Overview

Dataset statistics

Number of variables6
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory50.3 B

Variable types

Categorical2
Text3
DateTime1

Dataset

Description부산광역시_동래구_직업소개소등록현황_20230817
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15026214

Alerts

유무료구분 is highly imbalanced (87.3%)Imbalance
법인명 has unique valuesUnique
등록일 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:17:20.289032
Analysis finished2023-12-10 17:17:21.419892
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유무료구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
유료
56 
무료
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
유료 56
98.2%
무료 1
 
1.8%

Length

2023-12-11T02:17:21.596432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:17:21.821572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 56
98.2%
무료 1
 
1.8%

법인명
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-11T02:17:22.197845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length11
Mean length7.4912281
Min length3

Characters and Unicode

Total characters427
Distinct characters143
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

Unique57 ?
Unique (%)100.0%

Sample

1st row유숙남직업소개소
2nd row김재효직업소개소
3rd row진실직업소개소
4th row모두모아개발
5th row파출박사직업소개소
ValueCountFrequency (%)
직업소개소 5
 
6.6%
주식회사 2
 
2.6%
유숙남직업소개소 1
 
1.3%
mommy 1
 
1.3%
1
 
1.3%
kiddie 1
 
1.3%
패스파인더 1
 
1.3%
세정인력 1
 
1.3%
필인력개발 1
 
1.3%
대성개발 1
 
1.3%
Other values (61) 61
80.3%
2023-12-11T02:17:22.906133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 38
 
8.9%
개 34
 
8.0%
인 25
 
5.9%
업 21
 
4.9%
19
 
4.4%
력 18
 
4.2%
직 17
 
4.0%
발 15
 
3.5%
주 10
 
2.3%
사 8
 
1.9%
Other values (133) 222
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 373
87.4%
Space Separator 19
 
4.4%
Uppercase Letter 11
 
2.6%
Lowercase Letter 9
 
2.1%
Open Punctuation 7
 
1.6%
Close Punctuation 7
 
1.6%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 38
 
10.2%
개 34
 
9.1%
인 25
 
6.7%
업 21
 
5.6%
력 18
 
4.8%
직 17
 
4.6%
발 15
 
4.0%
주 10
 
2.7%
사 8
 
2.1%
동 6
 
1.6%
Other values (114) 181
48.5%
Uppercase Letter
ValueCountFrequency (%)
E 2
18.2%
G 2
18.2%
K 1
9.1%
D 1
9.1%
I 1
9.1%
R 1
9.1%
B 1
9.1%
M 1
9.1%
N 1
9.1%
Lowercase Letter
ValueCountFrequency (%)
m 2
22.2%
d 2
22.2%
i 2
22.2%
e 1
11.1%
y 1
11.1%
o 1
11.1%
Space Separator
ValueCountFrequency (%)
19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 373
87.4%
Common 34
 
8.0%
Latin 20
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 38
 
10.2%
개 34
 
9.1%
인 25
 
6.7%
업 21
 
5.6%
력 18
 
4.8%
직 17
 
4.6%
발 15
 
4.0%
주 10
 
2.7%
사 8
 
2.1%
동 6
 
1.6%
Other values (114) 181
48.5%
Latin
ValueCountFrequency (%)
m 2
 
10.0%
d 2
 
10.0%
i 2
 
10.0%
E 2
 
10.0%
G 2
 
10.0%
K 1
 
5.0%
D 1
 
5.0%
I 1
 
5.0%
R 1
 
5.0%
B 1
 
5.0%
Other values (5) 5
25.0%
Common
ValueCountFrequency (%)
19
55.9%
( 7
 
20.6%
) 7
 
20.6%
& 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 373
87.4%
ASCII 54
 
12.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 38
 
10.2%
개 34
 
9.1%
인 25
 
6.7%
업 21
 
5.6%
력 18
 
4.8%
직 17
 
4.6%
발 15
 
4.0%
주 10
 
2.7%
사 8
 
2.1%
동 6
 
1.6%
Other values (114) 181
48.5%
ASCII
ValueCountFrequency (%)
19
35.2%
( 7
 
13.0%
) 7
 
13.0%
m 2
 
3.7%
d 2
 
3.7%
i 2
 
3.7%
E 2
 
3.7%
G 2
 
3.7%
K 1
 
1.9%
D 1
 
1.9%
Other values (9) 9
16.7%

법인개인구분
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
개인
46 
법인
11 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 46
80.7%
법인 11
 
