tidyr

问题 This question already has answers here : How do I deal with special characters like \^$.?*|+()[{ in my regex? (2 answers) Closed 2 years ago . I have the following data set D7 name sex_age eye_color height 1 J M.34 Other 61 2 A F.55 Blue 59 3 T M.76 Brown 51 4 D F.19 Other 57 I want to separate the column sex_age into sex column and age column, so I type separate(D7,sex_age,c('sex','age'),sep='.') But it generates name sex age eye_color height 1 J Other 61 2 A Blue 59 3 T Brown 51 4 D Other

问题 I have a set of data where I have annual totals for specific values stored in one row (observation). I'd like to tidy the data in R so that this total row is broken out for each month using a simple equation (total/12) that stores the annual total divided by 12 in each of 12 rows as a monthly total. I'm trying to do this in R but am very beginner and not quite sure where to start. Example is below: Date | Total 2015 | 12,000 Some R function to convert to: Date | Total 01-01-2015 | 1,000 02-01

问题 When I use the complete() function to fill in rows in my data that have no cases I find it is creating many duplicate rows as well. These can be removed with the unique() function, but I want to understand how I can avoid generating all these extra rows in the first place. library(dplyr) library(tidyr) # An incomplete table mtcars %>% group_by(vs, cyl) %>% count() # complete() creates a table with many duplicate rows temp <- mtcars %>% group_by(vs, cyl) %>% count() %>% complete(vs = c(0, 1),

问题 I have a dataframe with a value column for multiple year. The years might not follow a sequence and might have a missing 5th year. Here is an example dataframe df = data.frame(code = c("AFG", "AGO", "ALB", "AND", "ARB", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AUT", "AUT", "AUT", "ABW", "AFG", "AGO", "ALB", "AND", "ARB", "ARE", "ARG", "ARM", "ARM"), PPT = c(123, 42, 23, 5, 42, 4, 23, 25, 42, 23, NA, 5563, 56, 54, 645, 6, 4,53, 656, 65, 5563, 646, 6, 66, 54), Year = c(1990, 1991, 1992

问题 I am importing a series of surveys as .csv files and combining into one data set. The problem is for one of the seven files some of the variables are importing slightly differently. The data set is huge and I would like to find a way to write a function to run over dataset that is giving me trouble. In some of the variables there is an underscore when there should be a dot. Not all variables are of the same format but the ones that are incorrect are, in that the underscore is always the 6th

问题 My data looks like this: # A tibble: 6 x 4 name val time x1 <chr> <dbl> <date> <dbl> 1 C Farolillo 7 2016-04-20 51.5 2 C Farolillo 3 2016-04-21 56.3 3 C Farolillo 7 2016-04-22 56.3 4 C Farolillo 13 2016-04-23 57.9 5 C Farolillo 7 2016-04-24 58.7 6 C Farolillo 9 2016-04-25 59.0 I am trying to use the pivot_wider function to expand out the data based on the name column. I use the following code: yy <- d %>% pivot_wider(., names_from = name, values_from = val) Which gives me the following

问题 I have a table with data from an stream gauge arranged as this: Water.Year May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr 1 1953-1954 55.55 43.62 30.46 26.17 26.76 41.74 19.92 41.25 28.77 20.96 12.47 10.51 2 1954-1955 23.49 81.35 46.71 29.33 67.83 133.30 37.62 30.16 21.07 19.38 13.87 10.63 3 1955-1956 9.87 51.59 55.36 63.03 154.08 98.15 104.06 32.85 22.89 17.30 15.68 10.88 > data <- structure(list(Water.Year = structure(1:6, .Label = c("1953-1954", "1954-1955", "1955-1956", "1956-1957",

问题 I'm creating a shiny app in which the user will upload a .csv file that contains several variables. Using dplyr , I will select the first four variables, shown below, and convert them from long format. DATA df <- read.table(text = c(" Customer Rate Factor Power W1 6 TK1 5 W2 3 TK1 0 W3 1 TK1 0 W4 2 TK1 0 W5 4 TK1 0 W6 8 TK1 0 W7 5 TK1 0 W8 7 TK1 3 W1 6 TK2 0 W2 3 TK2 1 W3 1 TK2 0 W4 2 TK2 5 W5 4 TK2 0 W6 8 TK2 0 W7 5 TK2 0 W8 7 TK2 3 W1 6 TK3 0 W2 3 TK3 5 W3 1 TK3 1 W4 2 TK3 0 W5 4 TK3 0 W6 8

问题 I am using tidyr and lubridate to convert a wide table to a long table. The following works just fine. > (df <- data.frame(hh_id = 1:2, bday_01 = ymd(20150309), bday_02 = ymd(19850911), bday_03 = ymd(19801231))) hh_id bday_01 bday_02 bday_03 1 1 2015-03-09 1985-09-11 1980-12-31 2 2 2015-03-09 1985-09-11 1980-12-31 > gather(df, person_num, bday, starts_with("bday_0")) hh_id person_num bday 1 1 bday_01 2015-03-09 2 2 bday_01 2015-03-09 3 1 bday_02 1985-09-11 4 2 bday_02 1985-09-11 5 1 bday_03

问题 I have a data frame with variables in the rows and the columns that both contain variables, so I am trying to use pivot wide tidy the data. My data looks like the following: head(df) # A tibble: 6 x 4 State Year Var X <chr> <dbl> <chr> <dbl> 1 ALABAMA 2001 APPALACHIAN REGIONAL COMMISSION (ARC) 3048031 2 ALABAMA 2001 CORPORATION FOR NATIONAL AND COMMUNITY SERVICE (CNCS) 1765835 3 ALABAMA 2001 DEPARTMENT OF AGRICULTURE (USDA) 282530429 4 ALABAMA 2001 DEPARTMENT OF COMMERCE (DOC) 17838084 5