Overview

Dataset statistics

Number of variables6
Number of observations34
Missing cells4
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory54.9 B

Variable types

Categorical2
Text1
Numeric3

Dataset

Description(주)한국가스기술공사의 경영평가 지표별 평가등급에 대한 정보로 구분, 항목, 가중치(비계량, 계량) 점수 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15103617/fileData.do

Alerts

가중치(비계량) is highly overall correlated with 가중치(계량) and 1 other fieldsHigh correlation
가중치(계량) is highly overall correlated with 가중치(비계량) and 1 other fieldsHigh correlation
점수(계량) is highly overall correlated with 가중치(비계량) and 1 other fieldsHigh correlation
구분 is highly overall correlated with 등급(비계량)High correlation
등급(비계량) is highly overall correlated with 구분High correlation
항목 has 2 (5.9%) missing valuesMissing
가중치(비계량) has 2 (5.9%) missing valuesMissing
가중치(비계량) has 15 (44.1%) zerosZeros
가중치(계량) has 15 (44.1%) zerosZeros
점수(계량) has 15 (44.1%) zerosZeros

Reproduction

Analysis started2023-12-12 19:01:33.886468
Analysis finished2023-12-12 19:01:35.896073
Duration2.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Memory size404.0 B
경영관리(3. 재무성과관리)
11 
경영관리(2. 사회적 책임)
5 
경영관리(5. 보수 및 복리후생관리)
4 
경영관리(1. 경영전략 및 리더십)
3 
주요사업(1. 가스플랜트 정비사업)
3 
Other values (5)
8 

Length

Max length36
Median length27
Mean length18.147059
Min length14

Unique

Unique2 ?
Unique (%)5.9%

Sample

1st row경영관리(1. 경영전략 및 리더십)
2nd row경영관리(1. 경영전략 및 리더십)
3rd row경영관리(1. 경영전략 및 리더십)
4th row경영관리(2. 사회적 책임)
5th row경영관리(2. 사회적 책임)

Common Values

ValueCountFrequency (%)
경영관리(3. 재무성과관리) 11
32.4%
경영관리(2. 사회적 책임) 5
14.7%
경영관리(5. 보수 및 복리후생관리) 4
 
11.8%
경영관리(1. 경영전략 및 리더십) 3
 
8.8%
주요사업(1. 가스플랜트 정비사업) 3
 
8.8%
경영관리(4. 조직 및 인적자원관리) 2
 
5.9%
주요사업(2. 가스플랜트 엔지니어링 및 건설사업) 2
 
5.9%
주요사업(3. 신성장사업) 2
 
5.9%
주요사업(4. 주요사업 계량지표 구성의 적정성 및 목표의 도전성) 1
 
2.9%
가점(공공기관 혁신계획 실행노력과 성과 가점) 1
 
2.9%

Length

2023-12-13T04:01:36.000679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:01:36.180923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
및 12
 
11.0%
경영관리(3 11
 
10.1%
재무성과관리 11
 
10.1%
경영관리(2 5
 
4.6%
사회적 5
 
4.6%
책임 5
 
4.6%
가스플랜트 5
 
4.6%
경영관리(5 4
 
3.7%
보수 4
 
3.7%
복리후생관리 4
 
3.7%
Other values (25) 43
39.4%

항목
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing2
Missing (%)5.9%
Memory size404.0 B
2023-12-13T04:01:36.520662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length13.28125
Min length6

Characters and Unicode

Total characters425
Distinct characters122
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

Unique32 ?
Unique (%)100.0%

Sample

1st row(1) 리더십
2nd row(2) 전략기획 및 경영혁신
3rd row(3) 국민소통
4th row(1) 일자리 및 균등한 기회
5th row(2) 안전 및 재난관리
ValueCountFrequency (%)
및 9
 
8.2%
2 8
 
7.3%
1 8
 
7.3%
3 4
 
3.6%
적정성 3
 
2.7%
가스플랜트 3
 
2.7%
㉯ 3
 
2.7%
㉮ 3
 
2.7%
성과관리의 3
 
2.7%
보수 2
 
1.8%
Other values (59) 64
58.2%
2023-12-13T04:01:37.184463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
78
 
