如何从同时包含数字和字符串的DataFrame单元格中拆分提取数值与货币单位

实现步骤 #

• 导入依赖并构造原始数据

import pandas as pd

# 原始数据样例
raw_df = pd.DataFrame({
    "Mode": ["Car", "Bike"],
    "Small": ["20USD", "10RS"],
    "medium": ["40USD", "30RS"],
    "Large": ["60USD", "45RS"]
})

• 提取货币单位列
  由于样例中同一行所有金额的货币单位一致，直接从任意金额列提取非数字字符即可：

raw_df['Currency'] = raw_df['Small'].str.extract(r'(\D+)', expand=False)

• 转换金额列为纯数值
  遍历所有金额列，提取数字部分并转换为整数类型：

amount_cols = ["Small", "medium", "Large"]
for col in amount_cols:
    raw_df[col] = raw_df[col].str.extract(r'(\d+)', expand=False).astype(int)

• 调整列顺序与列名，匹配目标输出格式

result_df = raw_df[["Mode", "Currency", "Small", "medium", "Large"]].rename(columns={"medium": "Medium"})

输出结果 #

打印result_df即可得到你需要的格式：

Mode Currency  Small  Medium  Large
0   Car      USD     20      40     60
1  Bike       RS     10      30     45

内容的提问来源于stack exchange，提问作者Chandan N