dplyr

问题 This question already has answers here : Converting Yes and No to 0 and 1 in R (3 answers) Closed last year . I need to replace the Yes and No values to 1 and 0 in 200 columns. I was using with the command data %>% mutate(x=ifelse(x=="Yes", 1,0)) but i have to go through each column at a time, and i was wondering if there was any way i could do it all at once. 回答1: You may use ifelse on the entire data frame: df <- data.frame(v1=c("Yes","No"), v2=c("No","Yes"), stringsAsFactors=FALSE) ifelse

问题 I am working with the R programming language. I am trying to replicate the following tutorial with some fake data that I generated: https://plotly.com/r/dropdowns/. That is, I generated some fake data and made 4 scatter plots. Using the "plotly" library, I then want to "attach" these 4 plots together and let the user "toggle" (switch, shuffle) between these graphs. I have attached the code below: #load libraries library(plotly) library(MASS) library(dplyr) # create data x <- sample( LETTERS[1

问题 I want to exclude participants from an analysis that are too old (age >90). Usually I would do it like that: df <- data.frame(age=c(1,10, 100), x= 1:3, y= 1:3) df[df$age > 90, ] <- NA I can't figure out how to do this with dplyr. If we want to replace one variable we can use library(dplyr) df <- data.frame(age=c(1,10, 100), x= 1:3, y= 1:3) df %>% mutate(age= replace(age, age> 90, NA)) So I thought I could use df %>% mutate_all(function(i) replace(i, age> 90, NA)) I also tried mutate_if and

问题 I want to exclude participants from an analysis that are too old (age >90). Usually I would do it like that: df <- data.frame(age=c(1,10, 100), x= 1:3, y= 1:3) df[df$age > 90, ] <- NA I can't figure out how to do this with dplyr. If we want to replace one variable we can use library(dplyr) df <- data.frame(age=c(1,10, 100), x= 1:3, y= 1:3) df %>% mutate(age= replace(age, age> 90, NA)) So I thought I could use df %>% mutate_all(function(i) replace(i, age> 90, NA)) I also tried mutate_if and

问题 I have a dataframe (df1) with multiple columns (ID, Number, Location, Field, Weight). I also have another dataframe (df2) with more information (ID, PassRate, Number, Weight). I am trying to use dplyr and %in% to filter out rows in df1 that have the same two values as df2. So far I have: df_sub <- subset(df1, df1$ID %in% df2$ID & df1$Weight %in% df2$Weight) But this is only subsetting on the first condition...any idea why? 回答1: From the question and sample code, it is unclear whether you want

问题 I have a data frame as follows: head(newStormObject) FATALITIES INJURIES PROPVALDMG CROPVALDMG EVTYPE total 1 0 15 2.5e+05 0 TORNADO 15 2 0 0 2.5e+04 0 TORNADO 0 3 0 3 2.5e+07 0 TORNADO 3 4 0 3 2.5e+07 0 TORNADO 3 5 0 0 0.0e+00 0 TSTM WIND 1 6 0 0 0.0e+00 0 HAIL 2 7 0 0 0.0e+00 0 HAIL 3 8 0 0 0.0e+00 0 TSTM WIND 0 9 0 0 0.0e+00 0 HAIL 0 10 0 0 0.0e+00 0 TSTM WIND 0 11 0 0 0.0e+00 0 TSTM WIND 0 12 0 0 0.0e+00 0 HAIL 1 13 0 0 0.0e+00 0 HAIL 1 14 0 0 0.0e+00 0 HAIL 5 15 0 0 0.0e+00 0 TSTM WIND 0

问题 I have a data frame as follows: head(newStormObject) FATALITIES INJURIES PROPVALDMG CROPVALDMG EVTYPE total 1 0 15 2.5e+05 0 TORNADO 15 2 0 0 2.5e+04 0 TORNADO 0 3 0 3 2.5e+07 0 TORNADO 3 4 0 3 2.5e+07 0 TORNADO 3 5 0 0 0.0e+00 0 TSTM WIND 1 6 0 0 0.0e+00 0 HAIL 2 7 0 0 0.0e+00 0 HAIL 3 8 0 0 0.0e+00 0 TSTM WIND 0 9 0 0 0.0e+00 0 HAIL 0 10 0 0 0.0e+00 0 TSTM WIND 0 11 0 0 0.0e+00 0 TSTM WIND 0 12 0 0 0.0e+00 0 HAIL 1 13 0 0 0.0e+00 0 HAIL 1 14 0 0 0.0e+00 0 HAIL 5 15 0 0 0.0e+00 0 TSTM WIND 0

问题 This question already has answers here : Idiom for ifelse-style recoding for multiple categories (12 answers) Closed 2 years ago . I have like below mentioned dataframe: Records: ID Remarks Value 1 ABC 10 1 AAB 12 1 ZZX 15 2 XYZ 12 2 ABB 14 By utilizing the above mentioned dataframe, I want to add new column Status in the existing dataframe. Where if the Remarks is ABC, AAB or ABB than status would be TRUE and for XYZ and ZZX it should be FALSE . I am using below mentioned method for that but

问题 I'm trying to compare two columns of different data frames to create a new data frame. If the value of the row of the first col is less than the second, it will add a 1 to the new column. When the value is greater, it will add a 2 and so on. I'll give you an example. I have this df df1 <- data.frame(col=c(1,seq(1:9),9,10)) # col # 1 1 # 2 1 # 3 2 # 4 3 # 5 4 # 6 5 # 7 6 # 8 7 # 9 8 # 10 9 # 11 9 # 12 10 And this one, which has less rows df2<-data.frame(col2=c(3,6,8)) # col2 # 1 3 # 2 6 # 3 8

问题 I have a dataframe df.sample like this id <- c("A","A","A","A","A","A","A","A","A","A","A") date <- c("2018-11-12","2018-11-12","2018-11-12","2018-11-12","2018-11-12", "2018-11-12","2018-11-12","2018-11-14","2018-11-14","2018-11-14", "2018-11-12") hour <- c(8,8,9,9,13,13,16,6,7,19,7) min <- c(47,59,6,18,22,36,12,32,12,21,47) value <- c(70,70,86,86,86,74,81,77,79,83,91) df.sample <- data.frame(id,date,hour,min,value,stringsAsFactors = F) df.sample$date <- as.Date(df.sample$date,format="%Y-%m-