Overview

Dataset statistics

Number of variables7
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory59.3 B

Variable types

Categorical2
Text2
DateTime2
Numeric1

Dataset

Description제주특별자치도에서 제공하는 노동조합 현황 정보로 행정관청명, 노동조합명, 사업장명, 설립일, 조합원수, 상급단체 정보를 제공합니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15099677/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
조합원수 is highly overall correlated with 상급단체High correlation
상급단체 is highly overall correlated with 조합원수High correlation
노동조합명 has unique valuesUnique
조합원수 has 1 (1.8%) zerosZeros

Reproduction

Analysis started2023-12-12 21:45:51.054251
Analysis finished2023-12-12 21:45:51.888004
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정관청명
Categorical

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size588.0 B
제주시
25 
제주특별자치도
18 
서귀포시
14 

Length

Max length7
Median length4
Mean length4.5087719
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 25
43.9%
제주특별자치도 18
31.6%
서귀포시 14
24.6%

Length

2023-12-13T06:45:51.968209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:45:52.087390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 25
43.9%
제주특별자치도 18
31.6%
서귀포시 14
24.6%

노동조합명
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-13T06:45:52.245502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length19
Mean length13.789474
Min length7

Characters and Unicode

Total characters786
Distinct characters142
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

Unique57 ?
Unique (%)100.0%

Sample

1st row전국항운노동조합연맹 제주특별자치도항운노동조합
2nd row전자노련 제주지역자동차노동조합
3rd row제주특별자치도 해상산업노동조합
4th row제주의소리 노동조합
5th row제주평등보육노동조합
ValueCountFrequency (%)
노동조합 16
 
18.4%
제주특별자치도 6
 
6.9%
전국항운노동조합연맹 1
 
1.1%
베올리아산업개발코리아(주 1
 
1.1%
제주특별자치도경제통상진흥원 1
 
1.1%
제주항공제주예약센터노동조합 1
 
1.1%
직원노동조합 1
 
1.1%
제주국제대학교 1
 
1.1%
제주현대자동차운수(주)노동조합 1
 
1.1%
제주북부광역환경관리센터노동조합 1
 
1.1%
Other values (57) 57
65.5%
2023-12-13T06:45:52.569289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 65
 
8.3%
노 62
 
7.9%
합 59
 
7.5%
조 58
 
7.4%
주 46
 
5.9%
제 45
 
5.7%
30
 
3.8%
자 15
 
1.9%
도 13
 
1.7%
리 12
 
1.5%
Other values (132) 381
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 733
93.3%
Space Separator 30
 
3.8%
Uppercase Letter 7
 
0.9%
Close Punctuation 6
 
0.8%
Open Punctuation 6
 
0.8%
Other Symbol 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 65
 
8.9%
노 62
 
8.5%
합 59
 
8.0%
조 58
 
7.9%
주 46
 
6.3%
제 45
 
6.1%
자 15
 
2.0%
도 13
 
1.8%
리 12
 
1.6%
국 9
 
1.2%
Other values (123) 349
47.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
28.6%
J 2
28.6%
I 1
14.3%
E 1
14.3%
U 1
14.3%
Space Separator
ValueCountFrequency (%)
30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 737
93.8%
Common 42
 
5.3%
Latin 7
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 65
 
8.8%
노 62
 
8.4%
합 59
 
8.0%
조 58
 
7.9%
주 46
 
6.2%
제 45
 
6.1%
자 15
 
2.0%
도 13
 
1.8%
리 12
 
1.6%
국 9
 
1.2%
Other values (124) 353
47.9%
Latin
ValueCountFrequency (%)
C 2
28.6%
J 2
28.6%
I 1
14.3%
E 1
14.3%
U 1
14.3%
Common
ValueCountFrequency (%)
30
71.4%
) 6
 
14.3%
( 6
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 733
93.3%
ASCII 49
 
6.2%
None 4
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 65
 
8.9%
노 62
 
8.5%
합 59
 
8.0%
조 58
 
7.9%
주 46
 
6.3%
제 45
 
6.1%
자 15
 
2.0%
도 13
 
1.8%
리 12
 
1.6%
국 9
 
1.2%
Other values (123) 349
47.6%
ASCII
ValueCountFrequency (%)
30
61.2%
) 6
 
12.2%
( 6
 
12.2%
C 2
 
4.1%
J 2
 
4.1%
I 1
 
2.0%
E 1
 
2.0%
U 1
 
2.0%
None
ValueCountFrequency (%)
㈜ 4
100.0%

사업장명
Text

Distinct48
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-13T06:45:52.777420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.3684211
Min length2

