Every Nth row, set every cell to zero whose index (plus one) is divisible by N. More on reddit.com

>>> np.full(3, np.nan) But the bigger question is why would you want to? Edit: as an explanation, your example does not work because you initialized an array of ints. ints have no "NaN" value, only floats do. So your method would work if you initialized an array of floats: >>> x = np.array([0.0,0.0,0.0]) >>> x.fill(np.nan) >>> x array([ nan, nan, nan]) Or converted the ints to floats: >>> x = np.array([0,0,0], dtype=np.float) >>> x.fill(np.nan) >>> x array([ nan, nan, nan]) But the np.full() method is much better. More on reddit.com

Tried implementing numpy in C, ended up digging a cool rabbit hole... ... I'm really new to python and wanted to share my first "project". More on reddit.com

Let's break it down: input() gets user input and returns a string, e.g. "1 2 3 4 5" input().split() splits that input on whitespaces, e.g. ["1", "2", "3", ...] int() converts a string to a integer, e.g. "1" -> 1 map(fn, sequence) applies the function fn to each element in the sequence, e.g. fn(sequence[0]), fn(sequence[1]), ... map(int, input().split()) applies int to each string element in the input, e.g. ["1", "2", "3", ...] -> int("1"), int("2"), ... list() turns any iterator/generator to a list, e.g. int("1"), int("2"), ... => [1, 2, 3, ...] Example: In []: list(map(int, input().split())) Input: 1 2 3 4 5 Out[]: [1, 2, 3, 4, 5] Note: this is the same as, which may be easier to read: In []: [int(n) for n in input().split()] Input: 1 2 3 4 5 Out[]: [1, 2, 3, 4, 5] More on reddit.com