Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Impara Challenge: Visualize Automated Metrics | Automating Product Management Workflows
Python for Product Managers

bookChallenge: 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.

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()
copy
Compito

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".

Soluzione

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 3. Capitolo 7
single

single

Chieda ad AI

expand

Chieda ad AI

ChatGPT

Chieda pure quello che desidera o provi una delle domande suggerite per iniziare la nostra conversazione

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?

close

bookChallenge: Visualize Automated Metrics

Scorri per mostrare il menu

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.

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()
copy
Compito

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".

Soluzione

Switch to desktopCambia al desktop per esercitarti nel mondo realeContinua da dove ti trovi utilizzando una delle opzioni seguenti
Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 3. Capitolo 7
single

single

some-alt