Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells12933
Missing cells (%)12.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory869.1 KiB
Average record size in memory89.0 B

Variable types

Text8
Categorical1
Boolean1

Dataset

Description시대별 행정기관의 명칭 변경과 관련 근거법에 대한 데이터로 기관의 변천연혁을 확인하고 시대별 기록물의 생산기관을 파악할 수 있습니다.
Author행정안전부 국가기록원
URLhttps://www.data.go.kr/data/15084424/fileData.do

Alerts

설립일 has 468 (4.7%) missing valuesMissing
폐지일 has 3027 (30.3%) missing valuesMissing
설치관련법령 has 8233 (82.3%) missing valuesMissing
설치근거 has 1204 (12.0%) missing valuesMissing
전거코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:05:02.993429
Analysis finished2023-12-12 02:05:04.994308
Duration2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관코드
Text

Distinct9892
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:05:05.204352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length7.109
Min length7

Characters and Unicode

Total characters71090
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9819 ?
Unique (%)98.2%

Sample

1st row9941913
2nd row1214498
3rd row9908456
4th row1330447
5th row1272320
ValueCountFrequency (%)
9918826 7
 
0.1%
4130036 6
 
0.1%
9918943 6
 
0.1%
9918829 4
 
< 0.1%
9922462 4
 
< 0.1%
9919324 4
 
< 0.1%
9918697 4
 
< 0.1%
4060044 4
 
< 0.1%
9918828 3
 
< 0.1%
9917564 3
 
< 0.1%
Other values (9882) 9955
99.6%
2023-12-12T11:05:05.675665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15052
21.2%
0 11094
15.6%
3 8474
11.9%
9 7904
11.1%
2 6987
9.8%
4 6301
8.9%
5 4628
 
6.5%
7 3635
 
5.1%
6 3633
 
5.1%
8 3374
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71082
> 99.9%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15052
21.2%
0 11094
15.6%
3 8474
11.9%
9 7904
11.1%
2 6987
9.8%
4 6301
8.9%
5 4628
 
6.5%
7 3635
 
5.1%
6 3633
 
5.1%
8 3374
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71082
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15052
21.2%
0 11094
15.6%
3 8474
11.9%
9 7904
11.1%
2 6987
9.8%
4 6301
8.9%
5 4628
 
6.5%
7 3635
 
5.1%
6 3633
 
5.1%
8 3374
 
4.7%
Latin
ValueCountFrequency (%)
B 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15052
21.2%
0 11094
15.6%
3 8474
11.9%
9 7904
11.1%
2 6987
9.8%
4 6301
8.9%
5 4628
 
6.5%
7 3635
 
5.1%
6 3633
 
5.1%
8 3374
 
4.7%

전거코드
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:05:06.217407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowOG0092002
2nd rowOG0121168
3rd rowOG0029057
4th rowOG0123295
5th rowOG0082214
ValueCountFrequency (%)
og0092002 1
 
< 0.1%
og0019149 1
 
< 0.1%
og0091186 1
 
< 0.1%
og0090412 1
 
< 0.1%
og0072362 1
 
< 0.1%
og0063169 1
 
< 0.1%
og0119970 1
 
< 0.1%
pn0010757 1
 
< 0.1%
og0030370 1
 
< 0.1%
og0075129 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-12T11:05:06.734814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24814
27.6%
O 8709
 
9.7%
G 8709
 
9.7%
1 6622
 
7.4%
2 6083
 
6.8%
3 5367
 
6.0%
7 5127
 
5.7%
8 4926
 
5.5%
9 4604
 
5.1%
6 4300
 
4.8%
Other values (4) 10739
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70000
77.8%
Uppercase Letter 20000
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24814
35.4%
1 6622
 
9.5%
2 6083
 
8.7%
3 5367
 
7.7%
7 5127
 
7.3%
8 4926
 
7.0%
9 4604
 
6.6%
6 4300
 
6.1%
4 4147
 
5.9%
5 4010
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
O 8709
43.5%
G 8709
43.5%
P 1291
 
6.5%
N 1291
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
Common 70000
77.8%
Latin 20000
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24814
35.4%
1 6622
 
