From eff6e52c3deca24c9e261407286c6d03ed604366 Mon Sep 17 00:00:00 2001 From: halcyon-past Date: Sun, 6 Oct 2024 10:26:30 +0530 Subject: [PATCH 1/2] Added Whatsapp Chat Analyzer --- Data_Science/Whatsapp_Chat_Analyzer/README.md | 76 +++++ .../images/emoji_distribution.png | Bin 0 -> 64414 bytes .../images/emoji_usage_author.png | Bin 0 -> 33732 bytes .../images/message_distribution.png | Bin 0 -> 64905 bytes .../images/sample_messages.png | Bin 0 -> 238225 bytes .../images/top_days_messages.png | Bin 0 -> 30799 bytes .../images/word_cloud.png | Bin 0 -> 640003 bytes Data_Science/Whatsapp_Chat_Analyzer/main.py | 273 ++++++++++++++++++ 8 files changed, 349 insertions(+) create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/README.md create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/images/emoji_distribution.png create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/images/emoji_usage_author.png create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/images/message_distribution.png create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/images/sample_messages.png create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/images/top_days_messages.png create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/images/word_cloud.png create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/main.py diff --git a/Data_Science/Whatsapp_Chat_Analyzer/README.md b/Data_Science/Whatsapp_Chat_Analyzer/README.md new file mode 100644 index 0000000000..91412bc1ef --- /dev/null +++ b/Data_Science/Whatsapp_Chat_Analyzer/README.md @@ -0,0 +1,76 @@ +## **WhatsApp Chat Analyzer** + +### 🎯 **Goal** + +The main goal of this project is to analyze WhatsApp chat data to derive meaningful insights, such as user engagement, emoji usage, and response patterns. It aims to provide an interactive visualization to explore user activity within a chat. + +### 🧵 **Dataset** + +The dataset is provided by the user in the form of a `.txt` or `.zip` file, which contains WhatsApp chat data exported from the messaging app. + +### 🧾 **Description** + +This project allows users to upload WhatsApp chat files, which are then processed to extract useful information, including message counts, emoji usage, and response times. The data is visualized using interactive charts and plots, enabling easy exploration of user behavior in the chat. + +### 🧮 **What I had done!** + +1. Implemented a file upload feature to allow users to upload WhatsApp chat files (`.txt` or `.zip`). +2. Processed the uploaded chat data to extract relevant information using regular expressions. +3. Extracted details such as date, time, author, message content, and emojis. +4. Analyzed message data to calculate statistics like messages sent, average response time, word count, and emoji usage. +5. Visualized the extracted information using various charts such as pie charts, bar charts, and polar plots. +6. Generated a word cloud of the most frequently used words in the chat. + +### 🚀 **Models Implemented** + +No machine learning models were used in this project. Instead, the focus is on text processing, data analysis, and visualization of chat data. + +### 📚 **Libraries Needed** + +- `streamlit` - For creating the web application. +- `pandas` - For handling and processing data. +- `plotly.express` and `plotly.graph_objs` - For creating interactive visualizations. +- `matplotlib.pyplot` and `seaborn` - For additional plotting and visualization. +- `wordcloud` - For