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python arrays list numpy

Answers (1)

September 9, 2025 Score: 0 Rep: 16,982 Quality: Medium Completeness: 60%

The steps before, during, and after this problem statement are some mix of under-specified and undesirable. Avoid a list representation entirely. Use row-packed form, and if you are memory-constrained and can abide a 0 packing value, then you can use CSR (which will have the second dimension correct, and the first dimension as an implicit product).

import numpy as np
import scipy.sparse
nrows = 3
ncols = np.array((4, 9, 1))
nmaxcols = ncols.max()
ntotalcols = ncols.sum()
rand = np.random.defaultrng(seed=0)
packed = rand.random(size=(nrows, ntotalcols), dtype=np.float32)
print('If you can use this packed form directly (there are many operations that can), then STOP HERE.')
np.setprintoptions(precision=7)
print(packed)
print()
print(
    "You could use this form if 0 is an acceptable padding value "
    "(you haven't responded to specify)."
)
sparse = scipy.sparse.lilarray((nrows*ncols.size, nmaxcols))
x = 0
y = 0

There are vectorised options to construct this as well; this form is easy to understand.

for width in ncols:
    xnew = x + width
    ynew = y + nrows
    sparse[y: ynew, 0: width] = packed[:, x: xnew]
    x = xnew
    y = ynew
csr = sparse.tocsr()
print(csr.toarray())

If you can use this packed form directly (there are many operations that can), then STOP HERE.
[[0.85 0.64 0.51 0.27 0.31 0.04 0.08 0.02 0.18 0.81 0.65 0.91 0.5  0.61]
 [0.97 0.73 0.63 0.54 0.56 0.94 0.28 0.82 0.67 0.   0.39 0.86 0.55 0.03]
 [0.76 0.73 0.85 0.18 0.09 0.86 0.02 0.54 0.08 0.3  0.48 0.42 0.4  0.03]]
You could use this form if 0 is an acceptable padding value (you haven't responded to specify).
[[0.85 0.64 0.51 0.27 0.   0.   0.   0.   0.  ]
 [0.97 0.73 0.63 0.54 0.   0.   0.   0.   0.  ]
 [0.76 0.73 0.85 0.18 0.   0.   0.   0.   0.  ]
 [0.31 0.04 0.08 0.02 0.18 0.81 0.65 0.91 0.5 ]
 [0.56 0.94 0.28 0.82 0.67 0.   0.39 0.86 0.55]
 [0.09 0.86 0.02 0.54 0.08 0.3  0.48 0.42 0.4 ]
 [0.61 0.   0.   0.   0.   0.   0.   0.   0.  ]
 [0.03 0.   0.   0.   0.   0.   0.   0.   0.  ]
 [0.03 0.   0.   0.   0.   0.   0.   0.   0.  ]]