Overview

Dataset statistics

Number of variables18
Number of observations1102
Missing cells5871
Missing cells (%)29.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory148.6 KiB
Average record size in memory138.1 B

Variable types

Text12
Categorical2
DateTime3
Boolean1

Dataset

Description삼일운동데이터베이스는 삼일운동 기초 정보를 종합하고 GIS(지리정보체계)와 연동한 데이터베이스로 조선 소요사건 관계 서류, 일본 외무성 기록, 삼일운동 관련 판결문, 재한 선교사 자료 등 삼일운동과 관련한 자료에서 추출한 지역별, 유형별 정보를 제공합니다.
Author교육부 국사편찬위원회
URLhttps://www.data.go.kr/data/15083503/fileData.do

Alerts

경찰사무 여부 has constant value ""Constant
제공 has constant value ""Constant
제공일자 has constant value ""Constant
기구유형 is highly imbalanced (63.1%)Imbalance
폐지일자(추정) has 28 (2.5%) missing valuesMissing
관할구역 헌병 지역코드 has 1005 (91.2%) missing valuesMissing
관할구역 헌병 지역명 has 1003 (91.0%) missing valuesMissing
관할구역 경찰사무 지역코드 has 894 (81.1%) missing valuesMissing
관학구역 경찰사무 지역명 has 895 (81.2%) missing valuesMissing
경찰사무 여부 has 1099 (99.7%) missing valuesMissing
비고 has 944 (85.7%) missing valuesMissing
기구(id) has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:44:16.015874
Analysis finished2023-12-12 17:44:19.146702
Duration3.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기구(id)
Text

UNIQUE 

Distinct1102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2023-12-13T02:44:19.380125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.116152
Min length3

Characters and Unicode

Total characters12250
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1102 ?
Unique (%)100.0%

Sample

1st rowMPH
2nd rowMPHA
3rd rowMPHA01
4th rowMPHA01_00_01
5th rowMPHA01_00_02
ValueCountFrequency (%)
mph 1
 
0.1%
mphj03_00_03 1
 
0.1%
mphj02_00_03 1
 
0.1%
mphj02_00_04 1
 
0.1%
mphj02_00_05 1
 
0.1%
mphj03 1
 
0.1%
mphj04_01_03 1
 
0.1%
mphj03_00_01 1
 
0.1%
mphj03_00_04 1
 
0.1%
mphj04_01_02 1
 
0.1%
Other values (1092) 1092
99.1%
2023-12-13T02:44:19.867089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3437
28.1%
_ 1889
15.4%
H 1213
 
9.9%
M 1206
 
9.8%
P 1102
 
9.0%
1 736
 
6.0%
2 480
 
3.9%
3 346
 
2.8%
4 322
 
2.6%
5 249
 
2.0%
Other values (16) 1270
 
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5926
48.4%
Uppercase Letter 4435
36.2%
Connector Punctuation 1889
 
15.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 1213
27.4%
M 1206
27.2%
P 1102
24.8%
I 121
 
2.7%
A 112
 
2.5%
L 105
 
2.4%
J 96
 
2.2%
F 93
 
2.1%
K 88
 
2.0%
E 62
 
1.4%
Other values (5) 237
 
5.3%
Decimal Number
ValueCountFrequency (%)
0 3437
58.0%
1 736
 
12.4%
2 480
 
8.1%
3 346
 
5.8%
4 322
 
5.4%
5 249
 
4.2%
6 176
 
3.0%
7 96
 
1.6%
8 57
 
1.0%
9 27
 
0.5%
Connector Punctuation
ValueCountFrequency (%)
_ 1889
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7815
63.8%
Latin 4435
36.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 1213
27.4%
M 1206
27.2%
P 1102
24.8%
I 121
 
2.7%
A 112
 
2.5%
L 105
 
2.4%
J 96
 
2.2%
F 93
 
2.1%
K 88
 
2.0%
E 62
 
1.4%
Other values (5) 237
 
5.3%
Common
ValueCountFrequency (%)
0 3437
44.0%
_ 1889
24.2%
1 736
 
9.4%
2 480
 
6.1%
3 346
 
4.4%
4 322
 
4.1%
5 249
 
3.2%
6 176
 
2.3%
7 96
 
1.2%
8 57
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3437
28.1%
_ 1889
15.4%
H 1213
 
9.9%
M 1206
 
9.8%
P 1102
 
9.0%
1 736
 
6.0%
2 480
 
3.9%
3 346
 
2.8%
4 322
 
2.6%
5 249
 
2.0%
Other values (16) 1270
 
10.4%

상위기구(id)
Text

Distinct193
Distinct (%)17.5%
Missing1
Missing (%)0.1%
Memory size8.7 KiB
2023-12-13T02:44:20.261703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.8555858
Min length3

Characters and Unicode

Total characters7548
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.9%

Sample

1st rowMPH
2nd rowMPHA
3rd rowMPHA01
4th rowMPHA01
5th rowMPHA01
ValueCountFrequency (%)
mpha01 24
 
2.2%
mphk02 14
 
1.3%
mph 13
 
1.2%
mphf03 13
 
1.2%
mphd01 12
 
1.1%
mphi05 12
 
1.1%
mphj05 12
 
1.1%
mphm05 11
 
1.0%
mphb04 11
 
1.0%
mpha06 11
 
1.0%
Other values (183) 968
87.9%
2023-12-13T02:44:20.794406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1382
18.3%
H 1211
16.0%
M 1204
16.0%
P 1101
14.6%
1 443
 
5.9%
_ 385
 
5.1%
2 258
 
3.4%
4 180
 
2.4%
3 173
 
2.3%
5 137
 
1.8%
Other values (16) 1074
14.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4395
58.2%
Decimal Number 2768
36.7%
Connector Punctuation 385
 
5.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 1211
27.6%
M 1204
27.4%
P 1101
25.1%
I 120
 
2.7%
A 111
 
2.5%
L 104
 
2.4%
J 95
 
2.2%
F 92
 
2.1%
K 87
 
2.0%
E 61
 
1.4%
Other values (5) 209
 
4.8%
Decimal Number
ValueCountFrequency (%)
0 1382
49.9%
1 443
 
16.0%
2 258
 
9.3%
4 180
 
6.5%
3 173
 
6.2%
5 137
 
4.9%
6 106
 
3.8%
7 51
 
1.8%
8 28
 
1.0%
9 10
 
0.4%
Connector Punctuation
ValueCountFrequency (%)
_ 385
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4395
58.2%
Common 3153
41.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 1211
27.6%
M 1204
27.4%
P 1101
25.1%
I 120
 
2.7%
A 111
 
2.5%
L 104
 
2.4%
J 95
 
2.2%
F 92
 
2.1%
K 87
 
2.0%
E 61
 
1.4%
Other values (5) 209
 
4.8%
Common
ValueCountFrequency (%)
0 1382
43.8%
1 443
 
14.1%
_ 385
 
12.2%
2 258
 
8.2%
4 180
 
5.7%
3 173
 
5.5%
5 137
 
4.3%
6 106
 
3.4%
7 51
 
1.6%
8 28
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1382
18.3%
H 1211
16.0%
M 1204
16.0%
P 1101
14.6%
1 443
 
5.9%
_ 385
 
5.1%
2 258
 
3.4%
4 180
 
2.4%
3 173
 
2.3%
5 137
 
1.8%
Other values (16) 1074
14.2%

상위기구 포함 기구명
Text

Distinct1101
Distinct (%)100.0%
Missing1
Missing (%)0.1%
Memory size8.7 KiB
2023-12-13T02:44:21.050021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length14.647593
Min length12