19.3%

Length

2023-12-11T02:17:23.215341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:17:23.408366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 46
80.7%
법인 11
 
19.3%

사업소주소(도로명)
Text

Distinct55
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-11T02:17:23.872218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length40
Mean length30.22807
Min length18

Characters and Unicode

Total characters1723
Distinct characters102
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)93.0%

Sample

1st row부산광역시 동래구 충렬대로237번길 96 (복천동)
2nd row부산광역시 동래구 충렬대로331번길 5, 2층(안락동)
3rd row부산광역시 동래구 명륜로 146-3 (명륜동)
4th row부산광역시 동래구 충렬대로155번길 25 (온천동)
5th row부산광역시 동래구 충렬대로 177 (명륜동), 3층
ValueCountFrequency (%)
부산광역시 57
 
17.3%
동래구 57
 
17.3%
온천동 19
 
5.8%
충렬대로 14
 
4.3%
명륜동 9
 
2.7%
2층 9
 
2.7%
수안동 4
 
1.2%
충렬대로237번길 4
 
1.2%
아시아드대로 4
 
1.2%
안락동 4
 
1.2%
Other values (112) 148
45.0%
2023-12-11T02:17:24.770738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
272
 
15.8%
동 123
 
7.1%
시 65
 
3.8%
래 61
 
3.5%
산 58
 
3.4%
부 57
 
3.3%
광 57
 
3.3%
역 57
 
3.3%
구 57
 
3.3%
로 57
 
3.3%
Other values (92) 859
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1009
58.6%
Space Separator 272
 
15.8%
Decimal Number 272
 
15.8%
Open Punctuation 56
 
3.3%
Close Punctuation 56
 
3.3%
Other Punctuation 46
 
2.7%
Uppercase Letter 10
 
0.6%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 123
 
12.2%
시 65
 
6.4%
래 61
 
6.0%
산 58
 
5.7%
부 57
 
5.6%
광 57
 
5.6%
역 57
 
5.6%
구 57
 
5.6%
로 57
 
5.6%
대 34
 
3.4%
Other values (69) 383
38.0%
Decimal Number
ValueCountFrequency (%)
1 57
21.0%
2 44
16.2%
3 36
13.2%
0 26
9.6%
7 24
8.8%
4 22
 
8.1%
5 19
 
7.0%
6 17
 
6.2%
9 15
 
5.5%
8 12
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
S 2
20.0%
K 2
20.0%
B 2
20.0%
H 1
10.0%
U 1
10.0%
A 1
10.0%
Y 1
10.0%
Other Punctuation
ValueCountFrequency (%)
. 34
73.9%
, 12
 
26.1%
Space Separator
ValueCountFrequency (%)
272
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1009
58.6%
Common 704
40.9%
Latin 10
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 123
 
12.2%
시 65
 
6.4%
래 61
 
6.0%
산 58
 
5.7%
부 57
 
5.6%
광 57
 
5.6%
역 57
 
5.6%
구 57
 
5.6%
로 57
 
5.6%
대 34
 
3.4%
Other values (69) 383
38.0%
Common
ValueCountFrequency (%)
272
38.6%
1 57
 
8.1%
( 56
 
8.0%
) 56
 
8.0%
2 44
 
6.2%
3 36
 
5.1%
. 34
 
4.8%
0 26
 
3.7%
7 24
 
3.4%
4 22
 
3.1%
Other values (6) 77
 
10.9%
Latin
ValueCountFrequency (%)
S 2
20.0%
K 2
20.0%
B 2
20.0%
H 1
10.0%
U 1
10.0%
A 1
10.0%
Y 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1009
58.6%
ASCII 714
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
272
38.1%
1 57
 
