dbscan

frontend/pages/clustering:_kmeans.py

@@ -18,18 +18,18 @@ if "data" in st.session_state:
         max_iter = row1[0].number_input("max_iter",step=1,min_value=1)
 
 
-        st.form_submit_button('launch')
+        st.form_submit_button("launch")
 
     if len(data_name) == 2:
         x = data[data_name].to_numpy()
 
-        kmeans = KMeans(n_clusters=n_clusters, init='random', n_init=n_init, max_iter=max_iter, random_state=111)
+        kmeans = KMeans(n_clusters=n_clusters, init="random", n_init=n_init, max_iter=max_iter, random_state=111)
         y_kmeans = kmeans.fit_predict(x)
 
         fig, ax = plt.subplots(figsize=(12,8))
-        plt.scatter(x[:, 0], x[:, 1], c=y_kmeans, s=50, cmap='viridis')
+        plt.scatter(x[:, 0], x[:, 1], c=y_kmeans, s=50, cmap="viridis")
         centers = kmeans.cluster_centers_
-        plt.scatter(centers[:, 0], centers[:, 1], c='black', s=200, marker='X')
+        plt.scatter(centers[:, 0], centers[:, 1], c="black", s=200, marker="X")
         st.pyplot(fig)
 
 else: