matplotlib.pyplot as plt

Given data

data = [7, 11, 12, 3, 6, 5, 10, 6, 5, 12, 8]

Create a box plot

plt.figure(figsize=(6, 4)) plt.boxplot(data, vert=False) plt.title('Box Plot of the Given Data') plt.xlabel('Values') plt.grid(True) plt.show()Here is the box plot for the given data set: 7, 11, 12, 3, 6, 5, 10, 6, 5, 12, 8.

The box plot shows the distribution of the data, highlighting the median, quartiles, and potential outliers. The "box" itself spans from the first quartile (Q1) to the third quartile (Q3), with the line inside the box representing the median (Q2). The "whiskers" extend from the minimum value to the maximum value, excluding outliers.

Would you like further details on interpreting the box plot or any other related concepts?

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Here are some follow-up questions for deeper understanding:

1. How do you interpret the quartiles (Q1, Q2, and Q3) in a box plot?
2. What are potential outliers in a box plot, and how can they be identified?
3. How do you calculate the interquartile range (IQR) for a data set?
4. What are the advantages of using a box plot over other graph types?
5. Can you use a box plot to compare multiple data sets?

Tip: When drawing box plots for multiple data sets, it's helpful to align them side by side to compare their spread and central tendencies.