dummy-variable

问题 This question already has answers here : Generate a dummy-variable (16 answers) Closed 2 years ago . I'm designing a neural Network in R. For that I have to prepare my data and have imported a table. For example: time hour Money day 1: 20000616 1 9.35 5 2: 20000616 2 6.22 5 3: 20000616 3 10.65 5 4: 20000616 4 11.42 5 5: 20000616 5 10.12 5 6: 20000616 6 7.32 5 Now I need a dummyfication. My final table should look like this: time Money day 1 2 3 4 5 6 1: 20000616 9.35 5 1 0 0 0 0 0 2: 20000616

问题 Heyho, I am a beginner in R and have a problem to which I couldn't find a solution so far. I would like to transform dummy variables back to categorical variables. |dummy1| dummy2|dummy3| |------| ------|------| | 0 | 1 |0 | | 1 | 0 |0 | | 0 | 1 |0 | | 0 | 0 |1 | into: |dummy | |------| |dummy2| |dummy1| |dummy2| |dummy3| Do you have any idea how to do that in R? Thanks in advance. 回答1: You can do this with data.table id_cols = c("x1", "x2") data.table::melt.data.table(data = dt, id.vars = id

问题 This is an example data frame, where PRE5_id1,POST5_id1, PRE5_id2, POST5_id2 are the variables that I would like to get. I am looking for a lead and lag value which will have five values of 1 in the years before natural death (PRE5) and 5 years after the year of natural death (POST5). I am not sure how to stay within the group of country when creating these PRE and POST variables, in which case the PRE and POST variables go to +5 and -5 only within the same country. I am planning to do a

问题 This is an example data frame, where PRE5_id1,POST5_id1, PRE5_id2, POST5_id2 are the variables that I would like to get. I am looking for a lead and lag value which will have five values of 1 in the years before natural death (PRE5) and 5 years after the year of natural death (POST5). I am not sure how to stay within the group of country when creating these PRE and POST variables, in which case the PRE and POST variables go to +5 and -5 only within the same country. I am planning to do a

问题 I have a dataframe that looks kind of like this with many more rows and columns: > df <- data.frame(country = c ("Australia","Australia","Australia","Angola","Angola","Angola","US","US","US"), year=c("1945","1946","1947"), leader = c("David", "NA", "NA", "NA","Henry","NA","Tom","NA","Chris"), natural.death = c(0,NA,NA,NA,1,NA,1,NA,0),gdp.growth.rate=c(1,4,3,5,6,1,5,7,9)) > df country year leader natural.death gdp.growth.rate 1 Australia 1945 David 0 1 2 Australia 1946 NA NA 4 3 Australia 1947

问题 Starting with a training data set for a variable var1 as: var1 A B C D I want to create a model (let's call it dummy_model1 ) that would then transform the training data set to: var1_A var1_B var1_C var1_D 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 This functionality (or similar) exists in, among others, the dummies package in R and get_dummies in Pandas , or even case statements in SQL . I'd like to then be able to apply dummy_model1 to a new data set: var1 C 7 # A and get the following output: var1_A

问题 I have a set of dataframes where one of the columns contains a categorical variable. I'd like to convert it to several dummy variables, in which case I'd normally use get_dummies . What happens is that get_dummies looks at the data available in each dataframe to find out how many categories there are, and thus create the appropriate number of dummy variables. However, in the problem I'm working right now, I actually know in advance what the possible categories are. But when looking at each

问题 I have a set of dataframes where one of the columns contains a categorical variable. I'd like to convert it to several dummy variables, in which case I'd normally use get_dummies . What happens is that get_dummies looks at the data available in each dataframe to find out how many categories there are, and thus create the appropriate number of dummy variables. However, in the problem I'm working right now, I actually know in advance what the possible categories are. But when looking at each

问题 I am trying to change the category variables into dummy variables. "season","holiday","workingday","weather","temp","atemp","humidity","windspeed", "registered","count","hour","dow" are all variables. Here is my code: #dummy library(dummies) #set up new dummy variables data.new = data.frame(data) data.new = cbind(data.new,dummy(data.new$season, sep = "_")) data.new = cbind(data.new,dummy(data.new$holiday, sep = "_")) data.new = cbind(data.new,dummy(data.new$weather, sep = "_")) data.new =

问题 I am using the dummies package to generate dummy variables for categorical variables, some with more than two categories. testdf<- data.frame( "A" = as.factor(c(1,2,2,3,3,1)), "B" = c('A','B','A','B','C','C'), "C"= c('D','D','E','D','D','E')) # #Generate dummy variables: # testdf<- cbind(testdf, dummy(testdf$C, sep='_')) testdf<- cbind(testdf, dummy(testdf$B, sep='_')) For both commands I get: Warning message: In model.matrix.default(~x - 1, model.frame(~x - 1), contrasts = FALSE) : non-list