Apprendre Visualizing Adverse Event Rates | Clinical Data Analysis and Visualization

Monitoring and analyzing adverse drug events is a critical aspect of pharmacy practice. Adverse events—unintended and harmful outcomes from medication use—can impact patient safety and treatment outcomes. By tracking these events and visualizing their frequency, you can quickly identify which medications are associated with higher risks. Visualization helps you communicate findings clearly to healthcare teams, supporting informed decisions and proactive risk management.


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import pandas as pd

# Create a DataFrame with drugs and reported adverse event counts
data = {
    "Drug": ["Amlodipine", "Metformin", "Warfarin", "Atorvastatin"],
    "Adverse_Events": [15, 22, 8, 12]
}
df = pd.DataFrame(data)
print(df)

To understand the distribution of adverse events among different drugs, you can use a pie chart. This type of chart makes it easy to see the proportion of total events attributed to each medication, allowing you to focus on drugs with higher reported issues.


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# Customizing the pie chart with percentages for clarity
plt.figure(figsize=(6, 6))
plt.pie(
    df["Adverse_Events"],
    labels=df["Drug"],
    autopct="%1.1f%%",
    startangle=90,
    shadow=True
)
plt.title("Proportion of Adverse Events by Drug")
plt.show()

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Merci pour vos commentaires !

Section 3. Chapitre 2

Demandez à l'IA

Posez n'importe quelle question ou essayez l'une des questions suggérées pour commencer notre discussion

Suggested prompts:

Can you explain how to interpret the pie chart results?

What other types of visualizations can I use for this data?

How can I add more drugs or events to the analysis?

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              123456789
            
import pandas as pd

# Create a DataFrame with drugs and reported adverse event counts
data = {
    "Drug": ["Amlodipine", "Metformin", "Warfarin", "Atorvastatin"],
    "Adverse_Events": [15, 22, 8, 12]
}
df = pd.DataFrame(data)
print(df)


              1234567891011
            
# Customizing the pie chart with percentages for clarity
plt.figure(figsize=(6, 6))
plt.pie(
    df["Adverse_Events"],
    labels=df["Drug"],
    autopct="%1.1f%%",
    startangle=90,
    shadow=True
)
plt.title("Proportion of Adverse Events by Drug")
plt.show()

Tout était clair ?

Merci pour vos commentaires !

Section 3. Chapitre 2

Visualizing Adverse Event Rates

1. What type of chart is suitable for showing proportions of adverse events by drug?

2. Why is it important to visualize adverse event data?

3. Which matplotlib function is used to create a pie chart?

Visualizing Adverse Event Rates

1. What type of chart is suitable for showing proportions of adverse events by drug?

2. Why is it important to visualize adverse event data?

3. Which matplotlib function is used to create a pie chart?