import streamlit as st
import preprocessor,helper
import matplotlib.pyplot as plt

st.markdown(
    "<h1 style='text-align: center;'>Chat Analysis Space</h1>",
    unsafe_allow_html=True
    )

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 uniquw users
    user_list = df["user"].unique().tolist()
    if "group_notification" in user_list:
        user_list.remove("group_notification")
    user_list.sort()
    user_list.insert(0, "Overall")
    # 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_messages,links=helper.fetch_stats(selected_user,df)
        st.title("Top Statistics")
        col1, col2, col3, col4 = st.columns(4)
        
        with col1:
            st.header("Total Message")
            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(links)    

        if selected_user=="overall":    
            col1,col2=st.beta_columns(2)  
        
        # 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
        st.title("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)



        # finding the busiest users in the group(Group level)
        if selected_user == 'Overall':
            st.title('Most Busy Users')

            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='red')
                #ax.set_xlabel('Users')
                #ax.set_ylabel('Message Count')
                #ax.set_title('Top 5 Most Active Users')
                plt.xticks(rotation='vertical')
                st.pyplot(fig)

            with col2:
                st.dataframe(new_df)

       # WordCloud
        st.title("Wordcloud")
        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 commmon 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)