Overview

Dataset statistics

Number of variables5
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory46.1 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description서울특별시 양천구에 등록된 노동조합단체 정보 노동조합단체명, 사업장명, 소속단체명, 노동조합주소 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15038378/fileData.do

Alerts

데이터 기준일 has constant value ""Constant
연번 has unique valuesUnique
노동조합 명칭 has unique valuesUnique
대표자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:55:48.609269
Analysis finished2023-12-12 12:55:49.224599
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T21:55:49.333189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-12T21:55:49.504035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

노동조합 명칭
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T21:55:49.741711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length11.230769
Min length8

Characters and Unicode

Total characters292
Distinct characters78
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row삼기통산 노동조합
2nd row승지실업 노동조합
3rd row삼용운수 노동조합
4th row(주)동훈운수 노동조합
5th row광일실업(주) 노동조합
ValueCountFrequency (%)
노동조합 25
47.2%
삼기통산 1
 
1.9%
서울시 1
 
1.9%
서울특별시 1
 
1.9%
ntv서울지국 1
 
1.9%
승아운수㈜ 1
 
1.9%
서영산업 1
 
1.9%
방송통신심의위원회 1
 
1.9%
sbs 1
 
1.9%
해성운수 1
 
1.9%
Other values (19) 19
35.8%
2023-12-12T21:55:50.121495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
9.6%
동 28
 
9.6%
합 28
 
9.6%
조 27
 
9.2%
노 26
 
8.9%
( 7
 
2.4%
) 7
 
2.4%
주 6
 
2.1%
서 6
 
2.1%
업 5
 
1.7%
Other values (68) 124
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 240
82.2%
Space Separator 28
 
9.6%
Uppercase Letter 8
 
2.7%
Open Punctuation 7
 
2.4%
Close Punctuation 7
 
2.4%
Other Symbol 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 28
 
11.7%
합 28
 
11.7%
조 27
 
11.2%
노 26
 
10.8%
주 6
 
2.5%
서 6
 
2.5%
업 5
 
2.1%
운 5
 
2.1%
회 4
 
1.7%
국 4
 
1.7%
Other values (57) 101
42.1%
Uppercase Letter
ValueCountFrequency (%)
S 2
25.0%
T 1
12.5%
V 1
12.5%
B 1
12.5%
N 1
12.5%
P 1
12.5%
D 1
12.5%
Space Separator
ValueCountFrequency (%)
28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 242
82.9%
Common 42
 
14.4%
Latin 8
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 28
 
11.6%
합 28
 
11.6%
조 27
 
11.2%
노 26
 
10.7%
주 6
 
2.5%
서 6
 
2.5%
업 5
 
2.1%
운 5
 
2.1%
회 4
 
1.7%
국 4
 
1.7%
Other values (58) 103
42.6%
Latin
ValueCountFrequency (%)
S 2
25.0%
T 1
12.5%
V 1
12.5%
B 1
12.5%
N 1
12.5%
P 1
12.5%
D 1
12.5%
Common
ValueCountFrequency (%)
28
66.7%
( 7
 
16.7%
) 7
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 240
82.2%
ASCII 50
 
17.1%
None 2
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28
56.0%
( 7
 
14.0%
) 7
 
14.0%
S 2
 
4.0%
T 1
 
2.0%
V 1
 
2.0%
B 1
 
2.0%
N 1
 
2.0%
P 1
 
2.0%
D 1
 
2.0%
Hangul
ValueCountFrequency (%)
동 28
 
11.7%
합 28
 
11.7%
조 27
 
11.2%
노 26
 
10.8%
주 6
 
2.5%
서 6
 
2.5%
업 5
 
2.1%
운 5
 
2.1%
회 4
 
1.7%
국 4
 
1.7%
Other values (57) 101
42.1%
None
ValueCountFrequency (%)
㈜ 2
100.0%

대표자
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T21:55:50.378738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters78
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row이동희
2nd row양형근
3rd row한원태
4th row민한기
5th row김상대
ValueCountFrequency (%)
이동희 1
 