Characters and Unicode

Total characters16127
Distinct characters611
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1101 ?
Unique (%)100.0%

Sample

1st row朝鮮(駐箚)憲兵隊司令部 京城憲兵隊
2nd row京城憲兵隊 京城憲兵分隊
3rd row京城憲兵分隊 往十里憲兵駐在所
4th row京城憲兵分隊 淸凉里憲兵駐在所
5th row京城憲兵分隊 敦岩里憲兵駐在所
ValueCountFrequency (%)
京城憲兵分隊 25
 
1.1%
成川憲兵分隊 15
 
0.7%
尙州憲兵分隊 14
 
0.6%
朝鮮(駐箚)憲兵隊司令部 13
 
0.6%
裡里憲兵分隊 13
 
0.6%
慶源憲兵分隊 13
 
0.6%
端川憲兵分隊 13
 
0.6%
瑞興憲兵分隊 12
 
0.5%
忠州憲兵分隊 12
 
0.5%
開城憲兵分隊 12
 
0.5%
Other values (1058) 2060
93.6%
2023-12-13T02:44:21.513814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
憲 2202
13.7%
兵 2202
13.7%
所 1390
 
8.6%
分 1202
 
7.5%
1101
 
6.8%
駐 895
 
5.5%
在 882
 
5.5%
隊 816
 
5.1%
遣 498
 
3.1%
里 228
 
1.4%
Other values (601) 4711
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15000
93.0%
Space Separator 1101
 
6.8%
Open Punctuation 13
 
0.1%
Close Punctuation 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
憲 2202
14.7%
兵 2202
14.7%
所 1390
 
9.3%
分 1202
 
8.0%
駐 895
 
6.0%
在 882
 
5.9%
隊 816
 
5.4%
遣 498
 
3.3%
里 228
 
1.5%
川 212
 
1.4%
Other values (598) 4473
29.8%
Space Separator
ValueCountFrequency (%)
1101
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 15000
93.0%
Common 1127
 
7.0%

Most frequent character per script

Han
ValueCountFrequency (%)
憲 2202
14.7%
兵 2202
14.7%
所 1390
 
9.3%
分 1202
 
8.0%
駐 895
 
6.0%
在 882
 
5.9%
隊 816
 
5.4%
遣 498
 
3.3%
里 228
 
1.5%
川 212
 
1.4%
Other values (598) 4473
29.8%
Common
ValueCountFrequency (%)
1101
97.7%
( 13
 
1.2%
) 13
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
CJK 15000
93.0%
ASCII 1127
 
7.0%

Most frequent character per block

CJK
ValueCountFrequency (%)
憲 2202
14.7%
兵 2202
14.7%
所 1390
 
9.3%
分 1202
 
8.0%
駐 895
 
6.0%
在 882
 
5.9%
隊 816
 
5.4%
遣 498
 
3.3%
里 228
 
1.5%
川 212
 
1.4%
Other values (598) 4473
29.8%
ASCII
ValueCountFrequency (%)
1101
97.7%
( 13
 
1.2%
) 13
 
1.2%

기구명
Text

Distinct1068
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2023-12-13T02:44:21.791405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7
Mean length7.2404719
Min length5

Characters and Unicode

Total characters7979
Distinct characters610
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1038 ?
Unique (%)94.2%

Sample

1st row朝鮮(駐箚)憲兵隊司令部
2nd row京城憲兵隊
3rd row京城憲兵分隊
4th row往十里憲兵駐在所
5th row淸凉里憲兵駐在所
ValueCountFrequency (%)
金谷憲兵駐在所 3
 
0.3%
縣里憲兵駐在所 3
 
0.3%
松亭憲兵駐在所 3
 
0.3%
土城憲兵駐在所 3
 
0.3%
五柳憲兵駐在所 2
 
0.2%
雲峰憲兵駐在所 2
 
0.2%
院里憲兵駐在所 2
 
0.2%
廣川憲兵駐在所 2
 
0.2%
館洞憲兵駐在所 2
 
0.2%
西倉憲兵駐在所 2
 
0.2%
Other values (1058) 1078
97.8%
2023-12-13T02:44:22.179674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
憲 1102
13.8%
兵 1102
13.8%
所 1005
12.6%
駐 883
 
11.1%
在 882
 
11.1%
里 203
 
2.5%
分 201
 
2.5%
遣 113
 
1.4%
隊 101
 
1.3%
山 80
 
1.0%
Other values (600) 2307
28.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7977
> 99.9%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
憲 1102
13.8%
兵 1102
13.8%
所 1005
12.6%
駐 883
 
11.1%
在 882
 
11.1%
里 203
 
2.5%
分 201
 
2.5%
遣 113
 
1.4%
隊 101
 
1.3%
山 80
 
1.0%
Other values (598) 2305
28.9%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 7977
> 99.9%
Common 2
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
憲 1102
13.8%
兵 1102
13.8%
所 1005
12.6%
駐 883
 
11.1%
在 882
 
11.1%
里 203
 
2.5%
分 201
 
2.5%
遣 113
 
1.4%
隊 101
 
1.3%
山 80
 
1.0%
Other values (598) 2305
28.9%
Common
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 7977
> 99.9%
ASCII 2
 
< 0.1%

Most frequent character per block

CJK
ValueCountFrequency (%)
憲 1102
13.8%
兵 1102
13.8%
所 1005
12.6%
駐 883
 
11.1%
在 882
 
11.1%
里 203
 
2.5%
分 201
 
2.5%
遣 113
 
1.4%
隊 101
 
1.3%
山 80
 
1.0%
Other values (598) 2305
28.9%
ASCII
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

기구유형
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
헌병주재소
879 
헌병분견소
113 
헌병분대
 
87
헌병대본부
 
13
헌병파출소
 
6
Other values (2)
 
4

Length

Max length6
Median length5
Mean length4.9165154
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row헌병대사령부
2nd row헌병대본부
3rd row헌병분대
4th row헌병주재소
5th row헌병주재소

Common Values

ValueCountFrequency (%)
헌병주재소 879
79.8%
헌병분견소 113
 
10.3%
헌병분대 87
 
7.9%
헌병대본부 13
 
1.2%
헌병파출소 6
 
0.5%
주재소 3
 
0.3%
헌병대사령부 1
 
0.1%

Length

2023-12-13T02:44:22.348556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:22.492124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
헌병주재소 879
79.8%
헌병분견소 113
 
10.3%
헌병분대 87
 
7.9%
헌병대본부 13
 
1.2%
헌병파출소 6
 
0.5%
주재소 3
 
0.3%
헌병대사령부 1
 
0.1%

설치일자(추정)
Date

Distinct17
Distinct (%)1.5%
Missing1
Missing (%)0.1%
Memory size8.7 KiB
Minimum1910-08-29 00:00:00
Maximum1919-01-09 00:00:00
2023-12-13T02:44:22.608536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:44:22.752837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

폐지일자(추정)
Date

MISSING 

Distinct9
Distinct (%)0.8%
Missing28
Missing (%)2.5%
Memory size8.7 KiB
Minimum1914-12-18 00:00:00
Maximum1919-12-01 00:00:00
2023-12-13T02:44:22.868347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:44:23.036355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

설치장소코드
Text

Distinct1087
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2023-12-13T02:44:23.394064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.8647913
Min length3

Characters and Unicode

Total characters10871
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1072 ?
Unique (%)97.3%

Sample

1st rowZ01
2nd rowZ01
3rd rowZ01_00_038
4th rowA05_12_014
5th rowA05_05_019
ValueCountFrequency (%)
z01 2
 
