Lära Challenge: Visualize Automated Metrics | Automating Product Management Workflows

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.


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import 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()

Uppgift

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".

Lösning

Var allt tydligt?

Tack för dina kommentarer!

Avsnitt 3. Kapitel 7

single

Fråga AI

Fråga vad du vill eller prova någon av de föreslagna frågorna för att starta vårt samtal

Suggested prompts:

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?

Svep för att visa menyn


              12345678910111213141516171819202122232425262728293031
            
import 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()