3.8%
양형근 1
 
3.8%
안경희 1
 
3.8%
배철호 1
 
3.8%
김학균 1
 
3.8%
김현우 1
 
3.8%
김병길 1
 
3.8%
김병일 1
 
3.8%
전숙희 1
 
3.8%
이준호 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T21:55:50.799864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 9
 
11.5%
이 4
 
5.1%
기 3
 
3.8%
희 3
 
3.8%
한 3
 
3.8%
호 3
 
3.8%
병 2
 
2.6%
전 2
 
2.6%
식 2
 
2.6%
상 2
 
2.6%
Other values (41) 45
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 9
 
11.5%
이 4
 
5.1%
기 3
 
3.8%
희 3
 
3.8%
한 3
 
3.8%
호 3
 
3.8%
병 2
 
2.6%
전 2
 
2.6%
식 2
 
2.6%
상 2
 
2.6%
Other values (41) 45
57.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 9
 
11.5%
이 4
 
5.1%
기 3
 
3.8%
희 3
 
3.8%
한 3
 
3.8%
호 3
 
3.8%
병 2
 
2.6%
전 2
 
2.6%
식 2
 
2.6%
상 2
 
2.6%
Other values (41) 45
57.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 9
 
11.5%
이 4
 
5.1%
기 3
 
3.8%
희 3
 
3.8%
한 3
 
3.8%
호 3
 
3.8%
병 2
 
2.6%
전 2
 
2.6%
식 2
 
2.6%
상 2
 
2.6%
Other values (41) 45
57.7%

주 소
Text

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T21:55:51.044167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length27.769231
Min length21

Characters and Unicode

Total characters722
Distinct characters75
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

Unique24 ?
Unique (%)92.3%

Sample

1st row서울특별시 양천구 남부순환로74길 2 (신월동)
2nd row서울특별시 양천구 목동로1길 40 (신정동)
3rd row서울특별시 양천구 가로공원로 71 (신월동)
4th row서울특별시 양천구 가로공원로 71 (신월동)
5th row서울특별시 양천구 남부순환로72길 11 (신월동)
ValueCountFrequency (%)
서울특별시 26
20.6%
양천구 26
20.6%
신월동 6
 
4.8%
가로공원로 4
 
3.2%
11 3
 
2.4%
목동동로 3
 
2.4%
신월로 3
 
2.4%
목동서로 3
 
2.4%
신정동 2
 
1.6%
71 2
 
1.6%
Other values (47) 48
38.1%
2023-12-12T21:55:51.451204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
 
13.9%
동 44
 
6.1%
서 31
 
4.3%
로 31
 
4.3%
1 31
 
4.3%
양 27
 
3.7%
울 26
 
3.6%
) 26
 
3.6%
( 26
 
3.6%
별 26
 
3.6%
Other values (65) 354
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 447
61.9%
Space Separator 100
 
13.9%
Decimal Number 100
 
13.9%
Close Punctuation 26
 
3.6%
Open Punctuation 26
 
3.6%
Other Punctuation 19
 
2.6%
Uppercase Letter 3
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 44
 
9.8%
서 31
 
6.9%
로 31
 
6.9%
양 27
 
6.0%
울 26
 
5.8%
별 26
 
5.8%
특 26
 
5.8%
천 26
 
5.8%
구 26
 
5.8%
시 26
 
5.8%
Other values (48) 158
35.3%
Decimal Number
ValueCountFrequency (%)
1 31
31.0%
2 14
14.0%
3 13
13.0%
0 12
 
12.0%
6 8
 
8.0%
7 7
 
7.0%
5 6
 
6.0%
4 6
 
6.0%
9 2
 
2.0%
8 1
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 447
61.9%
Common 272
37.7%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 44
 
