getting index of nan values in numpy array
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Getting the index of nan values from where condition and passing it to original array but it is returning empty
#Input
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
iris_2d = np.genfromtxt(url, delimiter = ',', dtype = 'float')# random number from 0 to 150 as high is none
iris_2d[np.random.randint(150, size = 20), np.random.randint(4, size = 20)] = np.nan
( iris_2d[np.where(iris_2d[a,b]==np.nan)])
python-3.x numpy
edited Nov 9 at 10:01
Xatyrian
784320
asked Nov 9 at 8:30
Rajneesh Master
53
add a comment |
up vote
0
down vote
favorite
Getting the index of nan values from where condition and passing it to original array but it is returning empty
#Input
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
iris_2d = np.genfromtxt(url, delimiter = ',', dtype = 'float')# random number from 0 to 150 as high is none
iris_2d[np.random.randint(150, size = 20), np.random.randint(4, size = 20)] = np.nan
( iris_2d[np.where(iris_2d[a,b]==np.nan)])
python-3.x numpy
edited Nov 9 at 10:01
Xatyrian
784320
asked Nov 9 at 8:30
Rajneesh Master
53
By definitionnan!=nanwhich is why your code does not work.
– Paul Panzer
Nov 9 at 9:18
thank you i know now.
– Rajneesh Master
Nov 9 at 10:40
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
Getting the index of nan values from where condition and passing it to original array but it is returning empty
#Input
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
iris_2d = np.genfromtxt(url, delimiter = ',', dtype = 'float')# random number from 0 to 150 as high is none
iris_2d[np.random.randint(150, size = 20), np.random.randint(4, size = 20)] = np.nan
( iris_2d[np.where(iris_2d[a,b]==np.nan)])
python-3.x numpy
edited Nov 9 at 10:01
Xatyrian
784320
asked Nov 9 at 8:30
Rajneesh Master
53
Getting the index of nan values from where condition and passing it to original array but it is returning empty
#Input
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
iris_2d = np.genfromtxt(url, delimiter = ',', dtype = 'float')# random number from 0 to 150 as high is none
iris_2d[np.random.randint(150, size = 20), np.random.randint(4, size = 20)] = np.nan
( iris_2d[np.where(iris_2d[a,b]==np.nan)])
python-3.x numpy
python-3.x numpy
edited Nov 9 at 10:01
Xatyrian
784320
asked Nov 9 at 8:30
Rajneesh Master
53
edited Nov 9 at 10:01
Xatyrian
784320
asked Nov 9 at 8:30
Rajneesh Master
53
edited Nov 9 at 10:01
Xatyrian
784320
edited Nov 9 at 10:01
Xatyrian
784320
edited Nov 9 at 10:01
Xatyrian
784320
784320
asked Nov 9 at 8:30
Rajneesh Master
53
asked Nov 9 at 8:30
Rajneesh Master
53
asked Nov 9 at 8:30
Rajneesh Master
53
53
By definitionnan!=nanwhich is why your code does not work.
– Paul Panzer
Nov 9 at 9:18
thank you i know now.
– Rajneesh Master
Nov 9 at 10:40
add a comment |
By definitionnan!=nanwhich is why your code does not work.
– Paul Panzer
Nov 9 at 9:18
thank you i know now.
– Rajneesh Master
Nov 9 at 10:40
By definition
nan!=nan which is why your code does not work.– Paul Panzer
Nov 9 at 9:18
By definition
nan!=nan which is why your code does not work.– Paul Panzer
Nov 9 at 9:18
thank you i know now.
– Rajneesh Master
Nov 9 at 10:40
thank you i know now.
– Rajneesh Master
Nov 9 at 10:40
add a comment |
1 Answer
1
active
oldest
votes
up vote
0
down vote
accepted
I downloaded the data from the url that you mentioned, and saved it as 'iris_data.txt'. Try the following code. It gives you indices of nan in the numpy array iris_2d.
import numpy as np
iris_2d = np.genfromtxt('iris_data.txt', delimiter = ',', dtype = 'float')
nan_indx = np.argwhere(np.isnan(iris_2d))
print nan_indx.shape
print " "
print nan_indx[0:5,:]
Output:
(150, 2)
[[0 4]
[1 4]
[2 4]
[3 4]
[4 4]]
answered Nov 9 at 8:54
Siddharth Satpathy
303213
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
I downloaded the data from the url that you mentioned, and saved it as 'iris_data.txt'. Try the following code. It gives you indices of nan in the numpy array iris_2d.
import numpy as np
iris_2d = np.genfromtxt('iris_data.txt', delimiter = ',', dtype = 'float')
nan_indx = np.argwhere(np.isnan(iris_2d))
print nan_indx.shape
print " "
print nan_indx[0:5,:]
Output:
(150, 2)
[[0 4]
[1 4]
[2 4]
[3 4]
[4 4]]
answered Nov 9 at 8:54
Siddharth Satpathy
303213
add a comment |
up vote
0
down vote
accepted
I downloaded the data from the url that you mentioned, and saved it as 'iris_data.txt'. Try the following code. It gives you indices of nan in the numpy array iris_2d.
import numpy as np
iris_2d = np.genfromtxt('iris_data.txt', delimiter = ',', dtype = 'float')
nan_indx = np.argwhere(np.isnan(iris_2d))
print nan_indx.shape
print " "
print nan_indx[0:5,:]
Output:
(150, 2)
[[0 4]
[1 4]
[2 4]
[3 4]
[4 4]]
answered Nov 9 at 8:54
Siddharth Satpathy
303213
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
I downloaded the data from the url that you mentioned, and saved it as 'iris_data.txt'. Try the following code. It gives you indices of nan in the numpy array iris_2d.
import numpy as np
iris_2d = np.genfromtxt('iris_data.txt', delimiter = ',', dtype = 'float')
nan_indx = np.argwhere(np.isnan(iris_2d))
print nan_indx.shape
print " "
print nan_indx[0:5,:]
Output:
(150, 2)
[[0 4]
[1 4]
[2 4]
[3 4]
[4 4]]
answered Nov 9 at 8:54
Siddharth Satpathy
303213
I downloaded the data from the url that you mentioned, and saved it as 'iris_data.txt'. Try the following code. It gives you indices of nan in the numpy array iris_2d.
import numpy as np
iris_2d = np.genfromtxt('iris_data.txt', delimiter = ',', dtype = 'float')
nan_indx = np.argwhere(np.isnan(iris_2d))
print nan_indx.shape
print " "
print nan_indx[0:5,:]
Output:
(150, 2)
[[0 4]
[1 4]
[2 4]
[3 4]
[4 4]]
answered Nov 9 at 8:54
Siddharth Satpathy
303213
answered Nov 9 at 8:54
Siddharth Satpathy
303213
answered Nov 9 at 8:54
Siddharth Satpathy
303213
answered Nov 9 at 8:54
Siddharth Satpathy
303213
303213
add a comment |
add a comment |
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By definition
nan!=nanwhich is why your code does not work.– Paul Panzer
Nov 9 at 9:18
thank you i know now.
– Rajneesh Master
Nov 9 at 10:40