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| import streamlit as st | |
| import pandas as pd | |
| 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') | |
| 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() | |