Pandas DataFrame对比time索引与spending_time列 替换sender列Unknown值

实现逻辑 #

先构造spending_time到对应recipient的映射字典，再逐行匹配time值替换sender列的Unknown字段即可。

代码实现 #

import pandas as pd

# 读取CSV数据
df = pd.read_csv("your_file_path.csv")

# 构建spending_time到recipient的映射表
spend_time_recipient_map = df.set_index("spending_time")["recipient"].to_dict()

# 替换sender列的Unknown值
df["sender"] = df.apply(
    lambda row: spend_time_recipient_map.get(row["time"], row["sender"])
    if row["sender"] == "Unknown"
    else row["sender"],
    axis=1
)

# 导出结果到csv可选
print(df.to_csv(index=False))

处理后结果 #

time,transaction_hash,index,value,recipient,spending_time,sender
2009-01-09 03:54:39,a0241106ee5a597c9,0,50.0,Paul,2009-01-12 03:30:25,Coinbase
2009-01-12 03:30:25,1338530e9831e9e16,1,40.0,Me,2009-01-12 06:02:13,Paul
2009-01-12 06:02:13,546c4fb42b41e14be,1,30.0,John,2009-01-12 06:12:16,Me
2009-01-12 06:02:14,eaf0775ebca408f7r,1,17.0,Paul,2010-09-22 06:06:02,Unknown
2009-01-12 06:02:15,732a865bf5414eab2,1,15.0,Paul,2010-02-23 14:01:23,Unknown
2009-01-12 06:12:16,591e911da64588073,1,29.0,John,2009-01-12 06:34:22,John
2009-01-12 06:34:22,12b52732a85c191ba,1,28.0,Sara,2009-01-12 20:04:20,John

内容的提问来源于stack exchange，提问作者sci9