0.2%
z01_00_168 2
 
0.2%
j06_08_003 2
 
0.2%
i04_04_014 2
 
0.2%
a09_07_004 2
 
0.2%
f24_06_008 2
 
0.2%
a19_02_004 2
 
0.2%
a06_01_007 2
 
0.2%
m04_12_003 2
 
0.2%
m16_23 2
 
0.2%
Other values (1077) 1082
98.2%
2023-12-13T02:44:24.061185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3614
33.2%
_ 2165
19.9%
1 1308
 
12.0%
2 496
 
4.6%
3 381
 
3.5%
4 367
 
3.4%
5 354
 
3.3%
6 343
 
3.2%
7 291
 
2.7%
8 241
 
2.2%
Other values (16) 1311
 
12.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7603
69.9%
Connector Punctuation 2165
 
19.9%
Uppercase Letter 1102
 
10.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 121
11.0%
H 111
10.1%
L 105
9.5%
M 104
9.4%
A 102
9.3%
J 96
8.7%
F 93
8.4%
K 88
8.0%
E 62
 
5.6%
D 57
 
5.2%
Other values (4) 163
14.8%
Decimal Number
ValueCountFrequency (%)
0 3614
47.5%
1 1308
 
17.2%
2 496
 
6.5%
3 381
 
5.0%
4 367
 
4.8%
5 354
 
4.7%
6 343
 
4.5%
7 291
 
3.8%
8 241
 
3.2%
9 208
 
2.7%
Connector Punctuation
ValueCountFrequency (%)
_ 2165
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9769
89.9%
Latin 1102
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 121
11.0%
H 111
10.1%
L 105
9.5%
M 104
9.4%
A 102
9.3%
J 96
8.7%
F 93
8.4%
K 88
8.0%
E 62
 
5.6%
D 57
 
5.2%
Other values (4) 163
14.8%
Common
ValueCountFrequency (%)
0 3614
37.0%
_ 2165
22.2%
1 1308
 
13.4%
2 496
 
5.1%
3 381
 
3.9%
4 367
 
3.8%
5 354
 
3.6%
6 343
 
3.5%
7 291
 
3.0%
8 241
 
2.5%
Other values (2) 209
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10871
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3614
33.2%
_ 2165
19.9%
1 1308
 
12.0%
2 496
 
4.6%
3 381
 
3.5%
4 367
 
3.4%
5 354
 
3.3%
6 343
 
3.2%
7 291
 
2.7%
8 241
 
2.2%
Other values (16) 1311
 
12.1%

설치장소명
Text

Distinct1091
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2023-12-13T02:44:24.510794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length15.436479
Min length3

Characters and Unicode

Total characters17011
Distinct characters741
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1080 ?
Unique (%)98.0%

Sample

1st row京城府
2nd row京城府
3rd row京畿道 京城府 大和町二丁目
4th row京畿道 高陽郡 漢芝面 下往十里
5th row京畿道 高陽郡 崇仁面 淸凉里
ValueCountFrequency (%)
咸鏡南道 121
 
2.8%
京畿道 111
 
2.6%
江原道 111
 
2.6%
平安北道 105
 
2.4%
黃海道 104
 
2.4%
咸鏡北道 96
 
2.2%
慶尙北道 93
 
2.1%
平安南道 88
 
2.0%
全羅南道 62
 
1.4%
全羅北道 57
 
1.3%
Other values (1937) 3395
78.2%
2023-12-13T02:44:25.150087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3262
19.2%
道 1118
 
6.6%
郡 1084
 
6.4%
面 1067
 
6.3%
里 806
 
4.7%
北 471
 
2.8%
南 460
 
2.7%
洞 273
 
1.6%
山 271
 
1.6%
安 270
 
1.6%
Other values (731) 7929
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13747
80.8%
Space Separator 3263
 
19.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
道 1118
 
8.1%
郡 1084
 
7.9%
面 1067
 
7.8%
里 806
 
5.9%
北 471
 
3.4%
南 460
 
3.3%
洞 273
 
2.0%
山 271
 
2.0%
安 270
 
2.0%
平 265
 
1.9%
Other values (728) 7662
55.7%
Space Separator
ValueCountFrequency (%)
3262
> 99.9%
　 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
* 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 13747
80.8%
Common 3264
 
19.2%

Most frequent character per script

Han
ValueCountFrequency (%)
道 1118
 
8.1%
郡 1084
 
7.9%
面 1067
 
7.8%
里 806
 
5.9%
北 471
 
3.4%
南 460
 
3.3%
洞 273
 
2.0%
山 271
 
2.0%
安 270
 
2.0%
平 265
 
1.9%
Other values (728) 7662
55.7%
Common
ValueCountFrequency (%)
3262
99.9%
* 1
 
< 0.1%
　 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 13747
80.8%
ASCII 3263
 
19.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3262
> 99.9%
* 1
 
< 0.1%
CJK
ValueCountFrequency (%)
道 1118
 
8.1%
郡 1084
 
7.9%
面 1067
 
7.8%
里 806
 
5.9%
北 471
 
3.4%
南 460
 
3.3%
洞 273
 
2.0%
山 271
 
2.0%
安 270
 
2.0%
平 265
 
1.9%
Other values (728) 7662
55.7%
None
ValueCountFrequency (%)
　 1
100.0%

관할구역 헌병 지역코드
Text

MISSING 

Distinct95
Distinct (%)97.9%
Missing1005
Missing (%)91.2%
Memory size8.7 KiB
2023-12-13T02:44:25.495251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length199
Median length63
Mean length14.134021
Min length1

Characters and Unicode

Total characters1371
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)95.9%

Sample

1st rowA
2nd rowZ01_00_003;Z01_00_077;Z01_00_168;A03_11_001;Z01_00_109;Z01_00_021;Z01_00_036;Z01_00_152;Z01_00_059;Z01_00_074;Z01_00_102;Z01_00_126;Z01_00_041;Z01_00_054;A14;A12;A18;A07;A02
3rd rowA10;A13;A20;A06
4th rowA08;A11;A15
5th rowA08_09;A16_05;A16_16;A16_09;A16_07;A16_10;A16_11;A16_01;A22;A09
ValueCountFrequency (%)
m16;m11 2
 
2.1%
g16;g17;g19;g15;g13 2
 
2.1%
m05;m13;m12 1
 
1.0%
j09;j02_01;j02_05;j02_02;j02_03 1
 
1.0%
j07 1
 
1.0%
j01;j11 1
 
1.0%
j 1
 
1.0%
i02;i10;i05 1
 
1.0%
i13 1
 
1.0%
i07;i01_02;i01_04 1
 
1.0%
Other values (85) 85
87.6%
2023-12-13T02:44:25.965653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 259
18.9%
; 210
15.3%
1 200
14.6%
_ 84
 
6.1%
2 56
 
4.1%
M 48
 
3.5%
5 48
 
3.5%
6 44
 
3.2%
4 40
 
2.9%
3 38
 
2.8%
Other values (16) 344
25.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 770
56.2%
Uppercase Letter 307
 
22.4%
Other Punctuation 210
 
15.3%
Connector Punctuation 84
 
6.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 48
15.6%
F 32
10.4%
H 29
9.4%
A 27
8.8%
G 25
8.1%
I 25
8.1%
E 23
7.5%
K 15
 
4.9%
J 15
 
4.9%
C 15
 
4.9%
Other values (4) 53
17.3%
Decimal Number
ValueCountFrequency (%)
0 259
33.6%
1 200
26.0%
2 56
 
