Overview

Dataset statistics

Number of variables5
Number of observations47
Missing cells13
Missing cells (%)5.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory42.8 B

Variable types

Categorical1
Text4

Dataset

Description경기도_고양시_관내 노동조합 현황 데이터로 노동조합 명칭, 사업장명, 노동조합 사무실 소재지, 전화번호 등 에 대한 항목을 제공합니다.
URLhttps://www.data.go.kr/data/3079212/fileData.do

Alerts

행정관청명 has constant value ""Constant
전화번호 has 13 (27.7%) missing valuesMissing
노동조합명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:44:06.936906
Analysis finished2023-12-12 15:44:07.663056
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정관청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
고양시청
47 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고양시청 47
100.0%

Length

2023-12-13T00:44:07.752123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:44:07.877584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고양시청 47
100.0%

노동조합명
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-13T00:44:08.083906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length11.93617
Min length6

Characters and Unicode

Total characters561
Distinct characters138
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row(주)깨끗한도시 노동조합
2nd row(주)명광노동조합
3rd row(주)벽제개발노동조합
4th row(주)원당기업 노동조합
5th row(주)한양컨트리클럽 노동조합
ValueCountFrequency (%)
노동조합 30
34.5%
농협대학교 2
 
2.3%
단결노동조합 1
 
1.1%
서울고속도로일반노동조합 1
 
1.1%
서울매일버스 1
 
1.1%
일산노동조합 1
 
1.1%
서울매일버스한마음노동조합 1
 
1.1%
세기상운 1
 
1.1%
승문기업(주)노동조합 1
 
1.1%
신영산업(합)노동조합 1
 
1.1%
Other values (47) 47
54.0%
2023-12-13T00:44:08.547885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
합 49
 
8.7%
노 46
 
8.2%
조 46
 
8.2%
동 45
 
8.0%
40
 
7.1%
( 15
 
2.7%
) 15
 
2.7%
주 11
 
2.0%
업 11
 
2.0%
스 10
 
1.8%
Other values (128) 273
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 481
85.7%
Space Separator 40
 
7.1%
Open Punctuation 15
 
2.7%
Close Punctuation 15
 
2.7%
Uppercase Letter 4
 
0.7%
Lowercase Letter 4
 
0.7%
Other Symbol 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
합 49
 
10.2%
노 46
 
9.6%
조 46
 
9.6%
동 45
 
9.4%
주 11
 
2.3%
업 11
 
2.3%
스 10
 
2.1%
일 10
 
2.1%
기 10
 
2.1%
산 9
 
1.9%
Other values (116) 234
48.6%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
B 1
25.0%
M 1
25.0%
T 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
t 1
25.0%
k 1
25.0%
h 1
25.0%
e 1
25.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 483
86.1%
Common 70
 
12.5%
Latin 8
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
합 49
 
10.1%
노 46
 
9.5%
조 46
 
9.5%
동 45
 
9.3%
주 11
 
2.3%
업 11
 
2.3%
스 10
 
2.1%
일 10
 
2.1%
기 10
 
2.1%
산 9
 
1.9%
Other values (117) 236
48.9%
Latin
ValueCountFrequency (%)
C 1
12.5%
B 1
12.5%
M 1
12.5%
t 1
12.5%
k 1
12.5%
T 1
12.5%
h 1
12.5%
e 1
12.5%
Common
ValueCountFrequency (%)
40
57.1%
( 15
 
21.4%
) 15
 
21.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 481
85.7%
ASCII 78
 
13.9%
None 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
합 49
 
10.2%
노 46
 
9.6%
조 46
 
9.6%
동 45
 
9.4%
주 11
 
2.3%
업 11
 
2.3%
스 10
 
2.1%
일 10
 
2.1%
기 10
 
2.1%
산 9
 
1.9%
Other values (116) 234
48.6%
ASCII
ValueCountFrequency (%)
40
51.3%
( 15
 
19.2%
) 15
 
19.2%
C 1
 
1.3%
B 1
 
1.3%
M 1
 
1.3%
t 1
 
1.3%
k 1
 
1.3%
T 1
 
1.3%
h 1
 
1.3%
None
ValueCountFrequency (%)
㈜ 2
100.0%

사업장명
Text

Distinct43
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-13T00:44:08.870008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length7.3404255
Min length3

Characters and Unicode

Total characters345
Distinct characters132
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)85.1%

Sample

1st row㈜깨끗한도시
2nd row(주)명광엔지니어링건축사사무소
3rd row(주)벽제개발
4th row㈜원당기업
5th row(주)한양컨트리클럽
ValueCountFrequency (%)
서울매일버스 3
 
5.9%
농협대학교 2
 
3.9%
고양도시관리공사 2
 
3.9%
우신교통(주 2
 
3.9%
영도건설산업㈜ 1
 
2.0%
㈜깨끗한도시 1
 
2.0%
웅비환경 1
 
2.0%
서울고속도로㈜ 1
 
2.0%
세기상운 1
 
2.0%
승문기업(주 1
 
2.0%
Other values (36) 36
70.6%
2023-12-13T00:44:09.320249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 17
 
4.9%
( 17
 
4.9%
업 12
 
3.5%
기 10
 
2.9%
주 10
 
2.9%
스 9
 
2.6%
산 9
 
2.6%
㈜ 8
 
2.3%
일 7
 
2.0%
고 7
 
2.0%
Other values (122) 239
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 294
85.2%
Close Punctuation 17
 
4.9%
Open Punctuation 17
 
4.9%
Other Symbol 8
 
2.3%
Space Separator 4
 
1.2%
Uppercase Letter 3
 
0.9%
Lowercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 12
 
4.1%
기 10
 
3.4%
주 10
 
3.4%
스 9
 
3.1%
산 9
 
3.1%
일 7
 
2.4%
고 7
 
2.4%
양 7
 
2.4%
공 7
 
2.4%
교 6
 
2.0%
Other values (113) 210
71.4%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
M 1
33.3%
B 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
k 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 8
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 302
87.5%
Common 38
 
11.0%
Latin 5
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 12
 
4.0%
기 10
 
3.3%
주 10
 
3.3%
스 9
 
3.0%
산 9
 
3.0%
㈜ 8
 
2.6%
일 7
 
2.3%
고 7
 
2.3%
양 7
 
2.3%
공 7
 
2.3%
Other values (114) 216
71.5%
Latin
ValueCountFrequency (%)
C 1
20.0%
M 1
20.0%
B 1
20.0%
t 1
20.0%
k 1
20.0%
Common
ValueCountFrequency (%)
) 17
44.7%
( 17
44.7%
4
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 294
85.2%
ASCII 43
 
12.5%
None 8
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 17
39.5%
( 17
39.5%
4
 
9.3%
C 1
 
2.3%
M 1
 
2.3%
B 1
 
2.3%
t 1
 
2.3%
k 1
 
2.3%
Hangul
ValueCountFrequency (%)
업 12
 
4.1%
기 10
 
3.4%
주 10
 
3.4%
스 9
 
3.1%
산 9
 
3.1%
일 7
 
2.4%
고 7
 
2.4%
양 7
 
2.4%
공 7
 
2.4%
교 6
 
2.0%
Other values (113) 210
71.4%
None
ValueCountFrequency (%)
㈜ 8
100.0%

주사무소소재지
Text

Distinct45
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-13T00:44:09.681886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length27.446809
Min length17

Characters and Unicode

Total characters1290
Distinct characters115
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)91.5%

Sample

1st row경기도 고양시 일산동구 성석로271
2nd row경기도 고양시 덕양구 안진2길4
3rd row경기도 고양시 덕양구 통일로771번길 16 (관산동)
4th row경기도 고양시 일산동구 지영로 100번길 69
5th row경기도 고양시 덕양구 고양대로1643번길 164 (원당동)
ValueCountFrequency (%)
경기도 46
17.5%
고양시 46
17.5%
일산동구 18
 