generating a word cloud. +- `nltk` - For stopwords and text processing. +- `emojis` - For extracting emojis from messages. +- `collections.Counter` - For counting occurrences of emojis. +- `numpy` - For numerical operations. +- `requests` - For downloading custom stopwords. +- `re` - For regular expressions. +- `zipfile`, `io` - For handling file uploads in `.zip` format. + +### 📊 **Exploratory Data Analysis Results** + +Below are some visualizations derived from the chat data: + +1. **Basic Information** + ![Sample Messages](images/sample_messages.png) + +2. **Emoji Distribution** + ![Emoji Distribution Pie Chart](images/emoji_distribution.png) + +3. **Emoji Usage by Author** + ![Emoji Usage Bar Chart](images/emoji_usage_author.png) + +4. **Top 10 Days With Most Messages** + ![Messages Bar Chart](images/top_days_messages.png) + +5. **Message Distribution by Day** + ![Messages Polar Chart](images/message_distribution.png) + +6. **Word Cloud** + ![Word Cloud](images/word_cloud.png) + +### 📈 **Performance of the Models based on the Accuracy Scores** + +No machine learning models were used in this project. It is purely focused on data analysis and visualization of WhatsApp chat data. + +### 📢 **Conclusion** + +This project successfully provides an interactive analysis of WhatsApp chat data, including statistics on user engagement, emoji usage, and response times. Users can explore individual and group message patterns, and the visualizations make it easy to understand user behavior. This type of analysis can be helpful for studying group dynamics or understanding communication patterns. + +### ✒️ **Your Signature** + +Created by Aritro Saha - +[Website](https://aritro.tech/) | [GitHub](https://github.com/halcyon-past) | [LinkedIn](https://www.linkedin.com/in/aritro-saha/) \ No newline at end of file diff --git a/Data_Science/Whatsapp_Chat_Analyzer/images/emoji_distribution.png b/Data_Science/Whatsapp_Chat_Analyzer/images/emoji_distribution.png new file mode 100644 index 0000000000000000000000000000000000000000..b14a4deb85584da102bd0ff74648dacde283c99f GIT binary patch literal 64414 zcma&N1yEee7B)IF3^2I6yITkj!GaS!KnM=O-3d0hTL_ZiAp{aUxDQT(Ly+JSEVu-h zw>jtDbMAZfUj46X*D&mY?$xVT_xiqXbw_KcDPWbYnXviMWveUB1m`gWB znODGD)7#DUc8#FP#)QZi9J}vm)2ZjqlM_&egd)#%Z0zn7eKzGtVztUiof&h;bqZD{ozTxq+ zhhKn403TPfH73{mry?9Gt_Fw9to4h~q9uX;`@n_JG(dhSPx_eur-MUbFuG|X!zP@O zRtVC9!%-hMO7nO3=lFRbFCG&EmcRb`kOWeDTdF^Ir{=c$NuLFLd<>_T0#j;iTUGwu 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columns=["emoji", "count"]) + + # Combine date and time into DateTime column + message_df['DateTime'] = pd.to_datetime(message_df['Date'].dt.strftime('%Y-%m-%d') + ' ' + + message_df['Time'] + ' ' + message_df['AM/PM'], format='mixed') + message_df = message_df.sort_values(by='DateTime') + + # Calculate response times + message_df['Response Time'] = pd.NaT + last_message_time = {} + for index, row in message_df.iterrows(): + author, current_time = row['Author'], row['DateTime'] + if author in last_message_time: + last_time = last_message_time[author] + if last_time is not pd.NaT: + message_df.at[index, 'Response Time'] = (current_time - last_time).total_seconds() + last_message_time[author] = current_time + + return df, message_df, emoji_df, emoji_author_df + +# Function to extract text file from zip archive +def extract_text_file(uploaded_file): + """ + Extracts a text file from a zip archive. + + Args: + uploaded_file (UploadedFile): The uploaded