7.3%
5 48
 
6.2%
6 44
 
5.7%
4 40
 
5.2%
3 38
 
4.9%
7 35
 
4.5%
9 26
 
3.4%
8 24
 
3.1%
Other Punctuation
ValueCountFrequency (%)
; 210
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1064
77.6%
Latin 307
 
22.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 48
15.6%
F 32
10.4%
H 29
9.4%
A 27
8.8%
G 25
8.1%
I 25
8.1%
E 23
7.5%
K 15
 
4.9%
J 15
 
4.9%
C 15
 
4.9%
Other values (4) 53
17.3%
Common
ValueCountFrequency (%)
0 259
24.3%
; 210
19.7%
1 200
18.8%
_ 84
 
7.9%
2 56
 
5.3%
5 48
 
4.5%
6 44
 
4.1%
4 40
 
3.8%
3 38
 
3.6%
7 35
 
3.3%
Other values (2) 50
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1371
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 259
18.9%
; 210
15.3%
1 200
14.6%
_ 84
 
6.1%
2 56
 
4.1%
M 48
 
3.5%
5 48
 
3.5%
6 44
 
3.2%
4 40
 
2.9%
3 38
 
2.8%
Other values (16) 344
25.1%

관할구역 헌병 지역명
Text

MISSING 

Distinct97
Distinct (%)98.0%
Missing1003
Missing (%)91.0%
Memory size8.7 KiB
2023-12-13T02:44:26.287269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length175
Median length53
Mean length15.212121
Min length3

Characters and Unicode

Total characters1506
Distinct characters278
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)96.0%

Sample

1st row京畿道
2nd row京畿道 京城府, 高陽郡, 加平郡, 楊州郡 九里面, 蘆海面, 渼金面, 別內面, 瓦阜面, 眞乾面, 榛接面, 和道面
3rd row京城府內 岡崎町, 三坂通, 漢江通, 京町, 榮町, 錦町, 大島町, 淸水町, 彌生町, 山手町, 岩根町, 靑葉町自1丁目 至3丁目, 元町自1丁目 至4丁目, 二村洞, 桃花洞, 麻浦洞始興郡 富川郡 仁川府, 金浦郡 江華郡
4th row龍仁郡 水原郡 振威郡 廣州郡
5th row驪州郡 利川郡 安城郡
ValueCountFrequency (%)
慶尙北道 5
 
1.4%
英陽郡 3
 
0.8%
咸鏡北道 3
 
0.8%
江原道 3
 
0.8%
通川郡 3
 
0.8%
海州郡 2
 
0.5%
榮州郡 2
 
0.5%
奉化郡 2
 
0.5%
忠淸北道 2
 
0.5%
安東郡 2
 
0.5%
Other values (322) 341
92.7%
2023-12-13T02:44:26.806082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
273
18.1%
郡 240
 
15.9%
, 99
 
6.6%
面 70
 
4.6%
山 34
 
2.3%
川 33
 
2.2%
州 28
 
1.9%
道 25
 
1.7%
城 21
 
1.4%
安 19
 
1.3%
Other values (268) 664
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1130
75.0%
Space Separator 273
 
18.1%
Other Punctuation 99
 
6.6%
Decimal Number 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
郡 240
 
21.2%
面 70
 
6.2%
山 34
 
3.0%
川 33
 
2.9%
州 28
 
2.5%
道 25
 
2.2%
城 21
 
1.9%
安 19
 
1.7%
內 16
 
1.4%
原 15
 
1.3%
Other values (263) 629
55.7%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
4 1
25.0%
Space Separator
ValueCountFrequency (%)
273
100.0%
Other Punctuation
ValueCountFrequency (%)
, 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 1130
75.0%
Common 376
 
25.0%

Most frequent character per script

Han
ValueCountFrequency (%)
郡 240
 
21.2%
面 70
 
6.2%
山 34
 
3.0%
川 33
 
2.9%
州 28
 
2.5%
道 25
 
2.2%
城 21
 
1.9%
安 19
 
1.7%
內 16
 
1.4%
原 15
 
1.3%
Other values (263) 629
55.7%
Common
ValueCountFrequency (%)
273
72.6%
, 99
 
26.3%
1 2
 
0.5%
3 1
 
0.3%
4 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
CJK 1130
75.0%
ASCII 376
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
273
72.6%
, 99
 
26.3%
1 2
 
0.5%
3 1
 
0.3%
4 1
 
0.3%
CJK
ValueCountFrequency (%)
郡 240
 
21.2%
面 70
 
6.2%
山 34
 
3.0%
川 33
 
2.9%
州 28
 
2.5%
道 25
 
2.2%
城 21
 
1.9%
安 19
 
1.7%
內 16
 
1.4%
原 15
 
1.3%
Other values (263) 629
55.7%

관할구역 경찰사무 지역코드
Text

MISSING 

Distinct202
Distinct (%)97.1%
Missing894
Missing (%)81.1%
Memory size8.7 KiB
2023-12-13T02:44:27.041296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length230
Median length146
Mean length19.360577
Min length1

Characters and Unicode

Total characters4027
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique196 ?
Unique (%)94.2%

Sample

1st rowA
2nd rowA05;A16_02; A16_03; A16_04; A16_06; A16_08; A16_13; A16_14; A16_15
3rd rowA01
4th rowZ01_00_003;Z01_00_077;Z01_00_168;Z01_00_126;Z01_00_168;Z01_00_021;Z01_00_036;Z01_00_041;Z01_00_006;Z01_00_059;Z01_00_074;Z01_00_102;Z01_00_120;Z01_00_121;Z01_00_122;Z01_00_123;Z01_00_109;Z01_00_152;Z01_00_153;Z01_00_154;Z01_00_155
5th rowA10
ValueCountFrequency (%)
b02 2
 
0.9%
f16 2
 
0.9%
f10 2
 
0.9%
g16_09;g16_15;g16_10 2
 
0.9%
f08 2
 
0.9%
b08 2
 
0.9%
j02_01;j02_05;j02_02;j02_03 1
 
0.5%
i10_05;i10_11;i10_01;i10_10 1
 
0.5%
j06_06;j06_03 1
 
0.5%
i10_06;i10_13;i10_05;i10_11;i10_01;i10_10;i05 1
 
0.5%
Other values (200) 200
92.6%
2023-12-13T02:44:27.361768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 832
20.7%
1 649
16.1%
_ 546
13.6%
; 441
11.0%
6 172
 
4.3%
2 139
 
3.5%
3 132
 
3.3%
4 131
 
3.3%
M 119
 
3.0%
5 106
 
2.6%
Other values (18) 760
18.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2382
59.2%
Uppercase Letter 648
 
16.1%
Connector Punctuation 546
 
13.6%
Other Punctuation 441
 
11.0%
Space Separator 9
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 119
18.4%
I 83
12.8%
G 61
9.4%
H 56
8.6%
A 51
7.9%
J 51
7.9%
D 50
7.7%
L 44
 
6.8%
K 38
 
5.9%
B 27
 
4.2%
Other values (4) 68
10.5%
Decimal Number
ValueCountFrequency (%)
0 832
34.9%
1 649
27.2%
6 172
 
7.2%
2 139
 
5.8%
3 132
 
5.5%
4 131
 
5.5%
5 106
 
4.5%
7 89
 
3.7%
9 75
 
3.1%
8 57
 
2.4%
Connector Punctuation
ValueCountFrequency (%)
_ 546
100.0%
Other Punctuation
ValueCountFrequency (%)
; 441
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3379
83.9%
Latin 648
 
16.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 832
24.6%
1 649
19.2%
_ 546
16.2%
; 441
13.1%
6 172
 