6.8%
덕양구 15
 
5.7%
일산서구 12
 
4.6%
지영동 3
 
1.1%
대화동 3
 
1.1%
고봉로678번길 3
 
1.1%
283(대화동 2
 
0.8%
일산로 2
 
0.8%
Other values (102) 113
43.0%
2023-12-13T00:44:10.222607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
216
 
16.7%
양 69
 
5.3%
고 58
 
4.5%
동 51
 
4.0%
시 50
 
3.9%
경 47
 
3.6%
구 47
 
3.6%
도 46
 
3.6%
기 46
 
3.6%
1 43
 
3.3%
Other values (105) 617
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 800
62.0%
Space Separator 216
 
16.7%
Decimal Number 199
 
15.4%
Open Punctuation 28
 
2.2%
Close Punctuation 28
 
2.2%
Other Punctuation 10
 
0.8%
Dash Punctuation 8
 
0.6%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 69
 
8.6%
고 58
 
7.2%
동 51
 
6.4%
시 50
 
6.2%
경 47
 
5.9%
구 47
 
5.9%
도 46
 
5.8%
기 46
 
5.8%
로 42
 
5.2%
일 39
 
4.9%
Other values (89) 305
38.1%
Decimal Number
ValueCountFrequency (%)
1 43
21.6%
4 24
12.1%
2 22
11.1%
6 22
11.1%
0 18
9.0%
7 18
9.0%
3 16
 
8.0%
5 13
 
6.5%
8 12
 
6.0%
9 11
 
5.5%
Space Separator
ValueCountFrequency (%)
216
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 801
62.1%
Common 489
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 69
 
8.6%
고 58
 
7.2%
동 51
 
6.4%
시 50
 
6.2%
경 47
 
5.9%
구 47
 
5.9%
도 46
 
5.7%
기 46
 
5.7%
로 42
 
5.2%
일 39
 
4.9%
Other values (90) 306
38.2%
Common
ValueCountFrequency (%)
216
44.2%
1 43
 
8.8%
( 28
 
5.7%
) 28
 
5.7%
4 24
 
4.9%
2 22
 
4.5%
6 22
 
4.5%
0 18
 
3.7%
7 18
 
3.7%
3 16
 
3.3%
Other values (5) 54
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 800
62.0%
ASCII 489
37.9%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
216
44.2%
1 43
 
8.8%
( 28
 
5.7%
) 28
 
5.7%
4 24
 
4.9%
2 22
 
4.5%
6 22
 
4.5%
0 18
 
3.7%
7 18
 
3.7%
3 16
 
3.3%
Other values (5) 54
 
11.0%
Hangul
ValueCountFrequency (%)
양 69
 
8.6%
고 58
 
7.2%
동 51
 
6.4%
시 50
 
6.2%
경 47
 
5.9%
구 47
 
5.9%
도 46
 
5.8%
기 46
 
5.8%
로 42
 
5.2%
일 39
 
4.9%
Other values (89) 305
38.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

전화번호
Text

MISSING 

Distinct33
Distinct (%)97.1%
Missing13
Missing (%)27.7%
Memory size508.0 B
2023-12-13T00:44:10.454818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length11

Characters and Unicode

Total characters408
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)94.1%

Sample

1st row031-925-3340
2nd row031-968-2377
3rd row031-963-8700
4th row031-978-8844
5th row031-960-6952
ValueCountFrequency (%)
031-977-0135 2
 
5.9%
031-912-7031 1
 
2.9%
031-925-3340 1
 
2.9%
031-977-7060 1
 
2.9%
031-995-0555 1
 
2.9%
031-977-5789 1
 
2.9%
031-977-4126 1
 
2.9%
031-917-0090 1
 
2.9%
031-977-6086 1
 
2.9%
031-930-3343 1
 
2.9%
Other values (23) 23
67.6%
2023-12-13T00:44:10.844815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71
17.4%
- 68
16.7%
3 54
13.2%
1 52
12.7%
9 44
10.8%
7 33
8.1%
6 20
 
4.9%
2 18
 
4.4%
8 17
 
4.2%
5 16
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 340
83.3%
Dash Punctuation 68
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71
20.9%
3 54
15.9%
1 52
15.3%
9 44
12.9%
7 33
9.7%
6 20
 