Characters and Unicode

Total characters420
Distinct characters118
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

Unique42 ?
Unique (%)73.7%

Sample

1st row항운
2nd row버스운송
3rd row어로어업
4th row제주의소리
5th row제주특별자치도
ValueCountFrequency (%)
제주특별자치도 5
 
8.6%
서귀포운수㈜ 2
 
3.4%
제주국제대학교 2
 
3.4%
어로어업 2
 
3.4%
항운 2
 
3.4%
예래클리프주식회사 2
 
3.4%
제주경마장 1
 
1.7%
재주관광서비스 1
 
1.7%
제주의료원 1
 
1.7%
베올리아산업개발코리아㈜ 1
 
1.7%
Other values (39) 39
67.2%
2023-12-13T06:45:53.168303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 42
 
10.0%
제 31
 
7.4%
자 11
 
2.6%
도 11
 
2.6%
) 11
 
2.6%
( 10
 
2.4%
특 9
 
2.1%
별 9
 
2.1%
치 9
 
2.1%
㈜ 9
 
2.1%
Other values (108) 268
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 376
89.5%
Uppercase Letter 13
 
3.1%
Close Punctuation 11
 
2.6%
Open Punctuation 10
 
2.4%
Other Symbol 9
 
2.1%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 42
 
11.2%
제 31
 
8.2%
자 11
 
2.9%
도 11
 
2.9%
특 9
 
2.4%
별 9
 
2.4%
치 9
 
2.4%
리 9
 
2.4%
운 9
 
2.4%
사 8
 
2.1%
Other values (98) 228
60.6%
Uppercase Letter
ValueCountFrequency (%)
C 4
30.8%
J 4
30.8%
D 2
15.4%
I 1
 
7.7%
E 1
 
7.7%
U 1
 
7.7%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 385
91.7%
Common 22
 
5.2%
Latin 13
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 42
 
10.9%
제 31
 
8.1%
자 11
 
2.9%
도 11
 
2.9%
특 9
 
2.3%
별 9
 
2.3%
치 9
 
2.3%
㈜ 9
 
2.3%
리 9
 
2.3%
운 9
 
2.3%
Other values (99) 236
61.3%
Latin
ValueCountFrequency (%)
C 4
30.8%
J 4
30.8%
D 2
15.4%
I 1
 
7.7%
E 1
 
7.7%
U 1
 
7.7%
Common
ValueCountFrequency (%)
) 11
50.0%
( 10
45.5%
1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 376
89.5%
ASCII 35
 
8.3%
None 9
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 42
 
11.2%
제 31
 
8.2%
자 11
 
2.9%
도 11
 
2.9%
특 9
 
2.4%
별 9
 
2.4%
치 9
 
2.4%
리 9
 
2.4%
운 9
 
2.4%
사 8
 
2.1%
Other values (98) 228
60.6%
ASCII
ValueCountFrequency (%)
) 11
31.4%
( 10
28.6%
C 4
 
11.4%
J 4
 
11.4%
D 2
 
5.7%
I 1
 
2.9%
E 1
 
2.9%
1
 
2.9%
U 1
 
2.9%
None
ValueCountFrequency (%)
㈜ 9
100.0%

설립일
Date

Distinct55
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum1980-09-27 00:00:00
Maximum2022-02-22 00:00:00
2023-12-13T06:45:53.329566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:45:53.509960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

조합원수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean171.08772
Minimum0
Maximum1960
Zeros1
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-13T06:45:53.921151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q114
median43
Q3154
95-th percentile722.2
Maximum1960
Range1960
Interquartile range (IQR)140

Descriptive statistics

Standard deviation352.98448
Coefficient of variation (CV)2.0631784
Kurtosis15.481738
Mean171.08772
Median Absolute Deviation (MAD)35
Skewness3.7698864
Sum9752
Variance124598.05
MonotonicityNot monotonic
2023-12-13T06:45:54.063596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
8 3
 
