric	Check for numeric columns
isoweek	Extract the ISO week number
isoyear	Extract the ISO week-based year
kron	Kronecker product
kurtosis	Excess kurtosis
lag	Lag values
last_index_of	Find last index of substring
lead	Lead values
left_join	Join rows from the left table
length	Get length
lens	Lens Library
levels	Get factor levels
list_files	List files in directory
list_logs	List Pipeline Logs
lm	Linear Model
log	Natural logarithm
mad	Median absolute deviation
make_date	Construct a Date value
make_datetime	Construct a Datetime value
make_period	Create a period value
map	Map a function over a list
matches	Match columns by regex
matmul	Matrix multiplication
max	Maximum value
mday	Extract the day of month
mean	Compute arithmetic mean of numeric values
median	Median
min	Minimum value
min_rank	Minimum Rank
minute	Extract the minute
mode	Mode
modify	Multiple Lens Transformations
month	Extract or label the month
mutate	Mutate DataFrame
mutate_node	Mutate Pipeline Node Metadata
n	Group size aggregation
n_distinct	Count distinct values
na	Generic NA
na_bool	Boolean NA
na_float	Float NA
na_int	Integer NA
na_string	String NA
ncol	Number of columns
ndarray	Create an N-dimensional array
ndarray_data	Get NDArray data
nest	Nest columns into sub-dataframes
nesting	Helper to find combinations present in data
nobs	Number of Observations
node	Configure a Pipeline Node
node_lens	Pipeline Node Lens
normalize	Normalize values
now	Get the current datetime
nrow	Number of rows
ntile	N-tiles
ordered	Create ordered factors
over	Transform Focused Value
package_info	Get package information
packages	List available packages
parallel	Combine Pipelines in Parallel
parse_date	Parse dates from strings
parse_datetime	Parse datetimes from strings
parse_file	Parse T-Doc Comments
patch	Overlay one pipeline onto another
path_abs	Resolve relative path to absolute
path_basename	Get filename component of a path
path_dirname	Get directory portion of a path
path_ext	Get file extension
path_join	Join multiple path segments
path_stem	Get filename without extension
pchisq	Chi-squared distribution CDF
percent_rank	Percent Rank
pf	F distribution CDF
pipeline_assert	Assert Pipeline Validity
pipeline_copy	Copy Pipeline Node Artifacts to Local Directory
pipeline_cycles	Detect Pipeline Cycles
pipeline_deps	List Node Dependencies
pipeline_depth	Maximum Topological Depth
pipeline_dot	Export Pipeline as DOT Graph
pipeline_edges	Pipeline Dependency Edges
pipeline_leaves	Pipeline Leaf Nodes
pipeline_node	Get Pipeline Node
pipeline_nodes	List Pipeline Nodes
pipeline_print	Pretty-Print a Pipeline
pipeline_roots	Pipeline Root Nodes
pipeline_run	Run Pipeline
pipeline_summary	Pipeline Summary
pipeline_to_frame	Convert Pipeline to DataFrame
pipeline_validate	Validate a Pipeline
pivot_longer	Pivot longer
pivot_wider	Pivot wider
pm	Check whether a time is after noon
pnorm	Normal distribution CDF
poly	Polynomial basis expansion
populate_pipeline	Populate Pipeline
pow	Power function
predict	Linear Model Prediction
pretty_print	Pretty-print a value
print	Print values to standard output
prune	Prune Pipeline Leaf Nodes
pt	Student t distribution CDF
pull	Extract column as vector
pyn	Configure a Python Pipeline Node
quantile	Quantiles
quarter	Extract the quarter
quo	Capture an expression with its lexical environment (quosure)
quos	Capture multiple expressions with their lexical environment (quosures)
range	Range
read_arrow	Read Arrow IPC file
read_csv	Read CSV file
read_file	Read file contents
read_log	Read Node Build Log
read_node	Read Pipeline Node Artifact
read_parquet	Read Parquet file
rebuild_node	Rebuild a Pipeline Node
