如何用Pandas多列分组并绘制符合需求的Feature路线图柱状图？

一、数据聚合：计算Feature核心指标 #

首先用Pandas对原始数据按Feature ID分组，提取每个Feature的关键信息：用户故事数量、起止Sprint、总点数，以及Sprint跨度。

import pandas as pd

# 导入数据集（示例数据，实际可替换为pd.read_csv读取文件）
data = {
    "Feature ID": ["01", "01", "02", "03", "01", "01", "04"],
    "User Story ID": [101, 102, 103, 104, 105, 106, 107],
    "Sprint": [1, 1, 1, 1, 2, 2, 2],
    "Points": [3, 5, 2, 5, 5, 2, 2]
}
df = pd.DataFrame(data)

# 分组计算统计量
feature_summary = df.groupby("Feature ID").agg(
    Story_Count=("User Story ID", "count"),
    Start_Sprint=("Sprint", "min"),
    End_Sprint=("Sprint", "max"),
    Total_Points=("Points", "sum")
).reset_index()

# 计算Sprint覆盖的跨度
feature_summary["Sprint_Span"] = feature_summary["End_Sprint"] - feature_summary["Start_Sprint"] + 1

执行后得到的feature_summary包含所有核心指标：

二、可视化：生成Feature路线图 #

1. 简洁版：展示Feature的Sprint跨度与核心指标

用横向条形图直观展示每个Feature的Sprint覆盖范围，同时标注故事数和总点数：

import matplotlib.pyplot as plt

plt.figure(figsize=(10, 6))
y_pos = range(len(feature_summary))

# 绘制覆盖Sprint的条形
plt.barh(y_pos, feature_summary["Sprint_Span"], left=feature_summary["Start_Sprint"], height=0.6, color="#4CAF50")

# 为每个条形添加标注
for i, row in feature_summary.iterrows():
    x_center = row["Start_Sprint"] + row["Sprint_Span"] / 2
    plt.text(x_center, y_pos[i], 
             f"Stories: {row['Story_Count']}\nPoints: {row['Total_Points']}",
             ha="center", va="center", color="white", fontweight="bold")

# 设置坐标轴与样式
plt.yticks(y_pos, feature_summary["Feature ID"])
plt.xlabel("Sprint Number")
plt.ylabel("Feature ID")
plt.title("Feature Roadmap: Sprint Coverage & Metrics")
plt.xticks(range(feature_summary["Start_Sprint"].min(), feature_summary["End_Sprint"].max() + 1))
plt.grid(axis="x", linestyle="--", alpha=0.7)

plt.tight_layout()
plt.show()

2. 细致版：展示每个User Story的分布

如果需要看每个Feature下具体用户故事的Sprint分布和点数，可以用如下代码：

df_sorted = df.sort_values("Feature ID")
plt.figure(figsize=(10, 8))
y_offset = 0
feature_y_map = {}

for feature_id, group in df_sorted.groupby("Feature ID"):
    feature_y_map[feature_id] = y_offset
    # 为每个User Story绘制单独的条形
    for _, story in group.iterrows():
        plt.barh(y_offset, 1, left=story["Sprint"] - 0.5, height=0.4, color=f"C{int(feature_id)}")
        plt.text(story["Sprint"], y_offset, f"#{story['User Story ID']} ({story['Points']})", ha="center", va="center", fontsize=9)
    y_offset += 1

# 设置坐标轴与样式
plt.yticks(range(len(feature_y_map)), feature_y_map.keys())
plt.xlabel("Sprint Number")
plt.ylabel("Feature ID")
plt.title("Feature Roadmap with Individual User Stories")
plt.xticks(range(df["Sprint"].min(), df["Sprint"].max() + 1))
plt.grid(axis="x", linestyle="--", alpha=0.7)

plt.tight_layout()
plt.show()

内容的提问来源于stack exchange，提问作者Ammy