dplyr

问题 I have two data frames: df1 = data.frame(index=c(0,3,4),n1=c(1,2,3)) df1 # index n1 # 1 0 1 # 2 3 2 # 3 4 3 df2 = data.frame(index=c(1,2,3),n2=c(4,5,6)) df2 # index n2 # 1 1 4 # 2 2 5 # 3 3 6 I want to join these to: index n 1 0 1 2 1 4 3 2 5 4 3 8 (index 3 in two df, so add 2 and 6 in each df) 5 4 3 6 5 0 (index 5 not exists in either df, so set 0) 7 6 0 (index 6 not exists in either df, so set 0) The given data frames are just part of large dataset. Can I do it using dplyr or other packages

问题 I have two data frames: df1 = data.frame(index=c(0,3,4),n1=c(1,2,3)) df1 # index n1 # 1 0 1 # 2 3 2 # 3 4 3 df2 = data.frame(index=c(1,2,3),n2=c(4,5,6)) df2 # index n2 # 1 1 4 # 2 2 5 # 3 3 6 I want to join these to: index n 1 0 1 2 1 4 3 2 5 4 3 8 (index 3 in two df, so add 2 and 6 in each df) 5 4 3 6 5 0 (index 5 not exists in either df, so set 0) 7 6 0 (index 6 not exists in either df, so set 0) The given data frames are just part of large dataset. Can I do it using dplyr or other packages

问题 I am trying to recode several variables but with different recode schemes. The recoding scheme is saved in a list where each element is a named vector of the form old = new . Each element is the recoding scheme for each variable in the data frame I am using the mutate_at function and the recode . I think that the problem is that I cannot extract the variable name to use it to get the correct recoding scheme from the list I tried deparse(substitute(.)) as in here and also this didn;t help Also

问题 I am trying to recode several variables but with different recode schemes. The recoding scheme is saved in a list where each element is a named vector of the form old = new . Each element is the recoding scheme for each variable in the data frame I am using the mutate_at function and the recode . I think that the problem is that I cannot extract the variable name to use it to get the correct recoding scheme from the list I tried deparse(substitute(.)) as in here and also this didn;t help Also

问题 I've recently started trying to do all of my code in the tidyverse. This has sometimes lead me to difficulties. Here is a simple task that I haven't been able to complete in the tidyverse: I need a column in a dataframe that returns the position index of the first non-na value from the left. Does anyone know how to achieve this in dplyr using mutate? Here is the desired output. data.frame( "X1"=c(100,rep(NA,8)), "X2"=c(NA,10,rep(NA,7)), "X3"=c(NA,NA,1000,1000,rep(NA,5)), "X4"=c(rep(NA,4),25

问题 I need to add a fingerprint to each row in a dataset so to check with a later version of the same set to look for difference. I know how to add hash for each row in R like below: data.frame(iris,hash=apply(iris,1,digest)) I am learning to use dplyr as the dataset is getting huge and I need to store them in SQL Server, I tried something like below but the hash is not working, all rows give the same hash: iris %>% rowwise() %>% mutate(hash=digest(.)) Any clue for row-wise hashing using dplyr?

问题 Why in the code below dplyr's filter doesn't return the same data.frame as base R subsetting? In fact none of them works as expected. I'd like to remove observations/rows which, simultaneously, b==1 AND c==1 . That is, I'd like to remove only the third row. require(dplyr) df <- data.frame(a=c(0,0,0,0,1,1,1), b=c(0,0,1,1,0,0,1), c=c(1,NA,1,NA,1,NA,NA)) filter(df, !(b==1 & c==1)) df[!(df$b==1 & df$c==1),] 回答1: Or use complete.cases to convert NA to FALSE in the result logic vector so that you

问题 Why in the code below dplyr's filter doesn't return the same data.frame as base R subsetting? In fact none of them works as expected. I'd like to remove observations/rows which, simultaneously, b==1 AND c==1 . That is, I'd like to remove only the third row. require(dplyr) df <- data.frame(a=c(0,0,0,0,1,1,1), b=c(0,0,1,1,0,0,1), c=c(1,NA,1,NA,1,NA,NA)) filter(df, !(b==1 & c==1)) df[!(df$b==1 & df$c==1),] 回答1: Or use complete.cases to convert NA to FALSE in the result logic vector so that you

问题 Why in the code below dplyr's filter doesn't return the same data.frame as base R subsetting? In fact none of them works as expected. I'd like to remove observations/rows which, simultaneously, b==1 AND c==1 . That is, I'd like to remove only the third row. require(dplyr) df <- data.frame(a=c(0,0,0,0,1,1,1), b=c(0,0,1,1,0,0,1), c=c(1,NA,1,NA,1,NA,NA)) filter(df, !(b==1 & c==1)) df[!(df$b==1 & df$c==1),] 回答1: Or use complete.cases to convert NA to FALSE in the result logic vector so that you

问题 I have a dataframe which has multiple values in a single file. I want to divide it into multiple files around 25 from the file. Pattern for the file is where there is one blank row and a header title is there , it is a new df. I Have tried this Splitting dataframes in R based on empty rows but this does not take care of any blank row within the new df (V1 column 9th row). I want the data to be divided on empty row and a header title my data and code i have tried is given below . Also how can