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")
    df=preprocessor.preprocess(data)


    # fetch unique users
    user_list=df['user'].unique().tolist()
    user_list.sort()
    user_list.insert(0,"Overall")

    selected_user=st.sidebar.selectbox("Show analysis wrt",user_list)

    if st.sidebar.button("Show Analysis"):
        num_messages,num_words,num_media,num_link=helper.fetch_stats(selected_user,df)
        st.title("Top Statistics")
        col1,col2,col3,col4=st.columns(4)

        with col1:
            st.header("Total Mesages")
            st.title(num_messages)
        with col2:
            st.header("Total Word")
            st.title(num_words)
        with col3:
            st.header("Media Files")
            st.title(num_media)
        with col4:
            st.header("Links Shared")
            st.title(num_link)


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


        # activity map
        st.title("Daily timeline")
        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)
            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)
            plt.xticks(rotation='vertical')
            st.pyplot(fig)

        st.title("Weekly Activity Map")
        user_heatmap = helper.activity_heatmap(selected_user,df)
        fig,ax = plt.subplots()
        ax = sns.heatmap(user_heatmap)
        st.pyplot(fig)

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

            col1,col2=st.columns(2)

            with col1:
                ax.bar(x.index, x.values)
                plt.xticks(rotation='vertical')
                st.pyplot(fig)

            with col2:
                st.dataframe(new_df)

        # WordCloud
        st.title("Word Cloud")
        df_wc=helper.create_wordcloud(selected_user,df)
        fig,ax=plt.subplots()
        ax.imshow(df_wc)
        st.pyplot(fig)

        # most common words
        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)

        # emoji analysis
        emoji_df = helper.emoji_helper(selected_user, df)
        st.title("Emoji Analysis")

        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)