Overview

Dataset statistics

Number of variables13
Number of observations81
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory109.6 B

Variable types

Text3
Categorical5
Numeric3
DateTime2

Dataset

Description여수시 내에 소재지를 둔 기업에서 노동자들이 자체적으로 형성한 노동조합 현황을 조사하여 정리한 데이터입니다. 데이터 목록으로는 노동조합단체명, 노동조합형태, 노동조합주소, 주소의 좌표인 경도, 위도, 노동조합 최초설립일자, 소속단체명 등이 있습니다.
Author전라남도 여수시
URLhttps://www.data.go.kr/data/15107955/fileData.do

Alerts

소재지지번주소 has constant value ""Constant
소재지전화번호 has constant value ""Constant
소속사업장명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
전체조합원수 is highly overall correlated with 소속단체명High correlation
노동조합형태 is highly overall correlated with 소속단체명High correlation
소속단체명 is highly overall correlated with 전체조합원수 and 1 other fieldsHigh correlation
노동조합형태 is highly imbalanced (54.7%)Imbalance
노동조합단체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:54:52.929873
Analysis finished2023-12-12 03:54:56.119490
Duration3.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노동조합단체명
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-12T12:54:56.367352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length10.271605
Min length6

Characters and Unicode

Total characters832
Distinct characters155
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)100.0%

Sample

1st row그린노동조합
2nd row성동기업노동조합
3rd row재원산업(주)노동조합
4th row여수시도시관리공단 공무직노동조합
5th row삼호관광노동조합
ValueCountFrequency (%)
노동조합 22
 
20.4%
여수시도시관리공단 3
 
2.8%
그린노동조합 1
 
0.9%
신정상운 1
 
0.9%
krcc 1
 
0.9%
sy탱크터미널 1
 
0.9%
폴리미래(주)노동조합 1
 
0.9%
한화솔루션tdi노동조합 1
 
0.9%
위스컴 1
 
0.9%
여수지역건설 1
 
0.9%
Other values (75) 75
69.4%
2023-12-12T12:54:56.991099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 83
 
10.0%
조 81
 
9.7%
합 80
 
9.6%
노 78
 
9.4%
27
 
3.2%
수 26
 
3.1%
여 25
 
3.0%
시 12
 
1.4%
업 12
 
1.4%
주 12
 
1.4%
Other values (145) 396
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 768
92.3%
Space Separator 27
 
3.2%
Open Punctuation 11
 
1.3%
Close Punctuation 11
 
1.3%
Uppercase Letter 10
 
1.2%
Lowercase Letter 3
 
0.4%
Other Symbol 1
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 83
 
10.8%
조 81
 
10.5%
합 80
 
10.4%
노 78
 
10.2%
수 26
 
3.4%
여 25
 
3.3%
시 12
 
1.6%
업 12
 
1.6%
주 12
 
1.6%
화 11
 
1.4%
Other values (129) 348
45.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
20.0%
D 1
10.0%
S 1
10.0%
T 1
10.0%
I 1
10.0%
Y 1
10.0%
R 1
10.0%
K 1
10.0%
E 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
66.7%
k 1
33.3%
Space Separator
ValueCountFrequency (%)
27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 769
92.4%
Common 50
 
6.0%
Latin 13
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 83
 
10.8%
조 81
 
10.5%
합 80
 
10.4%
노 78
 
10.1%
수 26
 
3.4%
여 25
 
3.3%
시 12
 
1.6%
업 12
 
1.6%
주 12
 
1.6%
화 11
 
1.4%
Other values (130) 349
45.4%
Latin
ValueCountFrequency (%)
C 2
15.4%
c 2
15.4%
D 1
7.7%
S 1
7.7%
T 1
7.7%
I 1
7.7%
Y 1
7.7%
R 1
7.7%
K 1
7.7%
E 1
7.7%
Common
ValueCountFrequency (%)
27
54.0%
( 11
22.0%
) 11
22.0%
1 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 768
92.3%
ASCII 63
 
