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RatanPrakash
Refactor code to replace 'preprocessor' with 'helper' for improved organization and clarity
137c7fb
| import streamlit as st | |
| import helper | |
| import matplotlib.pyplot as plt | |
| st.sidebar.title('Whatsapp Chat Analyzer') | |
| st.sidebar.write('Upload your whatsapp chat file to analyze the chat') | |
| st.sidebar.write('The chat file should be a .txt file exported from whatsapp') | |
| uploaded_file = st.sidebar.file_uploader('Choose a file') | |
| if uploaded_file is not None: | |
| chat_data = uploaded_file.getvalue().decode('utf-8') | |
| df = helper.preprocess_data(chat_data) | |
| # st.write(df) | |
| #unique users dropdown menu to select user | |
| unique_users = df['user'].unique() | |
| unique_users = list(unique_users) | |
| unique_users.sort() | |
| unique_users.insert(0, 'All') | |
| selected_user = st.sidebar.selectbox('Select a user', unique_users) | |
| st.sidebar.write(selected_user) | |
| #fetch stats | |
| user_df, total_messages, media_messages, links, emojis, total_words = helper.fetch_stats(selected_user, df) | |
| st.title(f'User: {selected_user}') | |
| # st.write(user_df) | |
| #display below data side by side | |
| col1, col2, col3 = st.columns(3) | |
| with col1: | |
| st.write('Total messages:', total_messages) | |
| st.write('Media messages:', media_messages) | |
| with col2: | |
| st.write('Links shared:', links) | |
| st.write('Emojis shared:', emojis) | |
| with col3: | |
| st.write('Total words:', total_words) | |
| #busiest users (users with most messages) | |
| with st.expander('Busiest users'): | |
| if selected_user == 'All': | |
| busiest_users, plot = helper.busiest_users(df) | |
| st.write('Busiest users:') | |
| st.write(busiest_users) | |
| st.pyplot(plot) | |
| with st.expander('View word cloud and most common words'): | |
| st.pyplot(helper.word_cloud(df, selected_user)) | |
| st.write('Most common words') | |
| temp_df, plot = helper.most_common_words(selected_user, df) | |
| st.write(temp_df) | |
| st.pyplot(plot) | |
| st.write("Most common emojis") | |
| temp_df = helper.most_common_emojis(selected_user, df) | |
| st.write(temp_df) | |
| with st.expander("Activity over time"): | |
| col1, col2 = st.columns(2) | |
| with col1: #left | |
| _, plot = helper.daily_timeline(selected_user, df) | |
| st.pyplot(plot) | |
| _, plot = helper.weekday_activity_map(selected_user, df) | |
| st.pyplot(plot) | |
| with col2: #right | |
| _, plot = helper.monthly_timeline(selected_user, df) | |
| st.pyplot(plot) | |
| _, plot = helper.month_activity_map(selected_user, df) | |
| st.pyplot(plot) | |
| st.write("Messages sent by hour") | |
| _, plot = helper.hour_activity_map(selected_user, df) | |
| st.pyplot(plot) | |
| st.write("weekly heatmap") | |
| plot = helper.activity_heatmap(selected_user, df) | |
| st.pyplot(plot) | |
| with st.expander("Links shared"): | |
| temp_df = helper.extract_links(df) | |
| st.write(temp_df) | |
| common_domains, plot = helper.plot_common_domains(df) | |
| st.pyplot(plot) | |
| st.write("Most common domains") | |
| st.write(common_domains) | |