Group coordinates by euclidean distance
Project description
Group coordinates by euclidean distance
from a_pandas_ex_group_coordinates_by_distance import pd_add_group_coordinates_by_distance
pd_add_group_coordinates_by_distance()
import pandas as pd
#first way, from list/tuple
coordinates = [(745.8010864257812, 519.8585205078125),
(747.8574829101562, 522.5038452148438),
(747.9273071289062, 517.1298828125),
(747.9273071289062, 517.1298828125),
(750.921142578125, 522.3074951171875),
(756.1781005859375, 449.8744812011719),
(757.0703125, 461.237548828125),
(757.0703125, 461.237548828125),
(757.1057739257812, 438.6798095703125),
(830.8739624023438, 144.21884155273438),
(759.8501586914062, 435.39776611328125),
(759.8501586914062, 435.39776611328125),
(761.2493896484375, 468.02178955078125),
(761.2493896484375, 468.02178955078125),
(764.5658569335938, 521.395263671875),
(1079.3170166015625, 199.76937866210938),
(770.1127319335938, 474.63946533203125),
(770.3933715820312, 425.3490295410156),
(773.7312622070312, 516.6536254882812),
(776.908447265625, 515.5355224609375),
(776.908447265625, 515.5355224609375),
(778.0835571289062, 520.68896484375),
(779.8836059570312, 519.2072143554688),
(780.3491821289062, 420.33465576171875),
(780.3491821289062, 420.33465576171875),
(782.48388671875, 478.8080139160156),
(782.48388671875, 478.8080139160156),
(1083.74462890625, 151.22621154785156),
(1083.74462890625, 151.22621154785156),
(1083.74462890625, 151.22621154785156),
(1083.74462890625, 151.22621154785156),
(784.2761840820312, 478.5111083984375),
(759.8501586914062, 435.39776611328125),
(784.2761840820312, 478.5111083984375),
(819.1412353515625, 137.67359924316406),
(819.1412353515625, 137.67359924316406),
(819.1412353515625, 137.67359924316406),
(797.492919921875, 524.4356079101562),
(825.904541015625, 125.7273941040039),
(826.0745849609375, 149.3106231689453),
(800.8538818359375, 446.9717102050781),
(800.8538818359375, 446.9717102050781),
(801.9922485351562, 517.8736572265625),
(801.9922485351562, 517.8736572265625),
(802.3947143554688, 520.4193725585938),
(802.3947143554688, 520.4193725585938),
(804.0225830078125, 519.9164428710938),
(804.0225830078125, 519.9164428710938),
(808.3038940429688, 431.790771484375),
(808.3038940429688, 431.790771484375),
(809.5233154296875, 464.2477722167969),
(809.5233154296875, 464.2477722167969),
(812.5013427734375, 438.7483825683594),
(813.3584594726562, 449.6587829589844)]
df=pd.Q_group_coordinates_by_distance_df(coordinates=coordinates,max_euclidean_distance=100)
print(df)
x y item
0 745.801086 519.858521 0
1 747.857483 522.503845 0
2 747.927307 517.129883 0
3 750.921143 522.307495 0
4 756.178101 449.874481 0
5 757.070312 461.237549 0
6 757.105774 438.679810 0
7 759.850159 435.397766 0
8 761.249390 468.021790 0
9 764.565857 521.395264 0
10 770.112732 474.639465 0
11 770.393372 425.349030 0
12 773.731262 516.653625 0
13 776.908447 515.535522 0
14 778.083557 520.688965 0
15 779.883606 519.207214 0
16 782.483887 478.808014 0
17 784.276184 478.511108 0
18 797.492920 524.435608 0
19 800.853882 446.971710 0
20 801.992249 517.873657 0
21 802.394714 520.419373 0
22 804.022583 519.916443 0
23 809.523315 464.247772 0
24 813.358459 449.658783 0
25 830.873962 144.218842 1
26 819.141235 137.673599 1
27 825.904541 125.727394 1
28 826.074585 149.310623 1
29 1079.317017 199.769379 2
30 1083.744629 151.226212 2
#second way, directly from DataFrame with 2 columns (column names don't matter, just the right order (x,y))
df2=pd.DataFrame(coordinates)
df3=df2.d_group_coordinates_by_distance_df(max_euclidean_distance=100)
print(df3)
x y item
0 745.801086 519.858521 0
1 747.857483 522.503845 0
2 747.927307 517.129883 0
3 750.921143 522.307495 0
4 756.178101 449.874481 0
5 757.070312 461.237549 0
6 757.105774 438.679810 0
7 759.850159 435.397766 0
8 761.249390 468.021790 0
9 764.565857 521.395264 0
10 770.112732 474.639465 0
11 770.393372 425.349030 0
12 773.731262 516.653625 0
13 776.908447 515.535522 0
14 778.083557 520.688965 0
15 779.883606 519.207214 0
16 782.483887 478.808014 0
17 784.276184 478.511108 0
18 797.492920 524.435608 0
19 800.853882 446.971710 0
20 801.992249 517.873657 0
21 802.394714 520.419373 0
22 804.022583 519.916443 0
23 809.523315 464.247772 0
24 813.358459 449.658783 0
25 830.873962 144.218842 1
26 819.141235 137.673599 1
27 825.904541 125.727394 1
28 826.074585 149.310623 1
29 1079.317017 199.769379 2
30 1083.744629 151.226212 2
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