7.6%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 83
 
10.8%
조 81
 
10.5%
합 80
 
10.4%
노 78
 
10.2%
수 26
 
3.4%
여 25
 
3.3%
시 12
 
1.6%
업 12
 
1.6%
주 12
 
1.6%
화 11
 
1.4%
Other values (129) 348
45.3%
ASCII
ValueCountFrequency (%)
27
42.9%
( 11
17.5%
) 11
17.5%
C 2
 
3.2%
c 2
 
3.2%
D 1
 
1.6%
S 1
 
1.6%
T 1
 
1.6%
I 1
 
1.6%
Y 1
 
1.6%
Other values (5) 5
 
7.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

노동조합형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size780.0 B
기업단위노조
66 
지역단위노조
10 
단위노조 산하조직
 
4
전국단위노조
 
1

Length

Max length9
Median length6
Mean length6.1481481
Min length6

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
기업단위노조 66
81.5%
지역단위노조 10
 
12.3%
단위노조 산하조직 4
 
4.9%
전국단위노조 1
 
1.2%

Length

2023-12-12T12:54:57.210827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:54:57.392125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기업단위노조 66
77.6%
지역단위노조 10
 
11.8%
단위노조 4
 
4.7%
산하조직 4
 
4.7%
전국단위노조 1
 
1.2%

노동조합주소
Text

Distinct69
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-12T12:54:57.918158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length35
Mean length25.469136
Min length19

Characters and Unicode

Total characters2063
Distinct characters102
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)81.5%

Sample

1st row전라남도 여수시 봉계3길 19(봉계동)
2nd row전라남도 여수시 진달래길 310-92(월내동)
3rd row전라남도 여수시 산단중앙로 77-33 재원산업(주) (화치동)
4th row전라남도 여수시 오동도로 116 여수시도시관리공단 (수정동)
5th row전라남도 여수시 여수산단2로 55 삼호실업 현장사무실 (화치동)
ValueCountFrequency (%)
전라남도 81
19.2%
여수시 81
19.2%
여수산단로 23
 
5.5%
낙포동 15
 
3.6%
1384 10
 
2.4%
여수산단2로 10
 
2.4%
화치동 9
 
2.1%
월하동 7
 
1.7%
신월로 5
 
1.2%
신월동 5
 
1.2%
Other values (129) 176
41.7%
2023-12-12T12:54:58.664483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
358
17.4%
여 132
 
6.4%
수 128
 
6.2%
남 86
 
4.2%
) 83
 
4.0%
( 83
 
4.0%
도 83
 
4.0%
시 83
 
4.0%
전 82
 
4.0%
라 81
 
3.9%
Other values (92) 864
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1225
59.4%
Space Separator 358
 
17.4%
Decimal Number 297
 
14.4%
Close Punctuation 83
 
4.0%
Open Punctuation 83
 
4.0%
Dash Punctuation 17
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 132
 
10.8%
수 128
 
10.4%
남 86
 
7.0%
도 83
 
6.8%
시 83
 
6.8%
전 82
 
6.7%
라 81
 
6.6%
동 81
 
6.6%
로 65
 
5.3%
단 50
 
4.1%
Other values (78) 354
28.9%
Decimal Number
ValueCountFrequency (%)
1 58
19.5%
2 53
17.8%
3 45
15.2%
4 35
11.8%
8 26
8.8%
0 18
 
6.1%
6 18
 
6.1%
7 16
 
5.4%
9 15
 
5.1%
5 13
 
4.4%
Space Separator
ValueCountFrequency (%)
358
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1225
59.4%
Common 838
40.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 132
 
10.8%
수 128
 
10.4%
남 86
 
7.0%
도 83
 
6.8%
시 83
 
6.8%
전 82
 
6.7%
라 81
 
6.6%
동 81
 
6.6%
로 65
 
5.3%
단 50
 
4.1%
Other values (78) 354
28.9%
Common
ValueCountFrequency (%)
358
42.7%
) 83
 
9.9%
( 83
 
9.9%
1 58
 
6.9%
2 53
 
6.3%
3 45
 
5.4%
4 35
 
4.2%
8 26
 
3.1%
0 18
 
2.1%
6 18
 
2.1%
Other values (4) 61
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1225
59.4%
ASCII 838
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
358
42.7%
) 83
 