5.3%
14 3
 
5.3%
4 3
 
5.3%
12 2
 
3.5%
105 2
 
3.5%
13 2
 
3.5%
63 2
 
3.5%
186 2
 
3.5%
412 1
 
1.8%
100 1
 
1.8%
Other values (36) 36
63.2%
ValueCountFrequency (%)
0 1
 
1.8%
1 1
 
1.8%
4 3
5.3%
8 3
5.3%
10 1
 
1.8%
12 2
3.5%
13 2
3.5%
14 3
5.3%
17 1
 
1.8%
19 1
 
1.8%
ValueCountFrequency (%)
1960 1
1.8%
1588 1
1.8%
803 1
1.8%
702 1
1.8%
593 1
1.8%
412 1
1.8%
383 1
1.8%
314 1
1.8%
256 1
1.8%
199 1
1.8%

상급단체
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Memory size588.0 B
미가맹
28 
한국노총
4 
민주노총
3 
민)공공운수연맹
3 
한)자동차노련
3 
Other values (13)
16 

Length

Max length10
Median length8
Mean length4.7368421
Min length3

Unique

Unique10 ?
Unique (%)17.5%

Sample

1st row한)항운노련
2nd row한)자동차노련
3rd row한)선원노련
4th row미가맹
5th row민주노총

Common Values

ValueCountFrequency (%)
미가맹 28
49.1%
한국노총 4
 
7.0%
민주노총 3
 
5.3%
민)공공운수연맹 3
 
5.3%
한)자동차노련 3
 
5.3%
한)관광·서비스노련 2
 
3.5%
한)전택노련 2
 
3.5%
한)연합노련 2
 
3.5%
한)공공연맹 1
 
1.8%
한)선원노련 1
 
1.8%
Other values (8) 8
 
14.0%

Length

2023-12-13T06:45:54.214459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미가맹 28
49.1%
한국노총 4
 
7.0%
민주노총 3
 
5.3%
민)공공운수연맹 3
 
5.3%
한)자동차노련 3
 
5.3%
한)관광·서비스노련 2
 
3.5%
한)전택노련 2
 
3.5%
한)연합노련 2
 
3.5%
한)식품산업노련 1
 
1.8%
한)공공산업노련 1
 
1.8%
Other values (8) 8
 
14.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2022-04-01 00:00:00
Maximum2022-04-01 00:00:00
2023-12-13T06:45:54.309620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:45:54.400299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T06:45:51.515339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:45:54.483095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정관청명노동조합명사업장명설립일조합원수상급단체
행정관청명1.0001.0001.0001.0000.2200.000
노동조합명1.0001.0001.0001.0001.0001.000
사업장명1.0001.0001.0000.9850.8330.350
설립일1.0001.0000.9851.0000.0000.960
조합원수0.2201.0000.8330.0001.0000.877
상급단체0.0001.0000.3500.9600.8771.000
2023-12-13T06:45:54.576808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상급단체행정관청명
상급단체1.0000.000
행정관청명0.0001.000
2023-12-13T06:45:54.655236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조합원수행정관청명상급단체
조합원수1.0000.1380.567
행정관청명0.1381.0000.000
상급단체0.5670.0001.000

Missing values

2023-12-13T06:45:51.659195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:45:51.826953image/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

행정관청명노동조합명사업장명설립일조합원수상급단체데이터기준일자
0제주특별자치도전국항운노동조합연맹 제주특별자치도항운노동조합항운1980-11-28593한)항운노련2022-04-01
1제주특별자치도전자노련 제주지역자동차노동조합버스운송1988-10-20702한)자동차노련2022-04-01
2제주특별자치도제주특별자치도 해상산업노동조합어로어업1989-01-091960한)선원노련2022-04-01
3제주특별자치도제주의소리 노동조합제주의소리2009-02-1112미가맹2022-04-01
4제주특별자치도제주평등보육노동조합제주특별자치도2017-06-08105민주노총2022-04-01
5제주특별자치도제주예능인노동조합제주특별자치도2017-10-2719예능인노련2022-04-01
6제주특별자치도제주관광서비스노동조합재주관광서비스2018-03-27383민)서비스연맹2022-04-01
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