extract() function returns elements of input_array if they satisfy some specified condition. Parameters : array : Input array. User apply conditions on input_array elements condition : [array_like]Condition on the basis of which user extract elements.
I assume you wanted columns 1
and 9
?
To select multiple columns at once, use
X = data[:, [1, 9]]
To select one at a time, use
x, y = data[:, 1], data[:, 9]
With names:
data[:, ['Column Name1','Column Name2']]
You can get the names from data.dtype.names
…
Assuming you want to get columns 1 and 9 with that code snippet, it should be:
extractedData = data[:,[1,9]]
if you want to extract only some columns:
idx_IN_columns = [1, 9]
extractedData = data[:,idx_IN_columns]
if you want to exclude specific columns:
idx_OUT_columns = [1, 9]
idx_IN_columns = [i for i in xrange(np.shape(data)[1]) if i not in idx_OUT_columns]
extractedData = data[:,idx_IN_columns]
Just:
>>> m = np.matrix(np.random.random((5, 5)))
>>> m
matrix([[0.91074101, 0.65999332, 0.69774588, 0.007355 , 0.33025395],
[0.11078742, 0.67463754, 0.43158254, 0.95367876, 0.85926405],
[0.98665185, 0.86431513, 0.12153138, 0.73006437, 0.13404811],
[0.24602225, 0.66139215, 0.08400288, 0.56769924, 0.47974697],
[0.25345299, 0.76385882, 0.11002419, 0.2509888 , 0.06312359]])
>>> m[:,[1, 2]]
matrix([[0.65999332, 0.69774588],
[0.67463754, 0.43158254],
[0.86431513, 0.12153138],
[0.66139215, 0.08400288],
[0.76385882, 0.11002419]])
The columns need not to be in order:
>>> m[:,[2, 1, 3]]
matrix([[0.69774588, 0.65999332, 0.007355 ],
[0.43158254, 0.67463754, 0.95367876],
[0.12153138, 0.86431513, 0.73006437],
[0.08400288, 0.66139215, 0.56769924],
[0.11002419, 0.76385882, 0.2509888 ]])
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