Numpy standard deviation

Numpy calculate standard deviation

import numpy
numbers = [1,5,6,7,9,11,13]
standard = numpy.std(numbers) #Calculates standard deviation
print(standard)

Numpy stdev

# Calculate standard deviaton based on population/sample
import numpy as np
values = [1,5,4,3,3,4]
# as default, std() calculates basesd on a population
# by specifying ddof=1, it calculates based on the sample
np.std(values)				# ==1.247219128924647
np.std(values ,ddof=1)		# ==1.3662601021279464

Source: honingds.com

Numpy standard deviation

aux = np.array( [[0, 0, 0], [1, 2, 3]] )
np.std( aux, axis=0 )

Std python

import numpy as np
values=[1,10,100]
print(np.std(values))
values=[1,10,100,np.nan]
print(np.nanstd(values))

Similar codes

1 vote137 views1 answer
How to find which 2 rows of a df are the most similar
Python
133 votes154 views6 answers
Input function in python
Python
0 vote147 views2 answers
Stable version of django
Python
4 votes140 views3 answers
Print bold python
Python
1 vote151 views1 answer
The name tf.train.Optimizer is deprecated. Please use tf.compat.v1.train.Optimizer instead.
Python
1 vote185 views1 answer
Telnet python
Python
0 vote158 views2 answers
Python turtle jupyter notebook
Python
2 votes141 views4 answers
ValueError: Input contains NaN, infinity or a value too large for dtype('float32').
Python
9 votes143 views2 answers
Merge 2 dataframes pythom
Python
5 votes205 views4 answers
Data normalization python
Python