9.5%
2 6083
 
8.7%
3 5367
 
7.7%
7 5127
 
7.3%
8 4926
 
7.0%
9 4604
 
6.6%
6 4300
 
6.1%
4 4147
 
5.9%
5 4010
 
5.7%
Latin
ValueCountFrequency (%)
O 8709
43.5%
G 8709
43.5%
P 1291
 
6.5%
N 1291
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24814
27.6%
O 8709
 
9.7%
G 8709
 
9.7%
1 6622
 
7.4%
2 6083
 
6.8%
3 5367
 
6.0%
7 5127
 
5.7%
8 4926
 
5.5%
9 4604
 
5.1%
6 4300
 
4.8%
Other values (4) 10739
11.9%

기관명
Text

Distinct6458
Distinct (%)64.6%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T11:05:07.062906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length5.1661166
Min length2

Characters and Unicode

Total characters51656
Distinct characters513
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5412 ?
Unique (%)54.1%

Sample

1st row엄다우체국
2nd row재산법인납세과
3rd row관리국
4th row연평파출소
5th row보호과
ValueCountFrequency (%)
총무과 132
 
1.3%
경무과 91
 
0.9%
관리과 91
 
0.9%
수사과 90
 
0.9%
서무과 84
 
0.8%
운영지원과 82
 
0.8%
정보과 65
 
0.7%
경비과 65
 
0.7%
보안과 64
 
0.6%
방범과 56
 
0.6%
Other values (6448) 9179
91.8%
2023-12-12T11:05:07.559607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 3977
 
7.7%
관 1552
 
3.0%
국 1534
 
3.0%
사 1297
 
2.5%
동 1163
 
2.3%
정 1105
 
2.1%
지 1080
 
2.1%
소 1038
 
2.0%
우 885
 
1.7%
무 884
 
1.7%
Other values (503) 37141
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50107
97.0%
Decimal Number 1331
 
2.6%
Uppercase Letter 58
 
0.1%
Dash Punctuation 43
 
0.1%
Close Punctuation 38
 
0.1%
Open Punctuation 38
 
0.1%
Other Punctuation 36
 
0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 3977
 
7.9%
관 1552
 
3.1%
국 1534
 
3.1%
사 1297
 
2.6%
동 1163
 
2.3%
정 1105
 
2.2%
지 1080
 
2.2%
소 1038
 
2.1%
우 885
 
1.8%
무 884
 
1.8%
Other values (470) 35592
71.0%
Uppercase Letter
ValueCountFrequency (%)
P 41
70.7%
C 3
 
5.2%
I 3
 
5.2%
O 2
 
3.4%
S 2
 
3.4%
U 1
 
1.7%
F 1
 
1.7%
M 1
 
1.7%
E 1
 
1.7%
D 1
 
1.7%
Other values (2) 2
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 448
33.7%
2 422
31.7%
3 160
 
12.0%
0 78
 
5.9%
5 62
 
4.7%
4 47
 
3.5%
6 45
 
3.4%
9 26
 
2.0%
8 23
 
1.7%
7 20
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
n 1
20.0%
e 1
20.0%
p 1
20.0%
o 1
20.0%
t 1
20.0%
Other Punctuation
ValueCountFrequency (%)
· 21
58.3%
. 14
38.9%
& 1
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50107
97.0%
Common 1486
 
2.9%
Latin 63
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 3977
 
7.9%
관 1552
 
3.1%
국 1534
 
3.1%
사 1297
 
2.6%
동 1163
 
2.3%
정 1105
 
2.2%
지 1080
 
2.2%
소 1038
 
2.1%
우 885
 
1.8%
무 884
 
1.8%
Other values (470) 35592
71.0%
Latin
ValueCountFrequency (%)
P 41
65.1%
C 3
 
4.8%
I 3
 
4.8%
O 2
 
3.2%
S 2
 
3.2%
U 1
 
1.6%
n 1
 
1.6%
F 1
 
1.6%
M 1
 
1.6%
e 1
 
1.6%
Other values (7) 7
 
11.1%
Common
ValueCountFrequency (%)
1 448
30.1%
2 422
28.4%
3 160
 
10.8%
0 78
 
5.2%
5 62
 
4.2%
4 47
 
3.2%
6 45
 
3.0%
- 43
 
2.9%
) 38
 
2.6%
( 38
 
2.6%
Other values (6) 105
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50107
97.0%
ASCII 1528
 
