Delete apps.py

apps.py

@@ -1,140 +0,0 @@
-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)
-
-    # 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"):
-
-        # 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
-        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,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')
-                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)
-
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