Overview

Dataset statistics

Number of variables17
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.7 KiB
Average record size in memory140.3 B

Variable types

Numeric2
Categorical12
Text3

Alerts

소관부처 has constant value ""Constant
대상연도 has constant value ""Constant
온실가스 배출량 단위 has constant value ""Constant
에너지 사용량 단위 has constant value ""Constant
온실가스 배출량 원단위 단위 is highly overall correlated with 에너지 사용량 and 5 other fieldsHigh correlation
에너지 사용량 원단위 값 is highly overall correlated with 에너지 사용량 and 6 other fieldsHigh correlation
매출액(원) is highly overall correlated with 에너지 사용량 and 6 other fieldsHigh correlation
지정구분 is highly overall correlated with 에너지 사용량 and 5 other fieldsHigh correlation
에너지 사용량 원단위 단위 is highly overall correlated with 에너지 사용량 and 5 other fieldsHigh correlation
온실가스 배출량 원단위 값 is highly overall correlated with 에너지 사용량 and 5 other fieldsHigh correlation
에너지 사용량 is highly overall correlated with 지정구분 and 5 other fieldsHigh correlation
지정업종 is highly overall correlated with 에너지 사용량 원단위 값 and 1 other fieldsHigh correlation
온실가스 배출량 원단위 값 is highly imbalanced (60.7%)Imbalance
에너지 사용량 원단위 값 is highly imbalanced (61.5%)Imbalance
매출액(원) is highly imbalanced (61.5%)Imbalance
연번 has unique valuesUnique
온실가스 배출량 has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:40:35.881900
Analysis finished2023-12-10 10:40:40.712718
Duration4.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:40:40.869243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T19:40:41.196178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

소관부처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
국토교통부
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국토교통부 100
100.0%

Length

2023-12-10T19:40:41.416349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:40:41.591458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국토교통부 100
100.0%

법인명
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:40:41.998642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.97
Min length4

Characters and Unicode

Total characters797
Distinct characters160
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row(유)호남고속
2nd row(주)경기고속
3rd row(주)경남고속
4th row(주)공항리무진
5th row(주)국민은행
ValueCountFrequency (%)
주식회사 5
 
4.7%
경원여객자동차(주 2
 
1.9%
농협은행(주 1
 
0.9%
롯데글로벌로지스(주 1
 
0.9%
람정제주개발 1
 
0.9%
동원로엑스(주 1
 
0.9%
동아운수(주 1
 
0.9%
동성교통(주 1
 
0.9%
도명특송(주 1
 
0.9%
대창운수(주 1
 
0.9%
Other values (92) 92
86.0%
2023-12-10T19:40:42.824262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 86
 
10.8%
( 79
 
9.9%
) 79
 
9.9%
수 18
 
2.3%
스 18
 
2.3%
고 15
 
1.9%
속 15
 
1.9%
원 14
 
1.8%
운 14
 
1.8%
대 14
 
1.8%
Other values (150) 445
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 627
78.7%
Open Punctuation 79
 
9.9%
Close Punctuation 79
 
9.9%
Space Separator 7
 
0.9%
Uppercase Letter 4
 
0.5%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 86
 
13.7%
수 18
 
2.9%
스 18
 
2.9%
고 15
 
2.4%
속 15
 
2.4%
원 14
 
2.2%
운 14
 
2.2%
대 14
 
2.2%
사 12
 
1.9%
동 11
 
1.8%
Other values (142) 410
65.4%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
J 1
25.0%
G 1
25.0%
S 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Decimal Number
ValueCountFrequency (%)
9 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 627
78.7%
Common 166
 
20.8%
Latin 4
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 86
 
13.7%
수 18
 
2.9%
스 18
 
2.9%
고 15
 
2.4%
속 15
 
2.4%
원 14
 
2.2%
운 14
 
2.2%
대 14
 
2.2%
사 12
 
1.9%
동 11
 
1.8%
Other values (142) 410
65.4%
Common
ValueCountFrequency (%)
( 79
47.6%
) 79
47.6%
7
 
4.2%
9 1
 
0.6%
Latin
ValueCountFrequency (%)
C 1
25.0%
J 1
25.0%
G 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 627
78.7%
ASCII 170
 