3.0%
None 21
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 3977
 
7.9%
관 1552
 
3.1%
국 1534
 
3.1%
사 1297
 
2.6%
동 1163
 
2.3%
정 1105
 
2.2%
지 1080
 
2.2%
소 1038
 
2.1%
우 885
 
1.8%
무 884
 
1.8%
Other values (470) 35592
71.0%
ASCII
ValueCountFrequency (%)
1 448
29.3%
2 422
27.6%
3 160
 
10.5%
0 78
 
5.1%
5 62
 
4.1%
4 47
 
3.1%
6 45
 
2.9%
- 43
 
2.8%
P 41
 
2.7%
) 38
 
2.5%
Other values (22) 144
 
9.4%
None
ValueCountFrequency (%)
· 21
100.0%

기관전체명
Text

Distinct9872
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:05:07.968858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length34
Mean length19.6434
Min length3

Characters and Unicode

Total characters196434
Distinct characters525
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9780 ?
Unique (%)97.8%

Sample

1st row정보통신부 전남체신청 함평우체국 엄다우체국
2nd row국세청 서울지방국세청 관악세무서 재산법인납세과
3rd row체신부 전북체신청 관리국
4th row경찰청 인천광역시지방경찰청 인천중부경찰서 연평파출소
5th row법무부 서울출입국관리사무소 보호과
ValueCountFrequency (%)
경찰청 1416
 
4.3%
정보통신부 647
 
2.0%
국세청 546
 
1.7%
경기도 340
 
1.0%
우정사업본부 257
 
0.8%
법무부 257
 
0.8%
노동부 209
 
0.6%
해양경찰청 207
 
0.6%
서울체신청 195
 
0.6%
경기도지방경찰청 195
 
0.6%
Other values (8770) 28730
87.1%
2023-12-12T11:05:08.498130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23001
 
11.7%
청 8357
 
4.3%
부 7410
 
3.8%
경 7111
 
3.6%
국 5932
 
3.0%
지 5118
 
2.6%
찰 4840
 
2.5%
과 4449
 
2.3%
방 3975
 
2.0%
정 3893
 
2.0%
Other values (515) 122348
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 171657
87.4%
Space Separator 23001
 
11.7%
Decimal Number 1518
 
0.8%
Uppercase Letter 73
 
< 0.1%
Close Punctuation 46
 
< 0.1%
Open Punctuation 46
 
< 0.1%
Other Punctuation 45
 
< 0.1%
Dash Punctuation 43
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 8357
 
4.9%
부 7410
 
4.3%
경 7111
 
4.1%
국 5932
 
3.5%
지 5118
 
3.0%
찰 4840
 
2.8%
과 4449
 
2.6%
방 3975
 
2.3%
정 3893
 
2.3%
서 3766
 
2.2%
Other values (479) 116806
68.0%
Uppercase Letter
ValueCountFrequency (%)
P 42
57.5%
T 5
 
6.8%
I 4
 
5.5%
F 4
 
5.5%
A 4
 
5.5%
C 3
 
4.1%
U 2
 
2.7%
O 2
 
2.7%
S 2
 
2.7%
M 1
 
1.4%
Other values (4) 4
 
5.5%
Decimal Number
ValueCountFrequency (%)
1 528
34.8%
2 478
31.5%
3 170
 
11.2%
0 85
 
5.6%
5 68
 
4.5%
4 61
 
4.0%
6 45
 
3.0%
9 39
 
2.6%
8 23
 
1.5%
7 21
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
p 1
20.0%
o 1
20.0%
t 1
20.0%
e 1
20.0%
n 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 22
48.9%
· 22
48.9%
& 1
 
2.2%
Space Separator
ValueCountFrequency (%)
23001
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 171657
87.4%
Common 24699
 
12.6%
Latin 78
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 8357
 
4.9%
부 7410
 
4.3%
경 7111
 
4.1%
국 5932
 
3.5%
지 5118
 
3.0%
찰 4840
 
2.8%
과 4449
 
2.6%
방 3975
 
2.3%
정 3893
 
2.3%
서 3766
 
2.2%
Other values (479) 116806
68.0%
Latin
ValueCountFrequency (%)
P 42
53.8%
T 5
 
