Tidy Messy Data


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Documentation for package ‘tidyr’ version 1.1.3

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billboard Song rankings for Billboard top 100 in the year 2000
chop Chop and unchop
complete Complete a data frame with missing combinations of data
construction Completed construction in the US in 2018
crossing Expand data frame to include all possible combinations of values
drop_na Drop rows containing missing values
expand Expand data frame to include all possible combinations of values
expand_grid Create a tibble from all combinations of inputs
extract Extract a character column into multiple columns using regular expression groups
fill Fill in missing values with previous or next value
fish_encounters Fish encounters
full_seq Create the full sequence of values in a vector
gather Gather columns into key-value pairs
hoist Rectangle a nested list into a tidy tibble
nest Nest and unnest
nesting Expand data frame to include all possible combinations of values
nest_legacy Legacy versions of 'nest()' and 'unnest()'
pack Pack and unpack
pivot_longer Pivot data from wide to long
pivot_wider Pivot data from long to wide
population World Health Organization TB data
relig_income Pew religion and income survey
replace_na Replace NAs with specified values
separate Separate a character column into multiple columns with a regular expression or numeric locations
separate_rows Separate a collapsed column into multiple rows
smiths Some data about the Smith family
spread Spread a key-value pair across multiple columns
table1 Example tabular representations
table2 Example tabular representations
table3 Example tabular representations
table4a Example tabular representations
table4b Example tabular representations
table5 Example tabular representations
unchop Chop and unchop
uncount "Uncount" a data frame
unite Unite multiple columns into one by pasting strings together
unnest Nest and unnest
unnest_auto Rectangle a nested list into a tidy tibble
unnest_legacy Legacy versions of 'nest()' and 'unnest()'
unnest_longer Rectangle a nested list into a tidy tibble
unnest_wider Rectangle a nested list into a tidy tibble
unpack Pack and unpack
us_rent_income US rent and income data
who World Health Organization TB data
world_bank_pop Population data from the world bank