python - SFrame from numpy array -
i create sframe numpy array:
what want:
np.arange(16).reshape(4, 4)
=>
+----+----+----+----+ | 0 | 1 | 2 | 3 | +----+----+----+----+ | 0 | 1 | 2 | 3 | | 4 | 5 | 6 | 7 | | 8 | 9 | 10 | 11 | | 12 | 13 | 14 | 15 | +----+----+----+----+ [4 rows x 4 columns]
if do:
print sframe(np.arange(16).reshape(4, 4))
i get:
+--------------------------+ | x1 | +--------------------------+ | [0.0, 1.0, 2.0, 3.0] | | [4.0, 5.0, 6.0, 7.0] | | [8.0, 9.0, 10.0, 11.0] | | [12.0, 13.0, 14.0, 15.0] | +--------------------------+ [4 rows x 1 columns]
i can want if convert numpy array pandas dataframe , pandas dataframe sframe:
print sframe(pd.dataframe(np.arange(16).reshape(4, 4))) +----+----+----+----+ | 0 | 1 | 2 | 3 | +----+----+----+----+ | 0 | 1 | 2 | 3 | | 4 | 5 | 6 | 7 | | 8 | 9 | 10 | 11 | | 12 | 13 | 14 | 15 | +----+----+----+----+ [4 rows x 4 columns]
the question is: "how can create sfame numpy array in way pandas dataframe reads it(array nxm => dataframe n rows , m columns), without using pandas intermediate step?
i has issue, find multi-indexing hard in sframe.
may silly fix still workable;
from graphlab import sframe,sarray data=np.arange(16).reshape(4, 4).t sf=sframe(map(sarray,data)
should result in this
x1 x2 x3 x4 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
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