18.4%
( 22
 
5.2%
) 22
 
5.2%
리 17
 
4.0%
성 17
 
4.0%
관 12
 
2.8%
및 9
 
2.1%
1 8
 
1.9%
2 8
 
1.9%
과 7
 
1.6%
Other values (112) 225
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 263
61.9%
Space Separator 78
 
18.4%
Open Punctuation 22
 
5.2%
Close Punctuation 22
 
5.2%
Decimal Number 22
 
5.2%
Other Symbol 10
 
2.4%
Uppercase Letter 6
 
1.4%
Other Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 17
 
6.5%
성 17
 
6.5%
관 12
 
4.6%
및 9
 
3.4%
과 7
 
2.7%
비 6
 
2.3%
전 6
 
2.3%
산 6
 
2.3%
생 6
 
2.3%
적 5
 
1.9%
Other values (92) 172
65.4%
Uppercase Letter
ValueCountFrequency (%)
B 1
16.7%
A 1
16.7%
D 1
16.7%
T 1
16.7%
I 1
16.7%
E 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 8
36.4%
2 8
36.4%
3 4
18.2%
4 1
 
4.5%
5 1
 
4.5%
Other Symbol
ValueCountFrequency (%)
㉮ 3
30.0%
㉯ 3
30.0%
㉰ 2
20.0%
㉳ 1
 
10.0%
㉱ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Other Punctuation
ValueCountFrequency (%)
· 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 273
64.2%
Common 146
34.4%
Latin 6
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 17
 
6.2%
성 17
 
6.2%
관 12
 
4.4%
및 9
 
3.3%
과 7
 
2.6%
비 6
 
2.2%
전 6
 
2.2%
산 6
 
2.2%
생 6
 
2.2%
적 5
 
1.8%
Other values (97) 182
66.7%
Common
ValueCountFrequency (%)
78
53.4%
( 22
 
15.1%
) 22
 
15.1%
1 8
 
5.5%
2 8
 
5.5%
3 4
 
2.7%
· 2
 
1.4%
4 1
 
0.7%
5 1
 
0.7%
Latin
ValueCountFrequency (%)
B 1
16.7%
A 1
16.7%
D 1
16.7%
T 1
16.7%
I 1
16.7%
E 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 263
61.9%
ASCII 150
35.3%
None 12
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
52.0%
( 22
 
14.7%
) 22
 
14.7%
1 8
 
5.3%
2 8
 
5.3%
3 4
 
2.7%
B 1
 
0.7%
4 1
 
0.7%
5 1
 
0.7%
A 1
 
0.7%
Other values (4) 4
 
2.7%
Hangul
ValueCountFrequency (%)
리 17
 
6.5%
성 17
 
6.5%
관 12
 
4.6%
및 9
 
3.4%
과 7
 
2.7%
비 6
 
2.3%
전 6
 
2.3%
산 6
 
2.3%
생 6
 
2.3%
적 5
 
1.9%
Other values (92) 172
65.4%
None
ValueCountFrequency (%)
㉮ 3
25.0%
㉯ 3
25.0%
㉰ 2
16.7%
· 2
16.7%
㉳ 1
 
8.3%
㉱ 1
 
8.3%

가중치(비계량)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct8
Distinct (%)25.0%
Missing2
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean1.671875
Minimum0
Maximum11
Zeros15
Zeros (%)44.1%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T04:01:37.400572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum11
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3473024
Coefficient of variation (CV)1.403994
Kurtosis7.0117823
Mean1.671875
Median Absolute Deviation (MAD)1
Skewness2.259123
Sum53.5
Variance5.5098286
MonotonicityNot monotonic
2023-12-13T04:01:37.602027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 15
44.1%
2.0 4
 
