Python中动态转置DataFrame参数列（未知参数内容与数量）

假设我有如下表格（对应下方Python代码生成的pandas DataFrame）：

import pandas as pd
data = [["Car","Sport","Wheel", 4], 
        ["Car", "Sport","engine HP", 65], 
        ["Car", "Sport","windows", 5], 
        ["Car","Van","Wheel", 4], 
        ["Car", "Van","engine HP", 85], 
        ["Car", "Van","windows", 8],
        ["Truck","Small","Wheel", 4], 
        ["Truck", "Small","engine HP", 125], 
        ["Truck", "Small","windows", 2],
        ["Truck","Large","Wheel", 8], 
        ["Truck", "Large","engine HP", 200], 
        ["Truck", "Large","windows", 2]
        ]
  
df = pd.DataFrame(data)
# 定义表头
df.columns = ["Vehicle", "Type","Parameter","Value"]

需要对该DataFrame进行处理，将Parameter对应的Value转置为列，但预先不知道Parameter列的具体内容及参数类型数量，最终要得到如下结构的表格：

"Vehicle","Type","Wheel","Engine","Windows"
"Car","Sport",4,65,5
"Car","Van",4,85,8
"Truck","Small",4,125,2
"Truck","Large",8,200,2

请问该如何实现？

可以借助pandas的pivot方法实现需求，同时对列名做统一格式化处理，步骤如下：

1. 用pivot方法完成透视转换：指定Vehicle和Type作为行索引，Parameter作为列名，Value作为对应列的值，自动将所有参数转为列：

pivoted_df = df.pivot(index=["Vehicle", "Type"], columns="Parameter", values="Value").reset_index()

2. 格式化列名（比如把engine HP转为Engine，windows转为Windows），适配目标格式：

# 统一列名格式：首字母大写，含空格的参数取第一个单词
pivoted_df.columns = [col.split()[0].capitalize() if " " in col else col.capitalize() for col in pivoted_df.columns]

3. 输出符合要求的CSV格式内容：

print(pivoted_df.to_csv(index=False, quotechar='"'))

完整可运行代码：

import pandas as pd

data = [["Car","Sport","Wheel", 4], 
        ["Car", "Sport","engine HP", 65], 
        ["Car", "Sport","windows", 5], 
        ["Car","Van","Wheel", 4], 
        ["Car", "Van","engine HP", 85], 
        ["Car", "Van","windows", 8],
        ["Truck","Small","Wheel", 4], 
        ["Truck", "Small","engine HP", 125], 
        ["Truck", "Small","windows", 2],
        ["Truck","Large","Wheel", 8], 
        ["Truck", "Large","engine HP", 200], 
        ["Truck", "Large","windows", 2]
        ]
  
df = pd.DataFrame(data)
df.columns = ["Vehicle", "Type","Parameter","Value"]

# 透视转换
pivoted_df = df.pivot(index=["Vehicle", "Type"], columns="Parameter", values="Value").reset_index()

# 格式化列名
pivoted_df.columns = [col.split()[0].capitalize() if " " in col else col.capitalize() for col in pivoted_df.columns]

# 输出目标格式内容
print(pivoted_df.to_csv(index=False, quotechar='"'))

该方案无需提前知晓Parameter的具体内容和数量，pivot方法会自动识别所有参数并转为对应列，完全适配需求。

内容的提问来源于stack exchange，提问作者Julien