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app.py
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app.py
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import streamlit as st
import preprocessor, helper #local file func
import matplotlib.pyplot as plt
import seaborn as sns
st.sidebar.title("WhatsApp Chat Analyzer")
#create a file uploaded to upload txt file
uploaded_file = st.sidebar.file_uploader("Choose a file")
if uploaded_file is not None:
bytes_data = uploaded_file.getvalue()
#convert byte to string
data = bytes_data.decode("utf-8")
#call the preprocess func to give df
df = preprocessor.preprocess(data)
#provide an option to analyze data on group level or specific user
#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)
#button to analyze chat
if(st.sidebar.button("Show Analysis")):
#Display basic stats in 4 cols
num_messages, words, num_media_messages, num_links = helper.fetch_stats(selected_user,df)
col1, col2, col3, col4 = st.columns(4)
with col1:
st.header(":blue[Total Messages]")
st.title(num_messages)
with col2:
st.header(":blue[Total Words]")
st.title(words)
with col3:
st.header(":blue[Media Shared]")
st.title(num_media_messages)
with col4:
st.header(":blue[Links Shared]")
st.title(num_links)
#Monthly timeline
st.title(":blue[Monthly Chat 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(":blue[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(':blue[Activity Map]')
col1,col2 = st.columns(2)
#weekly activity
with col1:
st.header(":green[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)
#monthly activity
with col2:
st.header(":green[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)
#time activity
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(':blue[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 (Top Frequent words)
st.title(":blue[Wordcloud]")
df_wc = helper.create_wordcloud(selected_user,df)
fig,ax = plt.subplots()
ax.imshow(df_wc)
st.pyplot(fig)
# most common words
st.title(':blue[Most commmon 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.pyplot(fig)
# emoji analysis
st.title(":blue[Emoji Analysis]")
emoji_df = helper.emoji_helper(selected_user,df)
if emoji_df.shape[0] > 0:
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)
else:
st.write(":red[No Emojis Send by this user]")