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  2. sciPy function stats.binned_statistic () | python

sciPy function stats.binned_statistic () | python



stats.binned_statistic (x, values, statistic = & # 39; mean & # 39 ;, bins = 10, range = None) calculates statistic value for given data (array elements). 
It works similarly to the

# stats.binned_statistic () method

import numpy as np

from scipy import stats

 
# 1D array

arr = [ 20 , 2 , 7 , 1 , 34 ]

print ( "arr:" , arr) 

 

 
# median

print ( "binned_statistic for median:" , stats.binned_statistic (

arr, np.arange ( 5 ), statistic = `median` , bins = 4 )) 

Output: 

 arr: [20, 2, 7, 1, 34] binned_statistic for median: BinnedStatisticResult (statistic = array ([2., nan, 0., 4.]), bin_edges = array ([1 ., 9.25, 17.5, 25.75, 34.]), binnumber = arr ay ([3, 1, 1, 1, 4], dtype = int64))

Code # 2:

# stats.binned_statistic () method

import numpy as np

from scipy import stats

 
# greedy

arr = [ 20 , 2 , 7 , 1 , 34 ]

print ( " binned_statistic for mean: " , stats.binned_statistic (

arr, np.arange ( 5 ), statistic = ` mean` , bins = 2 )) 

Output: 

 binned_statistic for mean: BinnedStatisticResult (statistic = array ([2., 2.]), bin_edges = array ([1., 17.5, 34.]), binnumber = array ([2, 1, 1, 1, 2], dtype = int64))