app.py

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

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

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)
    st.dataframe(df)

    #  fetch multiple users
    user_list = df['user'].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"):
        num_messages, words, num_media_msg, 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_msg)

        with col4:
            st.header('Links shared')
            st.title(num_links)

        # finding the busiest user in the group
        if selected_user == 'Overall':
            st.title('Most Busy User')
            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, color='red')
                plt.xticks(rotation='vertical')
                st.pyplot(fig)
            with col2:
                st.dataframe(new_df)

        # wordcloud
        st.title("Most Common Words")
        df_wc = helper.create_wordcloud(selected_user, df)
        fig, ax = plt.subplots()
        ax.imshow(df_wc)
        st.pyplot(fig)

        # emoji analysis
        st.title("Emoji Analysis")
        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="%.2f")
            st.pyplot(fig)

        # 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("Activity Map")
        col1, col2 = st.columns(2)

        with col1:
            st.title('Most Busy Day')
            busy_day = helper.week_activity_map(selected_user, df)
            fig, ax = plt.subplots()
            ax.plot(busy_day.index, busy_day.values, color='blue')
            plt.xticks(rotation='vertical')
            st.pyplot(fig)

        with col2:
            st.title('Most Busy MONTH')
            busy_month = helper.month_activity_map(selected_user, df)
            fig, ax = plt.subplots()
            ax.plot(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)