You are a senior python engineer, you provide python code to answer questions. Твоя задача довести приложение до финального вида, с учетом всех замечаний и советов.
Certainly! Python is a versatile tool that can assist product managers in various tasks, such as conducting market research, automating parts of the product lifecycle, and creating dashboards or reports for stakeholder communication. Let me provide you with some examples and explanations for each area:

### 1. Conducting Market Research and Data Analytics

Python can be used to analyze large datasets and gather insights from them. Libraries like `pandas`, `numpy`, `matplotlib`, and `seaborn` make data analysis and visualization straightforward.

**Example: Analyzing Customer Feedback**

Here’s a simple example of using Python to analyze customer feedback:

```python
import pandas as pd
import matplotlib.pyplot as plt
from wordcloud import WordCloud

# Load customer feedback data
data = pd.read_csv('customer_feedback.csv')

# Display the first few rows
print(data.head())

# Create a word cloud of the feedback comments
text = " ".join(comment for comment in data.feedback)
wordcloud = WordCloud(width = 800, height = 400, max_font_size=110).generate(text)

# Visualize the word cloud
plt.figure(figsize=(10, 8))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis('off')
plt.show()
```

This script reads customer feedback from a CSV file and generates a word cloud to highlight frequently mentioned words, helping product managers identify common themes or issues.

### 2. Automating Parts of the Product Lifecycle

Python can automate repetitive tasks, which can help streamline the product lifecycle. This can include tasks like email notifications, scraping competitor data, or data entry.

**Example: Sending Automated Email Notifications**

Using `smtplib` and `email`, you can automate email notifications:

```python
import smtplib
from email.mime.text import MIMEText

def send_email(subject, body, to_email):
    smtp_server = 'smtp.example.com'
    from_email = 'your_email@example.com'
    password = 'your_password'
    
    msg = MIMEText(body)
    msg['Subject'] = subject
    msg['From'] = from_email
    msg['To'] = to_email

    with smtplib.SMTP(smtp_server, 587) as server:
        server.starttls()
        server.login(from_email, password)
        server.send_message(msg)
        print('Email sent to:', to_email)

# Example usage
send_email('Product Update', 'Details about the new features...', 'stakeholder@example.com')
```

This script sends an email using SMTP, which could be triggered based on certain conditions or events in the product lifecycle.

### 3. Creating Dashboards or Reports for Stakeholder Communication

Python, along with libraries like `Dash` or `Streamlit`, can create interactive dashboards that update stakeholders on key metrics and progress.

**Example: Creating a Simple Dashboard with Streamlit**

```python
import streamlit as st
import pandas as pd

# Load and display data
data = pd.read_excel('sales_data.xlsx')
st.title('Sales Data Dashboard')
st.write(data)

# Display total sales
total_sales = data['Sales'].sum()
st.metric(label="Total Sales", value=f"${total_sales}")

# Plot sales over months
sales_by_month = data.groupby('Month')['Sales'].sum()
st.line_chart(sales_by_month)
```

This example uses Streamlit to create a web-based dashboard displaying sales data from an Excel file. It provides stakeholders with a quick and interactive way to view and understand sales trends.

Each of these examples demonstrates how Python can be effectively used in product management for data analysis, automation, and communication. Depending on your specific needs, these scripts can be adapted and expanded to better fit various product management tasks.