8.0%
( 56
 
7.8%
) 56
 
7.8%
2 44
 
6.2%
3 36
 
5.0%
. 34
 
4.8%
0 26
 
3.6%
7 24
 
3.4%
4 22
 
3.1%
Other values (13) 87
 
12.2%
Hangul
ValueCountFrequency (%)
동 123
 
12.2%
시 65
 
6.4%
래 61
 
6.0%
산 58
 
5.7%
부 57
 
5.6%
광 57
 
5.6%
역 57
 
5.6%
구 57
 
5.6%
로 57
 
5.6%
대 34
 
3.4%
Other values (69) 383
38.0%

사업소주소(지번)
Text

Distinct50
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-11T02:17:25.206064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length19.54386
Min length17

Characters and Unicode

Total characters1114
Distinct characters34
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

Unique44 ?
Unique (%)77.2%

Sample

1st row부산광역시 동래구 복천동 380-8
2nd row부산광역시 동래구 안락동 789-4
3rd row부산광역시 동래구 명륜동 564-6
4th row부산광역시 동래구 온천동 1437-50
5th row부산광역시 동래구 명륜동 533-81
ValueCountFrequency (%)
부산광역시 57
25.0%
동래구 57
25.0%
온천동 22
 
9.6%
명륜동 12
 
5.3%
안락동 7
 
3.1%
수안동 5
 
2.2%
복천동 3
 
1.3%
낙민동 3
 
1.3%
명장동 3
 
1.3%
533-216 3
 
1.3%
Other values (51) 56
24.6%
2023-12-11T02:17:25.924231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
171
15.4%
동 114
 
10.2%
산 58
 
5.2%
부 57
 
5.1%
래 57
 
5.1%
구 57
 
5.1%
시 57
 
5.1%
역 57
 
5.1%
광 57
 
5.1%
- 56
 
5.0%
Other values (24) 373
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 627
56.3%
Decimal Number 260
23.3%
Space Separator 171
 
15.4%
Dash Punctuation 56
 
5.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 114
18.2%
산 58
9.3%
부 57
9.1%
래 57
9.1%
구 57
9.1%
시 57
9.1%
역 57
9.1%
광 57
9.1%
천 25
 
4.0%
온 22
 
3.5%
Other values (12) 66
10.5%
Decimal Number
ValueCountFrequency (%)
1 44
16.9%
2 39
15.0%
4 38
14.6%
3 35
13.5%
5 28
10.8%
8 22
8.5%
6 18
6.9%
9 15
 
5.8%
0 11
 
4.2%
7 10
 
3.8%
Space Separator
ValueCountFrequency (%)
171
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 627
56.3%
Common 487
43.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 114
18.2%
산 58
9.3%
부 57
9.1%
래 57
9.1%
구 57
9.1%
시 57
9.1%
역 57
9.1%
광 57
9.1%
천 25
 
4.0%
온 22
 
3.5%
Other values (12) 66
10.5%
Common
ValueCountFrequency (%)
171
35.1%
- 56
 
11.5%
1 44
 
9.0%
2 39
 
8.0%
4 38
 
7.8%
3 35
 
7.2%
5 28
 
5.7%
8 22
 
4.5%
6 18
 
3.7%
9 15
 
3.1%
Other values (2) 21
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 627
56.3%
ASCII 487
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
171
35.1%
- 56
 
11.5%
1 44
 
9.0%
2 39
 
8.0%
4 38
 
7.8%
3 35
 
7.2%
5 28
 
5.7%
8 22
 
4.5%
6 18
 
3.7%
9 15
 
3.1%
Other values (2) 21
 
4.3%
Hangul
ValueCountFrequency (%)
동 114
18.2%
산 58
9.3%
부 57
9.1%
래 57
9.1%
구 57
9.1%
시 57
9.1%
역 57
9.1%
광 57
9.1%
천 25
 