relocate	Move columns to a new position
rename	Rename DataFrame columns
rename_node	Rename a Pipeline Node
replace_first	Replace first occurrence
replace_na	Replace missing values
reshape	Reshape an NDArray
residuals	Model Residuals
rewire	Rewire a Node’s Dependencies
rm	Remove objects from the environment
rn	Configure an R Pipeline Node
round	Round values
round_date	Round dates to the nearest unit
row_lens	Row Lens
row_number	Row Number
run	Run a shell command
run_doctor	Run Package/Project Doctor
scaffold_package	Scaffold a new T package
scaffold_project	Scaffold a new T project
scale	Scale values
score	Model Scoring
sd	Standard Deviation
second	Extract the second
select	Select columns
select_node	Select Node Metadata Fields
semester	Extract the semester
semi_join	Filter rows using matches in another table
separate	Separate a character column into multiple columns
separate_rows	Split delimited values into rows
seq	Generate a sequence of integers
serialize	Serialize Value
set	Set Focused Value
shape	Get NDArray dimensions
shn	Configure a Shell Pipeline Node
sigma	Residual Standard Deviation
sign	Sign of number
signif	Significant-digit rounding
sin	Sine
sinh	Hyperbolic sine
skewness	Skewness
slice	Extract slice
slice_max	Keep rows with the largest values
slice_min	Keep rows with the smallest values
source	Get function source code
sqrt	Square root
standardize	Standardize values
starts_with	Check if string starts with prefix
str_count	Count regex matches
str_detect	Test whether a regex matches
str_extract	Extract the first regex match
str_extract_all	Extract all regex matches
str_flatten	Flatten a collection of strings
str_format	Named string interpolation
str_join	Join strings with a separator
str_lines	Split string into lines
str_nchar	Get character count
str_pad	Pad strings to a target width
str_repeat	Repeat a string
str_replace	Replace all occurrences
str_split	Split a string on a delimiter
str_sprintf	Format a string
str_string	Convert to string
str_substring	Extract substring
str_trim	Trim whitespace
str_trunc	Truncate strings for display
str_words	Split string into words
subgraph	Extract Connected Subgraph
sum	Sum of numeric values
summarize	Summarize data
summary	Model Summary
swap	Swap a Pipeline Node Implementation
t_doc	Generate Documentation
t_make	Build Pipeline Internally
t_read_json	Read Value from JSON
t_read_onnx	Read an ONNX model file
t_read_pmml	Read a PMML model file
t_run	Run a T script
t_test	Run tests
t_write_json	Write Value to JSON
tail	Get the last n rows/items
tan	Tangent
tanh	Hyperbolic tangent
to_array	Convert to NDArray
to_float	Convert to Float
to_integer	Convert to Integer
to_lower	Convert to lowercase
to_numeric	Convert to Numeric
to_upper	Convert to uppercase
today	Get the current date
trace_nodes	Trace Pipeline Nodes
transpose	Transpose matrix
trim_end	Trim trailing whitespace
trim_start	Trim leading whitespace
trimmed_mean	Trimmed mean
trunc	Truncate values
type	Get the type name of a value
tz	Extract the timezone label
uncount	Expand rows by weight
ungroup	Remove grouping
union	Combine two pipelines
unite	Combine multiple columns into one character column
unnest	Expand nested columns
update_flake_lock	Update Dependencies
upstream_of	Extract Upstream Subgraph
var	Variance
vcov	Variance-Covariance Matrix
wald_test	Joint Wald Test
wday	Extract or label the weekday
week	Extract the week number
where	Select columns by predicate
winsorize	Winsorize values
with_tz	Convert a datetime to a new timezone
write_arrow	Write Arrow IPC file
write_csv	Write CSV file
write_text	Write text to a file
yday	Extract the day of year
year	Extract the year component