9.9%
( 83
 
9.9%
1 58
 
6.9%
2 53
 
6.3%
3 45
 
5.4%
4 35
 
4.2%
8 26
 
3.1%
0 18
 
2.1%
6 18
 
2.1%
Other values (4) 61
 
7.3%
Hangul
ValueCountFrequency (%)
여 132
 
10.8%
수 128
 
10.4%
남 86
 
7.0%
도 83
 
6.8%
시 83
 
6.8%
전 82
 
6.7%
라 81
 
6.6%
동 81
 
6.6%
로 65
 
5.3%
단 50
 
4.1%
Other values (78) 354
28.9%

소재지지번주소
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
미기입
81 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미기입 81
100.0%

Length

2023-12-12T12:54:58.859320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:54:59.017456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미기입 81
100.0%

소재지전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
0
81 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 81
100.0%

Length

2023-12-12T12:54:59.155057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:54:59.314632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 81
100.0%

경도
Real number (ℝ)

Distinct62
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.70165
Minimum127.63905
Maximum127.77153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T12:54:59.466882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.63905
5-th percentile127.65038
Q1127.66462
median127.70392
Q3127.73373
95-th percentile127.75979
Maximum127.77153
Range0.1324835
Interquartile range (IQR)0.0691106

Descriptive statistics

Standard deviation0.040000263
Coefficient of variation (CV)0.00031323215
Kurtosis-1.3328518
Mean127.70165
Median Absolute Deviation (MAD)0.0393042
Skewness0.19189208
Sum10343.834
Variance0.001600021
MonotonicityNot monotonic
2023-12-12T12:54:59.682037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.7597928 9
 
11.1%
127.7078715 4
 
4.9%
127.6646186 4
 
4.9%
127.6625888 2
 
2.5%
127.6526921 2
 
2.5%
127.6799403 2
 
2.5%
127.7269082 2
 
2.5%
127.7102932 2
 
2.5%
127.7212302 1
 
1.2%
127.6574383 1
 
1.2%
Other values (52) 52
64.2%
ValueCountFrequency (%)
127.6390501 1
1.2%
127.6431446 1
1.2%
127.6443726 1
1.2%
127.6485462 1
1.2%
127.6503786 1
1.2%
127.650656 1
1.2%
127.6523541 1
1.2%
127.652424 1
1.2%
127.6526921 2
2.5%
127.6528526 1
1.2%
ValueCountFrequency (%)
127.7715336 1
 
1.2%
127.7633155 1
 
1.2%
127.7622277 1
 
1.2%
127.7597935 1
 
1.2%
127.7597928 9
11.1%
127.7548138 1
 
1.2%
127.7528832 1
 
1.2%
127.7527789 1
 
1.2%
127.7516552 1
 
1.2%
127.7448391 1
 
1.2%

위도
Real number (ℝ)

Distinct63
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.798919
Minimum34.721097
Maximum34.862118
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T12:54:59.881495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.721097
5-th percentile34.729998
Q134.757595
median34.812942
Q334.838438
95-th percentile34.850875
Maximum34.862118
Range0.1410205
Interquartile range (IQR)0.0808431

Descriptive statistics

Standard deviation0.04381253
Coefficient of variation (CV)0.0012590199
Kurtosis-1.3470131
Mean34.798919
Median Absolute Deviation (MAD)0.0352572
Skewness-0.30172939
Sum2818.7124
Variance0.0019195378
MonotonicityNot monotonic
2023-12-12T12:55:00.130193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.8481995 9
 