4.0%
온 22
 
3.5%
Other values (12) 66
10.5%

등록일
Date

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum1998-07-07 00:00:00
Maximum2023-06-30 00:00:00
2023-12-11T02:17:26.242045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:17:26.569605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2023-12-11T02:17:26.838254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유무료구분법인명법인개인구분사업소주소(도로명)사업소주소(지번)등록일
유무료구분1.0001.0000.0001.0001.0001.000
법인명1.0001.0001.0001.0001.0001.000
법인개인구분0.0001.0001.0001.0000.0001.000
사업소주소(도로명)1.0001.0001.0001.0001.0001.000
사업소주소(지번)1.0001.0000.0001.0001.0001.000
등록일1.0001.0001.0001.0001.0001.000
2023-12-11T02:17:27.081418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법인개인구분유무료구분
법인개인구분1.0000.000
유무료구분0.0001.000
2023-12-11T02:17:27.279903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유무료구분법인개인구분
유무료구분1.0000.000
법인개인구분0.0001.000

Missing values

2023-12-11T02:17:21.076863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:17:21.337415image/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

유무료구분법인명법인개인구분사업소주소(도로명)사업소주소(지번)등록일
0유료유숙남직업소개소개인부산광역시 동래구 충렬대로237번길 96 (복천동)부산광역시 동래구 복천동 380-81998-07-07
1유료김재효직업소개소개인부산광역시 동래구 충렬대로331번길 5, 2층(안락동)부산광역시 동래구 안락동 789-41998-11-14
2유료진실직업소개소개인부산광역시 동래구 명륜로 146-3 (명륜동)부산광역시 동래구 명륜동 564-62002-02-28
3유료모두모아개발개인부산광역시 동래구 충렬대로155번길 25 (온천동)부산광역시 동래구 온천동 1437-502003-06-24
4유료파출박사직업소개소개인부산광역시 동래구 충렬대로 177 (명륜동), 3층부산광역시 동래구 명륜동 533-812004-10-25
5유료세븐직업소개소개인부산광역시 동래구 명륜로94번길 16 (수안동)부산광역시 동래구 수안동 5932005-04-21
6유료태성개발직업소개소개인부산광역시 동래구 충렬대로 176. 지하1층 (명륜동)부산광역시 동래구 명륜동 533-2162005-05-02
7유료농심취업컨설팅개인부산광역시 동래구 충렬대로237번길 90 (복천동)부산광역시 동래구 복천동 380-52005-06-21
8유료거림ENG개인부산광역시 동래구 동래로 1 (온천동.(2층))부산광역시 동래구 온천동 425-272006-10-20
9유료동래가사원직업소개소개인부산광역시 동래구 충렬대로 306. B동 210호 (낙민동. 동래한양아파트)부산광역시 동래구 낙민동 172-32006-12-11
유무료구분법인명법인개인구분사업소주소(도로명)사업소주소(지번)등록일
47유료일새인력개발개인부산광역시 동래구 충렬대로 307, 3층(안락동)부산광역시 동래구 안락동 1041-72023-01-05
48유료남양인력개발개인부산광역시 동래구 충렬대로 439, 3층(안락동)부산광역시 동래구 안락동 293-32023-01-10
49유료태성인력개발개인부산광역시 동래구 충렬대로 176. 지하1층 (명륜동)부산광역시 동래구 명륜동 533-2162023-01-30
50유료아장스개인부산광역시 동래구 충렬대로 186, 5층(명륜동)부산광역시 동래구 명륜동 529-42023-03-09
51유료(주)정암기업법인부산광역시 동래구 충렬대로237번길 96, 203호(복천동)부산광역시 동래구 복천동 380-82023-03-14
52유료보필동행소개소개인부산광역시 동래구 미남로 148 3층부산광역시 동래구 온천동 1423-12023-04-10
53유료삼다인력개발개인부산광역시 동래구 명륜로75번길 11, 2층(수안동)부산광역시 동래구 수안동 4-12023-06-05
54유료BRIDGE개인부산광역시 동래구 충렬대로256번가길 25. 102동 1002호부산광역시 동래구 낙민동 288-292023-06-21
55유료케이피엠아이 주식회사법인부산광역시 동래구 금강로62번길 8. 2층 (온천동)부산광역시 동래구 온천동 425-92023-06-29
56유료오 행정사 탐정 기업 컨설팅 기업인증개인부산광역시 동래구 충렬대로 177부산광역시 동래구 명륜동 533-812023-06-30