示例#1
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    def part5():
        from statistics import mean as m, stdev as s, variance as v

        x = m(example_list)

        print("5 The mean is: ", x)

        y = s(example_list)
        print("5 standard div si: ", y)

        z = v(example_list)
        print("5 Variance is: ", z)
示例#2
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Calculator.multiplication(3, 33)
Calculator.addition(3, 33)
Calculator.subtraction(3, 33)
Calculator.division(3, 33)
print("--------")

exlist = [4, 3, 5, 8, 9, 12, 33]
x = mean(exlist)  #no need to use "s." as the function is imported separately
print(x)
x = s.median(exlist)
print(x)
x = s.stdev(exlist)
print(x)
x = v(exlist)  # no need to use complete name as the function is renamed
print(x)

#map#used when we want to perform an operation on all the elements of the list
doubled_list = list(
    map(Calculator.double, exlist)
)  #list function gathers the results into a list#first argument of map is the function that is to be applied. second is the list
print(doubled_list)
print("--------")

#reading data from csv file
with open('example.csv') as file:
    readcsv = csv.reader(file, delimiter=',')  #reads data from csv file

    dates = []
    colors = []
示例#3
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from statistics import variance

example_list = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
x = variance(example_list)

print(x)

print('New Method')

from statistics import variance as v

example_list = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
x = v(example_list)

print(x)

print('new method')

from statistics import variance, mean

example_list = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
x = variance(example_list)
y = mean(example_list)
print(x)
print(y)

print('new method')

from statistics import variance as v, mean as m

example_list = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
示例#4
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import statistics as s
list = [2, 3, 4, 5, 6, 8, 9, 8, 4]
x = s.variance(list)
#! or

from statistics import variance
list = [2, 3, 4, 5, 6, 8, 9, 8, 4]
y = variance(list)

#! or

from statistics import variance as v
list = [2, 3, 4, 5, 6, 8, 9, 8, 4]
z = v(list)

#! or
from statistics import variance, mean
list = [2, 3, 4, 5, 6, 8, 9, 8, 4]
t = variance(list)
m = mean(list)

#! or
from statistics import variance as v, mean as m
list = [2, 3, 4, 5, 6, 8, 9, 8, 4]
p = v(list)
q = m(list)
#! or
from statistics import *
list = [2, 3, 4, 5, 6, 8, 9, 8, 4]
a = variance(list)
b = mean(list)
示例#5
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##abbreviate import name statistics to s
##import statistics as s

##directly import variance from statistics, abbreviate as v and mean
from statistics import variance as v, mean

##import everything from statistics
##from statistic import *

example_list = [4, 6, 2, 6, 7, 8, 2, 5, 6, 8, 4, 6, 7, 2, 2]
##if using abbreviate import statistics name s
##var = s.variance(example_list)

##use import method variance from statistics as v
var = v(example_list)
##use import method mean from statistics
mea = mean(example_list)

print(var)
print(mea)
示例#6
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from statistics import variance as v

varList = [1, 2, 3, 9, 10, 5, 4, 2, 3, 6, 7]

x = v(varList)
print(x, ' = variance\n')
示例#7
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from statistics import variance as v, mean as m
from statistics import *

example_list = [4, 5, 6, 2, 3, 45, 5, 65, 464, 6, 464, 64, 64, 646, 5]
x1 = v(example_list)
x = variance(example_list)
y = m(example_list)

print(x1)
print(x)
print(y)
示例#8
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#   23. Module Import Syntax

import statistics as s
from statistics import median, stdev as d, variance as v

list = [1, 12, 67, 2, 3, 7, 9, 7, 4]

print('mean:', s.mean(list))
print('median:', median(list))
print('stdev:', d(list))
print('variance:', v(list))
示例#9
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from module_name import var_1 [as short_1], var_2 [as short_2], etc.

from module_name import * ---> all

'''

import statistics as s
example_list = [4, 6, 2, 5]
x = s.variance(example_list)
print(x)

from statistics import variance
print(variance(example_list))

from statistics import variance as v
print(v(example_list))

from statistics import variance, mean
x = variance(example_list)
y = mean(example_list)
print(x)
print(y)

from statistics import variance as v, mean as m
print(v(example_list))
print(m(example_list))

# to import everything
from statistics import *
print(variance(example_list))
print(median(example_list))
示例#10
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import statistics as s  #Allows us to write statistics as s

exList = [3, 5, 7, 3, 1, 5, 7, 9, 5, 5, 4, 3, 3, 6, 43, 2, 5, 6, 4, 7, 4]
print(s.mean(exList))

#if you only want to import one function from the library
from statistics import mean
#can also use shorthand here as well
from statistics import variance as v

print(mean(exList))
print(v(exList))

#allows you to import multiple
from statistics import stdev as st, mean as m
print(m(exList))
print(st(exList))
示例#11
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#from statistics import *

import statistics as stat

from statistics import mean, stdev as s

from statistics import variance as v

myList = [5,5,12,74,85,1,7,4,58,587,8,8,8,5,9,7,744,7,85,12,5,]


print(stat.median(myList))

print('mean is', mean(myList))

print('variance is', v(myList))

print('standard deviation is', s(myList))

#
# for n in myList:
#     print(n,end=' ')
#

#
# print('median is', median(myList))
#
# print('mode is', mode(myList))
#

#
示例#12
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import statistics 
s = [1,2,3,4]
x = statistics.mean(s) #variance, mode,median, stdev

from statistics import variance as v , mean as m
x = v(s)




(1.1 + 2.2) == 3.3
#False
#Turns out decimal fraction 0.1 will result into an infinitely long binary fraction of 0.000110011001100110011...
#so we use decimal module which has upto 15 decimal precision

from decimal import Decimal as d
print(d(1.1+2.2))           # 3.300000000000000266453525910037569701671600341796875
print(d('1.1') + d('2.2'))  # use string to get usual output i.e 3.3
print(d('1.1+2.2'))         # error

from fractions import Fraction as f
print(f(1.5))
# 3/2
print(f(1.1))
# 2476979795053773/2251799813685248
print(f('1.1'))
# 11/10

import math
print(math.pi)
# Output: 3.141592653589793
示例#13
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from statistics import variance as v, mean as m

exampleList = [4,5,6,7,8,93,2,543]
x = m(exampleList)
y = v(exampleList)
print(x)
print(y)