6.4%
I 4
 
5.1%
F 4
 
5.1%
A 4
 
5.1%
C 3
 
3.8%
U 2
 
2.6%
O 2
 
2.6%
S 2
 
2.6%
p 1
 
1.3%
Other values (9) 9
 
11.5%
Common
ValueCountFrequency (%)
23001
93.1%
1 528
 
2.1%
2 478
 
1.9%
3 170
 
0.7%
0 85
 
0.3%
5 68
 
0.3%
4 61
 
0.2%
) 46
 
0.2%
( 46
 
0.2%
6 45
 
0.2%
Other values (7) 171
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 171657
87.4%
ASCII 24755
 
12.6%
None 22
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23001
92.9%
1 528
 
2.1%
2 478
 
1.9%
3 170
 
0.7%
0 85
 
0.3%
5 68
 
0.3%
4 61
 
0.2%
) 46
 
0.2%
( 46
 
0.2%
6 45
 
0.2%
Other values (25) 227
 
0.9%
Hangul
ValueCountFrequency (%)
청 8357
 
4.9%
부 7410
 
4.3%
경 7111
 
4.1%
국 5932
 
3.5%
지 5118
 
3.0%
찰 4840
 
2.8%
과 4449
 
2.6%
방 3975
 
2.3%
정 3893
 
2.3%
서 3766
 
2.2%
Other values (479) 116806
68.0%
None
ValueCountFrequency (%)
· 22
100.0%

차수
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
4552 
4
4241 
2
1163 
1
 
44

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row3
4th row4
5th row3

Common Values

ValueCountFrequency (%)
3 4552
45.5%
4 4241
42.4%
2 1163
 
11.6%
1 44
 
0.4%

Length

2023-12-12T11:05:08.700412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:05:08.810488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 4552
45.5%
4 4241
42.4%
2 1163
 
11.6%
1 44
 
0.4%

설립일
Text

MISSING 

Distinct1569
Distinct (%)16.5%
Missing468
Missing (%)4.7%
Memory size156.2 KiB
2023-12-12T11:05:09.140189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9861519
Min length4

Characters and Unicode

Total characters95188
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique721 ?
Unique (%)7.6%

Sample

1st row2015-04-01
2nd row1984-11-02
3rd row2001-12-27
4th row2013-03-23
5th row1985-12-28
ValueCountFrequency (%)
2013-03-23 435
 
4.6%
1994-12-23 379
 
4.0%
1991-07-31 313
 
3.3%
1999-05-24 213
 
2.2%
2008-02-29 196
 
2.1%
2014-11-19 164
 
1.7%
2008-03-03 153
 
1.6%
1998-02-28 148
 
1.6%
1995-01-01 131
 
1.4%
1981-11-02 117
 
1.2%
Other values (1558) 7282
76.4%
2023-12-12T11:05:09.674813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19628
20.6%
- 19019
20.0%
1 16451
17.3%
2 11346
11.9%
9 9925
10.4%
3 5365
 
5.6%
8 3290
 
3.5%
7 2834
 
3.0%
4 2798
 
2.9%
5 2332
 
2.4%
Other values (5) 2200
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76158
80.0%
Dash Punctuation 19019
 
20.0%
Space Separator 8
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19628
25.8%
1 16451
21.6%
2 11346
14.9%
9 9925
13.0%
3 5365
 
7.0%
8 3290
 
4.3%
7 2834
 
3.7%
4 2798
 
3.7%
5 2332
 
3.1%
6 2189
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
u 1
50.0%
l 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 19019
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 95185
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19628
20.6%
- 19019
20.0%
1 16451
17.3%
2 11346
11.9%
9 9925
10.4%
3 5365
 
5.6%
8 3290
 
3.5%
7 2834
 
3.0%
4 2798
 
2.9%
5 2332
 
2.4%
Other values (2) 2197
 
2.3%
Latin
ValueCountFrequency (%)
J 1
33.3%
u 1
33.3%
l 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 95188
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19628
20.6%
- 19019
20.0%
1 16451
17.3%
2 11346
11.9%
9 9925
10.4%
3 5365
 
5.6%
8 3290
 
3.5%
7 2834
 
3.0%
4 2798
 
2.9%
5 2332
 
2.4%
Other values (5) 2200
 
2.3%

폐지일
Text

MISSING 

Distinct1151
Distinct (%)16.5%
Missing3027
Missing (%)30.3%
Memory size156.2 KiB
2023-12-12T11:05:10.016824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9962713
Min length4

