Converting nested lists of data into multidimensional Numpy arrays

In the code below I am building data up in a nested list. After the for loop what I would like is to cast it into a multidimensional Numpy array as neatly as possible. However, when I do the array conversion on it, it only seems to convert the outer list into an array. Even worse when I continue downward I wind up with dataPoints as shape `(100L,)`...so an array of lists where each list is my data (obviously I wanted a `(100,3)`). I have tried fooling with `numpy.asanyarray()` also but I can't seem to work it out. I would really like a 3d array from my 3d list from the outset if that is possible. If not, how can I get the array of lists into a 2d array without having to iterate and convert them all? Edit: I am also open to better way of structuring the data from the outset if it makes processing easier. However, it is coming over a serial port and the size is not known beforehand. ``` import numpy as np import time data = [] for _i in range(100): #build some list of lists d = [np.random.rand(), np.random.rand(), np.random.rand()] data.append([d,time.clock()]) dataArray = np.array(data) #now I have an array of lists of a list(of data) and a time dataPoints = dataArray[:,0] #this is the data in an array of lists ```