Challenge: Automate a Product Report
In product management, automating the creation of weekly reports saves time, reduces manual errors, and ensures stakeholders receive consistent updates. When generating such reports, follow best practices: organize your metrics clearly, use meaningful labels, and format the output for easy reading. Summarizing key data points like Daily Active Users (DAU), churn rate, and feature usage gives your team a quick snapshot of product health and engagement. Python makes this process straightforward by allowing you to calculate summaries and print well-formatted reports with minimal code.
12345678910111213141516171819202122# Hardcoded weekly metrics weekly_metrics = { "DAU": [120, 135, 140, 125, 150, 160, 155], "churn_rate": [0.02, 0.025, 0.018, 0.022, 0.019, 0.021, 0.02], "feature_A_usage": [50, 60, 55, 53, 65, 70, 68] } # Summarize metrics average_dau = sum(weekly_metrics["DAU"]) / len(weekly_metrics["DAU"]) average_churn = sum(weekly_metrics["churn_rate"]) / len(weekly_metrics["churn_rate"]) total_feature_a_usage = sum(weekly_metrics["feature_A_usage"]) # Format and print report report = ( "Weekly Product Metrics Report\n" "----------------------------\n" f"Average DAU: {average_dau:.1f}\n" f"Average Churn Rate: {average_churn:.2%}\n" f"Total Feature A Usage: {total_feature_a_usage}\n" ) print(report)
Swipe to start coding
Write a function that generates a formatted report summarizing weekly product metrics from the provided dictionary.
- Calculate the average value of the
"DAU"list. - Calculate the average value of the
"churn"list. - Calculate the total sum of the
"feature_B_usage"list. - Return a formatted string report with labeled lines for average DAU, average churn rate (as a percent with two decimals), and total Feature B usage.
Oplossing
Bedankt voor je feedback!
single
Vraag AI
Vraag AI
Vraag wat u wilt of probeer een van de voorgestelde vragen om onze chat te starten.
Can you explain what DAU and churn rate mean in this context?
How can I add more metrics to this report?
Can you show me how to customize the report formatting?
Geweldig!
Completion tarief verbeterd naar 4.76
Challenge: Automate a Product Report
Veeg om het menu te tonen
In product management, automating the creation of weekly reports saves time, reduces manual errors, and ensures stakeholders receive consistent updates. When generating such reports, follow best practices: organize your metrics clearly, use meaningful labels, and format the output for easy reading. Summarizing key data points like Daily Active Users (DAU), churn rate, and feature usage gives your team a quick snapshot of product health and engagement. Python makes this process straightforward by allowing you to calculate summaries and print well-formatted reports with minimal code.
12345678910111213141516171819202122# Hardcoded weekly metrics weekly_metrics = { "DAU": [120, 135, 140, 125, 150, 160, 155], "churn_rate": [0.02, 0.025, 0.018, 0.022, 0.019, 0.021, 0.02], "feature_A_usage": [50, 60, 55, 53, 65, 70, 68] } # Summarize metrics average_dau = sum(weekly_metrics["DAU"]) / len(weekly_metrics["DAU"]) average_churn = sum(weekly_metrics["churn_rate"]) / len(weekly_metrics["churn_rate"]) total_feature_a_usage = sum(weekly_metrics["feature_A_usage"]) # Format and print report report = ( "Weekly Product Metrics Report\n" "----------------------------\n" f"Average DAU: {average_dau:.1f}\n" f"Average Churn Rate: {average_churn:.2%}\n" f"Total Feature A Usage: {total_feature_a_usage}\n" ) print(report)
Swipe to start coding
Write a function that generates a formatted report summarizing weekly product metrics from the provided dictionary.
- Calculate the average value of the
"DAU"list. - Calculate the average value of the
"churn"list. - Calculate the total sum of the
"feature_B_usage"list. - Return a formatted string report with labeled lines for average DAU, average churn rate (as a percent with two decimals), and total Feature B usage.
Oplossing
Bedankt voor je feedback!
single