app.py

import streamlit as st
import preprocessor
import helper
import matplotlib.pyplot as plt
import seaborn as sns

st.sidebar.title("Whatsapp Chat Analyzer")

uploaded_file = st.sidebar.file_uploader("Choose a file")
if uploaded_file is not None:
    bytes_data = uploaded_file.getvalue()
    data = bytes_data.decode("utf-8")
    
    try:
        df = preprocessor.preprocess(data)
    except Exception as e:
        st.error(f"An error occurred during preprocessing: {e}")
        df = None

    if df is not None:
        st.dataframe(df)

        # Ensure 'User' column exists in the DataFrame
        if 'User' in df.columns:
            # Fetch unique users
            user_list = df['User'].unique().tolist()
            user_list.sort()
            user_list.insert(0, "Overall")
            selected_user = st.sidebar.selectbox("Show Analysis w.r.t", user_list)

            if st.sidebar.button("Show Analysis"):
                # Stats Area
                try:
                    num_messages, words, num_media_messages, num_links = helper.fetch_stats(selected_user, df)
                except Exception as e:
                    st.error(f"An error occurred while fetching stats: {e}")
                    num_messages, words, num_media_messages, num_links = 0, 0, 0, 0
                
                col1, col2, col3, col4 = st.columns(4)

                with col1:
                    st.header("Total Messages")
                    st.title(num_messages)
                with col2:
                    st.header("Total Words")
                    st.title(words)
                with col3:
                    st.header("Media Shared")
                    st.title(num_media_messages)
                with col4:
                    st.header("Links Shared")
                    st.title(num_links)

                #monthly timeline
                st.title("Monthly Timeline")
                timeline = helper.monthly_timeline(selected_user,df)
                fig,ax = plt.subplots()
                ax.plot(timeline['time'], timeline['message'], color='green')
                plt.xticks(rotation='vertical')
                st.pyplot(fig)

                # daily timeline
                daily_timeline = helper.daily_timeline(selected_user, df)
                fig, ax = plt.subplots()
                ax.plot(daily_timeline['only_date'], daily_timeline['message'], color='black')
                plt.xticks(rotation='vertical')
                st.pyplot(fig)

                # activity map
                st.title('Activity Map')
                col1,col2 = st.columns(2)

                with col1:
                    st.header("Most busy day")
                    busy_day = helper.week_activity_map(selected_user, df)
                    fig, ax = plt.subplots()
                    ax.bar(busy_day.index, busy_day.values, color='purple')
                    plt.xticks(rotation='vertical')
                    st.pyplot(fig)

                with col2:
                    st.header("Most busy month")
                    busy_month = helper.month_activity_map(selected_user, df)
                    fig, ax = plt.subplots()
                    ax.bar(busy_month.index, busy_month.values, color='orange')
                    plt.xticks(rotation='vertical')
                    st.pyplot(fig)

                    #weekly activity map
                    st.title("Weekly Activity Map")
                    user_heatmap = helper.activity_heatmap(selected_user, df)
                    fig, ax = plt.subplots()
                    ax = sns.heatmap(user_heatmap, cmap="YlGnBu")
                    st.pyplot(fig)

                # Finding the busiest users in the group (Group level)
                if selected_user == 'Overall':
                    st.title('Most Busy Users')
                    try:
                        x, new_df = helper.most_busy_users(df)
                        fig, ax = plt.subplots()

                        col1, col2 = st.columns(2)

                        with col1:
                            ax.bar(x.index, x.values, color='#33617d')
                            plt.xticks(rotation='vertical')
                            st.pyplot(fig)
                        with col2:
                            st.dataframe(new_df)
                    except Exception as e:
                        st.error(f"An error occurred during busiest users analysis: {e}")

                

                # Word Cloud
                st.title("WordCloud")
                try:
                    df_wc = helper.create_wordcloud(selected_user, df)
                    fig, ax = plt.subplots()
                    ax.imshow(df_wc)
                    st.pyplot(fig)
                except Exception as e:
                    st.error(f"An error occurred during word cloud creation: {e}")

                # Most common words
                try:
                    most_common_df = helper.most_common_words(selected_user, df)
                    fig, ax = plt.subplots()
                    ax.barh(most_common_df[0], most_common_df[1])
                    plt.xticks(rotation='vertical')
                    st.title('Most common words')
                    st.pyplot(fig)
                except Exception as e:
                    st.error(f"An error occurred during most common words analysis: {e}")

                # Emoji analysis
                st.title("Emoji Analysis")
                try:
                    emoji_df = helper.emoji_helper(selected_user, df)
                    col1, col2 = st.columns(2)

                    with col1:
                        st.dataframe(emoji_df)
                    with col2:
                        fig, ax = plt.subplots()
                        ax.pie(emoji_df[1].head(), labels=emoji_df[0].head(), autopct="%0.2f")
                        st.pyplot(fig)
                except Exception as e:
                    st.error(f"An error occurred during emoji analysis: {e}")