multiple-columns

I have a data frame with multiple columns. Now, I want to get rid of the row.names column (column 1), and thus I try to select all the other columns. E.g., newdata <- olddata[,2:10] is there a default symbol for the last column so I don't have to count all the columns? I tried newdata <- olddata[,2:] but it didn't work. I think it's better to focus on wanting to get rid of one column of data and not wanting to select every other column. You can do this as @Arun suggested: olddata[,-1] Or: olddata$ColNameToDelete <- NULL You can get the last column with ncol() : newdata <- olddata[,2:ncol

In my input file, columns are tab-separated, and the values inside each column are comma-separated. I want to print the first column with each comma separated value from the second. Mary,Tom,David cat,dog Kevin bird,rabbit John cat,bird ... for each record in the second column ( eg cat,dog ) i want to split record into array of [ cat, dog ] and cross print this against the first column. giving output ( just for this line ) Mary,Tom,David cat Mary,Tom,David dog output for whole file should be be: Mary,Tom,David cat Mary,Tom,David dog Kevin bird Kevin rabbit John cat John bird ... any suggest if

I have a pandas dataframe like the following: A B US,65,AMAZON 2016 US,65,EBAY 2016 My goal is to get to look like this: A B country code com US.65.AMAZON 2016 US 65 AMAZON US.65.AMAZON 2016 US 65 EBAY I know this question has been asked before here and here but none of them works for me. I have tried: df['country','code','com'] = df.Field.str.split('.') and df2 = pd.DataFrame(df.Field.str.split('.').tolist(),columns = ['country','code','com','A','B']) Am I missing something? Any help is much appreciated. You can use split with parameter expand=True and add one [] to left side: df[['country',

I have to build a table with 5 columns. The table width is variable (50% of content width). Some columns contain fixed-size buttons, so those columns should have a fixed with, say 100px. Some columns have text in them, so I want those columns to have variable column widths. For example: Column1: 20% of (tablewidth - sum(fixedwidth_columns))' Column2: 100px Column3: 40% of (tablewidth - sum(fixedwidth_columns)) Column4: 200px Column5: 40% of (tablewidth - sum(fixedwidth_columns)) What is the best way to achieve this? You could set the table-layout: fixed for the table element, then simply set

I have a data frame in R that has many rows (over 3000) with F0 (fundamental frequency) tracks of an utterance in it. The rows have the following information in them: speaker ID, group #, repetition #, accent type, sex, and then 50 columns of F0 points. The data looks like this: Speaker Sex Group Repetition Accent Word 1 2 3 4 105 M 1 1 N AILMENT 102.31030 102.31030 102.31030 102.31127 105 M 1 1 N COLLEGE 111.80641 111.80313 111.68612 111.36020 105 M 1 1 N FATHER 124.06655 124.06655 124.06655 124.06655 But instead of only going to X4, it has 50 points per row, so I have a 3562x56 data frame. I

I would like to combine three columns in one of my data sets into one with variable name "al_anim" and remove any duplicates, rank the values (animal ids) from lowest to highest, and re-number each animal from 1 to N under the variable name "new_id". anim1 <- c(1456,2569,5489,1456,4587) anim2 <- c(6531,6987,6987,15487,6531) anim3 <- c(4587,6548,7894,3215,8542) mydf <- data.frame(anim1,anim2,anim3) Any help would be very much appreciated! Baz Using mydf from your example: mydf <- data.frame(anim1, anim2, anim3) Stack the data: sdf <- stack(mydf) Then compute the unique elements using unique()