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app.py
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app.py
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import streamlit as st
import preprocessor,helper
import matplotlib.pyplot as plt
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"):
#stats_Area
num_messages,words,num_media_messages,deleted_messages,num_links = helper.fetch_stats(selected_user,df)
st.title("Top Statistics")
col1, col2, col3, col4, col5 = st.columns(5)
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("Deleted Messages")
st.title(deleted_messages)
with col5:
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 = "#644685")
plt.tick_params(axis='both', which='both', bottom=False, top=False, left=False, right=False)
for spine in plt.gca().spines.values():
spine.set_visible(False)
plt.xticks(rotation=90)
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["date"], daily_timeline["message"],color = "#644685")
plt.tick_params(axis='both', which='both', bottom=False, top=False, left=False, right=False)
for spine in plt.gca().spines.values():
spine.set_visible(False)
plt.xticks(rotation = 90)
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 = "#644685")
plt.tick_params(axis='both', which='both', bottom=False, top=False, left=False, right=False)
for spine in plt.gca().spines.values():
spine.set_visible(False)
plt.xticks(rotation = 80)
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 = "#8d6db0")
plt.tick_params(axis='both', which='both', bottom=False, top=False, left=False, right=False)
for spine in plt.gca().spines.values():
spine.set_visible(False)
plt.xticks(rotation = 80)
st.pyplot(fig)
# finding the busienst user in the group (Group Level)
if selected_user == "Overall":
st.title("Most Busy User")
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 = "#43234e")
plt.tick_params(axis='both', which='both', bottom=False, top=False, left=False, right=False)
for spine in plt.gca().spines.values():
spine.set_visible(False)
plt.xticks(rotation = 80)
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()
plt.tick_params(axis='both', which='both', bottom=False, top=False, left=False, right=False)
for spine in plt.gca().spines.values():
spine.set_visible(False)
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],color = "#43234e")
plt.xticks(rotation=90)
plt.tick_params(axis='both', which='both', bottom=False, top=False, left=False, right=False)
for spine in plt.gca().spines.values():
spine.set_visible(False)
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][0:5], labels = emoji_df[0][0:5],autopct ="%.1f%%")
# st.pyplot(fig)