Update app.py

app.py

@@ -175,54 +175,6 @@ if st.session_state.df is None:
             except Exception as e:
                 st.error(f"Error loading the file: {e}")
 
-    # Select
-    elif uploading_way == "select":
-                selected = st.selectbox("Select Dataset", ["Select", "Titanic Dataset","Iris Dataset", "Wine Dataset", 
-                                    "Diabetes Dataset", "Digits Dataset", 
-                                    "Olivetti Faces Dataset", "California Housing Dataset", 
-                                    "Covid-19 Dataset"])
-        
-
-                if selected == "Iris Dataset":
-                    from sklearn.datasets import load_iris
-                    iris = load_iris()
-                    df = pd.DataFrame(iris.data, columns=iris.feature_names)
-                    df['target'] = iris.target
-                    st.session_state.df = df
-
-                elif selected == "Wine Dataset":
-                    from sklearn.datasets import load_wine
-                    wine = load_wine()
-                    df = pd.DataFrame(wine.data, columns=wine.feature_names)
-                    df['target'] = wine.target
-                    st.session_state.df = df
-
-
-                elif selected == "Digits Dataset":
-                    from sklearn.datasets import load_digits
-                    digits = load_digits()
-                    df = pd.DataFrame(digits.data, columns=digits.feature_names)
-                    df['target'] = digits.target
-                    st.session_state.df = df
-
-                elif selected == "Olivetti Faces Dataset":
-                    from sklearn.datasets import fetch_olivetti_faces
-                    olivetti = fetch_olivetti_faces()
-                    df = pd.DataFrame(olivetti.data)
-                    df['target'] = olivetti.target
-                    st.session_state.df = df
-
-                elif selected == "California Housing Dataset":
-                    from sklearn.datasets import fetch_california_housing
-                    california = fetch_california_housing()
-                    df = pd.DataFrame(california.data, columns=california.feature_names)
-                    df['target'] = california.target
-                    st.session_state.df = df
-
-                elif selected == "Covid-19 Dataset":
-                    df = load_data("https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/owid-covid-data.csv")
-                    st.session_state.df = df
-
     # URL
     elif uploading_way == "url":
         url = st.text_input("Enter URL")
@@ -530,21 +482,17 @@ df.drop(columns={col_to_delete}, inplace=True)
         new_line()
         if st.checkbox("Show Word Cloud", value=False):
             text_col = st.selectbox("Select Text Column for Word Cloud", options=df.select_dtypes(include=[np.object]).columns.tolist())
-            text_data = ' '.join(df[text_col].dropna())
-            wordcloud = WordCloud(width=800, height=400).generate(text_data)
-            fig, ax = plt.subplots()
-            ax.imshow(wordcloud, interpolation='bilinear')
-            ax.axis('off')
-            st.pyplot(fig)
-            new_line()
+            text_data = ' '.join(df[text_col].dropna()).strip()  # Collect and strip the text data
+        
+            if text_data:  # Check if there is any text data
+                wordcloud = WordCloud(width=800, height=400).generate(text_data)
+                fig, ax = plt.subplots()
+                ax.imshow(wordcloud, interpolation='bilinear')
+                ax.axis('off')
+                st.pyplot(fig)
+            else:
+                st.write("No words available to create a word cloud.")
 
-        new_line()
-        if st.checkbox("Show Text Statistics", value=False):
-            text_col = st.selectbox("Select Text Column for Statistics", options=df.select_dtypes(include=[np.object]).columns.tolist())
-            text_stats = df[text_col].dropna().apply(lambda x: {'length': len(x), 'word_count': len(x.split())})
-            text_stats_df = pd.DataFrame(list(text_stats))
-            st.write(text_stats_df.describe())
-            new_line()
 
 
         new_line()