Difference between np.nan and np.NaN
Is there any difference between np.Nan and np.nan? As per my understanding both are used for null values but if you look here
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame([[np.nan,2,np.nan,0],[3,4,np.nan,1],[np.nan,np.nan,np.nan,5]],columns=list('ABCD'))
print(df)
print(np.nan == np.NaN)
I get following output:
A B C D
0 NaN 2.0 NaN 0
1 3.0 4.0 NaN 1
2 NaN NaN NaN 5
False
Process finished with exit code 0
Now if these are same print(np.nan == np.NaN) should return True and why are the values in dataframe populated as NaN?
I get NaN is not a number so it might be treating it that way and hence changing the entry in dataframe but I am still not sure.
arrays numpy nan
asked Nov 22 '18 at 18:14
user10089194user10089194
386
add a comment |
Is there any difference between np.Nan and np.nan? As per my understanding both are used for null values but if you look here
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame([[np.nan,2,np.nan,0],[3,4,np.nan,1],[np.nan,np.nan,np.nan,5]],columns=list('ABCD'))
print(df)
print(np.nan == np.NaN)
I get following output:
A B C D
0 NaN 2.0 NaN 0
1 3.0 4.0 NaN 1
2 NaN NaN NaN 5
False
Process finished with exit code 0
Now if these are same print(np.nan == np.NaN) should return True and why are the values in dataframe populated as NaN?
I get NaN is not a number so it might be treating it that way and hence changing the entry in dataframe but I am still not sure.
arrays numpy nan
asked Nov 22 '18 at 18:14
user10089194user10089194
386
np.nan is np.NaN is True. They are alias.
– B. M.
Nov 22 '18 at 18:17
1
In pycharm, I get false.
– user10089194
Nov 22 '18 at 18:19
4
@user10089194 You should not use equality to testnans, it will always return False. i.e.np.nan == np.nanis alsoFalse. But testing identity withis,np.nan is np.NaNisTrue. See IEEE 754 Floating Point Special Values in the NumPy docs.
– miradulo
Nov 22 '18 at 18:58
Understood. Thanks.
– user10089194
Nov 22 '18 at 20:10
add a comment |
Is there any difference between np.Nan and np.nan? As per my understanding both are used for null values but if you look here
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame([[np.nan,2,np.nan,0],[3,4,np.nan,1],[np.nan,np.nan,np.nan,5]],columns=list('ABCD'))
print(df)
print(np.nan == np.NaN)
I get following output:
A B C D
0 NaN 2.0 NaN 0
1 3.0 4.0 NaN 1
2 NaN NaN NaN 5
False
Process finished with exit code 0
Now if these are same print(np.nan == np.NaN) should return True and why are the values in dataframe populated as NaN?
I get NaN is not a number so it might be treating it that way and hence changing the entry in dataframe but I am still not sure.
arrays numpy nan
asked Nov 22 '18 at 18:14
user10089194user10089194
386
Is there any difference between np.Nan and np.nan? As per my understanding both are used for null values but if you look here
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame([[np.nan,2,np.nan,0],[3,4,np.nan,1],[np.nan,np.nan,np.nan,5]],columns=list('ABCD'))
print(df)
print(np.nan == np.NaN)
I get following output:
A B C D
0 NaN 2.0 NaN 0
1 3.0 4.0 NaN 1
2 NaN NaN NaN 5
False
Process finished with exit code 0
Now if these are same print(np.nan == np.NaN) should return True and why are the values in dataframe populated as NaN?
I get NaN is not a number so it might be treating it that way and hence changing the entry in dataframe but I am still not sure.
arrays numpy nan
arrays numpy nan
asked Nov 22 '18 at 18:14
user10089194user10089194
386
asked Nov 22 '18 at 18:14
user10089194user10089194
386
asked Nov 22 '18 at 18:14
user10089194user10089194
386
asked Nov 22 '18 at 18:14
user10089194user10089194
386
asked Nov 22 '18 at 18:14
user10089194user10089194
386
386
np.nan is np.NaN is True. They are alias.
– B. M.
Nov 22 '18 at 18:17
1
In pycharm, I get false.
– user10089194
Nov 22 '18 at 18:19
4
@user10089194 You should not use equality to testnans, it will always return False. i.e.np.nan == np.nanis alsoFalse. But testing identity withis,np.nan is np.NaNisTrue. See IEEE 754 Floating Point Special Values in the NumPy docs.
– miradulo
Nov 22 '18 at 18:58
Understood. Thanks.
– user10089194
Nov 22 '18 at 20:10
add a comment |
np.nan is np.NaN is True. They are alias.
– B. M.
Nov 22 '18 at 18:17
1
In pycharm, I get false.
– user10089194
Nov 22 '18 at 18:19
4
@user10089194 You should not use equality to testnans, it will always return False. i.e.np.nan == np.nanis alsoFalse. But testing identity withis,np.nan is np.NaNisTrue. See IEEE 754 Floating Point Special Values in the NumPy docs.
– miradulo
Nov 22 '18 at 18:58
Understood. Thanks.
– user10089194
Nov 22 '18 at 20:10
np.nan is np.NaN is True. They are alias.
– B. M.
Nov 22 '18 at 18:17
np.nan is np.NaN is True. They are alias.
– B. M.
Nov 22 '18 at 18:17
1
1
In pycharm, I get false.
– user10089194
Nov 22 '18 at 18:19
In pycharm, I get false.
– user10089194
Nov 22 '18 at 18:19
4
4
@user10089194 You should not use equality to test
nans, it will always return False. i.e. np.nan == np.nan is also False. But testing identity with is, np.nan is np.NaN is True. See IEEE 754 Floating Point Special Values in the NumPy docs.– miradulo
Nov 22 '18 at 18:58
@user10089194 You should not use equality to test
nans, it will always return False. i.e. np.nan == np.nan is also False. But testing identity with is, np.nan is np.NaN is True. See IEEE 754 Floating Point Special Values in the NumPy docs.– miradulo
Nov 22 '18 at 18:58
Understood. Thanks.
– user10089194
Nov 22 '18 at 20:10
Understood. Thanks.
– user10089194
Nov 22 '18 at 20:10
add a comment |
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np.nan is np.NaN is True. They are alias.
– B. M.
Nov 22 '18 at 18:17
1
In pycharm, I get false.
– user10089194
Nov 22 '18 at 18:19
4
@user10089194 You should not use equality to test
nans, it will always return False. i.e.np.nan == np.nanis alsoFalse. But testing identity withis,np.nan is np.NaNisTrue. See IEEE 754 Floating Point Special Values in the NumPy docs.– miradulo
Nov 22 '18 at 18:58
Understood. Thanks.
– user10089194
Nov 22 '18 at 20:10