Create app.py

app.py

@@ -0,0 +1,126 @@
+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 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)