## Sequential Integer Matrices in Python Without Packages

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Just when I think I'm decent at something, I find a simple thing I cannot overcome.

I need to create a symmetrical row x column matrix given a start and block for a checksum. The entries should be in sequential order.

```def main(start_index, block):
num_rows, num_cols = block, block
matrix = []

for r in range(num_rows):
temp = []

for c in range(num_cols):
temp.append(c)

matrix.append(temp)

return matrix
```

The output here is: `[[0, 1, 2], [0, 1, 2], [0, 1, 2]]`

What I'm trying to obtain is: `[[0, 1, 2], [3, 4, 5], [6, 7, 8]]`

And not just for a 3x3 but dynamically as well.

Note: No packages like numpy, that's not the point of this ask. Only native python.

You are appending `c` which is always a range between 0 and `num_cols`. You need to calculate `c` based on which row you are in. Something like:

```def main(start_index, block):
num_rows, num_cols = block, block
matrix = []

for r in range(num_rows):
temp = []

for c in range(0, num_cols):
temp.append(start_index + c + (r * num_cols))

matrix.append(temp)

return matrix

main(0, 3)

>> [[0, 1, 2], [3, 4, 5], [6, 7, 8]]
```

You could also write this as a generator from `start_index` to `row * columns` that generates your rows lazily. For example:

```def main(start_index, block):
num_rows, num_cols = block, block

total = num_rows * num_cols

for i in range(start_index, total + start_index, num_cols):
yield list(range(i, num_cols + i))

list(main(10, 4))
>> [[10, 11, 12, 13], [14, 15, 16, 17], [18, 19, 20, 21], [22, 23, 24, 25]]
```

Basic Operations in Python, To create an array of a sequence of integers between 0 and 10: to create an alias pointing to the NumPy package in order to shorten verbose module names, � Creating a Matrix in Python without numpy [duplicate] Ask Question Asked 3 years, 9 months ago. Active 1 year, 11 months ago. Viewed 36k times 8. 1. This question

Are you overcomplicating?

```In [1]: nrow, ncol, start = 3, 5, 7

In [2]: [[start+c+r*ncol for c in range(ncol)] for r in range(nrow)]
Out[2]: [[7, 8, 9, 10, 11], [12, 13, 14, 15, 16], [17, 18, 19, 20, 21]]
```

Should you prefer more descriptive names:

```In [3]: n_rows, n_cols, n_start = 3,5,7

In [4]: [[n_start + col + row*n_cols for col in range(n_cols)] for row in range(n_rows)]
Out[4]: [[7, 8, 9, 10, 11], [12, 13, 14, 15, 16], [17, 18, 19, 20, 21]]
```

Eventually, to have `itertools.count` you absolutely don't need to `import itertools`

```In [10]: def count(start=0, step=1):
...:     while True:
...:         yield start
...:         start += step

In [11]: nr, nc, item = 3, 4, count()

In [12]: [[next(item) for c in range(nc)] for r in range(nr)]
Out[12]: [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]

In [13]: nr, nc, item = 3, 4, count(start=4, step=3)

In [14]: [[next(item) for c in range(nc)] for r in range(nr)]
Out[14]: [[4, 7, 10, 13], [16, 19, 22, 25], [28, 31, 34, 37]]
```

array — Efficient arrays of numeric values — Python 3.8.5 , This module defines an object type which can compactly represent an array of basic values: characters, integers, floating point numbers. Arrays are sequence� The package also has a plugin function so you can add your own modules. To use Eigen, install it with pip and import it in your code. PyTorch is a library for Machine Learning, because of this it has matrix operations.

You can use itertools.count to create a generator for generating incrementing integers, every call to `next` will get the next integer

Then you can use this generator for filling in the values when you create your lists

```import itertools

def get_square_matrix(size):
counter = itertools.count(start_index)
matrix = []
for row in range(size):
matrix.append([next(counter) for _ in range(size)])
return matrix
```

8.6. array — Efficient arrays of numeric values — Python 2.7.18 , This module defines an object type which can compactly represent an array of basic values: characters, integers, floating point numbers. Arrays are sequence� There is another way to create a matrix in python. It is using the numpy matrix() methods. It is the lists of the list. For example, I will create three lists and will pass it the matrix() method. list1 = [2,5,1] list2 = [1,3,5] list3 = [7,5,8] matrix2 = np.matrix([list1,list2,list3]) matrix2 . You can also find the dimensional of the matrix

Python Matrix and Introduction to NumPy, You can treat lists of a list (nested list) as matrix in Python. However, there is a better way of working Python matrices using NumPy package. NumPy is a Print the Fibonacci sequence Array of integers, floats and complex Numbers The argument dtype=int doesn’t refer to Python int. It translates to NumPy int64 or simply np.int. NumPy offers you several integer fixed-sized dtypes that differ in memory and limits: np.int8: 8-bit signed integer (from -128 to 127) np.uint8: 8-bit unsigned integer (from 0 to 255) np.int16: 16-bit signed integer (from -32768 to 32767)

NumPy: Array Object - Exercises, Practice, Solution, Practice with solution of exercises on Python NumPy: Array Object array of size 2 x 3 (composed of 4-byte integer elements), also print the shape, Write a NumPy program to create a new shape to an array without changing its data. Write a NumPy program to convert (in sequence depth wise (along� In Python, we can implement a matrix as a nested list (list inside a list). We can treat each element as a row of the matrix. For example X = [[1, 2], [4, 5], [3, 6]] would represent a 3x2 matrix. First row can be selected as X[0] and the element in first row, first column can be selected as X[0][0].

Functions for Creating NumPy Arrays — Python Like You Mean It, Creating Sequential Arrays: arange and linspace �. The arange function allows you to initialize a sequence of integers based on a starting point (inclusive),� Multiplication of two matrices X and Y is defined only if the number of columns in X is equal to the number of rows Y. If X is a n x m matrix and Y is a m x l matrix then, XY is defined and has the dimension n x l (but YX is not defined). Here are a couple of ways to implement matrix multiplication in Python. Source Code: Matrix Multiplication

• Where did the 0th position in the 0th list entry go here? The 0 in [0,1,2] I manually fixed it `start_index-1` But I don't quite see where we missed the iteration.