11.8%
3.0 4
 
11.8%
1.0 3
 
8.8%
5.0 2
 
5.9%
4.0 2
 
5.9%
1.5 1
 
2.9%
11.0 1
 
2.9%
(Missing) 2
 
5.9%
ValueCountFrequency (%)
0.0 15
44.1%
1.0 3
 
8.8%
1.5 1
 
2.9%
2.0 4
 
11.8%
3.0 4
 
11.8%
4.0 2
 
5.9%
5.0 2
 
5.9%
11.0 1
 
2.9%
ValueCountFrequency (%)
11.0 1
 
2.9%
5.0 2
 
5.9%
4.0 2
 
5.9%
3.0 4
 
11.8%
2.0 4
 
11.8%
1.5 1
 
2.9%
1.0 3
 
8.8%
0.0 15
44.1%

등급(비계량)
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size404.0 B
0
16 
B
8 
C
7 
D+
 
1
B+
 
1

Length

Max length5
Median length1
Mean length1.1764706
Min length1

Unique

Unique3 ?
Unique (%)8.8%

Sample

1st rowB
2nd rowC
3rd rowC
4th rowB
5th rowB

Common Values

ValueCountFrequency (%)
0 16
47.1%
B 8
23.5%
C 7
20.6%
D+ 1
 
2.9%
B+ 1
 
2.9%
3.081 1
 
2.9%

Length

2023-12-13T04:01:37.843822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:01:38.063004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 16
47.1%
b 9
26.5%
c 7
20.6%
d 1
 
2.9%
3.081 1
 
2.9%

가중치(계량)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5
Minimum0
Maximum8
Zeros15
Zeros (%)44.1%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T04:01:38.282645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.75
Q32
95-th percentile5.7
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.0449494
Coefficient of variation (CV)1.3632996
Kurtosis2.917798
Mean1.5
Median Absolute Deviation (MAD)0.75
Skewness1.7337917
Sum51
Variance4.1818182
MonotonicityNot monotonic
2023-12-13T04:01:38.471639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 15
44.1%
2.0 5
 
14.7%
1.0 4
 
11.8%
3.0 4
 
11.8%
0.5 2
 
5.9%
7.0 1
 
2.9%
8.0 1
 
2.9%
5.0 1
 
2.9%
4.0 1
 
2.9%
ValueCountFrequency (%)
0.0 15
44.1%
0.5 2
 
5.9%
1.0 4
 
11.8%
2.0 5
 
14.7%
3.0 4
 
11.8%
4.0 1
 
2.9%
5.0 1
 
2.9%
7.0 1
 
2.9%
8.0 1
 
2.9%
ValueCountFrequency (%)
8.0 1
 
2.9%
7.0 1
 
2.9%
5.0 1
 
2.9%
4.0 1
 
2.9%
3.0 4
 
11.8%
2.0 5
 
14.7%
1.0 4
 
11.8%
0.5 2
 
5.9%
0.0 15
44.1%

점수(계량)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1507353
Minimum0
Maximum7.91
Zeros15
Zeros (%)44.1%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T04:01:38.702070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.416
Q31.331
95-th percentile4.8421
Maximum7.91
Range7.91
Interquartile range (IQR)1.331

Descriptive statistics

Standard deviation1.905086
Coefficient of variation (CV)1.655538
Kurtosis5.0409908
Mean1.1507353
Median Absolute Deviation (MAD)0.416
Skewness2.254221
Sum39.125
Variance3.6293526
MonotonicityNot monotonic
2023-12-13T04:01:38.878868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 15
44.1%
2.192 1
 
2.9%
4.0 1
 
2.9%
3.907 1
 
2.9%
7.91 1
 
2.9%
6.406 1
 
2.9%
3.0 1
 
2.9%
0.6 1
 
2.9%
0.363 1
 
2.9%
0.656 1
 
2.9%
Other values (10) 10
29.4%
ValueCountFrequency (%)
0.0 15
44.1%
0.363 1
 
2.9%
0.4 1
 
2.9%
0.432 1
 
2.9%
0.447 1
 
2.9%
0.559 1
 
2.9%
0.6 1
 
2.9%
0.633 1
 
2.9%
0.656 1
 
2.9%
0.751 1
 
2.9%
ValueCountFrequency (%)
7.91 1
2.9%
6.406 1
2.9%
4.0 1
2.9%
3.907 1
2.9%
3.0 1
2.9%
2.671 1
2.9%
2.192 1
2.9%
1.792 1
2.9%
1.459 1
2.9%
0.947 1
2.9%

