Numpy Array to Pandas Data Frame from XY Coordinates
I have a 2 dimensional numpy array:
arr = np.array([[1,2,3],[4,5,6],[7,8,9]])
How would I go about converting this to a pandas dataframe that would have an x coordinate, a y coordinate, and the corresponding array value at that index in a pandas dataframe like this:
x y val
0 0 1
0 1 4
0 2 7
1 0 2
1 1 5
1 2 8
...
+3
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2 answers
With a stack and reset index:
df = pd.DataFrame(arr).stack().rename_axis(['y', 'x']).reset_index(name='val')
df
Out:
y x val
0 0 0 1
1 0 1 2
2 0 2 3
3 1 0 4
4 1 1 5
5 1 2 6
6 2 0 7
7 2 1 8
8 2 2 9
If order is very important:
df.sort_values(['x', 'y'])[['x', 'y', 'val']].reset_index(drop=True)
Out:
x y val
0 0 0 1
1 0 1 4
2 0 2 7
3 1 0 2
4 1 1 5
5 1 2 8
6 2 0 3
7 2 1 6
8 2 2 9
+5
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Here's the NumPy method -
>>> arr
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
>>> shp = arr.shape
>>> r,c = np.indices(shp)
>>> pd.DataFrame(np.c_[r.ravel(), c.ravel(), arr.ravel('F')], \
columns=((['x','y','val'])))
x y val
0 0 0 1
1 0 1 4
2 0 2 7
3 1 0 2
4 1 1 5
5 1 2 8
6 2 0 3
7 2 1 6
8 2 2 9
+1
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