tidyverse_function_signup_2022

	A	B	C	D	E	F	G
1	package	funcs	Part	Presented in 2021	Name	Week to Present	Description
2	dplyr	distinct()	Part 3				Subset distinct/unique rows
3	dplyr	first()	Part 3				Extract the first, last or nth value from a vector
4	dplyr	last()	Part 3				Extract the first, last or nth value from a vector
5	dplyr	near()	Part 3				Compare two numeric vectors
6	dplyr	pull()	Part 3		Saffron	9	Extract a column as a vector
7	dplyr	relocate()	Part 3	x	Trisha	8	Use relocate() to change column positions, using the same syntax as select() to make it easy to move blocks of columns at once
8	dplyr	slice_max()	Part 3	x	Isabel	11	select rows with highest or lowest values of a variable.
9	dplyr	slice_min()	Part 3		Isabel	11	select rows with highest or lowest values of a variable.
10	dplyr	slice_sample()	Part 3				randomly selects rows.
11	ggplot2	geom_density()	Part 3	x	Mary	3	Adds a density plot that can show distribution of variables
12	ggplot2	geom_hex()	Part 3				Hexagonal heatmap of 2d bin counts
13	ggplot2	geom_jitter()	Part 3	x			adds a small amount of random variation to the location of each point, and is a useful way of handling overplotting caused by discreteness in smaller datasets.
14	ggplot2	geom_smooth()	Part 3	x	Mia	8	Aids the eye in seeing patterns in the presence of overplotting.
15	haven	zap_label()	Part 3				Removes label, leaving unlabelled vectors as is. Use this if you want to simply drop all label attributes from a data frame.
16	janitor	get_dupes()	Part 3		Becky	6	Get rows of a 'data.frame' with identical values for the specified variables.
17	janitor	remove_empty()	Part 3				Remove empty rows or columns from a data.frame
18	openxlsx	write.xlsx()	Part 3				Write data.frame or a list of data.frames to an xlsx file
19	dplyr	add_count()	Part 4				Add a column with group counts
20	dplyr	count()	Part 4	x			Count observations by group
21	dplyr	lead()	Part 4	x			Compute lagged or leading values
22	dplyr	n_distinct()	Part 4		Joseph	10	Efficiently count the number of unique values in a set of vectors
23	dplyr	ntile()	Part 4		Qijia	4	Categorize a vector into percentiles
24	dplyr	recode()	Part 4				Replace values
25	ggplot2	geom_tile()	Part 4	x			Plot rectangles and heatmaps
26	tidyr	separate_rows()	Part 4	x			Separate a collapsed column into multiple rows
27	tidyr	unite()	Part 4	x			Unite multiple columns into one by pasting strings together
28	dplyr	lag()	Part 5				Compute lagged or leading values
29	forcats	fct_collapse()	Part 5		Libby White	5	Collapse factor levels into manually defined groups
30	forcats	fct_infreq()	Part 5	x	Liz Wagner	10	Reorder factor levels by frequency
31	forcats	fct_lump()	Part 5		Kathryn Liu	5	Lump together factor levels into "other"
32	forcats	fct_recode()	Part 5				Change factor levels by hand
33	forcats	fct_relevel()	Part 5	x		9	Reorder factor levels by hand
34	forcats	fct_rev()	Part 5				Reverse order of factor levels: example should use ggplot2
35	lubridate	ceiling_date()	Part 5				Round, floor and ceiling methods for date-time objects
36	lubridate	floor_date()	Part 5	x			Round, floor and ceiling methods for date-time objects
37	lubridate	force_tz()	Part 5				Replace time zone to create new date-time
38	scales	breaks_pretty()	Part 5	x	Ashley Blair	6	Pretty breaks for date/times
39	scales	percent()	Part 5		barbara cassese		Label percentages
40	stringr	str_detect_all()	Part 5		Ngoc Le	9	Detect the presence or absence of a pattern in a string.
41	stringr	str_flatten()	Part 5				Collapse a string vector into one string
42	stringr	str_match()	Part 5				this is a bit advanced, requiring knowledge of regex; create groups and filter based on regex expression
43	stringr	str_trim()	Part 5				Trim whitespace from a string
44	stringr	str_wrap()	Part 5	x			Wrap strings into nicely formatted paragraphs.
45	tidyr	crossing()	Part 5	x			Expand data frame to include all possible combinations of values
46	tidyr	drop_na()	Part 5	x	Laura Jacobson	7	Drop rows containing missing values
47	tidyr	expand_grid()	Part 5				Create a tibble from all combinations of inputs
48	tidyr	extract()	Part 5		Shauna Rakshe	6	this is a bit advanced, requiring knowledge of regex; create groups and filter based on regex expression
49	tidyr	uncount()	Part 5				Duplicate rows according to a weighting variable
50	dplyr	coalesce()	Part 6		Yan Liu	6	Find first non-missing element
51	dplyr	rowwise()	Part 6				Compute on a data frame a row-at-a-time
52	purrr	pluck()	Part 6	x			Pluck or chuck a single element from a vector or environment
53	purrr	walk()	Part 6	x			Apply a function to each element of a list or atomic vector
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