array is (800, ) dimension, each element is (240, ) dimension, how to change to (800, 240)
0
I have a np array which is (800,) in shape, and each element in this array is (240, ) in shape, how to reshape this array to (800, 240) dimension?
python numpy-ndarray
asked Nov 21 at 2:56
Kevin Li
54
add a comment |
0
I have a np array which is (800,) in shape, and each element in this array is (240, ) in shape, how to reshape this array to (800, 240) dimension?
python numpy-ndarray
asked Nov 21 at 2:56
Kevin Li
54
1
What is the output ofa.shape(assuming your array is nameda)?
– Julian Peller
Nov 21 at 3:27
the a.shape is (800, ), a[0].shape is (240,), I would like to reshape this to an array with shape (800, 240)
– Kevin Li
Nov 21 at 3:35
1
I can't figure out how you created an array of that shape, if you can provide a simple snippet of code it would be nice (maybe with lower dimensions :P). Just to check, have you tried:a.reshape((800, 240))?
– Julian Peller
Nov 21 at 3:38
I tried to reshape, it does not work. Actually, I pull out this array from a pandas column. a = df['col'].values, then a.shape is (800, ), and each element in a, the shape is (240, ), so take first element as example, a[0].shape is (240, )
– Kevin Li
Nov 21 at 3:49
Found something. Posted it as an answer!
– Julian Peller
Nov 21 at 3:56
add a comment |
0
0
0
I have a np array which is (800,) in shape, and each element in this array is (240, ) in shape, how to reshape this array to (800, 240) dimension?
python numpy-ndarray
asked Nov 21 at 2:56
Kevin Li
54
I have a np array which is (800,) in shape, and each element in this array is (240, ) in shape, how to reshape this array to (800, 240) dimension?
python numpy-ndarray
python numpy-ndarray
asked Nov 21 at 2:56
Kevin Li
54
asked Nov 21 at 2:56
Kevin Li
54
asked Nov 21 at 2:56
Kevin Li
54
asked Nov 21 at 2:56
Kevin Li
54
asked Nov 21 at 2:56
Kevin Li
54
54
1
What is the output ofa.shape(assuming your array is nameda)?
– Julian Peller
Nov 21 at 3:27
the a.shape is (800, ), a[0].shape is (240,), I would like to reshape this to an array with shape (800, 240)
– Kevin Li
Nov 21 at 3:35
1
I can't figure out how you created an array of that shape, if you can provide a simple snippet of code it would be nice (maybe with lower dimensions :P). Just to check, have you tried:a.reshape((800, 240))?
– Julian Peller
Nov 21 at 3:38
I tried to reshape, it does not work. Actually, I pull out this array from a pandas column. a = df['col'].values, then a.shape is (800, ), and each element in a, the shape is (240, ), so take first element as example, a[0].shape is (240, )
– Kevin Li
Nov 21 at 3:49
Found something. Posted it as an answer!
– Julian Peller
Nov 21 at 3:56
add a comment |
1
What is the output ofa.shape(assuming your array is nameda)?
– Julian Peller
Nov 21 at 3:27
the a.shape is (800, ), a[0].shape is (240,), I would like to reshape this to an array with shape (800, 240)
– Kevin Li
Nov 21 at 3:35
1
I can't figure out how you created an array of that shape, if you can provide a simple snippet of code it would be nice (maybe with lower dimensions :P). Just to check, have you tried:a.reshape((800, 240))?
– Julian Peller
Nov 21 at 3:38
I tried to reshape, it does not work. Actually, I pull out this array from a pandas column. a = df['col'].values, then a.shape is (800, ), and each element in a, the shape is (240, ), so take first element as example, a[0].shape is (240, )
– Kevin Li
Nov 21 at 3:49
Found something. Posted it as an answer!
– Julian Peller
Nov 21 at 3:56
1
1
What is the output of
a.shape (assuming your array is named a)?– Julian Peller
Nov 21 at 3:27
What is the output of
a.shape (assuming your array is named a)?– Julian Peller
Nov 21 at 3:27
the a.shape is (800, ), a[0].shape is (240,), I would like to reshape this to an array with shape (800, 240)
– Kevin Li
Nov 21 at 3:35
the a.shape is (800, ), a[0].shape is (240,), I would like to reshape this to an array with shape (800, 240)
– Kevin Li
Nov 21 at 3:35
1
1
I can't figure out how you created an array of that shape, if you can provide a simple snippet of code it would be nice (maybe with lower dimensions :P). Just to check, have you tried:
a.reshape((800, 240))?– Julian Peller
Nov 21 at 3:38
I can't figure out how you created an array of that shape, if you can provide a simple snippet of code it would be nice (maybe with lower dimensions :P). Just to check, have you tried:
a.reshape((800, 240))?– Julian Peller
Nov 21 at 3:38
I tried to reshape, it does not work. Actually, I pull out this array from a pandas column. a = df['col'].values, then a.shape is (800, ), and each element in a, the shape is (240, ), so take first element as example, a[0].shape is (240, )
– Kevin Li
Nov 21 at 3:49
I tried to reshape, it does not work. Actually, I pull out this array from a pandas column. a = df['col'].values, then a.shape is (800, ), and each element in a, the shape is (240, ), so take first element as example, a[0].shape is (240, )
– Kevin Li
Nov 21 at 3:49
Found something. Posted it as an answer!