5.1%
2 139
 
4.1%
3 132
 
3.9%
4 131
 
3.9%
5 106
 
3.1%
7 89
 
2.6%
Other values (4) 142
 
4.2%
Latin
ValueCountFrequency (%)
M 119
18.4%
I 83
12.8%
G 61
9.4%
H 56
8.6%
A 51
7.9%
J 51
7.9%
D 50
7.7%
L 44
 
6.8%
K 38
 
5.9%
B 27
 
4.2%
Other values (4) 68
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4027
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 832
20.7%
1 649
16.1%
_ 546
13.6%
; 441
11.0%
6 172
 
4.3%
2 139
 
3.5%
3 132
 
3.3%
4 131
 
3.3%
M 119
 
3.0%
5 106
 
2.6%
Other values (18) 760
18.9%

관학구역 경찰사무 지역명
Text

MISSING 

Distinct202
Distinct (%)97.6%
Missing895
Missing (%)81.2%
Memory size8.7 KiB
2023-12-13T02:44:27.609455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length145
Median length77
Mean length21.130435
Min length3

Characters and Unicode

Total characters4374
Distinct characters413
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)95.2%

Sample

1st row京畿道
2nd row京畿道 高陽郡,楊州郡 九里面, 蘆海面, 渼金面, 別內面, 瓦阜面, 眞乾面, 榛接面, 和道面
3rd row京畿道 加平郡
4th row京畿道 京城府 內 岡崎町, 三坂通, 漢江通, 京町, 榮町, 錦町, 大島町, 淸水町, 彌生町, 山手町, 岩根町, 靑葉町自1丁目 至3丁目, 元町自1丁目 至4丁目, 麻浦洞, 二村洞
5th row京畿道 龍仁郡
ValueCountFrequency (%)
內 89
 
8.5%
咸鏡南道 24
 
2.3%
江原道 22
 
2.1%
黃海道 20
 
1.9%
慶尙北道 18
 
1.7%
京畿道 17
 
1.6%
咸鏡北道 17
 
1.6%
慶尙南道 16
 
1.5%
平安南道 14
 
1.3%
平安北道 13
 
1.2%
Other values (593) 793
76.0%
2023-12-13T02:44:28.070483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
837
19.1%
面 515
 
11.8%
, 445
 
10.2%
道 214
 
4.9%
郡 213
 
4.9%
內 117
 
2.7%
南 109
 
2.5%
北 103
 
2.4%
山 71
 
1.6%
咸 50
 
1.1%
Other values (403) 1700
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3088
70.6%
Space Separator 837
 
19.1%
Other Punctuation 445
 
10.2%
Decimal Number 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
面 515
 
16.7%
道 214
 
6.9%
郡 213
 
6.9%
內 117
 
3.8%
南 109
 
3.5%
北 103
 
3.3%
山 71
 
2.3%
咸 50
 
1.6%
鏡 46
 
1.5%
川 42
 
1.4%
Other values (398) 1608
52.1%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
4 1
25.0%
Space Separator
ValueCountFrequency (%)
837
100.0%
Other Punctuation
ValueCountFrequency (%)
, 445
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 3088
70.6%
Common 1286
29.4%

Most frequent character per script

Han
ValueCountFrequency (%)
面 515
 
16.7%
道 214
 
6.9%
郡 213
 
6.9%
內 117
 
3.8%
南 109
 
3.5%
北 103
 
3.3%
山 71
 
2.3%
咸 50
 
1.6%
鏡 46
 
1.5%
川 42
 
1.4%
Other values (398) 1608
52.1%
Common
ValueCountFrequency (%)
837
65.1%
, 445
34.6%
1 2
 
0.2%
3 1
 
0.1%
4 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 3088
70.6%
ASCII 1286
29.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
837
65.1%
, 445
34.6%
1 2
 
0.2%
3 1
 
0.1%
4 1
 
0.1%
CJK
ValueCountFrequency (%)
面 515
 
16.7%
道 214
 
6.9%
郡 213
 
6.9%
內 117
 
3.8%
南 109
 
3.5%
北 103
 
3.3%
山 71
 
2.3%
咸 50
 
1.6%
鏡 46
 
1.5%
川 42
 
1.4%
Other values (398) 1608
52.1%

경찰사무 여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)33.3%
Missing1099
Missing (%)99.7%
Memory size2.3 KiB
True
 
3
(Missing)
1099 
ValueCountFrequency (%)
True 3
 
0.3%
(Missing) 1099
99.7%
2023-12-13T02:44:28.183434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

출전자료
Text

Distinct172
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2023-12-13T02:44:28.387966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length314
Median length83
Mean length93.18784
Min length28

Characters and Unicode

Total characters102693
Distinct characters96
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)10.0%

Sample

1st row朝鮮駐箚憲兵條例 勅令第343號; 明治43年勅令第296號統監府警察官署官制中改正ノ件 勅令第358號
2nd row朝鮮駐箚憲兵條例 勅令第343號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號; 明治43年勅令第296號統監府警察官署官制中改正ノ件 勅令第358號
3rd row警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 朝鮮總督府令第126號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號中 改正 朝鮮總督府令第116號; 警察署ノ事務ヲ取扱フ憲兵分隊ノ名稱,位置,管轄區域 朝鮮總督府令第126號中 改正 朝鮮總督府令第117號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號中 改正 朝鮮總督府令第74號; 警察署ノ事務ヲ取扱フ憲兵分隊ノ名稱,位置,管轄區域 朝鮮總督府令第126號中 改正 朝鮮總督府令第75號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號
4th row憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第1號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號
5th row憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第1號
ValueCountFrequency (%)
憲兵隊司令部告示第2號 1772
24.5%
憲兵派遣所及出張所名稱,位置改正 1009
14.0%
憲兵派遣所及出張所名稱改稱 884
12.2%
憲兵隊司令部告示第1號 848
11.7%
憲兵派遣所及出張所名稱,位置 791
11.0%
朝鮮駐劄憲兵隊ノ管區及配置 357
 
4.9%
警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 271
 
3.8%
朝鮮總督府令第125號 199
 
2.8%
朝鮮總督府令第126號 186
 
2.6%
朝鮮總督府令第126號中改正 85
 
1.2%
Other values (49) 816
11.3%
2023-12-13T02:44:28.750153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
憲 6341
 
6.2%
兵 6341
 
6.2%
6118
 
6.0%
所 5658
 
5.5%
稱 3890
 
3.8%
第 3650
 
3.6%
號 3650
 
3.6%
令 3636
 
3.5%
隊 3371
 
3.3%
及 3055
 
3.0%
Other values (86) 56983
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86099
83.8%
Space Separator 6118
 
6.0%
Decimal Number 5453
 
5.3%
Other Punctuation 5021
 
4.9%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
憲 6341
 
7.4%
兵 6341
 
7.4%
所 5658
 
6.6%
稱 3890
 
4.5%
第 3650
 
4.2%
號 3650
 
4.2%
令 3636
 
4.2%
隊 3371
 
3.9%
及 3055
 
3.5%
名 3006
 
3.5%
Other values (71) 43501
50.5%
Decimal Number
ValueCountFrequency (%)
2 2422
44.4%
1 1620
29.7%
5 465
 
8.5%
6 371
 
6.8%
4 250
 
4.6%
3 114
 
2.1%
7 83
 
1.5%
9 69
 
1.3%
8 36
 
0.7%
0 23
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 2709
54.0%
; 2312
46.0%
Space Separator
ValueCountFrequency (%)
6118
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 84479
82.3%
Common 16594
 
