Create Multiple rows for each value in given column in pandas df

Question

I have a dataframe with points given in two columns x and y.

Thing  x  y  length_x  length_y
0     A  1  3         1         2
1     B  2  3         2         1

These (x,y) points are situated in the middle of one of the sides of a rectangle with vertex lengths length_x and length_y. What I wish to do is for each of these points give the coordinates of the rectangles they are on. That is: the following coordinated for Thing A would be:

(1+1*0.5, 3), (1-1*0.5,3), (1+1*0.5,3-2*0.5), (1-1*0.5, 3-2*0.5)

The half comes from the fact that the given lengths are the middle-points of an object so half the length is the distance from that point to the corner of the rectangle.

Hence my desired output is:

Thing  x  y  Corner_x  Corner_y  length_x  length_y
0     A  1  3       1.5       2.0         1         2
1     A  1  3       1.5       1.0         1         2
2     A  1  3       0.5       2.0         1         2
3     A  1  3       0.5       1.0         1         2
4     A  1  3       1.5       2.0         1         2
5     B  2  3       3.0       3.0         2         1
6     B  2  3       3.0       2.5         2         1
7     B  2  3       1.0       3.0         2         1
8     B  2  3       1.0       2.5         2         1
9     B  2  3       3.0       3.0         2         1

I tried to do this with defining a lambda returning two value but failed. Tried even to create multiple columns and then stack them, but it's really dirty.

bb = []
for thing in list_of_things:
    new_df = df[df['Thing']=='{}'.format(thing)]
    
    df = df.sort_values('x',ascending=False)
    df['corner 1_x'] = df['x']+df['length_x']/2
    df['corner 1_y'] = df['y']
    df['corner 2_x'] = df['x']+1df['x_length']/2
    df['corner 2_y'] = df['y']-df['length_y']/2
        .........

Note also that the first corner's coordinates need to be repeated as I later what to use geopandas to transform each of these sets of coordinates into a POLYGON.

What I am looking for is a way to generate these rows is a fast and clean way.

No. The point from which the calculations are made is not in the center of the rectangle. — Serge de Gosson de Varennes
– Serge de Gosson de Varennes, Commented Sep 6, 2021 at 12:59
OK, then you have to slightly adapt my answer, I misunderstood this point — mozway
– mozway, Commented Sep 6, 2021 at 13:10
Doesn't matter. A accepted the answer because the procedure is there. The rest is tweaking. — Serge de Gosson de Varennes
– Serge de Gosson de Varennes, Commented Sep 6, 2021 at 13:59

mozway · Accepted Answer · 2021-09-06 12:04:31Z

You can use apply to create your corners as lists and explode them to the four rows per group.

Finally join the output to the original dataframe:

df.join(df.apply(lambda r: pd.Series({'corner_x': [r['x']+r['length_x']/2, r['x']-r['length_x']/2],
                                      'corner_y': [r['y']+r['length_y']/2, r['y']-r['length_y']/2],
                                     }), axis=1).explode('corner_x').explode('corner_y'),
        how='right')

output:

  Thing  x  y  length_x  length_y corner_x corner_y
0     A  1  3         1         2      1.5        4
0     A  1  3         1         2      1.5        2
0     A  1  3         1         2      0.5        4
0     A  1  3         1         2      0.5        2
1     B  2  3         2         1        3      3.5
1     B  2  3         2         1        3      2.5
1     B  2  3         2         1        1      3.5
1     B  2  3         2         1        1      2.5

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Create Multiple rows for each value in given column in pandas df

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