關於Pandas Dataframe Series map 用法的效能問題

import time
import pandas as pd

data1 = [[i, f'data {i}'] for i in range(3, 99999)]
data2 = [[i, 'None'] for i in range(100001)]
df_offical  = pd.DataFrame(data1, columns=['地址', 'TWD97橫座標'])
df_Dajia    = pd.DataFrame(data2, columns=['地址', 'TWD97橫座標'])

now = time.time()

df_Dajia.set_index('地址', inplace=True)
df_Dajia.update(df_offical.set_index('地址'))
df_Dajia.reset_index()

print(f'time passed: {int(time.time() - now)} seconds\n')
print(df_Dajia)Copy

time passed: 0 seconds

          TWD97橫座標
地址                
0             None
1             None
2             None
3           data 3
4           data 4
...            ...
99996   data 99996
99997   data 99997
99998   data 99998
99999         None
100000        None

[100001 rows x 1 columns]Copy

>>> df_Dajia
   地址 TWD97橫座標
0   0     None
1   1     None
2   2     None
3   3     None
4   4     None
5   5     None
6   6     None
7   7     None
8   8     None
9   9     None
>>> df_offical
   地址 TWD97橫座標
0   3   data 3
1   4   data 4     # 地址欄位重複
2   4   data 5     # 地址欄位重複Copy

Traceback (most recent call last):
  File "D:\test4.py", line 18, in <module>
    df.Dajia['TWD97橫座標'] = df_Dajia['地址'].map(match_row)
  File "C:\Software\Python\lib\site-packages\pandas\core\series.py", line 4237, in map
    new_values = self._map_values(arg, na_action=na_action)
  File "C:\Software\Python\lib\site-packages\pandas\core\base.py", line 880, in _map_values
    new_values = map_f(values, mapper)
  File "pandas\_libs\lib.pyx", line 2870, in pandas._libs.lib.map_infer
  File "D:\test4.py", line 16, in match_row
    return find_val.values.item()
ValueError: can only convert an array of size 1 to a Python scalarCopy

>>> find_val = pd.Series(data=["data 4", "data 5"], name='TWD97橫座標')
>>> find_val.values.item()
Traceback (most recent call last):  
  File "<interactive input>", line 1, in <module>
ValueError: can only convert an array of size 1 to a Python scalarCopy

def Match_column(value):
    #第一次比對 如果空的話
    if df_offical[df_offical['地址'].isin([value])].index.empty:
    #第二次比對因為前面空值  所以目前嘗試取得號前面的自 不包含樓
        value = re.findall(".*號",value)
        if df_offical[ df_offical['地址'].isin([value])].index.empty :
            return "無"
        else:
            print(df_offical[ df_offical['地址'].isin(value)]['TWD97橫坐標'].values.item())
            return df_offical[df_offical['地址'].isin(value)]['TWD97縱坐標'].values.item()
    else:
        return df_offical[df_offical['地址'].isin([value])]['TWD97縱坐標'].values.item()
df_Dajia['TWD97縱坐標'] = df_Dajia['地址'].apply(Match_column) Copy

df_offical[df_offical['地址'].isin([value])]Copy