The project aims to see the mean value of Pokemon attack and defense and also plot a graph between attack and defense
Step: 1
First, we will import the necessary libraries then we upload the dataset
import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt
P = pd.read_csv('Pokemon_A.csv') P
P.info()
Step: 2
Now we see agglomeration values
Q=P[['Attack','Defence']]
def doAgglomerative(X, nclust=2): Model = AgglomerativeClustering(n_clusters=nclust,affinity='euclidean',linkage='ward') Clust_Labels = Model.fit_predict(X) return (Clust_Labels) Clust_Labels = doAgglomerative(Q,20) agglomerative = pd.DataFrame(Clust_Labels) Q.insert((Q.shape[1]),'agglomerative',agglomerative)
T=Q T['Name']=P['Name'] T
for i in range(20): names0=T[T['agglomerative']==i]['Name'] print('[ Agglomerative '+str(i)+' ]') print(list(set(names0))) print()
Step: 3
Now we calculate the mean value of
Q.groupby('agglomerative').mean()
Step: 4
Now we plot a graph of Agglomerative Clustering between Attack and Defenses
fig = plt.figure() ax = fig.add_subplot(111) scatter = ax.scatter(Q['Attack'],Q['Defence'],c=agglomerative[0],s=50) ax.set_title('Agglomerative Clustering') ax.set_xlabel('Attack') ax.set_ylabel('Defence') plt.rcParams['figure.figsize'] = (6,5) plt.colorbar(scatter)
Submitted by Sudipta Ghosh (Sudipta609)
Download packets of source code on Coders Packet
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