16.2%
Katakana 1614
 
1.6%
Hangul 6
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
憲 6341
 
7.5%
兵 6341
 
7.5%
所 5658
 
6.7%
稱 3890
 
4.6%
第 3650
 
4.3%
號 3650
 
4.3%
令 3636
 
4.3%
隊 3371
 
4.0%
及 3055
 
3.6%
名 3006
 
3.6%
Other values (62) 41881
49.6%
Common
ValueCountFrequency (%)
6118
36.9%
, 2709
16.3%
2 2422
 
14.6%
; 2312
 
13.9%
1 1620
 
9.8%
5 465
 
2.8%
6 371
 
2.2%
4 250
 
1.5%
3 114
 
0.7%
7 83
 
0.5%
Other values (5) 130
 
0.8%
Hangul
ValueCountFrequency (%)
에 1
16.7%
보 1
16.7%
제 1
16.7%
건 1
16.7%
한 1
16.7%
관 1
16.7%
Katakana
ValueCountFrequency (%)
ノ 1000
62.0%
ヲ 307
 
19.0%
フ 307
 
19.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 84479
82.3%
ASCII 16594
 
16.2%
Katakana 1614
 
1.6%
Hangul 6
 
< 0.1%

Most frequent character per block

CJK
ValueCountFrequency (%)
憲 6341
 
7.5%
兵 6341
 
7.5%
所 5658
 
6.7%
稱 3890
 
4.6%
第 3650
 
4.3%
號 3650
 
4.3%
令 3636
 
4.3%
隊 3371
 
4.0%
及 3055
 
3.6%
名 3006
 
3.6%
Other values (62) 41881
49.6%
ASCII
ValueCountFrequency (%)
6118
36.9%
, 2709
16.3%
2 2422
 
14.6%
; 2312
 
13.9%
1 1620
 
9.8%
5 465
 
2.8%
6 371
 
2.2%
4 250
 
1.5%
3 114
 
0.7%
7 83
 
0.5%
Other values (5) 130
 
0.8%
Katakana
ValueCountFrequency (%)
ノ 1000
62.0%
ヲ 307
 
19.0%
フ 307
 
19.0%
Hangul
ValueCountFrequency (%)
에 1
16.7%
보 1
16.7%
제 1
16.7%
건 1
16.7%
한 1
16.7%
관 1
16.7%

비고
Text

MISSING 

Distinct69
Distinct (%)43.7%
Missing944
Missing (%)85.7%
Memory size8.7 KiB
2023-12-13T02:44:29.006323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length362
Median length205
Mean length50.594937
Min length12

Characters and Unicode

Total characters7994
Distinct characters292
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)39.2%

Sample

1st row헌병사령관이 경무총장을 겸한다.
2nd row각 도의 헌병대장이 각 도의 경무부장을 겸한다.
3rd row헌병분대의 경찰사무 관할 구역은 헌병분대 직속 관할 구역만을 표기. 경성제1, 제2헌병분대를 경성헌병분대로 통합하고 양평분견소 소속을 여주헌병분대로, 파주분견소 소속을 개성헌병분대로 옮김(1915.12). 1916년 9월 6일 고양군 전체를 관할구역으로 함(고양경찰서 폐지, 용산헌병분대 관할 고양군 한지면도 관할을 경성헌병분대로 옮김)
4th row1914년 8월 27일 헌병대사령부 고시에는 나타나지 않으며 1917년 3월 1일 고시에 처음 나타난다. 해당 시기 사이의 헌병대사령부 고시에도 확인이 되지 않으므로 설치 시기를 1917년 3월 1일로 추정한다.
5th row1914년 8월 27일 헌병대사령부 고시에는 나타나지 않으며 1917년 3월 1일 고시에 처음 나타난다. 해당 시기 사이의 헌병대사령부 고시에도 확인이 되지 않으므로 설치 시기를 1917년 3월 1일로 추정한다.
ValueCountFrequency (%)
관할 159
 
9.0%
구역은 79
 
4.4%
직속 79
 
4.4%
헌병분대의 78
 
4.4%
헌병분대 78
 
4.4%
구역만을 78
 
4.4%
경찰사무 78
 
4.4%
표기 77
 
4.3%
1917년 30
 
1.7%
폐지 30
 
1.7%
Other values (403) 1010
56.9%
2023-12-13T02:44:29.446311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1672
 
20.9%
1 309
 
3.9%
분 282
 
3.5%
대 278
 
3.5%
헌 252
 
3.2%
병 252
 
3.2%
관 198
 
2.5%
할 181
 
2.3%
. 171
 
2.1%
구 165
 
2.1%
Other values (282) 4234
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5381
67.3%
Space Separator 1672
 
20.9%
Decimal Number 707
 
8.8%
Other Punctuation 208
 
2.6%
Lowercase Letter 8
 
0.1%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%
Connector Punctuation 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
분 282
 
5.2%
대 278
 
5.2%
헌 252
 
4.7%
병 252
 
4.7%
관 198
 
3.7%
할 181
 
3.4%
구 165
 
3.1%
역 164
 
3.0%
경 154
 
2.9%
의 120
 
2.2%
Other values (256) 3335
62.0%
Decimal Number
ValueCountFrequency (%)
1 309
43.7%
9 143
20.2%
7 66
 
9.3%
8 55
 
7.8%
2 38
 
5.4%
4 25
 
3.5%
3 23
 
3.3%
6 17
 
2.4%
5 17
 
2.4%
0 14
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
s 2
25.0%
k 1
12.5%
m 1
12.5%
y 1
12.5%
j 1
12.5%
r 1
12.5%
b 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 171
82.2%
, 36
 
17.3%
/ 1
 
0.5%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
1672
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5281
66.1%
Common 2605
32.6%
Han 100
 
1.3%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
분 282
 
5.3%
대 278
 
5.3%
헌 252
 
4.8%
병 252
 
4.8%
관 198
 
3.7%
할 181
 
3.4%
구 165
 
3.1%
역 164
 
3.1%
경 154
 
2.9%
의 120
 
2.3%
Other values (206) 3235
61.3%
Han
ValueCountFrequency (%)
所 9
 
9.0%
憲 8
 
8.0%
兵 8
 
8.0%
在 5
 
5.0%
駐 5
 
5.0%
遣 4
 
4.0%
分 3
 
3.0%
沙 3
 
3.0%
川 3
 
3.0%
石 2
 
2.0%
Other values (40) 50
50.0%
Common
ValueCountFrequency (%)
1672
64.2%
1 309
 
11.9%
. 171
 
6.6%
9 143
 
5.5%
7 66
 
2.5%
8 55
 
2.1%
2 38
 
1.5%
, 36
 
1.4%
4 25
 
1.0%
3 23
 
0.9%
Other values (9) 67
 
2.6%
Latin
ValueCountFrequency (%)
s 2
25.0%
k 1
12.5%
m 1
12.5%
y 1
12.5%
j 1
12.5%
r 1
12.5%
b 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5281
66.1%
ASCII 2613
32.7%
CJK 100
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1672
64.0%
1 309
 
