使用pyplot.stairs或Axes.stairs：

edges = [39.9, 42.9,45.9,48.9,51.9,54.9,57.9]
plt.stairs(df['cumulativePercent'], edges, fill=True)

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或

edges = [39.9, 42.9,45.9,48.9,51.9,54.9,57.9]
fig, ax = plt.subplots()
ax.stairs(df['cumulativePercent'], edges, fill=True)

型
输出量：

的数据

出现这个问题是因为hist方法试图从数据中创建自己的bin，而不是严格使用您提供的bin。您可以使用bar来绘制预分仓数据的直方图，而不是使用hist方法。这里是更新的完整代码：

import pandas as pd
import matplotlib.pyplot as plt
# Create the dataframe
idx = pd.IntervalIndex.from_breaks([39.9, 42.9,45.9,48.9,51.9,54.9,57.9])
df = pd.DataFrame({"Bin": idx, "Frequency": [2,2,5,5,12,3]})
n = df["Frequency"].sum()
# Calculate cumulative sum and cumulative percent
df['cumulativeSumFreq'] = df["Frequency"].cumsum()
df['cumulativePercent'] = (df["Frequency"]/n)*100
# Plotting the histogram using bar
left_edges = [interval.left for interval in df["Bin"]]
right_edges = [interval.right for interval in df["Bin"]]
# The bar heights will be the 'cumulativePercent' values
heights = df['cumulativePercent']
# Plot the bars
plt.bar(left_edges, heights, width=[right-left for left, right in zip(left_edges, right_edges)], align='edge', edgecolor='black')
# Label the x-axis
plt.xticks((left_edges + right_edges)[:-1], labels=[str(interval) for interval in df["Bin"]], rotation=45, ha="right")
plt.show()

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