#63EasyLists & Tuples· Nested Lists

NumPy-Style Array Operations

Libraries such as NumPy make matrix work one-liners, but every one of those operations is a loop underneath. Build them yourself with plain lists. Write `array_ops(values, rows, cols)`. If `rows * cols` differs from the number of values, return `{"error": "cannot reshape <len> values into <rows>x<cols>"}`. Otherwise return a dictionary with these keys, in order: - `"matrix"`: the values arranged row by row into `rows` lists of `cols` values (like `reshape`). - `"transposed"`: the matrix with rows and columns swapped. - `"row_max"`: the largest value of each row. - `"col_sums"`: the sum of each column. - `"above_mean"`: the values strictly greater than the mean of all values, in their original order (like boolean indexing).

Input format

`values`: a list of integers. `rows`, `cols`: positive integers.

Output format

A dictionary as described, or a dictionary with a single `error` key.

Examples

Input: values = [1,2,3,4,5,6], rows = 2, cols = 3

Output: {"matrix":[[1,2,3],[4,5,6]],"transposed":[[1,4],[2,5],[3,6]],"row_max":[3,6],"col_sums":[5,7,9],"above_mean":[4,5,6]}

The mean is 3.5, so 4, 5 and 6 are above it.

Input: values = [1,2,3,4,5], rows = 2, cols = 3

Output: {"error":"cannot reshape 5 values into 2x3"}

Six slots cannot hold five values.

Constraints

1 <= len(values) <= 10^4
1 <= rows, cols <= 10^4
-10^6 <= value <= 10^6

Study first

Lists and Tuples in Python

#python
#nested-lists
#matrices
#numpy