2 dimensions array of unknown size in Python

Question

I am pretty new at python and numpy, so sorry if the question is kind of obvious. Looking on the internet I could not find the right answer. I need to create a 2 dimensions (a.ndim -->2) array of unknown size in python. Is it possible? I have found a way for 1 dimension passing through a list but no luck with 2 dimension.

example

for i in range(0,Nsens):
    count=0
    for l in range (0,my_data.shape[0]):
        if my_data['Node_ID'][l]==sensors_name[i]:
            temp[count,i]=my_data['Temperature'][l]
            count=count+1
        else:
            count=count

Where temp is the array I need to initialize.

Answer 1

This shows a fairly high-performance (although slower than initializing to exact size) way to fill in an array of unknown size in numpy:

data = numpy.zeros( (1, 1) )
N = 0
while True:
    row = ...
    if not row: break
    # assume every row has shape (K,)
    K = row.shape[0]
    if (N >= data.shape[0]):
        # over-expand: any ratio around 1.5-2 should produce good behavior
        data.resize( (N*2, K) )
    if (K >= data.shape[1]):
        # no need to over-expand: presumably less common
        data.resize( (N, K+1) )
    # add row to data
    data[N, 0:K] = row

# slice to size of actual data
data = data[:N, :]

Adapting to your case:

if count > temp.shape[0]:
    temp.resize( (max( temp.shape[0]*2, count+1 ), temp.shape[1]) )
if i > temp.shape[1]:
    temp.resize( (temp.shape[0], max(temp.shape[1]*2, i+1)) )
# now safe to use temp[count, i]

You may also want to keep track of the actual data sizes (max count, max i) and trim the array later.