So I found this: Numpy: Fix array with rows of different lengths by filling the empty elements with zeros
But what I actually want is this:
mylist = [[1],[1,2],[1,2,3]]
mylist.fill()
>>> [[0,0,1], [0,1,2], [1,2,3]]
I know that pandas' fillna fills but the 0 are at the right part of my matrix and I need them at the left part. Any clues?
I think this should do it:
def fill(a):
length = max([len(i) for i in a])
return [[0]*(length-len(i)) + i for i in a]
fill(mylist)
#[[0,0,1], [0,1,2], [1,2,3]]
Since you tag pandas
pd.DataFrame(mylist).\
apply(lambda x: sorted(x, key=pd.notnull), 1).\
fillna(0).astype(int).values.tolist()
Out[89]: [[0, 0, 1], [0, 1, 2], [1, 2, 3]]
Fillna with 0 and sort values check if they are not 0's i.e
df = pd.DataFrame(mylist)
df.fillna(0).apply(lambda x : sorted(x,key=lambda x : x!=0),1).values.astype(int).tolist()
[[0, 0, 1], [0, 1, 2], [1, 2, 3]]