np.array() function is used to create an array in numpy.
Heres how you can create an array:
Scenario Questions
0-2 years experience
1How would you create a 3x4 matrix filled with 7.0 as float32?
2You have a Python list [1,2,3] and a tuple (4,5,6). What's the simplest way to make a 2x3 array from them?
3What happens if you do np.array([[1,2], [3,4,5]])? What dtype do you get and why?
2-5 years experience
1You're reading a CSV with mixed numeric columns and some missing values marked as 'NA'. How do you create a clean float64 array without the 'NA' strings polluting the dtype?
2A teammate's code creates a large array via np.array(list_of_lists) and it's slow. You notice the input is already a list of numpy arrays. How would you fix this?
3Debugging: your array shows dtype=object but you expected float64. The input data came from a JSON load. Walk me through finding the root cause.
5-8 years experience
1You need to create a 50GB array on a machine with 64GB RAM for a one-time computation. The data comes from a memory-mapped file. Which creation method do you use and what parameters matter?
2Design a helper that efficiently builds a large array from a stream of variable-length batches (e.g., from a DataLoader). You can't know the final size upfront. What's your strategy?
3Your team sees frequent OOM errors when creating arrays from pandas DataFrames via .values. What's happening under the hood and how do you create the array zero-copy when possible?
8+ years experience
1You're defining array creation standards for a data platform used by 50 engineers across ML, analytics, and backend teams. What conventions do you enforce around dtype, memory order, and copy semantics?
2The org is migrating a critical pipeline from pandas to NumPy for latency reasons. The pipeline does heavy columnar transformations. How do you architect the array creation layer to be both performant and maintainable?
3A legacy system passes you raw C-contiguous buffers via FFI. You need to wrap them as NumPy arrays without copies, but the buffers may be freed externally. How do you design a safe ownership model?
Follow-up Questions
What happens if you pass a list of lists with different inner lengths?
When would you choose np.empty over np.zeros?
How do you create an array without copying data from a bytes buffer?
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