Interactions

2023-12-13T04:01:35.127952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:01:34.288101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:01:34.687080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:01:35.241557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:01:34.407314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:01:34.808464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:01:35.398843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:01:34.544751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:01:34.961982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:01:39.033092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분항목가중치(비계량)등급(비계량)가중치(계량)점수(계량)
구분1.0001.0000.7590.7740.5070.168
항목1.0001.0001.0001.0001.0001.000
가중치(비계량)0.7591.0001.0000.8190.0000.000
등급(비계량)0.7741.0000.8191.0000.0000.000
가중치(계량)0.5071.0000.0000.0001.0000.982
점수(계량)0.1681.0000.0000.0000.9821.000
2023-12-13T04:01:39.205624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분등급(비계량)
구분1.0000.504
등급(비계량)0.5041.000
2023-12-13T04:01:39.362307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가중치(비계량)가중치(계량)점수(계량)구분등급(비계량)
가중치(비계량)1.000-0.715-0.6440.4820.425
가중치(계량)-0.7151.0000.9660.2410.000
점수(계량)-0.6440.9661.0000.0000.000
구분0.4820.2410.0001.0000.504
등급(비계량)0.4250.0000.0000.5041.000

Missing values

2023-12-13T04:01:35.578528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:01:35.690788image/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.
2023-12-13T04:01:35.831573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분항목가중치(비계량)등급(비계량)가중치(계량)점수(계량)
0경영관리(1. 경영전략 및 리더십)(1) 리더십2.0B0.00.0
1경영관리(1. 경영전략 및 리더십)(2) 전략기획 및 경영혁신5.0C0.00.0
2경영관리(1. 경영전략 및 리더십)(3) 국민소통1.0C0.50.4
3경영관리(2. 사회적 책임)(1) 일자리 및 균등한 기회3.0B2.01.459
4경영관리(2. 사회적 책임)(2) 안전 및 재난관리1.0B1.00.751
5경영관리(2. 사회적 책임)(3) 친환경·탄소중립1.0C0.50.447
6경영관리(2. 사회적 책임)(4) 상생·협력 및 지역발전2.0C2.01.792
7경영관리(2. 사회적 책임)(5) 윤리경영1.5D+1.00.633
8경영관리(3. 재무성과관리)(1) 재무예산관리3.0C0.00.0
9경영관리(3. 재무성과관리)(2) 재무예산성과0.000.00.0
구분항목가중치(비계량)등급(비계량)가중치(계량)점수(계량)
24경영관리(5. 보수 및 복리후생관리)(2) 총인건비관리0.003.03.0
25주요사업(1. 가스플랜트 정비사업)(1) 가스플랜트 책임정비 노력과 성과0.007.06.406
26주요사업(1. 가스플랜트 정비사업)(2) 가스 안전관리 강화0.008.07.91
27주요사업(1. 가스플랜트 정비사업)(3) 가스플랜트 정비사업 성과관리의 적정성11.0B0.00.0
28주요사업(2. 가스플랜트 엔지니어링 및 건설사업)(1) 엔지니어링 및 건설 사업성장성0.005.03.907
29주요사업(2. 가스플랜트 엔지니어링 및 건설사업)(2) 가스플랜트 엔지니어링 및 건설사업 성과관리의 적정성3.0B+0.00.0
30주요사업(3. 신성장사업)(1) 신성장 기술 개발활용 성과0.004.04.0
31주요사업(3. 신성장사업)(2) 신성장사업 성과관리의 적정성3.0B0.00.0
32주요사업(4. 주요사업 계량지표 구성의 적정성 및 목표의 도전성)<NA>4.0C0.00.0
33가점(공공기관 혁신계획 실행노력과 성과 가점)<NA>5.03.0810.00.0