Characters and Unicode

Total characters69704
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique509 ?
Unique (%)7.3%

Sample

1st row1999-05-24
2nd row1994-12-23
3rd row2013-07-01
4th row1994-08-03
5th row1991-07-30
ValueCountFrequency (%)
1999-05-24 666
 
9.6%
2013-03-23 550
 
7.9%
1994-12-23 219
 
3.1%
1998-02-28 203
 
2.9%
2014-11-19 164
 
2.4%
2008-02-29 139
 
2.0%
1999-09-01 111
 
1.6%
1995-01-01 104
 
1.5%
1981-11-02 96
 
1.4%
2001-12-27 94
 
1.3%
Other values (1140) 4623
66.3%
2023-12-12T11:05:10.539283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 13932
20.0%
0 13893
19.9%
1 11430
16.4%
2 8941
12.8%
9 7934
11.4%
3 3728
 
5.3%
8 2480
 
3.6%
5 2186
 
3.1%
4 2117
 
3.0%
7 1712
 
2.5%
Other values (2) 1351
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55740
80.0%
Dash Punctuation 13932
 
20.0%
Space Separator 32
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13893
24.9%
1 11430
20.5%
2 8941
16.0%
9 7934
14.2%
3 3728
 
6.7%
8 2480
 
4.4%
5 2186
 
3.9%
4 2117
 
3.8%
7 1712
 
3.1%
6 1319
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 13932
100.0%
Space Separator
ValueCountFrequency (%)
32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69704
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 13932
20.0%
0 13893
19.9%
1 11430
16.4%
2 8941
12.8%
9 7934
11.4%
3 3728
 
5.3%
8 2480
 
3.6%
5 2186
 
3.1%
4 2117
 
3.0%
7 1712
 
2.5%
Other values (2) 1351
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69704
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 13932
20.0%
0 13893
19.9%
1 11430
16.4%
2 8941
12.8%
9 7934
11.4%
3 3728
 
5.3%
8 2480
 
3.6%
5 2186
 
3.1%
4 2117
 
3.0%
7 1712
 
2.5%
Other values (2) 1351
 
1.9%

존재여부
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
6975 
True
3025 
ValueCountFrequency (%)
False 6975
69.8%
True 3025
30.2%
2023-12-12T11:05:10.701629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

설치관련법령
Text

MISSING 

Distinct1234
Distinct (%)69.8%
Missing8233
Missing (%)82.3%
Memory size156.2 KiB
2023-12-12T11:05:10.929467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length105
Median length82
Mean length46.255235
Min length4

Characters and Unicode

Total characters81733
Distinct characters213
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique966 ?
Unique (%)54.7%

Sample

1st row내무부직제 일부개정 1986.6.14 대통령령 제11922호 제20조 1항
2nd row농림수산부와그소속기관직제 전문개정 1994.12.23 대통령령 제14443호 제48조 제1항
3rd row법무부와그소속기관직제 일부개정 1991.9.30 대통령령 제13483호 제29조 제1항
4th row산업자원부와그소속기관직제 제정 1998.2.28 대통령령 제15728호 제4조 제3항
5th row통계청과 그 소속기관 직제 일부개정 2005.7.22 대통령령 18960호 별표1
ValueCountFrequency (%)
대통령령 1182
 
9.4%
일부개정 979
 
7.8%
제1항 487
 
3.9%
전문개정 333
 
2.7%
제정 325
 
2.6%
1항 263
 
2.1%
제4조 225
 
1.8%
제2조 220
 
1.8%
직제 194
 
1.5%
그 174
 
1.4%
Other values (1750) 8179
65.1%
2023-12-12T11:05:11.396043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10811
 
13.2%
1 6077
 
7.4%
제 5737
 
7.0%
. 3610
 
4.4%
9 3219
 
3.9%
2 3218
 
3.9%
령 2886
 
3.5%
부 2348
 
2.9%
정 2045
 
2.5%
0 1986
 
2.4%
Other values (203) 39796
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43156
52.8%
Decimal Number 23652
28.9%
Space Separator 10811
 
