Update app.py

app.py

@@ -4,77 +4,57 @@ import seaborn as sns
 import matplotlib.pyplot as plt
 from dataset_import import load_data
 from data_cleaning import clean_data
-from YTCommentScraper import get_transcript, summarize_with_langchain_and_openai
 
 st.title("AnalyzeYT Dataset Analysis")
 
-# Option to extract YouTube comments
-extract_comments = st.radio("Do you want to extract comments from a YouTube video?", ("No", "Yes"))
-
-if extract_comments == "Yes":
-    openai_api_key = st.text_input("Enter your OpenAI API Key:", type='password')
-    video_id = st.text_input("Enter the YouTube Video ID:")
-
-    if st.button('Extract and Summarize Comments'):
-        if openai_api_key and video_id:
-            try:
-                transcript, language_code = get_transcript(video_id)
-                summary = summarize_with_langchain_and_openai(transcript, language_code, openai_api_key)
-                st.write("Summary of YouTube Comments:")
-                st.markdown(summary)
-            except Exception as e:
-                st.write(str(e))
-        else:
-            st.write("Please enter both your OpenAI API Key and YouTube Video ID.")
-else:
-    # Proceed with normal data analysis
-    data = load_data()
-
-    if data is not None:
-        st.write("Loaded Data Preview:")
-        st.write(data.head())
-        
-        # Clean data
-        data = clean_data(data)
-        
-        st.write("Cleaned Data Preview:")
-        st.write(data.head())
-        
-        # Show data description of cleaned data
-        st.write("Cleaned Data Description:")
-        st.write(data.describe())
-
-        # Add correlation matrix for cleaned data
-        st.write("Correlation Matrix of Cleaned Data:")
-        corr = data.corr()
-        st.write(corr)
-        sns.heatmap(corr, annot=True, cmap='coolwarm')
+# Load dataset
+data = load_data()
+
+if data is not None:
+    st.write("Loaded Data Preview:")
+    st.write(data.head())
+    
+    # Clean data
+    data = clean_data(data)
+    
+    st.write("Cleaned Data Preview:")
+    st.write(data.head())
+    
+    # Show data description of cleaned data
+    st.write("Cleaned Data Description:")
+    st.write(data.describe())
+
+    # Add correlation matrix for cleaned data
+    st.write("Correlation Matrix of Cleaned Data:")
+    corr = data.corr()
+    st.write(corr)
+    sns.heatmap(corr, annot=True, cmap='coolwarm')
+    st.pyplot()
+
+    # Data visualization options for cleaned data
+    st.write("Data Visualization on Cleaned Data:")
+    chart_type = st.selectbox("Select Chart Type", ['Line Chart', 'Bar Chart', 'Histogram'])
+
+    if chart_type == 'Line Chart':
+        x_axis = st.selectbox("Select X-axis Column", data.columns)
+        y_axis = st.selectbox("Select Y-axis Column", data.columns)
+        title = st.text_input("Enter Chart Title", "Line Chart")
+        st.line_chart(data[[x_axis, y_axis]])
+        st.write(f"Line Chart: {title}")
+
+    elif chart_type == 'Bar Chart':
+        x_axis = st.selectbox("Select X-axis Column", data.columns)
+        y_axis = st.selectbox("Select Y-axis Column", data.columns)
+        title = st.text_input("Enter Chart Title", "Bar Chart")
+        st.bar_chart(data[[x_axis, y_axis]])
+        st.write(f"Bar Chart: {title}")
+
+    elif chart_type == 'Histogram':
+        selected_column = st.selectbox("Select Column for Histogram", data.columns)
+        bins = st.slider("Number of Bins", min_value=10, max_value=100, value=30)
+        title = st.text_input("Enter Chart Title", "Histogram")
+        plt.hist(data[selected_column], bins=bins)
+        plt.title(title)
+        plt.xlabel(selected_column)
+        plt.ylabel('Frequency')
         st.pyplot()
-
-        # Data visualization options for cleaned data
-        st.write("Data Visualization on Cleaned Data:")
-        chart_type = st.selectbox("Select Chart Type", ['Line Chart', 'Bar Chart', 'Histogram'])
-
-        if chart_type == 'Line Chart':
-            x_axis = st.selectbox("Select X-axis Column", data.columns)
-            y_axis = st.selectbox("Select Y-axis Column", data.columns)
-            title = st.text_input("Enter Chart Title", "Line Chart")
-            st.line_chart(data[[x_axis, y_axis]])
-            st.write(f"Line Chart: {title}")
-
-        elif chart_type == 'Bar Chart':
-            x_axis = st.selectbox("Select X-axis Column", data.columns)
-            y_axis = st.selectbox("Select Y-axis Column", data.columns)
-            title = st.text_input("Enter Chart Title", "Bar Chart")
-            st.bar_chart(data[[x_axis, y_axis]])
-            st.write(f"Bar Chart: {title}")
-
-        elif chart_type == 'Histogram':
-            selected_column = st.selectbox("Select Column for Histogram", data.columns)
-            bins = st.slider("Number of Bins", min_value=10, max_value=100, value=30)
-            title = st.text_input("Enter Chart Title", "Histogram")
-            plt.hist(data[selected_column], bins=bins)
-            plt.title(title)
-            plt.xlabel(selected_column)
-            plt.ylabel('Frequency')
-            st.pyplot()