Overview

Dataset statistics

Number of variables4
Number of observations264
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory32.5 B

Variable types

Text3
Categorical1

Dataset

Description체류자격은 일반체류자격과 영주자격으로 나누어지며, 입국하는 외국인은 일반체류자격 혹은 영주자격 중 하나에 해당하는 체류자격을 가지며, 일반체류자격 90일 이하의 기간동안 머물 수 있는 단기체류자격과 90일을 초과하여 법무부령으로 정하는 체류기간 상한 범위에서 거주할 수 있는 체류자격 등 체류자격 분류코드를 제공
Author법무부
URLhttps://www.data.go.kr/data/15103561/fileData.do

Alerts

체류자격 신약호 has unique valuesUnique
체류자격명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:59:33.077576
Analysis finished2023-12-12 06:59:33.602708
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

체류자격 신약호
Text

UNIQUE 

Distinct264
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T15:59:33.998154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.3863636
Min length3

Characters and Unicode

Total characters1422
Distinct characters21
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

Unique264 ?
Unique (%)100.0%

Sample

1st rowA-1
2nd rowA-2
3rd rowA-2-1
4th rowA-2-2
5th rowA-2-3
ValueCountFrequency (%)
a-1 1
 
0.4%
f-4-21 1
 
0.4%
f-5-6 1
 
0.4%
f-3-16 1
 
0.4%
f-3-17 1
 
0.4%
f-3-91 1
 
0.4%
f-4-11 1
 
0.4%
f-4-12 1
 
0.4%
f-4-13 1
 
0.4%
f-4-14 1
 
0.4%
Other values (254) 254
96.2%
2023-12-12T15:59:34.632775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 515
36.2%
1 163
 
11.5%
2 139
 
9.8%
F 110
 
7.7%
3 73
 
5.1%
4 60
 
4.2%
9 57
 
4.0%
5 52
 
3.7%
D 41
 
2.9%
E 32
 
2.3%
Other values (11) 180
 
12.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 641
45.1%
Dash Punctuation 515
36.2%
Uppercase Letter 266
18.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 163
25.4%
2 139
21.7%
3 73
11.4%
4 60
 
9.4%
9 57
 
8.9%
5 52
 
8.1%
7 31
 
4.8%
6 26
 
4.1%
8 26
 
4.1%
0 14
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
F 110
41.4%
D 41
 
15.4%
E 32
 
12.0%
H 25
 
9.4%
G 19
 
7.1%
C 15
 
5.6%
B 12
 
4.5%
A 9
 
3.4%
S 2
 
0.8%
T 1
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 515
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1156
81.3%
Latin 266
 
18.7%

Most frequent character per script

Common
ValueCountFrequency (%)
- 515
44.6%
1 163
 
14.1%
2 139
 
12.0%
3 73
 
6.3%
4 60
 
5.2%
9 57
 
4.9%
5 52
 
4.5%
7 31
 
2.7%
6 26
 
2.2%
8 26
 
2.2%
Latin
ValueCountFrequency (%)
F 110
41.4%
D 41
 
15.4%
E 32
 
12.0%
H 25
 
9.4%
G 19
 
7.1%
C 15
 
5.6%
B 12
 
4.5%
A 9
 
3.4%
S 2
 
0.8%
T 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 515
36.2%
1 163
 
11.5%
2 139
 
9.8%
F 110
 
7.7%
3 73
 
5.1%
4 60
 
4.2%
9 57
 
4.0%
5 52
 
3.7%
D 41
 
2.9%
E 32
 
2.3%
Other values (11) 180
 
12.7%

법명
Categorical

Distinct40
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
방문동거
25 
영주
25 
방문취업
24 
재외동포
21 
기타
19 
Other values (35)
150 

Length

Max length6
Median length4
Mean length3.2045455
Min length2

Unique

Unique14 ?
Unique (%)5.3%

Sample

1st row외교
2nd row공무
3rd row공무
4th row공무
5th row공무

Common Values

ValueCountFrequency (%)
방문동거 25
 
9.5%
영주 25
 
9.5%
방문취업 24
 
9.1%
재외동포 21
 
8.0%
기타 19
 
7.2%
동반 18
 
6.8%
거주 18
 
6.8%
단기방문 13
 
4.9%
관광통과 11
 
4.2%
비전문취업 10
 
3.8%
Other values (30) 80
30.3%

Length

2023-12-12T15:59:34.807825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
방문동거 25
 
9.5%
영주 25
 
9.5%
방문취업 24
 
9.1%
재외동포 21
 
8.0%
기타 19
 
7.2%
동반 18
 
6.8%
거주 18
 
6.8%
단기방문 13
 
4.9%
관광통과 11
 
4.2%
일반연수 10
 
3.8%
Other values (30) 80
30.3%

체류자격명
Text

UNIQUE 

Distinct264
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T15:59:35.098620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length12.651515
Min length2

Characters and Unicode

Total characters3340
Distinct characters234
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique264 ?
Unique (%)100.0%

