Overview

Dataset statistics

Number of variables6
Number of observations56
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory51.4 B

Variable types

Numeric1
Text2
Categorical1
DateTime2

Dataset

Description확인받은 녹색전문기업 중 기준일 시점에 유효한 목록들이며 순번, 신청기관명, 발급부처, 확인번호, 확인일자, 확인만료일자로 이루어져 있습니다.
Author한국산업기술진흥원
URLhttps://www.data.go.kr/data/15054158/fileData.do

Alerts

순번 has unique valuesUnique
신청기관명 has unique valuesUnique
확인번호 has unique valuesUnique

Reproduction

Analysis started2024-04-21 01:20:09.214954
Analysis finished2024-04-21 01:20:11.276688
Duration2.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.5
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-21T10:20:11.341114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.75
Q114.75
median28.5
Q342.25
95-th percentile53.25
Maximum56
Range55
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation16.309506
Coefficient of variation (CV)0.57226338
Kurtosis-1.2
Mean28.5
Median Absolute Deviation (MAD)14
Skewness0
Sum1596
Variance266
MonotonicityStrictly increasing
2024-04-21T10:20:11.463322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
30 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (46) 46
82.1%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%
47 1
1.8%

신청기관명
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-04-21T10:20:11.665255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.7857143
Min length6

Characters and Unicode

Total characters492
Distinct characters123
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st row에스이엘텍 주식회사
2nd row주식회사 스타스테크
3rd row(주)불스원
4th row주식회사 비알인포텍
5th row고암인더스트리(주)
ValueCountFrequency (%)
주식회사 20
 
25.3%
에스이엘텍 1
 
1.3%
테크유니온 1
 
1.3%
주)미래테크 1
 
1.3%
주)시너젠 1
 
1.3%
주)에코마인 1
 
1.3%
엠케이바이오텍 1
 
1.3%
주)네스랩 1
 
1.3%
주)범석엔지니어링 1
 
1.3%
주)엘에스케이화인텍스 1
 
1.3%
Other values (50) 50
63.3%
2024-04-21T10:20:11.967822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 55
 
11.2%
) 34
 
6.9%
( 34
 
6.9%
24
 
4.9%
사 23
 
4.7%
회 22
 
4.5%
식 21
 
4.3%
이 17
 
3.5%
스 13
 
2.6%
에 10
 
2.0%
Other values (113) 239
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 397
80.7%
Close Punctuation 34
 
6.9%
Open Punctuation 34
 
6.9%
Space Separator 24
 
4.9%
Other Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 55
 
13.9%
사 23
 
5.8%
회 22
 
5.5%
식 21
 
5.3%
이 17
 
4.3%
스 13
 
3.3%
에 10
 
2.5%
지 9
 
2.3%
앤 9
 
2.3%
텍 8
 
2.0%
Other values (109) 210
52.9%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 397
80.7%
Common 95
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 55
 
13.9%
사 23
 
5.8%
회 22
 
5.5%
식 21
 
5.3%
이 17
 
4.3%
스 13
 
3.3%
에 10
 
2.5%
지 9
 
2.3%
앤 9
 
2.3%
텍 8
 
2.0%
Other values (109) 210
52.9%
Common
ValueCountFrequency (%)
) 34
35.8%
( 34
35.8%
24
25.3%
. 3
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 397
80.7%
ASCII 95
 
19.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 55
 
13.9%
사 23
 
5.8%
회 22
 
5.5%
식 21
 
5.3%
이 17
 
4.3%
스 13
 
3.3%
에 10
 
2.5%
지 9
 
2.3%
앤 9
 
2.3%
텍 8
 
2.0%
Other values (109) 210
52.9%
ASCII
ValueCountFrequency (%)
) 34
35.8%
( 34
35.8%
24
25.3%
. 3
 
3.2%

발급부처
Categorical

Distinct6
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size580.0 B
중소벤처기업부
20 
환경부
14 
농림축산식품부
11 
과학기술정보통신부
7 
국토교통부
3 

Length

Max length9
Median length7
Mean length6.1428571
Min length3

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row중소벤처기업부
2nd row환경부
3rd row중소벤처기업부
4th row과학기술정보통신부
5th row중소벤처기업부

Common Values

ValueCountFrequency (%)
중소벤처기업부 20
35.7%
환경부 14
25.0%
농림축산식품부 11
19.6%
과학기술정보통신부 7
 
12.5%
국토교통부 3
 
5.4%
산업통상자원부 1
 
1.8%

Length

2024-04-21T10:20:12.108458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:20:12.202521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중소벤처기업부 20
35.7%
환경부 14
25.0%
농림축산식품부 11
19.6%
과학기술정보통신부 7
 
12.5%
국토교통부 3
 
5.4%
산업통상자원부 1
 
1.8%

확인번호
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-04-21T10:20:12.411659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters616
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st rowGE-24-00105
2nd rowGE-24-00104
3rd rowGE-23-00103
4th rowGE-23-00102
5th rowGE-23-00101
ValueCountFrequency (%)
ge-24-00105 1
 