11.1%
34.8129423 4
 
4.9%
34.7334762 4
 
4.9%
34.8108708 2
 
2.5%
34.8469538 2
 
2.5%
34.8131506 2
 
2.5%
34.8371576 2
 
2.5%
34.8175337 1
 
1.2%
34.8378505 1
 
1.2%
34.7529611 1
 
1.2%
Other values (53) 53
65.4%
ValueCountFrequency (%)
34.7210975 1
 
1.2%
34.7251587 1
 
1.2%
34.7277459 1
 
1.2%
34.7295805 1
 
1.2%
34.729998 1
 
1.2%
34.7308072 1
 
1.2%
34.7334643 1
 
1.2%
34.7334762 4
4.9%
34.7346805 1
 
1.2%
34.7447447 1
 
1.2%
ValueCountFrequency (%)
34.862118 1
 
1.2%
34.8614449 1
 
1.2%
34.8601089 1
 
1.2%
34.8528414 1
 
1.2%
34.8508752 1
 
1.2%
34.8496352 1
 
1.2%
34.8481995 9
11.1%
34.8470877 1
 
1.2%
34.8469538 2
 
2.5%
34.8460225 1
 
1.2%

설립일자
Date

Distinct76
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size780.0 B
Minimum1961-11-14 00:00:00
Maximum2022-03-10 00:00:00
2023-12-12T12:55:00.366170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:55:00.928010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소속단체명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
미기입
24 
전국화학노동조합연맹
19 
미가입
13 
전국민주화학섬유노동조합연맹
5 
전국항운노동조합연맹
4 
Other values (12)
16 

Length

Max length21
Median length14
Mean length7.0123457
Min length3

Unique

Unique9 ?
Unique (%)11.1%

Sample

1st row전국화학노동조합연맹
2nd row미기입
3rd row전국화학노동조합연맹
4th row미기입
5th row미기입

Common Values

ValueCountFrequency (%)
미기입 24
29.6%
전국화학노동조합연맹 19
23.5%
미가입 13
16.0%
전국민주화학섬유노동조합연맹 5
 
6.2%
전국항운노동조합연맹 4
 
4.9%
전국택시노동조합연맹 3
 
3.7%
화학노련 2
 
2.5%
전국금속노동조합연맹 2
 
2.5%
한국노총 전국자동차노조연맹 1
 
1.2%
한국노총 전국화학연맹 1
 
1.2%
Other values (7) 7
 
8.6%

Length

2023-12-12T12:55:01.166128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미기입 24
28.6%
전국화학노동조합연맹 19
22.6%
미가입 13
15.5%
전국민주화학섬유노동조합연맹 5
 
6.0%
전국항운노동조합연맹 4
 
4.8%
전국택시노동조합연맹 4
 
4.8%
화학노련 2
 
2.4%
전국금속노동조합연맹 2
 
2.4%
한국노총 2
 
2.4%
전국해상선원노동조합연맹 1
 
1.2%
Other values (8) 8
 
9.5%

대표자명
Text

Distinct80
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-12T12:55:01.550699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters243
Distinct characters83
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

Unique79 ?
Unique (%)97.5%

Sample

1st row이호현
2nd row배희용
3rd row최경민
4th row최지원
5th row김남기
ValueCountFrequency (%)
김종현 2
 
2.5%
이호현 1
 
1.2%
최종만 1
 
1.2%
정선규 1
 
1.2%
김성호 1
 
1.2%
정원희 1
 
1.2%
심재길 1
 
1.2%
권영균 1
 
1.2%
주선학 1
 
1.2%
유남길 1
 
1.2%
Other values (70) 70
86.4%
2023-12-12T12:55:02.141846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 20
 
8.2%
정 13
 
5.3%
종 10
 
4.1%
현 9
 
3.7%
이 9
 
3.7%
박 8
 
3.3%
선 6
 
2.5%
용 6
 
2.5%
성 6
 
2.5%
승 6
 
2.5%
Other values (73) 150
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 20
 
8.2%
정 13
 
5.3%
종 10
 
4.1%
현 9
 
3.7%
이 9
 
3.7%
박 8
 
3.3%
선 6
 
2.5%
용 6
 
2.5%
성 6
 
2.5%
승 6
 
2.5%
Other values (73) 150
61.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 20
 
8.2%
정 13
 
5.3%
종 10
 
4.1%
현 9
 
3.7%
이 9
 
3.7%
박 8
 
3.3%
선 6
 
2.5%
용 6
 
2.5%
성 6
 
2.5%
승 6
 
2.5%
Other values (73) 150
61.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 20
 
