55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
|
from flask import Flask, render_template
|
||
|
|
import pandas as pd
|
||
|
|
from scipy.cluster.hierarchy import linkage, fcluster
|
||
|
|
import seaborn as sns
|
||
|
|
from sklearn.preprocessing import LabelEncoder
|
||
|
|
import io
|
||
|
|
import base64
|
||
|
|
|
||
|
|
app = Flask(__name__)
|
||
|
|
|
||
|
|
# Load data from student-mat.csv
|
||
|
|
data = pd.read_csv('student-mat.csv')
|
||
|
|
|
||
|
|
def generate_clusters_image():
|
||
|
|
# Selecting columns of interest for clustering
|
||
|
|
features = data[['Pstatus', 'guardian', 'internet', 'romantic', 'famrel', 'freetime', 'goout', 'Dalc', 'Walc', 'health', 'absences']]
|
||
|
|
|
||
|
|
# Convert categorical variables to numerical using LabelEncoder
|
||
|
|
label_encoder = LabelEncoder()
|
||
|
|
features_categorical = features.select_dtypes(include='object')
|
||
|
|
features[features_categorical.columns] = features_categorical.apply(label_encoder.fit_transform)
|
||
|
|
|
||
|
|
# Calculate linkage matrix
|
||
|
|
linkage_matrix = linkage(features, method='ward')
|
||
|
|
|
||
|
|
# Cut the tree to form clusters
|
||
|
|
data['cluster'] = fcluster(linkage_matrix, 3, criterion='maxclust') # You can adjust the number of clusters
|
||
|
|
|
||
|
|
# Drop the 'cluster' column to avoid confusion in sns.clustermap
|
||
|
|
features_for_heatmap = features.copy() # Make a copy to avoid modifying the original DataFrame
|
||
|
|
features_for_heatmap['cluster'] = data['cluster']
|
||
|
|
features_for_heatmap = features_for_heatmap.drop('cluster', axis=1)
|
||
|
|
|
||
|
|
# Visualize clusters
|
||
|
|
sns.set(style='white')
|
||
|
|
g = sns.clustermap(features_for_heatmap, col_cluster=False, figsize=(24, 16), cmap="viridis")
|
||
|
|
|
||
|
|
# Save the image to a buffer
|
||
|
|
img_buffer = io.BytesIO()
|
||
|
|
g.savefig(img_buffer, format='png')
|
||
|
|
img_buffer.seek(0)
|
||
|
|
|
||
|
|
# Convert the image to a base64 string
|
||
|
|
img_base64 = base64.b64encode(img_buffer.read()).decode()
|
||
|
|
|
||
|
|
return img_base64
|
||
|
|
|
||
|
|
@app.route('/')
|
||
|
|
def index():
|
||
|
|
clusters_image = generate_clusters_image()
|
||
|
|
return render_template('index.html', clusters_image=clusters_image)
|
||
|
|
|
||
|
|
if __name__ == '__main__':
|
||
|
|
app.run(port=5000)
|