Python Statistics Module
Goal : Learn python by Implementation.
Objective :
To compute and understand
1. mean
2. median
3. mode
4. variance
5. standard deviation
Code:-
Statistics
To understand data statistics play a very important role.
it helps in collecting, organizing, analyzing, and interpreting data.
Data Analyst(descriptive and inferential statistics )
Descriptive Statistics - help to summarize or describe data.
identify important elements in datasets.
Inferential Statistics - Explains data elements via the relationship with other data elements.
explains what we found.
Measure of Central Tendency
Measure of Central Tendency,
Measure of dispersion
import statistics as s
dir(s)
Mean
from statistics import *
wt = [60,65,68,70,75]
mean(wt)
mean([])
from fractions import Fraction as F
mean([F(3, 7), F(1, 21), F(5, 3), F(1, 3)])
from decimal import Decimal as D
mean([D("0.5"), D("0.75"), D("0.625"), D("0.375")])
Suppose an investor purchases an equal value of shares in each of three companies, with P/E (price/earnings) ratios of 2.5, 3, and 10.
What is the average P/E ratio for the investor's portfolio?
harmonic_mean([2.5, 3, 10])
mean([2.5, 3, 10])
wt = [60,65,68,70,75,60,1000]
mean(wt)
harmonic_mean(wt)
Median
wt = [60,65,68,70,75,60,1000,80]
sorted(wt)
median_high(wt)
Mode
wt = [65,68,70,75,60,1000,80,60,60]
mode(wt)
Measure of dispersion
Variance
wt = [60,65,68,70,75]
mean(wt)
variance(wt)
Standard Deviation
stdev(wt)
pvariance(wt)
pstdev(wt)
dir ()
help(mean)
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