8.2%
정 13
 
5.3%
종 10
 
4.1%
현 9
 
3.7%
이 9
 
3.7%
박 8
 
3.3%
선 6
 
2.5%
용 6
 
2.5%
성 6
 
2.5%
승 6
 
2.5%
Other values (73) 150
61.7%

전체조합원수
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean147.69136
Minimum2
Maximum4255
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T12:55:02.422233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q19
median33
Q380
95-th percentile279
Maximum4255
Range4253
Interquartile range (IQR)71

Descriptive statistics

Standard deviation537.06877
Coefficient of variation (CV)3.6364265
Kurtosis45.904939
Mean147.69136
Median Absolute Deviation (MAD)27
Skewness6.4930094
Sum11963
Variance288442.87
MonotonicityNot monotonic
2023-12-12T12:55:02.677682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 7
 
8.6%
2 4
 
4.9%
5 3
 
3.7%
20 3
 
3.7%
30 3
 
3.7%
8 3
 
3.7%
33 3
 
3.7%
15 3
 
3.7%
16 2
 
2.5%
74 2
 
2.5%
Other values (45) 48
59.3%
ValueCountFrequency (%)
2 4
4.9%
3 7
8.6%
5 3
3.7%
6 1
 
1.2%
7 2
 
2.5%
8 3
3.7%
9 1
 
1.2%
10 1
 
1.2%
12 1
 
1.2%
13 1
 
1.2%
ValueCountFrequency (%)
4255 1
1.2%
2194 1
1.2%
950 1
1.2%
758 1
1.2%
279 1
1.2%
246 1
1.2%
193 1
1.2%
186 1
1.2%
165 1
1.2%
145 1
1.2%

소속사업장명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
미기입
81 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미기입 81
100.0%

Length

2023-12-12T12:55:02.860512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:55:02.983668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미기입 81
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
Minimum2022-11-17 00:00:00
Maximum2022-11-17 00:00:00
2023-12-12T12:55:03.077243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:55:03.217647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T12:54:55.217913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:54:54.261546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:54:54.752434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:54:55.362787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:54:54.424998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:54:54.921379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:54:55.512861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:54:54.586236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:54:55.089463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:55:03.334433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노동조합단체명노동조합형태노동조합주소경도위도설립일자소속단체명대표자명전체조합원수
노동조합단체명1.0001.0001.0001.0001.0001.0001.0001.0001.000
노동조합형태1.0001.0001.0000.0560.0000.9820.8200.7630.370
노동조합주소1.0001.0001.0001.0001.0000.8640.8240.9931.000
경도1.0000.0561.0001.0000.8610.8600.3150.9670.000
위도1.0000.0001.0000.8611.0000.9210.2050.9760.000
설립일자1.0000.9820.8640.8600.9211.0000.8090.9970.000
소속단체명1.0000.8200.8240.3150.2050.8091.0000.9840.843
대표자명1.0000.7630.9930.9670.9760.9970.9841.0001.000
전체조합원수1.0000.3701.0000.0000.0000.0000.8431.0001.000
2023-12-12T12:55:03.502245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소속단체명노동조합형태
소속단체명1.0000.563
노동조합형태0.5631.000
2023-12-12T12:55:03.725492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도전체조합원수노동조합형태소속단체명
경도1.0000.302-0.0780.0000.109
위도0.3021.0000.1320.0000.056
전체조합원수-0.0780.1321.0000.3070.584
노동조합형태0.0000.0000.3071.0000.563
소속단체명0.1090.0560.5840.5631.000

Missing values

2023-12-12T12:54:55.706024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:54:56.012118image/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

