Add geocoding function

[new-village]

Add latitude and longitude data from concatinated "prefecture_name", "city_name" and "street_number".

[new-village]

First, we should confirm to use "en_city_name" field.
If it is OK, we will get high accuary geocoding data from Open Street Map or other foreign geocoding services.

[new-village]

we don't use english address info because en_city_name is only 0.2% registration in Shimane prefecture.

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 21927 entries, 0 to 21926
Data columns (total 30 columns):
 #   Column                      Non-Null Count  Dtype 
---  ------                      --------------  ----- 
 0   sequence_number             21927 non-null  object
 1   corporate_number            21927 non-null  object
 2   process                     21927 non-null  object
 3   correct                     21927 non-null  object
 4   update_date                 21927 non-null  object
 5   change_date                 21927 non-null  object
 6   name                        21927 non-null  object
 7   name_image_id               354 non-null    object
 8   kind                        21927 non-null  object
 9   prefecture_name             21927 non-null  object
 10  city_name                   21927 non-null  object
 11  street_number               21862 non-null  object
 12  address_image_id            88 non-null     object
 13  prefecture_code             21927 non-null  object
 14  city_code                   21927 non-null  object
 15  post_code                   21927 non-null  object
 16  address_outside             0 non-null      object
 17  address_outside_image_id    0 non-null      object
 18  close_date                  2174 non-null   object
 19  close_cause                 2174 non-null   object
 20  successor_corporate_number  172 non-null    object
 21  change_cause                275 non-null    object
 22  assignment_date             21927 non-null  object
 23  latest                      21927 non-null  object
 24  en_name                     64 non-null     object
 25  en_prefecture_name          64 non-null     object
 26  en_city_name                64 non-null     object
 27  en_address_outside          0 non-null      object
 28  furigana                    10648 non-null  object
 29  hihyoji                     21927 non-null  object
dtypes: object(30)
memory usage: 5.0+ MB

[new-village]

parse address info & result is here

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 21927 entries, 0 to 21926
Data columns (total 37 columns):
 #   Column                      Non-Null Count  Dtype  
---  ------                      --------------  -----  
 0   sequence_number             21927 non-null  object 
 1   corporate_number            21927 non-null  object 
 2   process                     21927 non-null  object 
 3   correct                     21927 non-null  object 
 4   update_date                 21927 non-null  object 
 5   change_date                 21927 non-null  object 
 6   name                        21927 non-null  object 
 7   name_image_id               354 non-null    object 
 8   kind                        21927 non-null  object 
 9   prefecture_name             21927 non-null  object 
 10  city_name                   21927 non-null  object 
 11  street_number               21862 non-null  object 
 12  address_image_id            88 non-null     object 
 13  prefecture_code             21927 non-null  object 
 14  city_code                   21927 non-null  object 
 15  post_code                   21927 non-null  object 
 16  address_outside             0 non-null      object 
 17  address_outside_image_id    0 non-null      object 
 18  close_date                  2174 non-null   object 
 19  close_cause                 2174 non-null   object 
 20  successor_corporate_number  172 non-null    object 
 21  change_cause                275 non-null    object 
 22  assignment_date             21927 non-null  object 
 23  latest                      21927 non-null  object 
 24  en_name                     64 non-null     object 
 25  en_prefecture_name          64 non-null     object 
 26  en_city_name                64 non-null     object 
 27  en_address_outside          0 non-null      object 
 28  furigana                    10648 non-null  object 
 29  hihyoji                     21927 non-null  object 
 30  pref                        21927 non-null  object 
 31  city                        21927 non-null  object 
 32  town                        21927 non-null  object 
 33  addr                        21927 non-null  object 
 34  lat                         21682 non-null  float64
 35  lng                         21682 non-null  float64
 36  level                       21927 non-null  int64  

[new-village]

we confiremed that 245 of invalid address and unparsed data is in the Shimane data set.

3157	有限会社キリン洋傘店	島根県	松江市		白潟本町75-11	NaN	NaN	2
3176	三栄建設有限会社	島根県	松江市		上乃木町1980	NaN	NaN	2
3298	山新商事有限会社	島根県	松江市		上乃木町3244-2	NaN	NaN	2
3434	有限会社石昭	島根県	松江市		白潟本町69-3	NaN	NaN	2
3951	有限会社イワミ精機	島根県	鹿足郡吉賀町		柿木539-1	NaN	NaN	2
3952	有限会社斎藤石油店	島根県	鹿足郡吉賀町		柿木485-1	NaN	NaN	2
3973	有限会社小笠原	島根県	鹿足郡吉賀町		柿木642-2	NaN	NaN	2
4091	藤澤合名会社	島根県	松江市		None	NaN	NaN	2
4092	合資会社出雲合同自動車	島根県	松江市		None	NaN	NaN	2
4093	合資会社木村盛文館	島根県	松江市		None	NaN	NaN	2
4094	合資会社山陰秩父商会	島根県	松江市		None	NaN	NaN	2
4095	大栄商工合資会社	島根県	松江市		None	NaN	NaN	2
4096	松江商事合資会社	島根県	松江市		None	NaN	NaN	2