13.2%
Other Punctuation 4002
 
4.9%
Math Symbol 104
 
0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 5737
 
13.3%
령 2886
 
6.7%
부 2348
 
5.4%
정 2045
 
4.7%
호 1838
 
4.3%
조 1739
 
4.0%
직 1599
 
3.7%
통 1401
 
3.2%
개 1343
 
3.1%
관 1311
 
3.0%
Other values (183) 20909
48.4%
Decimal Number
ValueCountFrequency (%)
1 6077
25.7%
9 3219
13.6%
2 3218
13.6%
0 1986
 
8.4%
3 1979
 
8.4%
4 1639
 
6.9%
8 1616
 
6.8%
5 1477
 
6.2%
6 1228
 
5.2%
7 1213
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 3610
90.2%
· 224
 
5.6%
, 166
 
4.1%
: 1
 
< 0.1%
/ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
< 52
50.0%
> 52
50.0%
Space Separator
ValueCountFrequency (%)
10811
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43156
52.8%
Common 38577
47.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 5737
 
13.3%
령 2886
 
6.7%
부 2348
 
5.4%
정 2045
 
4.7%
호 1838
 
4.3%
조 1739
 
4.0%
직 1599
 
3.7%
통 1401
 
3.2%
개 1343
 
3.1%
관 1311
 
3.0%
Other values (183) 20909
48.4%
Common
ValueCountFrequency (%)
10811
28.0%
1 6077
15.8%
. 3610
 
9.4%
9 3219
 
8.3%
2 3218
 
8.3%
0 1986
 
5.1%
3 1979
 
5.1%
4 1639
 
4.2%
8 1616
 
4.2%
5 1477
 
3.8%
Other values (10) 2945
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43156
52.8%
ASCII 38353
46.9%
None 224
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10811
28.2%
1 6077
15.8%
. 3610
 
9.4%
9 3219
 
8.4%
2 3218
 
8.4%
0 1986
 
5.2%
3 1979
 
5.2%
4 1639
 
4.3%
8 1616
 
4.2%
5 1477
 
3.9%
Other values (9) 2721
 
7.1%
Hangul
ValueCountFrequency (%)
제 5737
 
13.3%
령 2886
 
6.7%
부 2348
 
5.4%
정 2045
 
4.7%
호 1838
 
4.3%
조 1739
 
4.0%
직 1599
 
3.7%
통 1401
 
3.2%
개 1343
 
3.1%
관 1311
 
3.0%
Other values (183) 20909
48.4%
None
ValueCountFrequency (%)
· 224
100.0%

설치근거
Text

MISSING 

Distinct3421
Distinct (%)38.9%
Missing1204
Missing (%)12.0%
Memory size156.2 KiB
2023-12-12T11:05:11.718752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length132
Median length84
Mean length54.326285
Min length1

Characters and Unicode

Total characters477854
Distinct characters308
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2357 ?
Unique (%)26.8%

Sample

1st row국세청과 그 소속기관 직제 시행규칙 [시행 2015.2.26.] [기획재정부령 제465호, 2015.2.26., 일부개정]
2nd row지방체신관서직제[일부개정 1984.11.02 대통령령 제11538호] 제5조
3rd row법무부와 그 소속기관 직제 시행규칙 [시행 2013.3.23.] [법무부령 제787호, 2013.3.23., 일부개정]
4th row구리시등 11개 시설치와 군관할구역의 조정 및 금성시 명칭변경에 관한 법률 제3798호(1985. 12. 28 공포, 1986. 1. 1 시행)
5th row내무부직제[대통령령 제11922호, 1986.6.14, 일부개정]
ValueCountFrequency (%)
시행 4393
 
6.2%
일부개정 3550
 
5.0%
대통령령 3342
 
4.7%
직제 3061
 
4.3%
소속기관 3026
 
4.3%
그 3022
 
4.3%
시행규칙 2067
 
2.9%
제정 1768
 
2.5%
2013.3.23 702
 
1.0%
제1호 686
 
1.0%
Other values (5289) 44918
63.7%
2023-12-12T11:05:12.179626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61774
 