Sample

1st row외교(A-1)
2nd row공무(A-2)
3rd row외국정부(A-2-1)
4th row국제기구(A-2-2)
5th row유엔사(A-2-3)
ValueCountFrequency (%)
평창올림픽 3
 
1.0%
어 2
 
0.6%
외교(a-1 1
 
0.3%
재외동포 1
 
0.3%
졸업자(f-4-14 1
 
0.3%
대학 1
 
0.3%
체류자(f-4-13 1
 
0.3%
6개월이상 1
 
0.3%
de계열 1
 
0.3%
직계가족(f-4-12 1
 
0.3%
Other values (301) 301
95.9%
2023-12-12T15:59:35.587924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 512
 
15.3%
( 262
 
7.8%
) 262
 
7.8%
1 162
 
4.9%
2 140
 
4.2%
F 114
 
3.4%
3 71
 
2.1%
4 63
 
1.9%
62
 
1.9%
9 58
 
1.7%
Other values (224) 1634
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1308
39.2%
Decimal Number 646
19.3%
Dash Punctuation 512
 
15.3%
Uppercase Letter 288
 
8.6%
Open Punctuation 262
 
7.8%
Close Punctuation 262
 
7.8%
Space Separator 62
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 54
 
4.1%
동 49
 
3.7%
기 47
 
3.6%
업 34
 
2.6%
취 33
 
2.5%
국 32
 
2.4%
사 30
 
2.3%
방 28
 
2.1%
가 27
 
2.1%
수 26
 
2.0%
Other values (199) 948
72.5%
Uppercase Letter
ValueCountFrequency (%)
F 114
39.6%
D 43
 
14.9%
E 34
 
11.8%
H 25
 
8.7%
G 19
 
6.6%
C 16
 
5.6%
A 15
 
5.2%
B 12
 
4.2%
T 7
 
2.4%
S 2
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 162
25.1%
2 140
21.7%
3 71
11.0%
4 63
 
9.8%
9 58
 
9.0%
5 52
 
8.0%
7 30
 
4.6%
6 28
 
4.3%
8 26
 
4.0%
0 16
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 512
100.0%
Open Punctuation
ValueCountFrequency (%)
( 262
100.0%
Close Punctuation
ValueCountFrequency (%)
) 262
100.0%
Space Separator
ValueCountFrequency (%)
62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1744
52.2%
Hangul 1308
39.2%
Latin 288
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 54
 
4.1%
동 49
 
3.7%
기 47
 
3.6%
업 34
 
2.6%
취 33
 
2.5%
국 32
 
2.4%
사 30
 
2.3%
방 28
 
2.1%
가 27
 
2.1%
수 26
 
2.0%
Other values (199) 948
72.5%
Common
ValueCountFrequency (%)
- 512
29.4%
( 262
15.0%
) 262
15.0%
1 162
 
9.3%
2 140
 
8.0%
3 71
 
4.1%
4 63
 
3.6%
62
 
3.6%
9 58
 
3.3%
5 52
 
3.0%
Other values (4) 100
 
5.7%
Latin
ValueCountFrequency (%)
F 114
39.6%
D 43
 
14.9%
E 34
 
11.8%
H 25
 
8.7%
G 19
 
6.6%
C 16
 
5.6%
A 15
 
5.2%
B 12
 
4.2%
T 7
 
2.4%
S 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2032
60.8%
Hangul 1308
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 512
25.2%
( 262
12.9%
) 262
12.9%
1 162
 
8.0%
2 140
 
6.9%
F 114
 
5.6%
3 71
 
3.5%
4 63
 
3.1%
62
 
3.1%
9 58
 
2.9%
Other values (15) 326
16.0%
Hangul
ValueCountFrequency (%)
자 54
 
4.1%
동 49
 
3.7%
기 47
 
3.6%
업 34
 
2.6%
취 33
 
2.5%
국 32
 
2.4%
사 30
 
2.3%
방 28
 
2.1%
가 27
 
2.1%
수 26
 
2.0%
Other values (199) 948
72.5%

체류자격설명
Text

Distinct261
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T15:59:35.932616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length25
Mean length13.765152
Min length2

Characters and Unicode

Total characters3634
Distinct characters292
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

Unique258 ?
Unique (%)97.7%

Sample

1st row외교
2nd row공무
3rd row외국정부 장기 공무수행자, 가족
4th row국제기구 공무수행자, 가족
5th row유엔군사령부 파견 외국군인, 가족
ValueCountFrequency (%)
및 32
 
3.9%
배우자 31
 
3.7%
미성년자녀 20
 
2.4%
자 12
 
1.4%
등 12
 
1.4%
미성년 11
 
1.3%
자녀 11
 
1.3%
후 10
 
1.2%
목적 9
 
1.1%
또는 8
 
1.0%
Other values (476) 673
81.2%
2023-12-12T15:59:36.523859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
565
 
15.5%
자 255
 
7.0%
국 82
 
2.3%
업 70
 
1.9%
기 56
 
1.5%
의 56
 
1.5%
인 46
 
1.3%
년 44
 
1.2%
사 44
 
1.2%
우 43
 
1.2%
Other values (282) 2373
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2779
76.5%
Space Separator 565
 
