Challenge: Visualize Automated Metrics
As a product manager, you often need to present a snapshot of key product metrics—such as feature adoption rates, churn, and daily active users (DAU)—in a clear, visual format. Python, combined with the matplotlib library, enables you to quickly generate summary charts that can be embedded in reports or shared with stakeholders. Recapping what you have learned so far, visualizing multiple metrics in a single chart helps you compare trends at a glance and communicate results effectively. Saving these charts as image files ensures you have ready-to-use visuals for product documentation or presentations.
12345678910111213141516171819202122232425262728293031import matplotlib.pyplot as plt # Hardcoded product metrics metrics = { "Feature Adoption Rate": 0.67, "Churn Rate": 0.13, "DAU": 3200 } # Prepare data for the bar chart labels = list(metrics.keys()) values = list(metrics.values()) # Create the bar chart plt.figure(figsize=(8, 5)) bars = plt.bar(labels, values, color=['skyblue', 'salmon', 'lightgreen']) # Add labels and title plt.ylabel("Value") plt.title("Product Metrics Overview") # Add value labels above bars for bar in bars: height = bar.get_height() plt.annotate(f"{height}", xy=(bar.get_x() + bar.get_width() / 2, height), xytext=(0, 3), textcoords="offset points", ha='center', va='bottom') # Save the chart as an image file plt.tight_layout() plt.savefig("product_metrics_overview.png") plt.close()
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Write a script that visualizes and saves a summary chart of product metrics. You will use a dictionary of metrics with three key metrics: "Feature Adoption Rate", "Churn Rate", and "DAU".
- Create a bar chart where each bar represents one of the metrics.
- Add axis labels and a chart title.
- Display the value of each metric above its respective bar.
- Save the chart as an image file named "summary_product_metrics.png".
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Can you explain what each of these metrics means?
How can I customize the chart for different metrics?
What are some best practices for presenting these charts to stakeholders?
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Challenge: Visualize Automated Metrics
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As a product manager, you often need to present a snapshot of key product metrics—such as feature adoption rates, churn, and daily active users (DAU)—in a clear, visual format. Python, combined with the matplotlib library, enables you to quickly generate summary charts that can be embedded in reports or shared with stakeholders. Recapping what you have learned so far, visualizing multiple metrics in a single chart helps you compare trends at a glance and communicate results effectively. Saving these charts as image files ensures you have ready-to-use visuals for product documentation or presentations.
12345678910111213141516171819202122232425262728293031import matplotlib.pyplot as plt # Hardcoded product metrics metrics = { "Feature Adoption Rate": 0.67, "Churn Rate": 0.13, "DAU": 3200 } # Prepare data for the bar chart labels = list(metrics.keys()) values = list(metrics.values()) # Create the bar chart plt.figure(figsize=(8, 5)) bars = plt.bar(labels, values, color=['skyblue', 'salmon', 'lightgreen']) # Add labels and title plt.ylabel("Value") plt.title("Product Metrics Overview") # Add value labels above bars for bar in bars: height = bar.get_height() plt.annotate(f"{height}", xy=(bar.get_x() + bar.get_width() / 2, height), xytext=(0, 3), textcoords="offset points", ha='center', va='bottom') # Save the chart as an image file plt.tight_layout() plt.savefig("product_metrics_overview.png") plt.close()
Swipe to start coding
Write a script that visualizes and saves a summary chart of product metrics. You will use a dictionary of metrics with three key metrics: "Feature Adoption Rate", "Churn Rate", and "DAU".
- Create a bar chart where each bar represents one of the metrics.
- Add axis labels and a chart title.
- Display the value of each metric above its respective bar.
- Save the chart as an image file named "summary_product_metrics.png".
Рішення
Дякуємо за ваш відгук!
single