Upload streamlit_app.py

src/streamlit_app.py

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+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()
+    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)
+
+
+