5.9%
2 18
 
5.3%
8 17
 
5.0%
5 16
 
4.7%
4 15
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 408
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71
17.4%
- 68
16.7%
3 54
13.2%
1 52
12.7%
9 44
10.8%
7 33
8.1%
6 20
 
4.9%
2 18
 
4.4%
8 17
 
4.2%
5 16
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71
17.4%
- 68
16.7%
3 54
13.2%
1 52
12.7%
9 44
10.8%
7 33
8.1%
6 20
 
4.9%
2 18
 
4.4%
8 17
 
4.2%
5 16
 
3.9%

Correlations

2023-12-13T00:44:10.947651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노동조합명사업장명주사무소소재지전화번호
노동조합명1.0001.0001.0001.000
사업장명1.0001.0000.9941.000
주사무소소재지1.0000.9941.0001.000
전화번호1.0001.0001.0001.000

Missing values

2023-12-13T00:44:07.498259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:44:07.612126image/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

행정관청명노동조합명사업장명주사무소소재지전화번호
0고양시청(주)깨끗한도시 노동조합㈜깨끗한도시경기도 고양시 일산동구 성석로271031-925-3340
1고양시청(주)명광노동조합(주)명광엔지니어링건축사사무소경기도 고양시 덕양구 안진2길4031-968-2377
2고양시청(주)벽제개발노동조합(주)벽제개발경기도 고양시 덕양구 통일로771번길 16 (관산동)031-963-8700
3고양시청(주)원당기업 노동조합㈜원당기업경기도 고양시 일산동구 지영로 100번길 69031-978-8844
4고양시청(주)한양컨트리클럽 노동조합(주)한양컨트리클럽경기도 고양시 덕양구 고양대로1643번길 164 (원당동)031-960-6952
5고양시청(합)서강기업 노동조합(합)서강기업경기도 고양시 일산동구 지영로100번길 64 (지영동)<NA>
6고양시청(합)수창기업 노동조합(합)수창기업경기도 고양시 일산동구 지영로 100-69 (지영동)031-978-7744
7고양시청(합)천일공사 노동조합(합)천일공사경기도 고양시 덕양구 무원로6번길 61031-938-2777
8고양시청kt링커스운송서비스 노동조합kt링커스고양시 일산동구 백석동 1141031-3001-1232
9고양시청The 매일 노동조합서울매일버스경기도 고양시 일산서구 킨텍스로 217-59, 제2킨텍스(대화동)<NA>
행정관청명노동조합명사업장명주사무소소재지전화번호
37고양시청일산서구 가로미화원 노동조합웅비환경경기도 고양시 일산서구 탄현로6번길 24-9, 지층 102호<NA>
38고양시청주식회사 킨텍스 노동조합킨텍스경기도 고양시 일산서구 킨텍스로217-60 (대화동)031-995-8213
39고양시청청안기업 노동조합청안기업경기도 고양시 일산동구 고봉로814번길 26-46<NA>
40고양시청코닉앤바우어케이알 노동조합코닉앤바우어케이알경기도 고양시 일산동구 일산로 142, 유니테크빌 벤쳐타운 426호(백석동)031-908-9740
41고양시청코엑스운수(주) 노동조합코엑스운수(주)경기도 고양시 일산서구 덕산로195번길 107 (가좌동)031-922-2508
42고양시청킨텍스플러스노동조합㈜킨텍스 플러스경기도 고양시 일산서구 일현로 140<NA>
43고양시청태현기업(주) 노동조합태현기업(주)경기도 고양시 덕양구 통일로 1108번길 57<NA>
44고양시청한국건설기술연구원열린노동조합한국건설기술연구원경기도 고양시 일산서구 고양대로 283(대화동)031-910-0133
45고양시청한국항공대학교노동조합한국항공대학교경기도 고양시 덕양구 항공대학로 76(화전동)02-300-0275
46고양시청홍성㈜우리노동조합홍성㈜경기도 고양시 덕양구 동헌로 111(관산동)031-968-9799