9.8%
서 31
 
6.9%
로 31
 
6.9%
양 27
 
6.0%
울 26
 
5.8%
별 26
 
5.8%
특 26
 
5.8%
천 26
 
5.8%
구 26
 
5.8%
시 26
 
5.8%
Other values (48) 158
35.3%
Common
ValueCountFrequency (%)
100
36.8%
1 31
 
11.4%
) 26
 
9.6%
( 26
 
9.6%
, 19
 
7.0%
2 14
 
5.1%
3 13
 
4.8%
0 12
 
4.4%
6 8
 
2.9%
7 7
 
2.6%
Other values (5) 16
 
5.9%
Latin
ValueCountFrequency (%)
S 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 447
61.9%
ASCII 275
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
36.4%
1 31
 
11.3%
) 26
 
9.5%
( 26
 
9.5%
, 19
 
6.9%
2 14
 
5.1%
3 13
 
4.7%
0 12
 
4.4%
6 8
 
2.9%
7 7
 
2.5%
Other values (7) 19
 
6.9%
Hangul
ValueCountFrequency (%)
동 44
 
9.8%
서 31
 
6.9%
로 31
 
6.9%
양 27
 
6.0%
울 26
 
5.8%
별 26
 
5.8%
특 26
 
5.8%
천 26
 
5.8%
구 26
 
5.8%
시 26
 
5.8%
Other values (48) 158
35.3%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-08-10
26 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-10
2nd row2023-08-10
3rd row2023-08-10
4th row2023-08-10
5th row2023-08-10

Common Values

ValueCountFrequency (%)
2023-08-10 26
100.0%

Length

2023-12-12T21:55:51.594512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:55:51.702260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-10 26
100.0%

Interactions

2023-12-12T21:55:48.903721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:55:51.774769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번노동조합 명칭대표자주 소
연번1.0001.0001.0000.916
노동조합 명칭1.0001.0001.0001.000
대표자1.0001.0001.0001.000
주 소0.9161.0001.0001.000

Missing values

2023-12-12T21:55:49.052882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:55:49.173237image/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

연번노동조합 명칭대표자주 소데이터 기준일
01삼기통산 노동조합이동희서울특별시 양천구 남부순환로74길 2 (신월동)2023-08-10
12승지실업 노동조합양형근서울특별시 양천구 목동로1길 40 (신정동)2023-08-10
23삼용운수 노동조합한원태서울특별시 양천구 가로공원로 71 (신월동)2023-08-10
34(주)동훈운수 노동조합민한기서울특별시 양천구 가로공원로 71 (신월동)2023-08-10
45광일실업(주) 노동조합김상대서울특별시 양천구 남부순환로72길 11 (신월동)2023-08-10
56영서기업(주) 노동조합권춘기서울특별시 양천구 신월로 305 (신정동)2023-08-10
67(주)신원지엘 노동조합김광락서울특별시 양천구 목동중앙북로 60, 204호 (목동,신화타워)2023-08-10
78(주)한성용역 노동조합양성호서울특별시 양천구 신월로 365, 302호 (신정동,청솔빌딩)2023-08-10
89(주)양천환경 노동조합변교식서울특별시 양천구 신월로 128, 401호 (신월동)2023-08-10
910청송환경㈜ 노동조합이정범서울특별시 양천구 목동중앙로1길 11 (목동)2023-08-10
연번노동조합 명칭대표자주 소데이터 기준일
1617서울택시 노동조합김기원서울특별시 양천구 가로공원로 69(신월동)2023-08-10
1718우리중부기업 노동조합이준호서울특별시 양천구 지양로 106 (신월동)2023-08-10
1819한국방송기술연합회 노동조합전숙희서울특별시 양천구 목동동로233, 10층(목동,한국방송회관)2023-08-10
1920해성운수 노동조합김병일서울특별시 양천구 가로공원로71(신월동)2023-08-10
2021SBS 노동조합김병길서울특별시 양천구 목동서로161(목동)2023-08-10
2122방송통신심의위원회 노동조합김현우서울특별시 양천구 목동동로233(목동)2023-08-10
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