21.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 86
 
13.7%
수 18
 
2.9%
스 18
 
2.9%
고 15
 
2.4%
속 15
 
2.4%
원 14
 
2.2%
운 14
 
2.2%
대 14
 
2.2%
사 12
 
1.9%
동 11
 
1.8%
Other values (142) 410
65.4%
ASCII
ValueCountFrequency (%)
( 79
46.5%
) 79
46.5%
7
 
4.1%
9 1
 
0.6%
C 1
 
0.6%
J 1
 
0.6%
G 1
 
0.6%
S 1
 
0.6%

주소
Text

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:40:43.408344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length23.96
Min length14

Characters and Unicode

Total characters2396
Distinct characters225
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

Unique90 ?
Unique (%)90.0%

Sample

1st row전라북도 전주시 덕진구 신복천변로 28 (팔복동1가)
2nd row경기도 광주시 광주대로 171 (송정동)
3rd row부산광역시 금정구 중앙대로 2008 6층 (남산동)
4th row서울특별시 강서구 개화동로8길 17 (개화동)
5th row서울특별시 영등포구 국제금융로8길 26 (여의도동)
ValueCountFrequency (%)
서울특별시 38
 
7.3%
경기도 23
 
4.4%
중구 11
 
2.1%
서구 10
 
1.9%
부산광역시 7
 
1.3%
광주광역시 5
 
1.0%
3층 5
 
1.0%
대전광역시 4
 
0.8%
강원도 4
 
0.8%
성남시 4
 
0.8%
Other values (329) 413
78.8%
2023-12-10T19:40:44.204885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
432
 
18.0%
로 105
 
4.4%
시 101
 
4.2%
구 90
 
3.8%
동 70
 
2.9%
서 65
 
2.7%
1 59
 
2.5%
) 59
 
2.5%
( 59
 
2.5%
도 47
 
2.0%
Other values (215) 1309
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1507
62.9%
Space Separator 432
 
18.0%
Decimal Number 326
 
13.6%
Close Punctuation 59
 
2.5%
Open Punctuation 59
 
2.5%
Uppercase Letter 5
 
0.2%
Dash Punctuation 4
 
0.2%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 105
 
7.0%
시 101
 
6.7%
구 90
 
6.0%
동 70
 
4.6%
서 65
 
4.3%
도 47
 
3.1%
대 43
 
2.9%
울 40
 
2.7%
특 39
 
2.6%
별 39
 
2.6%
Other values (195) 868
57.6%
Decimal Number
ValueCountFrequency (%)
1 59
18.1%
2 44
13.5%
3 42
12.9%
0 35
10.7%
6 30
9.2%
4 27
8.3%
8 27
8.3%
7 25
7.7%
9 23
 
7.1%
5 14
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
I 1
20.0%
C 1
20.0%
O 1
20.0%
L 1
20.0%
G 1
20.0%
Space Separator
ValueCountFrequency (%)
432
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1507
62.9%
Common 884
36.9%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 105
 
7.0%
시 101
 
6.7%
구 90
 
6.0%
동 70
 
4.6%
서 65
 
4.3%
도 47
 
3.1%
대 43
 
2.9%
울 40
 
2.7%
특 39
 
2.6%
별 39
 
2.6%
Other values (195) 868
57.6%
Common
ValueCountFrequency (%)
432
48.9%
1 59
 
6.7%
) 59
 
6.7%
( 59
 
6.7%
2 44
 
5.0%
3 42
 
4.8%
0 35
 
4.0%
6 30
 
3.4%
4 27
 
3.1%
8 27
 
3.1%
Other values (5) 70
 
7.9%
Latin
ValueCountFrequency (%)
I 1
20.0%
C 1
20.0%
O 1
20.0%
L 1
20.0%
G 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1507
62.9%
ASCII 889
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
432
48.6%
1 59
 
6.6%
) 59
 
6.6%
( 59
 
6.6%
2 44
 
4.9%
3 42
 
4.7%
0 35
 
3.9%
6 30
 
3.4%
4 27
 
3.0%
8 27
 
3.0%
Other values (10) 75
 
8.4%
Hangul
ValueCountFrequency (%)
로 105
 
7.0%
시 101
 
6.7%
구 90
 
6.0%
동 70
 
4.6%
서 65
 
4.3%
도 47
 
3.1%
대 43
 
2.9%
울 40
 
2.7%
특 39
 
2.6%
별 39
 
2.6%
Other values (195) 868
57.6%

대상연도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2020
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 100
100.0%

Length

2023-12-10T19:40:44.532139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:40:44.761664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 100
100.0%

