# -*- coding: utf-8 -*-
"""
Created on Tue Jun  1 17:06:57 2021

@author: Sim
"""
import statistics as stat
import pandas as pd
import numpy as np

df = pd.read_csv(r'D:\HTEX\Pythonbk\codesdata\bmi.csv')

ave1 = stat.mean(df['height'])
ave2 = stat.fmean(df['height'])
med = stat.median(df['height'])
mod1 = stat.mode(['a','a','a','b','b','b','c','d','d'])
mod2 = stat.multimode(['a','a','a','b','b','b','c','d','d'])
qq = stat.quantiles(df['height'])

print(ave1, ave2, med, mod1, mod2, qq)

#####################################

x = pd.DataFrame([[1,2], [3,4], [5,6]], columns=['A','B'])
print(x)
ave1 = x.mean()
ave2 = x.mean(axis=1)
print(ave1, ave2)

##

ave1 = df.mean(axis=0)
ave2 = df.mean(axis='index')
med1 = df['height'].median()
max1 = df['height'].max()
min1 = df['height'].min()
mod1 = df['height'].mode()
qq1 = df['height'].quantile(q=[.05, 0.1, 0.25, 0.5, 0.75, 1])

print(ave1, ave2, med1, max1, min1, mod1, qq1)

stat.multimode(['a','a','b','b','b','c','d','d'])

##########################################

med = np.percentile(x, q=50, axis=0)
qq = np.percentile(df['height'], q=[0, 25, 50, 75, 100])