zip file + + Returns: + str: Contents of the extracted text file or an error message + """ + try: + zip_file = zipfile.ZipFile(io.BytesIO(uploaded_file.read())) + text_file_name = next((name for name in zip_file.namelist() if name.endswith(".txt")), None) + if text_file_name: + return zip_file.read(text_file_name).decode("utf-8") + else: + return "No text file found in the zip archive." + except Exception as e: + return f"Error occurred: {str(e)}" + +# Main Streamlit app +def main(): + """ + Main function to run the Streamlit app. + """ + st.set_page_config("WhatsApp Chat Analyzer", page_icon="📲", layout="centered") + st.title("Chat Data Visualization") + + # File upload section + uploaded_file = st.file_uploader("Upload a chat file") + + if uploaded_file is not None: + file_extension = uploaded_file.name.split(".")[-1] + if file_extension == "txt": + file_contents = uploaded_file.read().decode("utf-8") + elif file_extension == "zip": + file_contents = extract_text_file(uploaded_file) + else: + st.error("Please upload a .txt or .zip file") + return + + # Process chat data + df, message_df, emoji_df, emoji_author_df = process_chat_file(file_contents) + + # Display basic information + st.header("Basic Information (First 20 Conversations)") + st.write(df.head(20)) + + # Display author stats + st.header("Author Stats") + for author in message_df['Author'].unique(): + req_df = df[df["Author"] == author] + st.subheader(f'Stats of {author}:') + st.write(f'Messages sent: {req_df.shape[0]}') + words_per_message = (np.sum(req_df['Word_count'])) / req_df.shape[0] + st.write(f"Words per message: {words_per_message:.2f}") + emoji_count = sum(req_df['Emoji'].str.len()) + st.write(f'Emojis sent: {emoji_count}') + avg_response_time = round(req_df['Response Time'].mean(), 2) + st.write(f'Average Response Time: {avg_response_time} seconds') + st.write('-----------------------------------') + + # Display emoji distribution + st.header("Emoji Distribution") + fig = px.pie(emoji_df, values='count', names='emoji', title='Emoji Distribution') + fig.update_traces(textposition='inside', textinfo='percent+label') + st.plotly_chart(fig) + + # Display emoji usage by author + st.header("Emoji Usage by Author") + fig = px.bar(emoji_author_df, x=emoji_author_df.index, y=emoji_author_df.columns, + title="Emoji Usage by Author", barmode='stack') + fig.update_layout(xaxis_title="Authors", yaxis_title="Count", legend_title="Emojis") + st.plotly_chart(fig) + + # Display top 10 days with most messages + st.header("Top 10 Days With Most Messages") + messages_per_day = df.groupby(df['DateTime'].dt.date).size().reset_index(name='Messages') + top_days = messages_per_day.sort_values(by='Messages', ascending=False).head(10) + fig = go.Figure(data=[go.Bar( + x=top_days['DateTime'], + y=top_days['Messages'], + marker=dict(color='rgba(58, 71, 80, 0.6)', line=dict(color='rgba(58, 71, 80, 1.0)', width=1.5)), + text=top_days['Messages'] + )]) + fig.update_layout( + title='Top 10 Days with Most Messages', + xaxis=dict(title='Date', tickfont=dict(size=14, color='rgb(107, 107, 107)')), + yaxis=dict(title='Number of Messages', titlefont=dict(size=16, color='rgb(107, 107, 107)')), + bargap=0.1, + bargroupgap=0.1, + paper_bgcolor='rgb(233, 233, 233)', + plot_bgcolor='rgb(233, 233, 233)', + ) + st.plotly_chart(fig) + + # Display message distribution by day + st.header("Message Distribution by Day") + day_df = message_df[["Message", "DateTime"]].copy() + day_df['day_of_week'] = day_df['DateTime'].dt.day_name() + day_df["message_count"] = 1 + day_counts = day_df.groupby("day_of_week").sum().reset_index() + fig = px.line_polar(day_counts, r='message_count', theta='day_of_week', line_close=True) + fig.update_traces(fill='toself') + fig.update_layout(polar=dict(radialaxis=dict(visible=True)), showlegend=False) + st.plotly_chart(fig) + + # Display word cloud + st.header("Word Cloud") + text = " ".join(str(review) for review in message_df.Message) + nltk.download('stopwords', quiet=True) + stopwords = set(nltk.corpus.stopwords.words('english')) + # Add custom stopwords here + stopwords_list = requests.get("https://gist.githubusercontent.com/rg089/35e00abf8941d72d419224cfd5b5925d/raw/12d899b70156fd0041fa9778d657330b024b959c/stopwords.txt").content + stopwords.update(list(set(stopwords_list.decode().splitlines()))) + #Create the Word Cloud + wordcloud = WordCloud(width=800, height=400, random_state=1, background_color='white', colormap='Set2', collocations=False, stopwords=stopwords).generate(text) + fig, ax = plt.subplots(figsize=(10, 5)) + ax.imshow(wordcloud, interpolation='bilinear') + ax.axis("off") + st.pyplot(fig) + + # Display Creator Details + html_temp = """ + + """ + st.markdown(html_temp, unsafe_allow_html=True) + +#driver code +if __name__ == "__main__": + main() \ No newline at end of file From 88a4b2f7e7fbe89a75b406992d6cfc11db8fabd2 Mon Sep 17 00:00:00 2001 From: halcyon-past Date: Sun, 6 Oct 2024 15:56:12 +0530 Subject: [PATCH 2/2] Added Sample Data --- Data_Science/Whatsapp_Chat_Analyzer/README.md | 2 ++ .../Sample_Data/sample_data_1.txt | 22 ++++++++++++++++++ .../Sample_Data/sample_data_2.txt | 15 ++++++++++++ .../Sample_Data/sample_data_3.txt | 16 +++++++++++++ .../Sample_Data/sample_data_4.txt | 13 +++++++++++ .../Sample_Data/sample_data_5.txt | 14 +++++++++++ .../Sample_Data/sample_zipped_data_1.zip | Bin 0 -> 604 bytes .../Sample_Data/sample_zipped_data_2.zip | Bin 0 -> 577 bytes 8 files changed, 82 insertions(+) create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_1.txt create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_2.txt create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_3.txt create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_4.txt create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_5.txt create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_zipped_data_1.zip create mode 100644 Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_zipped_data_2.zip diff --git a/Data_Science/Whatsapp_Chat_Analyzer/README.md b/Data_Science/Whatsapp_Chat_Analyzer/README.md index 91412bc1ef..2e44fb2669 100644 --- a/Data_Science/Whatsapp_Chat_Analyzer/README.md +++ b/Data_Science/Whatsapp_Chat_Analyzer/README.md @@ -8,6 +8,8 @@ The main goal of this project is to analyze WhatsApp chat data to derive meaning The dataset is provided by the user in the form of a `.txt` or `.zip` file, which contains WhatsApp chat data exported from the messaging app. +- Sample data has been provided [HERE](./Sample_Data/) + ### 🧾 **Description** This project allows users to upload WhatsApp chat files, which are then processed to extract useful information, including message counts, emoji usage, and response times. The data is visualized using interactive charts and plots, enabling easy exploration of user behavior in the chat. diff --git a/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_1.txt b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_1.txt new file mode 100644 index 0000000000..bd219ae278 --- /dev/null +++ b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_1.txt @@ -0,0 +1,22 @@ +24/01/24, 12:22 pm - John Doe: Hey there! 