– Julian Peller
Nov 21 at 3:56
Found something. Posted it as an answer!
– Julian Peller
Nov 21 at 3:56
add a comment |
1 Answer
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votes
0
Try with np.stack:
np.stack(a)
answered Nov 21 at 3:54
Julian Peller
849511
yes, it is. But I am a little bit confused, why use stack here.
– Kevin Li
Nov 21 at 4:00
I'm a bit confused too. The object you brought is new to me and my first shots (reshape and resize) didn't work. This solution works, in general, for sequences of arrays.
– Julian Peller
Nov 21 at 4:14
add a comment |
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0
Try with np.stack:
np.stack(a)
answered Nov 21 at 3:54
Julian Peller
849511
yes, it is. But I am a little bit confused, why use stack here.
– Kevin Li
Nov 21 at 4:00
I'm a bit confused too. The object you brought is new to me and my first shots (reshape and resize) didn't work. This solution works, in general, for sequences of arrays.
– Julian Peller
Nov 21 at 4:14
add a comment |
0
Try with np.stack:
np.stack(a)
answered Nov 21 at 3:54
Julian Peller
849511
yes, it is. But I am a little bit confused, why use stack here.
– Kevin Li
Nov 21 at 4:00
I'm a bit confused too. The object you brought is new to me and my first shots (reshape and resize) didn't work. This solution works, in general, for sequences of arrays.
– Julian Peller
Nov 21 at 4:14
add a comment |
0
0
0
Try with np.stack:
np.stack(a)
answered Nov 21 at 3:54
Julian Peller
849511
Try with np.stack:
np.stack(a)
answered Nov 21 at 3:54
Julian Peller
849511
answered Nov 21 at 3:54
Julian Peller
849511
answered Nov 21 at 3:54
Julian Peller
849511
answered Nov 21 at 3:54
Julian Peller
849511
849511
yes, it is. But I am a little bit confused, why use stack here.
– Kevin Li
Nov 21 at 4:00
I'm a bit confused too. The object you brought is new to me and my first shots (reshape and resize) didn't work. This solution works, in general, for sequences of arrays.
– Julian Peller
Nov 21 at 4:14
add a comment |
yes, it is. But I am a little bit confused, why use stack here.
– Kevin Li
Nov 21 at 4:00
I'm a bit confused too. The object you brought is new to me and my first shots (reshape and resize) didn't work. This solution works, in general, for sequences of arrays.
– Julian Peller
Nov 21 at 4:14
yes, it is. But I am a little bit confused, why use stack here.
– Kevin Li
Nov 21 at 4:00
yes, it is. But I am a little bit confused, why use stack here.
– Kevin Li
Nov 21 at 4:00
I'm a bit confused too. The object you brought is new to me and my first shots (reshape and resize) didn't work. This solution works, in general, for sequences of arrays.
– Julian Peller
Nov 21 at 4:14
I'm a bit confused too. The object you brought is new to me and my first shots (reshape and resize) didn't work. This solution works, in general, for sequences of arrays.
– Julian Peller
Nov 21 at 4:14
add a comment |
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1
What is the output of
a.shape(assuming your array is nameda)?– Julian Peller
Nov 21 at 3:27
the a.shape is (800, ), a[0].shape is (240,), I would like to reshape this to an array with shape (800, 240)
– Kevin Li
Nov 21 at 3:35
1
I can't figure out how you created an array of that shape, if you can provide a simple snippet of code it would be nice (maybe with lower dimensions :P). Just to check, have you tried:
a.reshape((800, 240))?– Julian Peller
Nov 21 at 3:38
I tried to reshape, it does not work. Actually, I pull out this array from a pandas column. a = df['col'].values, then a.shape is (800, ), and each element in a, the shape is (240, ), so take first element as example, a[0].shape is (240, )
– Kevin Li
Nov 21 at 3:49
Found something. Posted it as an answer!
– Julian Peller
Nov 21 at 3:56