12.9%
. 34995
 
7.3%
1 30099
 
6.3%
2 22041
 
4.6%
제 20713
 
4.3%
0 16124
 
3.4%
9 15509
 
3.2%
3 12456
 
2.6%
부 11526
 
2.4%
령 11406
 
2.4%
Other values (298) 241211
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 216180
45.2%
Decimal Number 129460
27.1%
Space Separator 61774
 
12.9%
Other Punctuation 45255
 
9.5%
Open Punctuation 12497
 
2.6%
Close Punctuation 12486
 
2.6%
Dash Punctuation 126
 
< 0.1%
Math Symbol 76
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 20713
 
9.6%
부 11526
 
5.3%
령 11406
 
5.3%
정 10218
 
4.7%
호 8773
 
4.1%
시 8393
 
3.9%
행 8357
 
3.9%
관 7364
 
3.4%
직 6833
 
3.2%
기 5947
 
2.8%
Other values (272) 116650
54.0%
Decimal Number
ValueCountFrequency (%)
1 30099
23.2%
2 22041
17.0%
0 16124
12.5%
9 15509
12.0%
3 12456
9.6%
4 8683
 
6.7%
8 6937
 
5.4%
5 6287
 
4.9%
7 6235
 
4.8%
6 5089
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 34995
77.3%
, 9593
 
21.2%
· 593
 
1.3%
/ 49
 
0.1%
" 22
 
< 0.1%
: 3
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
[ 11323
90.6%
( 1173
 
9.4%
〔 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
] 11312
90.6%
) 1173
 
9.4%
〕 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
> 38
50.0%
< 38
50.0%
Space Separator
ValueCountFrequency (%)
61774
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 261674
54.8%
Hangul 216180
45.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 20713
 
9.6%
부 11526
 
5.3%
령 11406
 
5.3%
정 10218
 
4.7%
호 8773
 
4.1%
시 8393
 
3.9%
행 8357
 
3.9%
관 7364
 
3.4%
직 6833
 
3.2%
기 5947
 
2.8%
Other values (272) 116650
54.0%
Common
ValueCountFrequency (%)
61774
23.6%
. 34995
13.4%
1 30099
11.5%
2 22041
 
8.4%
0 16124
 
6.2%
9 15509
 
5.9%
3 12456
 
4.8%
[ 11323
 
4.3%
] 11312
 
4.3%
, 9593
 
3.7%
Other values (16) 36448
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 261079
54.6%
Hangul 216172
45.2%
None 595
 
0.1%
Compat Jamo 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61774
23.7%
. 34995
13.4%
1 30099
11.5%
2 22041
 
8.4%
0 16124
 
6.2%
9 15509
 
5.9%
3 12456
 
4.8%
[ 11323
 
4.3%
] 11312
 
4.3%
, 9593
 
3.7%
Other values (13) 35853
13.7%
Hangul
ValueCountFrequency (%)
제 20713
 
9.6%
부 11526
 
5.3%
령 11406
 
5.3%
정 10218
 
4.7%
호 8773
 
4.1%
시 8393
 
3.9%
행 8357
 
3.9%
관 7364
 
3.4%
직 6833
 
3.2%
기 5947
 
2.8%
Other values (271) 116642
54.0%
None
ValueCountFrequency (%)
· 593
99.7%
〔 1
 
0.2%
〕 1
 
0.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 8
100.0%

Correlations

2023-12-12T11:05:12.293462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차수존재여부
차수1.0000.114
존재여부0.1141.000
2023-12-12T11:05:12.384019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차수존재여부
차수1.0000.075
존재여부0.0751.000
2023-12-12T11:05:12.470126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차수존재여부
차수1.0000.075
존재여부0.0751.000

Missing values

2023-12-12T11:05:04.559126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:05:04.747315image/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.
2023-12-12T11:05:04.892349image/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