🌟 +24/01/24, 12:22 pm - Jane Smith: How’s it going? 😊 +24/01/24, 12:23 pm - John Doe: Just chilling! What about you? 🛋️ +24/01/24, 12:23 pm - Jane Smith: Same here! Watching a movie 🎬 +24/01/24, 12:24 pm - John Doe: Which one? 🍿 +24/01/24, 12:25 pm - Jane Smith: A new action flick! 💥 +24/01/24, 12:26 pm - John Doe: Nice! I love action movies! 🥋 +24/01/24, 12:27 pm - Jane Smith: Me too! 😍 +24/01/24, 12:28 pm - John Doe: Let’s watch together sometime! 🎥 +24/01/24, 12:29 pm - Jane Smith: Definitely! 👍 +24/01/24, 12:30 pm - John Doe: What snacks should we get? 🍕 +24/01/24, 12:31 pm - Jane Smith: Popcorn and soda! 🥤 +24/01/24, 12:32 pm - John Doe: Sounds perfect! 😋 +24/01/24, 12:33 pm - Jane Smith: Can’t wait! ⏳ +24/01/24, 12:34 pm - John Doe: Same! 🎉 +24/01/24, 12:35 pm - Jane Smith: Let’s set a date! 📅 +24/01/24, 12:36 pm - John Doe: How about Friday? 🤔 +24/01/24, 12:37 pm - Jane Smith: Friday works! ✅ +24/01/24, 12:38 pm - John Doe: Awesome! 🙌 +24/01/24, 12:39 pm - Jane Smith: Looking forward to it! 🥳 +24/01/24, 12:40 pm - John Doe: Same here! 🌈 +24/01/24, 12:41 pm - Jane Smith: Talk later! 👋 diff --git a/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_2.txt b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_2.txt new file mode 100644 index 0000000000..40fcb30d61 --- /dev/null +++ b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_2.txt @@ -0,0 +1,15 @@ +24/01/24, 1:01 pm - Mike Johnson: What’s up? 🌞 +24/01/24, 1:02 pm - Emily Davis: Not much! Just working! 💻 +24/01/24, 1:03 pm - Mike Johnson: Same! Just finished a project. 📈 +24/01/24, 1:04 pm - Emily Davis: Nice! Celebrate later? 🎊 +24/01/24, 1:05 pm - Mike Johnson: Sounds great! 🎉 +24/01/24, 1:06 pm - Emily Davis: Where should we go? 🍔 +24/01/24, 1:07 pm - Mike Johnson: How about that new cafe? ☕ +24/01/24, 1:08 pm - Emily Davis: I’ve heard good things! 👍 +24/01/24, 1:09 pm - Mike Johnson: Let’s do it! 🥳 +24/01/24, 1:10 pm - Emily Davis: What time? 🕒 +24/01/24, 1:11 pm - Mike Johnson: 6 PM? ⏰ +24/01/24, 1:12 pm - Emily Davis: Perfect! 🤗 +24/01/24, 1:13 pm - Mike Johnson: Can’t wait! 🎈 +24/01/24, 1:14 pm - Emily Davis: Me neither! 🎊 +24/01/24, 1:15 pm - Mike Johnson: Talk to you later! 👋 diff --git a/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_3.txt b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_3.txt new file mode 100644 index 0000000000..908544b19f --- /dev/null +++ b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_3.txt @@ -0,0 +1,16 @@ +24/01/24, 2:00 pm - Sarah Brown: Just got back from the gym! 🏋️ +24/01/24, 2:01 pm - Kevin White: Nice! How was it? 💪 +24/01/24, 2:02 pm - Sarah Brown: Great! Feeling pumped! 🔥 +24/01/24, 2:03 pm - Kevin White: Awesome! What did you do? 🏃 +24/01/24, 2:04 pm - Sarah Brown: Cardio and weights! 🏋️‍♀️ +24/01/24, 2:05 pm - Kevin White: I need to hit the gym too! 🕔 +24/01/24, 2:06 pm - Sarah Brown: Yes! Let’s go together! 🤝 +24/01/24, 2:07 pm - Kevin White: When are you free? 📅 +24/01/24, 2:08 pm - Sarah Brown: Tomorrow evening? 🌇 +24/01/24, 2:09 pm - Kevin White: Sounds good! 🎯 +24/01/24, 2:10 pm - Sarah Brown: Great! Let’s crush it! 💥 +24/01/24, 2:11 pm - Kevin White: Yes! Motivation on! 🏆 +24/01/24, 2:12 pm - Sarah Brown: I’ll bring the energy! ⚡ +24/01/24, 2:13 pm - Kevin White: I’ll bring the snacks! 