import streamlit as st import preprocessor, 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) #st.dataframe(df) # fetch unique 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, num_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(num_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 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) 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(Group level) if selected_user == 'Overall': st.title('Most Busy Users') x, user_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') plt.xticks(rotation='vertical') st.pyplot(fig) with col2: st.dataframe(user_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)