Data Preprocessing task:

Please examine the data shape etc. Check for missing values and remove, if any. Drop the categorical

variables and scale the data.

Clustering Task:

Apply hierarchical clustering to the data using Euclidean distance to the normalized measurements.

Compare the dendrograms from single linkage and complete linkage. Choose the better method and

make clusters. Examine cluster profiles $($centroids$).$

$($Hint$\_$: To obtain cluster centroids for hierarchical clustering, compute the average values of each cluster

members, using groupby$()$ with the cluster centers followed by mean:

dataframe.groupby$($clusterlabel$).$mean$().)$

Question $1$:

How many clusters would you use? What distance is used for this cutoff?

Question $2$: The elementary public schools would like to choose a set of cereals to include in their

daily cafeterias. Every day a different cereal is offered, but all cereals should support a healthy diet.

For this goal, you are requested to find a cluster of "healthy cereals."

$$ Make clusters on the basis of your answer to Q $1$

$$ Make cluster profiles

$$ Choose the cluster that has the healthiest cereals for children $($in your opinion$),$ based on the

level of ingredients.

Incorporate your answers in the Jupyter notebook, using Markdown cells.

Run the Jupyter notebook from start to finish, save in HTML format and submit in

assignments space