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$).$