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Leer Challenge: Build a Visual Metrics Dashboard | Automating Reports and Visual Insights
Python Automation for Reports and Visual Insights
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bookChallenge: Build a Visual Metrics Dashboard

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Create a function create_dashboard(df) that accepts a DataFrame with Date, Product, and Sales columns and generates a dashboard figure with two side-by-side charts and a summary statistics box.

Compute summary statistics from the Sales column:

  • Total sales (sum), average sales (mean), maximum sales, and minimum sales

Create a figure with two subplots side by side using plt.subplots(1, 2), with the overall figure title "Sales Dashboard"

Left subplot — Line chart:

  • Group the data by Date and sum the sales, then plot as a line chart with markers
  • Set the title to "Sales Trend Over Time", x-label to "Date", y-label to "Sales"

Right subplot — Bar chart:

  • Group the data by Product and sum the sales, then plot as a bar chart
  • Set the title to "Sales by Product", x-label to "Product", y-label to "Sales"

Add a summary statistics text box at the bottom center of the figure using fig.text(). The text must follow this exact format:

Total Sales: {value:.2f}
Average Sales: {value:.2f}
Max Sales: {value:.2f}
Min Sales: {value:.2f}

Adjust the layout using plt.tight_layout() so the stats box doesn't overlap the charts.

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