Visualizing Drug Inventory Data
When managing a pharmacy, having a clear view of your medication inventory is essential. Visualizing stock data helps you spot shortages, overstocked drugs, and usage trends at a glance. The matplotlib library in Python is a powerful tool for creating these visualizations. One of the most helpful chart types for this purpose is the bar chart, which allows you to compare the stock levels of different medications side by side. With just a few lines of code, you can turn a simple inventory list into an informative chart that supports better decision-making.
123456789import matplotlib.pyplot as plt # Sample data: medication names and their stock levels medications = ["Aspirin", "Lisinopril", "Metformin", "Atorvastatin", "Amoxicillin"] stock_levels = [120, 45, 80, 30, 60] # Create a bar chart plt.bar(medications, stock_levels) plt.show()
Visualizations like bar charts make it easy for pharmacists to quickly assess current inventory. Instead of scanning through rows of numbers, you can instantly see which drugs are running low or which ones are well-stocked. This helps you prioritize restocking, avoid shortages, and reduce excess inventory. Decision-making becomes faster and more accurate when you use clear, visual representations of medication data.
12345678910import matplotlib.pyplot as plt medications = ["Aspirin", "Lisinopril", "Metformin", "Atorvastatin", "Amoxicillin"] stock_levels = [120, 45, 80, 30, 60] plt.bar(medications, stock_levels, color="skyblue") plt.xlabel("Medication Name") plt.ylabel("Stock Level") plt.title("Pharmacy Inventory: Medication Stock Levels") plt.show()
1. What type of chart is most effective for comparing stock levels of different medications?
2. Which matplotlib function is used to create a bar chart?
3. Why is it important to label axes in a medication inventory chart?
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When managing a pharmacy, having a clear view of your medication inventory is essential. Visualizing stock data helps you spot shortages, overstocked drugs, and usage trends at a glance. The matplotlib library in Python is a powerful tool for creating these visualizations. One of the most helpful chart types for this purpose is the bar chart, which allows you to compare the stock levels of different medications side by side. With just a few lines of code, you can turn a simple inventory list into an informative chart that supports better decision-making.
123456789import matplotlib.pyplot as plt # Sample data: medication names and their stock levels medications = ["Aspirin", "Lisinopril", "Metformin", "Atorvastatin", "Amoxicillin"] stock_levels = [120, 45, 80, 30, 60] # Create a bar chart plt.bar(medications, stock_levels) plt.show()
Visualizations like bar charts make it easy for pharmacists to quickly assess current inventory. Instead of scanning through rows of numbers, you can instantly see which drugs are running low or which ones are well-stocked. This helps you prioritize restocking, avoid shortages, and reduce excess inventory. Decision-making becomes faster and more accurate when you use clear, visual representations of medication data.
12345678910import matplotlib.pyplot as plt medications = ["Aspirin", "Lisinopril", "Metformin", "Atorvastatin", "Amoxicillin"] stock_levels = [120, 45, 80, 30, 60] plt.bar(medications, stock_levels, color="skyblue") plt.xlabel("Medication Name") plt.ylabel("Stock Level") plt.title("Pharmacy Inventory: Medication Stock Levels") plt.show()
1. What type of chart is most effective for comparing stock levels of different medications?
2. Which matplotlib function is used to create a bar chart?
3. Why is it important to label axes in a medication inventory chart?
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