11.8%
. 171
 
6.5%
9 143
 
5.5%
7 66
 
2.5%
8 55
 
2.1%
2 38
 
1.5%
, 36
 
1.4%
4 25
 
1.0%
3 23
 
0.9%
Other values (16) 75
 
2.9%
Hangul
ValueCountFrequency (%)
분 282
 
5.3%
대 278
 
5.3%
헌 252
 
4.8%
병 252
 
4.8%
관 198
 
3.7%
할 181
 
3.4%
구 165
 
3.1%
역 164
 
3.1%
경 154
 
2.9%
의 120
 
2.3%
Other values (206) 3235
61.3%
CJK
ValueCountFrequency (%)
所 9
 
9.0%
憲 8
 
8.0%
兵 8
 
8.0%
在 5
 
5.0%
駐 5
 
5.0%
遣 4
 
4.0%
分 3
 
3.0%
沙 3
 
3.0%
川 3
 
3.0%
石 2
 
2.0%
Other values (40) 50
50.0%

제공
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
국사편찬위원회
1102 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국사편찬위원회
2nd row국사편찬위원회
3rd row국사편찬위원회
4th row국사편찬위원회
5th row국사편찬위원회

Common Values

ValueCountFrequency (%)
국사편찬위원회 1102
100.0%

Length

2023-12-13T02:44:29.587662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:29.722296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국사편찬위원회 1102
100.0%

제공일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
Minimum2020-01-31 00:00:00
Maximum2020-01-31 00:00:00
2023-12-13T02:44:29.822551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:44:29.946838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T02:44:30.033545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기구유형설치일자(추정)폐지일자(추정)관할구역 헌병 지역코드관할구역 헌병 지역명비고
기구유형1.0000.8980.7041.0001.0001.000
설치일자(추정)0.8981.0000.6540.0000.0000.990
폐지일자(추정)0.7040.6541.0000.5000.4481.000
관할구역 헌병 지역코드1.0000.0000.5001.0001.0000.000
관할구역 헌병 지역명1.0000.0000.4481.0001.0000.000
비고1.0000.9901.0000.0000.0001.000