노동조합단체명노동조합형태노동조합주소소재지지번주소소재지전화번호경도위도설립일자소속단체명대표자명전체조합원수소속사업장명데이터기준일자
0그린노동조합기업단위노조전라남도 여수시 봉계3길 19(봉계동)미기입0127.66576334.7865922022-03-10전국화학노동조합연맹이호현5미기입2022-11-17
1성동기업노동조합기업단위노조전라남도 여수시 진달래길 310-92(월내동)미기입0127.73125334.8496352021-11-15미기입배희용5미기입2022-11-17
2재원산업(주)노동조합기업단위노조전라남도 여수시 산단중앙로 77-33 재원산업(주) (화치동)미기입0127.65065634.8203372021-08-06전국화학노동조합연맹최경민8미기입2022-11-17
3여수시도시관리공단 공무직노동조합기업단위노조전라남도 여수시 오동도로 116 여수시도시관리공단 (수정동)미기입0127.75165534.7450382021-07-12미기입최지원20미기입2022-11-17
4삼호관광노동조합기업단위노조전라남도 여수시 여수산단2로 55 삼호실업 현장사무실 (화치동)미기입0127.65235434.8014412021-05-17미기입김남기30미기입2022-11-17
5(주)동성케미컬 관리직 노동조합기업단위노조전라남도 여수시 여수산단2로 223-40 (화치동)미기입0127.65037934.8153072021-03-23미기입문종현2미기입2022-11-17
6금호티앤엘노동조합기업단위노조전라남도 여수시 여수산단로 1469-100 (낙포동)미기입0127.76222834.8528412020-06-24미기입장행선23미기입2022-11-17
7서초산업노동조합기업단위노조전라남도 여수시 여수산단로 334-27 롯데첨단소재(주) (평여동)미기입0127.6799434.8131512020-04-28미기입임경철17미기입2022-11-17
8여수시도시관리공단공기업노동조합기업단위노조전라남도 여수시 신월로 319 (신월동)미기입0127.70787134.7334762019-12-31미기입김일두3미기입2022-11-17
9㈜하이팩여수노동조합기업단위노조전라남도 여수시 여수산단로 1384 (낙포동)미기입0127.75979334.8481992019-12-09전국화학노동조합연맹정재윤33미기입2022-11-17
노동조합단체명노동조합형태노동조합주소소재지지번주소소재지전화번호경도위도설립일자소속단체명대표자명전체조합원수소속사업장명데이터기준일자
71금호석유 여수공장 노동조합기업단위노조전라남도 여수시 여수산단3로 118 (평여동)미기입0127.66728334.8251121989-03-27전국화학노동조합연맹이치훈186미기입2022-11-17
72금호미쓰이화학(주) 노동조합기업단위노조전라남도 여수시 여수산단2로 305 (화치동)미기입0127.64854634.8164341996-03-19화학노련오현우83미기입2022-11-17
73월드켐노동조합기업단위노조전라남도 여수시 여수산단2로 227 (화치동)미기입0127.65242434.8170651988-03-26전국화학노동조합연맹강기행6미기입2022-11-17
74대륙기업노동조합기업단위노조전라남도 여수시 여수산단로 1384 (낙포동)미기입0127.75979334.8481991988-05-16전국화학노동조합연맹이근원15미기입2022-11-17
75남해화학노동조합기업단위노조전라남도 여수시 여수산단로 1384 (낙포동)미기입0127.75979334.8481991977-10-13전국화학노동조합연맹정병권246미기입2022-11-17
76금호폴리켐노동조합기업단위노조전라남도 여수시 여수산단2로 116-46 (월하동)미기입0127.65737934.8112771990-03-10전국화학노동조합연맹진영철84미기입2022-11-17
77여수수산업협동조합노동조합기업단위노조전라남도 여수시 어항단지로 210 (봉산동)미기입0127.72821534.7299981990-01-23전국금융노동조합연맹송하정165미기입2022-11-17
78코리아카본블랙노동조합기업단위노조전라남도 여수시 진달래길 310-88 (월내동)미기입0127.73372934.8470881999-01-15전국화학노동조합연맹이종선76미기입2022-11-17
79(유)내오텍노동조합기업단위노조전라남도 여수시 여수산단로 918 (월내동)미기입0127.72690834.8469541989-01-08전국화학노동조합연맹이승권38미기입2022-11-17
80여수종합항운노동조합기업단위노조전라남도 여수시 여수산단로 1384 (낙포동)미기입0127.75979334.8481991989-03-29전국항운노동조합연맹김순종20미기입2022-11-17