Python pandas根据RT/RW/Kelurahan三列条件新建Zoning Status列

• 判断语法错误：代码中y == [2,5,...]、z == ['Batu Ampar']是拿单个单元格的数值/字符串，和整个Python列表做相等比较，结果永远为False，导致所有行都会被判定为Zonasi3。
• 匹配逻辑错误：分开判断RT属于某列表、RW属于某列表，会出现跨位置组合错配（比如RT12配RW5不属于Zonasi1，但按原逻辑会被误判），必须以(RT,RW)成对的形式做匹配才准确。

优先使用pandas向量化写法，运行效率远高于手写for循环，适配任意数据规模：

import numpy as np

# 定义两个分区对应的(RT, RW)成对组合集合，和你给出的示例组合一一对应
zonasi1_pairs = {(12,2), (15,5), (7,4), (11,4), (11,2), (10,2), (9,2), (14,2)}
zonasi2_pairs = {(1,4), (9,3), (6,5), (5,5), (8,2), (15,2), (17,2), (1,6), (10,4), (13,4), (4,4), (6,4), (12,4)}

# 构造匹配条件
is_batu_ampar = df_51['Kelurahan'] == 'Batu Ampar'
match_zonasi1 = is_batu_ampar & df_51.apply(lambda row: (row['RT'], row['RW']) in zonasi1_pairs, axis=1)
match_zonasi2 = is_batu_ampar & df_51.apply(lambda row: (row['RT'], row['RW']) in zonasi2_pairs, axis=1)

# 生成新列
df_51['Zoning Status'] = np.select(
    condlist=[match_zonasi1, match_zonasi2],
    choicelist=['Zonasi 1', 'Zonasi 2'],
    default='Zonasi 3'
)

如果需要沿用for循环的写法，修正后代码如下：

status_zonasi = []
zonasi1_pairs = {(12,2), (15,5), (7,4), (11,4), (11,2), (10,2), (9,2), (14,2)}
zonasi2_pairs = {(1,4), (9,3), (6,5), (5,5), (8,2), (15,2), (17,2), (1,6), (10,4), (13,4), (4,4), (6,4), (12,4)}

for rt, rw, kelurahan in zip(df_51['RT'], df_51['RW'], df_51['Kelurahan']):
    if kelurahan == 'Batu Ampar' and (rt, rw) in zonasi1_pairs:
        res = 'Zonasi 1'
    elif kelurahan == 'Batu Ampar' and (rt, rw) in zonasi2_pairs:
        res = 'Zonasi 2'
    else:
        res = 'Zonasi 3'
    status_zonasi.append(res)

df_51['Zoning Status'] = status_zonasi

后续如果需要调整分区对应的RT/RW组合，直接修改对应集合内的(RT,RW)元组即可，无需改动判断逻辑。

内容的提问来源于stack exchange，提问作者linggapratama28