app.py

import streamlit as st
import preprocess, helper
import matplotlib.pyplot as plt
import seaborn as sns
st.sidebar.title("Whats App 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=preprocess.preprocess(data)
    st.dataframe(df)

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

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

    if st.sidebar.button('Show Analysis'):

        #Stats Area
        num_messages, words , num_media_messages,num_links = helper.fetch_stats(selected_user,df)
        st.title("Top Statistics")
        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

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

        #Daily Timeline

        daily_timeline= helper.daily_timeline(selected_user, df)
        fig, ax = plt.subplots()
        st.title("Daily Timeline")
        ax.plot(daily_timeline['date'], daily_timeline['messages'],color='black')
        plt.xticks(rotation='vertical')
        st.pyplot(fig)

        #Activity Map
        st.title("Activity Map")
        col1,col2=st.columns(2)
        with col1:
            st.header("Mosy Busy Day")
            busy_day=helper.week_activity_map(selected_user, df)
            fig,ax=plt.subplots()
            ax.bar(busy_day.index,busy_day.values)
            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)

        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 user in the group(Group Level)
        if selected_user=="Overall":
            st.title("Most Busy Users")
            x,new_df=helper.most_busy_user(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)