🍌 +24/01/24, 2:14 pm - Sarah Brown: Perfect combo! 🙌 +24/01/24, 2:15 pm - Kevin White: Talk later! 👋 diff --git a/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_4.txt b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_4.txt new file mode 100644 index 0000000000..ec9450dbf7 --- /dev/null +++ b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_4.txt @@ -0,0 +1,13 @@ +24/01/24, 3:00 pm - Jessica Taylor: Just finished a book! 📚 +24/01/24, 3:01 pm - Brian Miller: Which one? 🤔 +24/01/24, 3:02 pm - Jessica Taylor: A mystery novel! 🔍 +24/01/24, 3:03 pm - Brian Miller: Cool! I love mysteries! 😍 +24/01/24, 3:04 pm - Jessica Taylor: You should read it! 📖 +24/01/24, 3:05 pm - Brian Miller: I will! Any recommendations? 💡 +24/01/24, 3:06 pm - Jessica Taylor: Definitely! I’ll send you the link! 🔗 +24/01/24, 3:07 pm - Brian Miller: Thanks! 😊 +24/01/24, 3:08 pm - Jessica Taylor: Let’s discuss it after you read! 🗣️ +24/01/24, 3:09 pm - Brian Miller: Sounds good! 🥳 +24/01/24, 3:10 pm - Jessica Taylor: Can’t wait! 🎊 +24/01/24, 3:11 pm - Brian Miller: Me neither! 🙌 +24/01/24, 3:12 pm - Jessica Taylor: Talk soon! 👋 diff --git a/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_5.txt b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_5.txt new file mode 100644 index 0000000000..875cb54102 --- /dev/null +++ b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_data_5.txt @@ -0,0 +1,14 @@ +24/01/24, 4:00 pm - Alex Wilson: Heading out for a walk! 🚶 +24/01/24, 4:01 pm - Mia Clark: Nice! Enjoy! 🌳 +24/01/24, 4:02 pm - Alex Wilson: Thanks! 🌼 +24/01/24, 4:03 pm - Mia Clark: Any plans for the weekend? 📅 +24/01/24, 4:04 pm - Alex Wilson: Thinking of a picnic! 🥪 +24/01/24, 4:05 pm - Mia Clark: That sounds fun! ☀️ +24/01/24, 4:06 pm - Alex Wilson: Want to join? 🎉 +24/01/24, 4:07 pm - Mia Clark: Yes! Count me in! ✌️ +24/01/24, 4:08 pm - Alex Wilson: Great! I’ll bring snacks! 🍩 +24/01/24, 4:09 pm - Mia Clark: I’ll bring drinks! 🥤 +24/01/24, 4:10 pm - Alex Wilson: Perfect combo! 🎯 +24/01/24, 4:11 pm - Mia Clark: Can’t wait for Saturday! ⏳ +24/01/24, 4:12 pm - Alex Wilson: Me neither! 🥳 +24/01/24, 4:13 pm - Mia Clark: See you then! 👋 diff --git a/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_zipped_data_1.zip b/Data_Science/Whatsapp_Chat_Analyzer/Sample_Data/sample_zipped_data_1.zip new file mode 100644 index 0000000000000000000000000000000000000000..a29324e4cfef69a642112b59d2da38471cf00b78 GIT binary patch literal 604 zcmWIWW@Zs#-~hr&b#9RiP;h{mfkA>nfuT4tw;(4qzACezAT=dEC9xzi-cYZkq9ing zmx29F3RAjRDpUGrAYEF)&A`a=m63q~Xc_}U=_E(LLk<$H-{(AfAIH2_;Z&Q1IFq3B zlp{N2ZaJ!LF+O`HGxuY+YqMrZn8&qozYv@wX5jNi=E3j#zwcN38OCq; z>{rO_HPtE6u7;QSMvJqOfXrsTg-sW^=6stlhhLs`N6%MI+x3Uee?D7%E;9YC=xv9t zMyW@0I=D=f6dgA(ICr$TggM#0T#_7M+s(xN>cQr2(+aCg57*}0RAW0iW2zPVmBfiH zGh930Pw%W-kP(poIii+}Lqm??xE^QWBKz5|Dm0`2ckHNGdaiI0FXON7cdvgJubF?- zY{v~|K_PQC^G7y*U)J0I+xRqxTU}?-JO=*XM^tr$IBjRXe9^bEz-1{{z}K~1!9R;% z81cz16e&K;zWb)$t1R<-i=0nhV)%OZ#b(1#UDiZ*U2CQI?n|fsTrl&=l@I*7xP?(kv$A?=^0LO2ok2b+{GYd6_nvF?W>xPW zyB{8U3w8&-6A$oa=g3pH@~;9$1t=B+ycwB9m=Q6IEC-5V7+BH>Vv!r)0p6@^ApML$ Nm#NJgzFwjxv z^6u?>3#LEu2s)oPSLRCC7Cq4;OJifKcI@~W`-}4rhgvun+dGBe6Q8RmncJ@qTNiRV zE?4wbuUG25`KmnE7Mzr5OcpFstzbSkk;OKHn=|T?v{%DrzZK;Vz9$=LRsLsQb-IE1 zkmj)s>aJN#Wzk+oVtWhok2+k|7ytBWZMfpa&;KGE{Y!cyRjzD5_3+Hn>z}8#p9q{J zp`>?7qM0x1^Wy`l**~8JzncBn-R+#it?kieU!HA}{&`P0CdO*1Oo_)-*ZJ>aw#-|< z*X2-%ycd ze&e(AOa1_Fc8&=<4!w^DhBqjx0=yZSM3@oL ih%5(+Mi^Mq2x5^NsR7=sY#{xNK$r%kj{