Missing values

2023-12-13T02:44:18.160126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:44:18.465345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-13T02:44:19.005297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기구(id)상위기구(id)상위기구 포함 기구명기구명기구유형설치일자(추정)폐지일자(추정)설치장소코드설치장소명관할구역 헌병 지역코드관할구역 헌병 지역명관할구역 경찰사무 지역코드관학구역 경찰사무 지역명경찰사무 여부출전자료비고제공제공일자
0MPH<NA><NA>朝鮮(駐箚)憲兵隊司令部헌병대사령부1910-08-29<NA>Z01京城府<NA><NA><NA><NA><NA>朝鮮駐箚憲兵條例 勅令第343號; 明治43年勅令第296號統監府警察官署官制中改正ノ件 勅令第358號헌병사령관이 경무총장을 겸한다.국사편찬위원회2020-01-31
1MPHAMPH朝鮮(駐箚)憲兵隊司令部 京城憲兵隊京城憲兵隊헌병대본부1910-08-29<NA>Z01京城府A京畿道A京畿道<NA>朝鮮駐箚憲兵條例 勅令第343號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號; 明治43年勅令第296號統監府警察官署官制中改正ノ件 勅令第358號각 도의 헌병대장이 각 도의 경무부장을 겸한다.국사편찬위원회2020-01-31
2MPHA01MPHA京城憲兵隊 京城憲兵分隊京城憲兵分隊헌병분대1910-08-29<NA>Z01_00_038京畿道 京城府 大和町二丁目<NA>京畿道 京城府, 高陽郡, 加平郡, 楊州郡 九里面, 蘆海面, 渼金面, 別內面, 瓦阜面, 眞乾面, 榛接面, 和道面A05;A16_02; A16_03; A16_04; A16_06; A16_08; A16_13; A16_14; A16_15京畿道 高陽郡,楊州郡 九里面, 蘆海面, 渼金面, 別內面, 瓦阜面, 眞乾面, 榛接面, 和道面<NA>警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 朝鮮總督府令第126號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號中 改正 朝鮮總督府令第116號; 警察署ノ事務ヲ取扱フ憲兵分隊ノ名稱,位置,管轄區域 朝鮮總督府令第126號中 改正 朝鮮總督府令第117號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號中 改正 朝鮮總督府令第74號; 警察署ノ事務ヲ取扱フ憲兵分隊ノ名稱,位置,管轄區域 朝鮮總督府令第126號中 改正 朝鮮總督府令第75號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號헌병분대의 경찰사무 관할 구역은 헌병분대 직속 관할 구역만을 표기. 경성제1, 제2헌병분대를 경성헌병분대로 통합하고 양평분견소 소속을 여주헌병분대로, 파주분견소 소속을 개성헌병분대로 옮김(1915.12). 1916년 9월 6일 고양군 전체를 관할구역으로 함(고양경찰서 폐지, 용산헌병분대 관할 고양군 한지면도 관할을 경성헌병분대로 옮김)국사편찬위원회2020-01-31
3MPHA01_00_01MPHA01京城憲兵分隊 往十里憲兵駐在所往十里憲兵駐在所헌병주재소1917-03-011919-08-20A05_12_014京畿道 高陽郡 漢芝面 下往十里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第1號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號1914년 8월 27일 헌병대사령부 고시에는 나타나지 않으며 1917년 3월 1일 고시에 처음 나타난다. 해당 시기 사이의 헌병대사령부 고시에도 확인이 되지 않으므로 설치 시기를 1917년 3월 1일로 추정한다.국사편찬위원회2020-01-31
4MPHA01_00_02MPHA01京城憲兵分隊 淸凉里憲兵駐在所淸凉里憲兵駐在所헌병주재소1917-03-011919-08-20A05_05_019京畿道 高陽郡 崇仁面 淸凉里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第1號1914년 8월 27일 헌병대사령부 고시에는 나타나지 않으며 1917년 3월 1일 고시에 처음 나타난다. 해당 시기 사이의 헌병대사령부 고시에도 확인이 되지 않으므로 설치 시기를 1917년 3월 1일로 추정한다.국사편찬위원회2020-01-31
5MPHA01_00_03MPHA01京城憲兵分隊 敦岩里憲兵駐在所敦岩里憲兵駐在所헌병주재소1917-03-011919-08-20A05_05_002京畿道 高陽郡 崇仁面 敦岩里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第1號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號1914년 8월 27일 헌병대사령부 고시에는 나타나지 않으며 1917년 3월 1일 고시에 처음 나타난다. 해당 시기 사이의 헌병대사령부 고시에도 확인이 되지 않으므로 설치 시기를 1917년 3월 1일로 추정한다.국사편찬위원회2020-01-31
6MPHA01_00_04MPHA01京城憲兵分隊 碌磻峴憲兵駐在所碌磻峴憲兵駐在所헌병주재소1917-03-011919-08-20A05_09_005京畿道 高陽郡 恩平面 碌磻里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第1號1914년 8월 27일 헌병대사령부 고시에는 나타나지 않으며 1917년 3월 1일 고시에 처음 나타난다. 해당 시기 사이의 헌병대사령부 고시에도 확인이 되지 않으므로 설치 시기를 1917년 3월 1일로 추정한다.국사편찬위원회2020-01-31
7MPHA01_00_05MPHA01京城憲兵分隊 孔德里憲兵駐在所孔德里憲兵駐在所헌병주재소1917-03-011919-08-20A05_02_015京畿道 高陽郡 龍江面 孔德里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第1號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號1914년 8월 27일 헌병대사령부 고시에는 나타나지 않으며 1917년 3월 1일 고시에 처음 나타난다. 해당 시기 사이의 헌병대사령부 고시에도 확인이 되지 않으므로 설치 시기를 1917년 3월 1일로 추정한다.국사편찬위원회2020-01-31
8MPHA01_00_06MPHA01京城憲兵分隊 纛島憲兵駐在所纛島憲兵駐在所헌병주재소1917-03-011919-08-20A05_01_004京畿道 高陽郡 纛島面 東纛島里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第1號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號1914년 8월 27일 헌병대사령부 고시에는 나타나지 않으며 1917년 3월 1일 고시에 처음 나타난다. 해당 시기 사이의 헌병대사령부 고시에도 확인이 되지 않으므로 설치 시기를 1917년 3월 1일로 추정한다.국사편찬위원회2020-01-31
9MPHA01_00_07MPHA01京城憲兵分隊 春風亭憲兵駐在所春風亭憲兵駐在所헌병주재소1917-03-011919-08-20A05_01_001京畿道 高陽郡 纛島面 廣壯里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第1號1914년 8월 27일 헌병대사령부 고시에는 나타나지 않으며 1917년 3월 1일 고시에 처음 나타난다. 해당 시기 사이의 헌병대사령부 고시에도 확인이 되지 않으므로 설치 시기를 1917년 3월 1일로 추정한다.국사편찬위원회2020-01-31
기구(id)상위기구(id)상위기구 포함 기구명기구명기구유형설치일자(추정)폐지일자(추정)설치장소코드설치장소명관할구역 헌병 지역코드관할구역 헌병 지역명관할구역 경찰사무 지역코드관학구역 경찰사무 지역명경찰사무 여부출전자료비고제공제공일자
1092MPHM07MPHM海州憲兵隊 松禾憲兵分隊松禾憲兵分隊헌병분대1910-08-291919-12-01M05_06_009黃海道 松禾郡 松禾面 邑內里M05;M13;M12松禾郡 長淵郡 殷栗郡M05黃海道 松禾郡<NA>朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號; 警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 朝鮮總督府令第126號中改正 朝鮮總督府令第45號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號中改正 朝鮮總督府令第44號; 警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 朝鮮總督府令第126號헌병분대의 경찰사무 관할 구역은 헌병분대 직속 관할 구역만을 표기국사편찬위원회2020-01-31
1093MPHM07_00_01MPHM07松禾憲兵分隊 水橋憲兵駐在所水橋憲兵駐在所헌병주재소1914-09-011919-08-20M05_04_006黃海道 松禾郡 蓬萊面 水橋里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置 憲兵隊司令部告示第1號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號<NA>국사편찬위원회2020-01-31
1094MPHM07_00_02MPHM07松禾憲兵分隊 艾川憲兵駐在所艾川憲兵駐在所헌병주재소1914-09-011919-08-20M05_09_005黃海道 松禾郡 長陽面 艾川里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱,位置 憲兵隊司令部告示第1號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號<NA>국사편찬위원회2020-01-31
1095MPHM07_00_03MPHM07松禾憲兵分隊 公稅憲兵駐在所公稅憲兵駐在所헌병주재소1914-09-011919-08-20M05_01_002黃海道 松禾郡 桃源面 公稅里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱,位置 憲兵隊司令部告示第1號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號<NA>국사편찬위원회2020-01-31
1096MPHM07_00_04MPHM07松禾憲兵分隊 豊川憲兵駐在所豊川憲兵駐在所헌병주재소1914-09-011919-08-20M05_12_003黃海道 松禾郡 豊海面 城上里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱,位置 憲兵隊司令部告示第1號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號<NA>국사편찬위원회2020-01-31
1097MPHM07_00_05MPHM07松禾憲兵分隊 沙器憲兵駐在所沙器憲兵駐在所헌병주재소1914-09-011919-08-20M05_07_006黃海道 松禾郡 雲遊面 沙器里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱,位置 憲兵隊司令部告示第1號; 憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號<NA>국사편찬위원회2020-01-31
1098MPHM07_00_06MPHM07松禾憲兵分隊 石灘憲兵駐在所石灘憲兵駐在所헌병주재소1917-08-011919-08-20M05_11_002黃海道 松禾郡 泉洞面 石灘里<NA><NA><NA><NA><NA>憲兵派遣所及出張所名稱改稱 憲兵隊司令部告示第2號; 憲兵派遣所及出張所名稱,位置改正 憲兵隊司令部告示第2號<NA>국사편찬위원회2020-01-31
1099MPHMX1MPHM海州憲兵隊 海州憲兵分隊海州憲兵分隊헌병분대1910-08-291917-08-01M16_23黃海道 海州郡 海州面M16;M11海州郡 瓮津郡M16_12;M16_01;M16_16;M16_03;M16_02;M16_05;M16_18;M16_15;M16_10;M11_07;M11_04;M11_06黃海道 海州郡 內 席洞面, 茄佐面, 月祿面, 高山面, 檢丹面, 代車面, 壯谷面, 雲山面, 彌栗面, 甕津郡 內 富民面, 龍淵面, 鳳鷗面<NA>朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號中改正 朝鮮總督府令第44號; 警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 朝鮮總督府令第126號中改正 朝鮮總督府令第45號; 警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 朝鮮總督府令第126號1917.8.1 해주분대 폐지, 옹진분대 신설국사편찬위원회2020-01-31
1100MPHMX1_X1MPHMX1海州憲兵分隊 馬山憲兵分遣所馬山憲兵分遣所헌병분견소1911-11-071917-08-01M11_05黃海道 甕津郡 馬山<NA><NA>M11_03;M11_11;M11_09;M11_10;M11_02;M11_01;M11_08;M11_05黃海道 甕津郡 內 東南面, 興嵋面, 西面, 龍泉面 交井面, 茄川面, 北面, 馬山面<NA>警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 朝鮮總督府令第126號中改正 朝鮮總督府令第45號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號中改正 朝鮮總督府令第44號; 警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 朝鮮總督府令第126號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第135號1917.8.1 해주분대 폐지, 옹진분대 신설과 함께 마산분견소 폐지. 사실상 해주분대 폐지하고 마산분견소를 옹진분대로 승격시킨 것국사편찬위원회2020-01-31
1101MPHMX2MPHM海州憲兵隊 新幕憲兵分隊新幕憲兵分隊헌병분대1910-08-291917-08-01M04_12_003黃海道 瑞興郡 禾回面 新幕里M02;M04_05;M04_02;M04_04;M04_06;A06_14;M04_12;M04_07;M07_07;M07_04;M07_03;M07_01;M07_02;M07_06;M07_05;M03_01;M03_10;M06_03;M15_06;M15_08;M15_10;M08_09;M15_09;M15_02;M15_11;M15_07;M15_03;M15_01;M15_04金川郡, 瑞興郡內 龍坪面, 內德面, 東部面, 梅陽面, 中部面, 禾回面, 木甘面, 新溪郡內 中東面, 赤余面, 美水面, 麻西面, 古面, 多面, 栗面, 沙芝面, 鳳山郡內 龜淵面, 山水面, 遂安郡內 大坪面, 平山郡內 寶山面, 西峰面, 新巖面, 文武面, 細谷面, 外邑面, 金巖面, 安城面, 上月面, 麟山面, 古之面, 馬山面M15_05;M15_08;M15_07;M15_02;M15_03;M04_12;M04_04;M04_06黃海道 平山郡 內 文武面, 西峰面, 上月面, 金巖面, 外邑面, 麟山面, 瑞興郡 內 禾回面, 東部面, 梅陽面<NA>朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號; 警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 朝鮮總督府令第126號; 朝鮮駐劄憲兵隊ノ管區及配置 朝鮮總督府令第125號中改正 朝鮮總督府令第44號; 警察署ノ事務ヲ取扱フ憲兵分隊,憲兵分遣所ノ名稱,位置,管轄區域 朝鮮總督府令第126號中改正 朝鮮總督府令第45號1917.8.1 서흥헌병분대 신설과 함께 폐지국사편찬위원회2020-01-31