1.8%
ge-24-00104 1
 
1.8%
ge-20-00064 1
 
1.8%
ge-21-00075 1
 
1.8%
ge-21-00074 1
 
1.8%
ge-21-00073 1
 
1.8%
ge-21-00072 1
 
1.8%
ge-21-00070 1
 
1.8%
ge-21-00071 1
 
1.8%
ge-21-00069 1
 
1.8%
Other values (46) 46
82.1%
2024-04-21T10:20:12.733650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 178
28.9%
- 112
18.2%
2 57
 
9.3%
G 56
 
9.1%
E 56
 
9.1%
1 37
 
6.0%
3 25
 
4.1%
8 24
 
3.9%
9 18
 
2.9%
7 16
 
2.6%
Other values (3) 37
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 392
63.6%
Dash Punctuation 112
 
18.2%
Uppercase Letter 112
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 178
45.4%
2 57
 
14.5%
1 37
 
9.4%
3 25
 
6.4%
8 24
 
6.1%
9 18
 
4.6%
7 16
 
4.1%
4 15
 
3.8%
6 14
 
3.6%
5 8
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
G 56
50.0%
E 56
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 504
81.8%
Latin 112
 
18.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 178
35.3%
- 112
22.2%
2 57
 
11.3%
1 37
 
7.3%
3 25
 
5.0%
8 24
 
4.8%
9 18
 
3.6%
7 16
 
3.2%
4 15
 
3.0%
6 14
 
2.8%
Latin
ValueCountFrequency (%)
G 56
50.0%
E 56
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 616
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 178
28.9%
- 112
18.2%
2 57
 
9.3%
G 56
 
9.1%
E 56
 
9.1%
1 37
 
6.0%
3 25
 
4.1%
8 24
 
3.9%
9 18
 
2.9%
7 16
 
2.6%
Other values (3) 37
 
6.0%

확인일자
Date

Distinct33
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Memory size580.0 B
Minimum2017-10-26 00:00:00
Maximum2024-03-14 00:00:00
2024-04-21T10:20:12.863783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:20:12.973199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

확인만료일자
Date

Distinct33
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Memory size580.0 B
Minimum2023-07-15 00:00:00
Maximum2027-03-13 00:00:00
2024-04-21T10:20:13.091262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:20:13.199069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

Interactions

2024-04-21T10:20:10.991238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:20:13.272326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번신청기관명발급부처확인번호확인일자확인만료일자
순번1.0001.0000.0001.0000.9730.973
신청기관명1.0001.0001.0001.0001.0001.000
발급부처0.0001.0001.0001.0000.0000.000
확인번호1.0001.0001.0001.0001.0001.000
확인일자0.9731.0000.0001.0001.0001.000
확인만료일자0.9731.0000.0001.0001.0001.000
2024-04-21T10:20:13.358036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번발급부처
순번1.0000.000
발급부처0.0001.000

Missing values

2024-04-21T10:20:11.139879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:20:11.234480image/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

순번신청기관명발급부처확인번호확인일자확인만료일자
01에스이엘텍 주식회사중소벤처기업부GE-24-001052024-03-142027-03-13
12주식회사 스타스테크환경부GE-24-001042024-01-252027-01-24
23(주)불스원중소벤처기업부GE-23-001032023-12-142026-12-13
34주식회사 비알인포텍과학기술정보통신부GE-23-001022023-09-142026-09-13
45고암인더스트리(주)중소벤처기업부GE-23-001012023-09-142026-09-13
56(주)쓰리텍산업통상자원부GE-23-000992023-07-272026-07-26
67(주)대우루컴즈환경부GE-23-001002023-07-272026-07-26
78주식회사 태흥에프엔지농림축산식품부GE-23-000972023-07-272026-07-26
89(주)신화엔바텍중소벤처기업부GE-23-000982023-07-272026-07-26
910쏠라리버 주식회사중소벤처기업부GE-23-000962023-06-152026-06-14
순번신청기관명발급부처확인번호확인일자확인만료일자
4647삼구화학공업(주)환경부GE-18-000482018-11-152024-11-14
4748(주) 오로라 디자인랩환경부GE-18-000492018-11-152024-11-14
4849(주)우진산전국토교통부GE-18-000452018-07-122024-07-11
4950(주)서우건설산업국토교통부GE-18-000422018-06-142024-06-13
5051(주)청우지엔티환경부GE-18-000442018-06-142024-06-13
5152(주)알엠소프트중소벤처기업부GE-18-000402018-05-172024-05-16
5253주식회사 에이유농림축산식품부GE-18-000362018-03-082024-03-07
5354주식회사사이클론환경부GE-18-000392018-03-082024-03-07
5455쉬프트정보통신(주)중소벤처기업부GE-17-000342017-11-232023-11-22
5556(주)지필로스중소벤처기업부GE-17-000312017-10-262023-10-25