BUAN $620$ Data Science Foundations

Designed by: Dr$.$ Roy Jafari

Programing Assignmnet #$6$

Fill in your name first:

$-$Name:

$-$Redlands Email ID:

In $[1]$: import pandas as pd

import matplotlib.pyplot as plt

import numpy as $np$

import seaborn as sns

Chapter $13-$ Excercise $8$

In this exercise, we would like to use the dataset Cereals.csv$.$ This dataset contains rows of information about different cereal products. We would like to perform clustering analysis on this dataset, first using K$-$means and then using PCA. Perform the following steps.

In $[2]$: cereal$\_$df $=$ pd$.$read$\_$csv$(\text{'}$Cereals$.$csv$\text{'})$

cereal$\_$df$.$head$()$

$\backslash$table$[[,$name,$mfr,$type,calories,protein,fat,sodium,fiber,carbo,sugars,potass,vitamins,shelf,weight,cups,rating$],[0,100\%{?}_B$ran,$N,C,70,4,1,130,10\mathrm{.}0,5\mathrm{.}0,6\mathrm{.}0,280\mathrm{.}0,25,3,1\mathrm{.}0,0\mathrm{.}33,68\mathrm{.}402973],[1,100\%{?}_{N}atura{l}_B$ran,Q$,C,120,3,5,15,2\mathrm{.}0,8\mathrm{.}0,8\mathrm{.}0,135\mathrm{.}0,0,3,1\mathrm{.}0,1\mathrm{.}00,33\mathrm{.}983679],[2,$All$-$Bran,K$,C,70,4,1,260,9\mathrm{.}0,7\mathrm{.}0,5\mathrm{.}0,320\mathrm{.}0,25,3,1\mathrm{.}0,0\mathrm{.}33,59\mathrm{.}425505],[3,$All$-$Bran$\_$with$\_$Extra$\_$Fiber,K$,C,50,4,0,140,14\mathrm{.}0,8\mathrm{.}0,0\mathrm{.}0,330\mathrm{.}0,25,3,1\mathrm{.}0,0\mathrm{.}50,93\mathrm{.}704912],[4,$Almond$\_$Delight,$R,C,110,2,2,200,1\mathrm{.}0,14\mathrm{.}0,8\mathrm{.}0,$NaN,$25,3,1\mathrm{.}0,0\mathrm{.}75,34\mathrm{.}384843]]$

a$.$ Impute a central tendency of the attribute for all the missing values.

In $[]$:

b$.$ What central tendency did you choose and why?

In $[]$:

c$.$ Why did we impute using the central tendency? why not other methods? Answer by commenting on how the data will b e used next $($clustering$).$

name,mfr$,$type,calories,protein,fat,sodium,fiber,carbo,sugars,potass,vitamins,shelf,weight,cups,rating

$100\%\_$Bran,N$,$C$,70,4,1,130,10,5,6,280,25,3,1,0\mathrm{.}33,68\mathrm{.}402973$

$100\%\_$Natural$\_$Bran,Q$,$C$,120,3,5,15,2,8,8,135,0,3,1,1,33\mathrm{.}983679$

All$-$Bran,K$,$C$,70,4,1,260,9,7,5,320,25,3,1,0\mathrm{.}33,59\mathrm{.}425505$

All$-$Bran$\_$with$\_$Extra$\_$Fiber,K$,$C$,50,4,0,140,14,8,0,330,25,3,1,0\mathrm{.}5,93\mathrm{.}704912$

Almond$\_$Delight,R$,$C$,110,2,2,200,1,14,8,,25,3,1,0\mathrm{.}75,34\mathrm{.}384843$

Apple$\_$Cinnamon$\_$Cheerios,G$,$C$,110,2,2,180,1\mathrm{.}5,10\mathrm{.}5,10,70,25,1,1,0\mathrm{.}75,29\mathrm{.}509541$

Apple$\_$Jacks,K$,$C$,110,2,0,125,1,11,14,30,25,2,1,1,33\mathrm{.}174094$

Basic$\_4,$G$,$C$,130,3,2,210,2,18,8,100,25,3,1\mathrm{.}33,0\mathrm{.}75,37\mathrm{.}038562$

Bran$\_$Chex,R$,$C$,90,2,1,200,4,15,6,125,25,1,1,0\mathrm{.}67,49\mathrm{.}120253$

Bran$\_$Flakes,P$,$C$,90,3,0,210,5,13,5,190,25,3,1,0\mathrm{.}67,53\mathrm{.}313813$

Cap'n'Crunch,Q$,$C$,120,1,2,220,0,12,12,35,25,2,1,0\mathrm{.}75,18\mathrm{.}042851$

Cheerios,G$,$C$,110,6,2,290,2,17,1,105,25,1,1,1\mathrm{.}25,50\mathrm{.}764999$

Cinnamon$\_$Toast$\_$Crunch,G$,$C$,120,1,3,210,0,13,9,45,25,2,1,0\mathrm{.}75,19\mathrm{.}823573$

Clusters,G$,$C$,110,3,2,140,2,13,7,105,25,3,1,0\mathrm{.}5,40\mathrm{.}400208$

Cocoa$\_$Puffs,G$,$C$,110,1,1,180,0,12,13,55,25,2,1,1,22\mathrm{.}736446$

Corn$\_$Chex,R$,$C$,110,2,0,280,0,22,3,25,25,1,1,1,41\mathrm{.}445019$

Corn$\_$Flakes,K$,$C$,100,2,0,290,1,21,2,35,25,1,1,1,45\mathrm{.}863324$

Corn$\_$Pops,K$,$C$,110,1,0,90,1,13,12,20,25,2,1,1,35\mathrm{.}782791$

Count$\_$Chocula,G$,$C$,110,1,1,180,0,12,13,65,25,2,1,1,22\mathrm{.}396513$

Cracklin'$\_$Oat$\_$Bran,K$,$C$,110,3,3,140,4,10,7,160,25,3,1,0\mathrm{.}5,40\mathrm{.}448772$

Cream$\_$of$\_$Wheat$\_($Quick$),$N$,$H$,100,3,0,80,1,21,0,,0,2,1,1,64\mathrm{.}533816$

Crispix,K$,$C$,110,2,0,220,1,21,3,30,25,3,1,1,46\mathrm{.}895644$

Crispy$\_$Wheat$\_$&$\_$Raisins,G$,$C$,100,2,1,140,2,11,10,120,25,3,1,0\mathrm{.}75,36\mathrm{.}176196$

Double$\_$Chex,R$,$C$,100,2,0,190,1,18,5,80,25,3,1,0\mathrm{.}75,44\mathrm{.}330856$

Froot$\_$Loops,K$,$C$,110,2,1,125,1,11,13,30,25,2,1,1,32\mathrm{.}207582$

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