지정구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
사업장
77 
업체
23 

Length

Max length3
Median length3
Mean length2.77
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사업장
2nd row업체
3rd row사업장
4th row사업장
5th row업체

Common Values

ValueCountFrequency (%)
사업장 77
77.0%
업체 23
 
23.0%

Length

2023-12-10T19:40:44.953856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:40:45.167099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업장 77
77.0%
업체 23
 
23.0%

지정업종
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
교통(여객)
44 
건물
26 
교통(화물)
16 
교통(철도)
7 
수송
 
4
Other values (2)
 
3

Length

Max length6
Median length6
Mean length4.68
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row교통(여객)
2nd row교통(여객)
3rd row교통(여객)
4th row교통(여객)
5th row건물

Common Values

ValueCountFrequency (%)
교통(여객) 44
44.0%
건물 26
26.0%
교통(화물) 16
 
16.0%
교통(철도) 7
 
7.0%
수송 4
 
4.0%
건설 2
 
2.0%
산업 1
 
1.0%

Length

2023-12-10T19:40:45.489902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:40:45.728532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교통(여객 44
44.0%
건물 26
26.0%
교통(화물 16
 
16.0%
교통(철도 7
 
7.0%
수송 4
 
4.0%
건설 2
 
2.0%
산업 1
 
1.0%

온실가스 배출량
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:40:46.341674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.05
Min length5

Characters and Unicode

Total characters605
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row21,850
2nd row109,380
3rd row14,747
4th row6,755
5th row111,653
ValueCountFrequency (%)
21,850 1
 
1.0%
17,284 1
 
1.0%
48,249 1
 
1.0%
31,886 1
 
1.0%
56,509 1
 
1.0%
17,824 1
 
1.0%
15,820 1
 
1.0%
25,931 1
 
1.0%
21,566 1
 
1.0%
17,398 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:40:47.251884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 100
16.5%
1 92
15.2%
2 62
10.2%
4 54
8.9%
8 48
7.9%
5 48
7.9%
9 46
7.6%
0 44
7.3%
3 42
6.9%
7 41
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 505
83.5%
Other Punctuation 100
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 92
18.2%
2 62
12.3%
4 54
10.7%
8 48
9.5%
5 48
9.5%
9 46
9.1%
0 44
8.7%
3 42
8.3%
7 41
8.1%
6 28
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 605
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 100
16.5%
1 92
15.2%
2 62
10.2%
4 54
8.9%
8 48
7.9%
5 48
7.9%
9 46
7.6%
0 44
7.3%
3 42
6.9%
7 41
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 605
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 100
16.5%
1 92
15.2%
2 62
10.2%
4 54
8.9%
8 48
7.9%
5 48
7.9%
9 46
7.6%
0 44
7.3%
3 42
6.9%
7 41
6.8%

온실가스 배출량 단위
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
tCO₂eq
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowtCO₂eq
2nd rowtCO₂eq
3rd rowtCO₂eq
4th rowtCO₂eq
5th rowtCO₂eq

Common Values

ValueCountFrequency (%)
tCO₂eq 100
100.0%

Length

2023-12-10T19:40:47.508674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:40:48.058762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
tco₂eq 100
100.0%

온실가스 배출량 원단위 값
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
78 
0
 
4
1
 
3
62
 
2
61
 
2
Other values (11)
11 

Length

Max length3
Median length1
Mean length1.12
Min length1

Unique

Unique11 ?
Unique (%)11.0%

Sample

1st row-
2nd row60
3rd row-
4th row-
5th row0

Common Values

ValueCountFrequency (%)
- 78
78.0%
0 4
 
4.0%
1 3
 
3.0%
62 2
 
2.0%
61 2
 
2.0%
60 1
 
1.0%
8 1
 
1.0%
66 1
 
1.0%
6 1
 
1.0%
3 1
 
1.0%
Other values (6) 6
 
6.0%

Length

2023-12-10T19:40:48.249584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
78
78.0%
0 4
 
4.0%
1 3
 
3.0%
62 2
 
2.0%
61 2
 
2.0%
60 1
 
1.0%
8 1
 
1.0%
66 1
 
1.0%
6 1
 
1.0%
3 1
 
1.0%
Other values (6) 6
 
6.0%

온실가스 배출량 원단위 단위
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
78 
tCO₂eq/억원
22 