기관코드전거코드기관명기관전체명차수설립일폐지일존재여부설치관련법령설치근거
483029941913OG0092002엄다우체국정보통신부 전남체신청 함평우체국 엄다우체국4<NA>1999-05-24N<NA><NA>
512391214498OG0121168재산법인납세과국세청 서울지방국세청 관악세무서 재산법인납세과42015-04-01<NA>Y<NA>국세청과 그 소속기관 직제 시행규칙 [시행 2015.2.26.] [기획재정부령 제465호, 2015.2.26., 일부개정]
144499908456OG0029057관리국체신부 전북체신청 관리국31984-11-021994-12-23N<NA>지방체신관서직제[일부개정 1984.11.02 대통령령 제11538호] 제5조
523211330447OG0123295연평파출소경찰청 인천광역시지방경찰청 인천중부경찰서 연평파출소42001-12-27<NA>Y<NA><NA>
218821272320OG0082214보호과법무부 서울출입국관리사무소 보호과32013-03-232013-07-01N<NA>법무부와 그 소속기관 직제 시행규칙 [시행 2013.3.23.] [법무부령 제787호, 2013.3.23., 일부개정]
286149923683PN0005894대관동충청남도 대천시 대관동31985-12-281994-08-03N<NA>구리시등 11개 시설치와 군관할구역의 조정 및 금성시 명칭변경에 관한 법률 제3798호(1985. 12. 28 공포, 1986. 1. 1 시행)
336179902415OG0016971대공2과내무부 치안본부 대공1부 대공2과41986-06-141991-07-30N내무부직제 일부개정 1986.6.14 대통령령 제11922호 제20조 1항내무부직제[대통령령 제11922호, 1986.6.14, 일부개정]
282783660053PN0005430갈마2동대전광역시 서구 갈마2동31997-12-04<NA>Y<NA>구 조례 제451호(1997. 12. 4 공포)
231191444011OG0088550봉남우체국정보통신부 전북체신청 봉남우체국3<NA><NA>Y<NA><NA>
353919910466OG0030685공사2과항만청 부산지방항만관리청 부산항건설사무소 공사2과41976-03-131977-12-16N<NA>지방항만관서직제[제정 1976.03.13 대통령령 제8019호] 제13조
기관코드전거코드기관명기관전체명차수설립일폐지일존재여부설치관련법령설치근거
529011332984OG0123901한산파출소경찰청 충청남도지방경찰청 서천경찰서 한산파출소42006-09-08<NA>Y<NA>충청남도지방경찰청과 경찰서의 조직 및 사무분장규칙 [시행 2006.9.8.] [훈령 제222호, 2006.9.8., 개정]
441521331344OG0083833형사과경찰청 경상북도지방경찰청 구미경찰서 형사과42004-12-31<NA>Y<NA>경찰청과그소속기관등직제시행규칙 [시행 2004.12.31.] [행정자치부령 제262호, 2004.12.31., 일부개정]
2883311000565OG0007537석탄국동력자원부 석탄국21978-01-011981-11-02N<NA>-
323405370054PN0012344마전동경상남도 거제시 마전동31995-01-01<NA>Y<NA>경기도 남양주시 등 33개 도농복합 형태의 시설치 등에 관한 법률[법률 제4774호(1994.08.03공포)]
414901612152OG0078729구조물과국토해양부 익산지방국토관리청 광주국토관리사무소 구조물과42012-03-302013-03-23N<NA>국토해양부와 그 소속기관 직제 시행규칙 [시행 2012.3.30.] [국토해양부령 제454호, 2012.3.30., 일부개정]
106659901617OG0016684운영과원호처 춘천원호지청 운영과31981-11-021984-12-31N지방원호관서직제 전문개정 1981.11.2 대통령령 제10607호 제6조 1항지방원호관서직제 전문개정 1981.11.2 대통령령 제10607호 제6조 1항
421801311333OG0080362제도총괄과행정안전부 조직실 제도정책관 제도총괄과42008-05-142013-03-23N<NA>행정안전부와 그 소속기관 직제 시행규칙 [시행 2008.5.14.] [행정안전부령 제17호, 2008.5.14., 전부개정]
306834720050PN0010085고산면전라북도 완주군 고산면31935-10-01<NA>Y<NA>조선총독부령 제112호(1935.09.28공포)
420451311538OG0080113기록정리과행정안전부 국가기록원 대통령기록관 기록정리과42012-06-072013-03-23N<NA>행정안전부와 그 소속기관 직제 시행규칙 [시행 2012.6.7.] [행정안전부령 제296호, 2012.6.7., 일부개정]
190021494401OG0074387천안지청고용노동부 대전지방고용노동청 천안지청32010-07-12<NA>Y<NA>고용노동부와 그 소속기관 직제 시행규칙 [시행 2010.7.12.] [고용노동부령 제1호, 2010.7.12., 일부개정]