15.5%
Decimal Number 82
 
2.3%
Uppercase Letter 58
 
1.6%
Close Punctuation 39
 
1.1%
Open Punctuation 39
 
1.1%
Dash Punctuation 37
 
1.0%
Other Punctuation 34
 
0.9%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 255
 
9.2%
국 82
 
3.0%
업 70
 
2.5%
기 56
 
2.0%
의 56
 
2.0%
인 46
 
1.7%
년 44
 
1.6%
사 44
 
1.6%
우 43
 
1.5%
수 41
 
1.5%
Other values (254) 2042
73.5%
Decimal Number
ValueCountFrequency (%)
3 17
20.7%
2 11
13.4%
0 11
13.4%
1 10
12.2%
5 9
11.0%
4 7
8.5%
9 6
 
7.3%
6 6
 
7.3%
7 4
 
4.9%
8 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
F 13
22.4%
D 10
17.2%
E 9
15.5%
T 6
10.3%
C 6
10.3%
A 6
10.3%
O 3
 
5.2%
U 2
 
3.4%
M 2
 
3.4%
H 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 27
79.4%
· 6
 
17.6%
/ 1
 
2.9%
Space Separator
ValueCountFrequency (%)
565
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2779
76.5%
Common 797
 
21.9%
Latin 58
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 255
 
9.2%
국 82
 
3.0%
업 70
 
2.5%
기 56
 
2.0%
의 56
 
2.0%
인 46
 
1.7%
년 44
 
1.6%
사 44
 
1.6%
우 43
 
1.5%
수 41
 
1.5%
Other values (254) 2042
73.5%
Common
ValueCountFrequency (%)
565
70.9%
) 39
 
4.9%
( 39
 
4.9%
- 37
 
4.6%
, 27
 
3.4%
3 17
 
2.1%
2 11
 
1.4%
0 11
 
1.4%
1 10
 
1.3%
5 9
 
1.1%
Other values (8) 32
 
4.0%
Latin
ValueCountFrequency (%)
F 13
22.4%
D 10
17.2%
E 9
15.5%
T 6
10.3%
C 6
10.3%
A 6
10.3%
O 3
 
5.2%
U 2
 
3.4%
M 2
 
3.4%
H 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2779
76.5%
ASCII 849
 
23.4%
None 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
565
66.5%
) 39
 
4.6%
( 39
 
4.6%
- 37
 
4.4%
, 27
 
3.2%
3 17
 
2.0%
F 13
 
1.5%
2 11
 
1.3%
0 11
 
1.3%
D 10
 
1.2%
Other values (17) 80
 
9.4%
Hangul
ValueCountFrequency (%)
자 255
 
9.2%
국 82
 
3.0%
업 70
 
2.5%
기 56
 
2.0%
의 56
 
2.0%
인 46
 
1.7%
년 44
 
1.6%
사 44
 
1.6%
우 43
 
1.5%
수 41
 
1.5%
Other values (254) 2042
73.5%
None
ValueCountFrequency (%)
· 6
100.0%

Missing values

2023-12-12T15:59:33.466543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:59:33.569932image/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.

Sample

체류자격 신약호법명체류자격명체류자격설명
0A-1외교외교(A-1)외교
1A-2공무공무(A-2)공무
2A-2-1공무외국정부(A-2-1)외국정부 장기 공무수행자, 가족
3A-2-2공무국제기구(A-2-2)국제기구 공무수행자, 가족
4A-2-3공무유엔사(A-2-3)유엔군사령부 파견 외국군인, 가족
5A-2-4공무기타공무(A-2-4)단기 공무수행, 관용여권 비자 면제협정국가 단기입국
6A-3-1협정미군현역(A-3-1)주한미군(현역및예비역)
7A-3-2협정미군군속(A-3-2)주한미군 군속,초청계약자,가족
8A-3-99협정기타협정(A-3-99)기타협정
9B-1사증면제사증면제(B-1)사증면제
체류자격 신약호법명체류자격명체류자격설명
254H-2-42방문취업연수방취(H-2-42)취업 외 목적 연수취업 후 자진귀국자
255H-2-51방문취업추첨방취(H-2-51)취업목적 한국말 시험 등으로 선발된 자
256H-2-52방문취업추첨방취(H-2-52)취업 외 목적 한국말 시험 등으로 선발된 자
257H-2-61방문취업변경방취(H-2-61)취업목적 무연고동포 연수 후 자격변경자
258H-2-62방문취업변경방취(H-2-62)취업 외 목적 무연고동포 연수 후 자격변경자
259H-2-71방문취업만기방취(H-2-71)취업목적 만기출국자 재입국자
260H-2-72방문취업변경방취(H-2-72)취업 외 목적 무연고동포 연수 후 자격변경자
261H-2-91방문취업기타방취(H-2-91)취업목적 기타(자격변경자 포함)
262H-2-92방문취업기타방취(H-2-92)취업 외 목적 기타(자격변경자 포함)
263T-1-1관광상륙관광상륙(T-1-1)선박도착 관광상륙 허가자