Length

Max length9
Median length1
Mean length2.76
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd rowtCO₂eq/억원
3rd row-
4th row-
5th rowtCO₂eq/억원

Common Values

ValueCountFrequency (%)
- 78
78.0%
tCO₂eq/억원 22
 
22.0%

Length

2023-12-10T19:40:48.516363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:40:48.727324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
78
78.0%
tco₂eq/억원 22
 
22.0%

에너지 사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean737.45
Minimum30
Maximum13278
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:40:48.952406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile180.55
Q1289
median397.5
Q3643.75
95-th percentile1832.05
Maximum13278
Range13248
Interquartile range (IQR)354.75

Descriptive statistics

Standard deviation1410.9094
Coefficient of variation (CV)1.9132272
Kurtosis64.331751
Mean737.45
Median Absolute Deviation (MAD)131.5
Skewness7.4387524
Sum73745
Variance1990665.3
MonotonicityNot monotonic
2023-12-10T19:40:49.225696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
341 2
 
2.0%
399 2
 
2.0%
324 2
 
2.0%
248 2
 
2.0%
377 2
 
2.0%
691 1
 
1.0%
302 1
 
1.0%
910 1
 
1.0%
621 1
 
1.0%
885 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
30 1
1.0%
96 1
1.0%
112 1
1.0%
143 1
1.0%
172 1
1.0%
181 1
1.0%
188 1
1.0%
199 1
1.0%
203 1
1.0%
208 1
1.0%
ValueCountFrequency (%)
13278 1
1.0%
3880 1
1.0%
3421 1
1.0%
2030 1
1.0%
2023 1
1.0%
1822 1
1.0%
1805 1
1.0%
1727 1
1.0%
1697 1
1.0%
1642 1
1.0%

에너지 사용량 단위
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
TJ
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
TJ 100
100.0%

Length

2023-12-10T19:40:49.531959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:40:49.730232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
tj 100
100.0%

에너지 사용량 원단위 값
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
78 
0.945353055
 
1
0.007230472
 
1
0.015372013
 
1
0.972720462
 
1
Other values (18)
18 

Length

Max length11
Median length1
Mean length3.19
Min length1

Unique

Unique22 ?
Unique (%)22.0%

Sample

1st row-
2nd row0.945353055
3rd row-
4th row-
5th row0.007230472

Common Values

ValueCountFrequency (%)
- 78
78.0%
0.945353055 1
 
1.0%
0.007230472 1
 
1.0%
0.015372013 1
 
1.0%
0.972720462 1
 
1.0%
0.112594676 1
 
1.0%
0.870514176 1
 
1.0%
0.004658457 1
 
1.0%
0.004416394 1
 
1.0%
0.872671105 1
 
1.0%
Other values (13) 13
 
13.0%

Length

2023-12-10T19:40:49.896987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
78
78.0%
0.975786076 1
 
1.0%
1.49925774 1
 
1.0%
0.387087969 1
 
1.0%
2.018212092 1
 
1.0%
1.429692495 1
 
1.0%
0.009956382 1
 
1.0%
0.091876923 1
 
1.0%
0.264209207 1
 
1.0%
0.022753366 1
 
1.0%
Other values (13) 13
 
13.0%

에너지 사용량 원단위 단위
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
78 
TJ/억원
22 

Length

Max length5
Median length1
Mean length1.88
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd rowTJ/억원
3rd row-
4th row-
5th rowTJ/억원

Common Values

ValueCountFrequency (%)
- 78
78.0%
TJ/억원 22
 
22.0%

Length

2023-12-10T19:40:50.141877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:40:50.348473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
78
78.0%
tj/억원 22
 
22.0%

검증수행기관
Categorical

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
(주)한국경영인증원
37 
한국표준협회
35 
산림조합중앙회
8 
(재)한국품질재단
4 
대일이엔씨기술(주)
 
3
Other values (6)
13 

Length

Max length18
Median length17
Mean length8.49
Min length5

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row(주)한국경영인증원
2nd row산림조합중앙회
3rd row(주)한국경영인증원
4th row(주)한국경영인증원
5th row한국표준협회

