zero-padding

What's the more pythonic way to pad an array with zeros at the end? def pad(A, length): ... A = np.array([1,2,3,4,5]) pad(A, 8) # expected : [1,2,3,4,5,0,0,0] In my real use case, in fact I want to pad an array to the closest multiple of 1024. Ex: 1342 => 2048, 3000 => 3072 numpy.pad with constant mode does what you need, where we can pass a tuple as second argument to tell how many zeros to pad on each size, a (2, 3) for instance will pad 2 zeros on the left side and 3 zeros on the right side: Given A as: A = np.array([1,2,3,4,5]) np.pad(A, (2, 3), 'constant') # array([0, 0, 1, 2, 3, 4, 5, 0,

I want to import a table ( .txt file) in R with read.table() . One column in my table is an ID with nine numerals - some ids begin with a 0, other with 1 or 2. R truncates the first 0 (012345678 becomes 12345678) which leads to problems when using this ID to merge another table. Can someone give me a hint how to solve the problem? agstudy As said in Ben's answer, colClasses is the easier way to do it. Here is an example: read.table(text = 'col1 col2 0012 0001245', head=T, colClasses=c('character','numeric')) col1 col2 1 0012 1245 ## col1 keep 00 but not col2 A reproducible example would be