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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)
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