dplyr

问题 Let's say I have a list of suburb names, crime rate and their council names on a separate table. I know that left_join(table1, table2, by=Suburb) will return the table with newly added rows due to the multiple matches for council. The problem is that suburbs 3 and 4 overlap into two councils. Is there a way to only get the left join to only return the first match only rather than creating new rows to facilitate for the extra ones? In addition, on Table 2, is there a function to only keep the

问题 Let's say I have a list of suburb names, crime rate and their council names on a separate table. I know that left_join(table1, table2, by=Suburb) will return the table with newly added rows due to the multiple matches for council. The problem is that suburbs 3 and 4 overlap into two councils. Is there a way to only get the left join to only return the first match only rather than creating new rows to facilitate for the extra ones? In addition, on Table 2, is there a function to only keep the

问题 This question already has answers here : Vectorized IF statement in R? (6 answers) Convert dataframe column to 1 or 0 for “true”/“false” values and assign to dataframe (5 answers) Closed 2 years ago . I'm currently trying to create a new column in my data frame based on another column using mutate(). I want to make the new column a binomial variable (1 or 0) based on whether the column its based on says "Active" or not. I'm currently trying to do it by saying: violations$outcome = if

问题 I am using dplyr and lubridate. I am using read_excel to export a data.frame into R from excel. In Excel, I have a column that consists of mdy_hms AM or PM. In R, my code consists of: df$dateTimeEtc And this prints out as an example: "2017-03-07 11:10:37 UTC" "2017-03-22 10:04:42 UTC" "2017-03-08 09:36:49 UTC" However, I have tried to use: df <- df %>% mutate(dateTimeEtc = mdy_hms(dateTimeEtc)) So that R recognizes these data points in a mdy_hms (not sure what to do to include the AM/PM)

问题 This question already has answers here : Convert continuous numeric values to discrete categories defined by intervals (2 answers) Closed 1 year ago . I have the following columns in a dataframe which difference between each row is 0.012 s : Time 0 0.012 0.024 0.036 0.048 0.060 0.072 0.084 0.096 0.108 I want to come up with intervals starting from beginning increasing by 0.030, so intervals or time window of every 0.03 later to be used in group by. 回答1: You can try findInterval like

问题 I am trying to create a dummy variable for years. Currently, my data has a birth_date and a program start_date for each observation. I have been able to create a variable measuring an individual's age in days, but what I am actually looking for is a variable: age_join_date that tells me the following: Individual birth_date start_date age_at_join_date A 1990-12-31 2010-12-31 20 yrs old B 1990-12-31 2011-12-31 21 yrs old Essentially what I care about is one's age at the time they joined the

问题 I have the raw data frame: igroup=c("A", "B", "C") demo_df=data.frame(date=c("2018-11-28", "2018-12-17", "2019-01-23"), group) Raw data frame: date group 1 2018-11-28 A 2 2018-12-17 B 3 2019-01-23 C I want to have a data frame that expand the date to next column but still keep the group information. For example, date from 2018-11-28 to 2018-12-16 is with group A, date from 2018-12-17 to 2019-01-22 is with group B and 2019-01-23 is with group C. This is the output ( result_df ) I want: time=c

问题 Closed. This question is not reproducible or was caused by typos. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 3 years ago . Improve this question Let's presume I have a data.fram called exprCore1 loaded in R-Studio, the df looks like this: measure qid value 1 p5 1 0.2 2 p100 1 0.8 3 map 1 0.22 4 p5 2 0.4 5 p100 2 0.5 6 map 2 0.32 Basically all want is every column in which the measurement method is "map"

问题 I am trying to plot a line graph of different types of cars sold per day in ** plotly ** on ** R **. The way the graph would look is that, it would have line graphs of each type of car that was sold on each day. So lets say I have the dataframe called ** df1 ** id date Value Honda 10/30/12 2 Honda 10/31/12 3 Honda 11/1/12 3 Merc 11/2/12 4 Merc 10/30/12 1 Merc 10/31/12 2 Toyota 11/1/12 3 Toyota 11/3/12 2 Now I want three lines(one line for each type of car) on the same x axis. I tried using

问题 I have the following data set id<-c(1,1,1,1,2,2,2,2,2,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4) s02<-c(001,002,003,004,001,002,003,004,005,001,002,003,004,005,006,007,001,002,003,004,005,006,007,008,009,010,011,012,013,014,015,016,017,018,019,020,021,022,023,024,025,026,027,028,029) dat1<-data.frame(id,s02) I would wish to create a data set based on this dat1. I would wish to have an R code that creates n s02 automatically as s02__0, s02__1, s02__2, s02__3, s02_