## Issue

I have a 2d NumPy array that looks like this:

```
array([[1, 1],
[1, 2],
[2, 1],
[2, 2],
[3, 1],
[5, 1],
[5, 2]])
```

and I want to group it and have an output that looks something like this:

```
Col1 Col2
group 1: 1-2, 1-2
group 2: 3-3, 1-1
group 3: 5-5, 1-2
```

I want to group the columns based on if they are consecutive.

So, for a unique value In column 1, group data in the second column if they are consecutive between rows. Now for a unique grouping of column 2, group column 1 if it is consecutive between rows.

The result can be thought of as corner points of a grid. In the above example, group 1 is a square grid, group 2 is a a point, and group 3 is a flat line.

My system won’t allow me to use pandas so I cannot use group_by in that library but I can use other standard libraries.

Any help is appreciated. Thank you

## Solution

Here you go …

Steps are:

- Get a list
`xUnique`

of unique column 1 values with sort order preserved. - Build a list
`xRanges`

of items of the form`[col1_value, [col2_min, col2_max]]`

holding the column 2 ranges for each column 1 value. - Build a list
`xGroups`

of items of the form`[[col1_min, col1_max], [col2_min, col2_max]]`

where the`[col1_min, col1_max]`

part is created by merging the`col1_value`

part of consecutive items in`xRanges`

if they differ by 1 and have identical`[col2_min, col2_max]`

value ranges for column 2. - Turn the ranges in each item of
`xGroups`

into strings and print with the required row and column headings. - Also package and print as a
`numpy.array`

to match the form of the input.

```
import numpy as np
data = np.array([
[1, 1],
[1, 2],
[2, 1],
[2, 2],
[3, 1],
[5, 1],
[5, 2]])
xUnique = list({pair[0] for pair in data})
xRanges = list(zip(xUnique, [[0, 0] for _ in range(len(xUnique))]))
rows, cols = data.shape
iRange = -1
for i in range(rows):
if i == 0 or data[i, 0] > data[i - 1, 0]:
iRange += 1
xRanges[iRange][1][0] = data[i, 1]
xRanges[iRange][1][1] = data[i, 1]
xGroups = []
for i in range(len(xRanges)):
if i and xRanges[i][0] - xRanges[i - 1][0] == 1 and xRanges[i][1] == xRanges[i - 1][1]:
xGroups[-1][0][1] = xRanges[i][0]
else:
xGroups += [[[xRanges[i][0], xRanges[i][0]], xRanges[i][1]]]
xGroupStrs = [ [f'{a}-{b}' for a, b in row] for row in xGroups]
groupArray = np.array(xGroupStrs)
print(groupArray)
print()
print(f'{"":<10}{"Col1":<8}{"Col2":<8}')
[print(f'{"group " + str(i) + ":":<10}{col1:<8}{col2:<8}') for i, (col1, col2) in enumerate(xGroupStrs)]
```

Output:

```
[['1-2' '1-2']
['3-3' '1-1']
['5-5' '1-2']]
Col1 Col2
group 0: 1-2 1-2
group 1: 3-3 1-1
group 2: 5-5 1-2
```

Answered By – constantstranger

Answer Checked By – Terry (BugsFixing Volunteer)