Common Values

ValueCountFrequency (%)
(주)한국경영인증원 37
37.0%
한국표준협회 35
35.0%
산림조합중앙회 8
 
8.0%
(재)한국품질재단 4
 
4.0%
대일이엔씨기술(주) 3
 
3.0%
㈜디엔브이비즈니스어슈어런스코리아 3
 
3.0%
㈜한국품질보증원 3
 
3.0%
이큐에이㈜ 3
 
3.0%
한국생산성본부인증원(주) 2
 
2.0%
(주)비에스아이그룹코리아 1
 
1.0%

Length

2023-12-10T19:40:50.557452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주)한국경영인증원 37
37.0%
한국표준협회 35
35.0%
산림조합중앙회 8
 
8.0%
재)한국품질재단 4
 
4.0%
대일이엔씨기술(주 3
 
3.0%
㈜디엔브이비즈니스어슈어런스코리아 3
 
3.0%
㈜한국품질보증원 3
 
3.0%
이큐에이㈜ 3
 
3.0%
한국생산성본부인증원(주 2
 
2.0%
주)비에스아이그룹코리아 1
 
1.0%

매출액(원)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
78 
182,683,071,861
 
1
23,470,113,000,000
 
1
7,637,255,920,891
 
1
187,309,722,609
 
1
Other values (18)
18 

Length

Max length18
Median length1
Mean length4.25
Min length1

Unique

Unique22 ?
Unique (%)22.0%

Sample

1st row-
2nd row182,683,071,861
3rd row-
4th row-
5th row23,470,113,000,000

Common Values

ValueCountFrequency (%)
- 78
78.0%
182,683,071,861 1
 
1.0%
23,470,113,000,000 1
 
1.0%
7,637,255,920,891 1
 
1.0%
187,309,722,609 1
 
1.0%
555,088,410,696 1
 
1.0%
83,398,986,443 1
 
1.0%
23,806,167,000,000 1
 
1.0%
25,971,413,000,000 1
 
1.0%
65,775,066,539 1
 
1.0%
Other values (13) 13
 
13.0%

Length

2023-12-10T19:40:50.801732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
78
78.0%
69,994,850,000 1
 
1.0%
228,179,579,000 1
 
1.0%
242,580,518,000 1
 
1.0%
37,855,288,000 1
 
1.0%
141,988,575,000 1
 
1.0%
13,790,150,000,000 1
 
1.0%
32,652,377,708 1
 
1.0%
403,468,150,060 1
 
1.0%
8,890,992,062,853 1
 
1.0%
Other values (13) 13
 
13.0%

Interactions

2023-12-10T19:40:39.711881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:40:39.297252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:40:39.907398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:40:39.457732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:40:50.968092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번법인명주소지정구분지정업종온실가스 배출량온실가스 배출량 원단위 값온실가스 배출량 원단위 단위에너지 사용량에너지 사용량 원단위 값에너지 사용량 원단위 단위검증수행기관매출액(원)
연번1.0000.9400.8720.0000.0001.0000.0000.0000.2510.1240.0000.2490.124
법인명0.9401.0000.9971.0001.0001.0001.0001.0001.0001.0001.0000.9981.000
주소0.8720.9971.0000.8460.9641.0000.0000.8360.9610.0000.8360.9830.000
지정구분0.0001.0000.8461.0000.4591.0000.9990.9960.7950.9750.9960.2240.975
지정업종0.0001.0000.9640.4591.0001.0000.7840.3860.4680.9030.3860.5360.903
온실가스 배출량1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
온실가스 배출량 원단위 값0.0001.0000.0000.9990.7841.0001.0001.0000.9231.0001.0000.3311.000
온실가스 배출량 원단위 단위0.0001.0000.8360.9960.3861.0001.0001.0000.7781.0000.9990.2291.000
에너지 사용량0.2511.0000.9610.7950.4681.0000.9230.7781.0000.8970.7780.4720.897
에너지 사용량 원단위 값0.1241.0000.0000.9750.9031.0001.0001.0000.8971.0001.0000.6361.000
에너지 사용량 원단위 단위0.0001.0000.8360.9960.3861.0001.0000.9990.7781.0001.0000.2291.000
검증수행기관0.2490.9980.9830.2240.5361.0000.3310.2290.4720.6360.2291.0000.636
매출액(원)0.1241.0000.0000.9750.9031.0001.0001.0000.8971.0001.0000.6361.000
2023-12-10T19:40:51.261417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온실가스 배출량 원단위 단위에너지 사용량 원단위 값매출액(원)지정구분에너지 사용량 원단위 단위온실가스 배출량 원단위 값검증수행기관지정업종
온실가스 배출량 원단위 단위1.0000.8860.8860.9420.9710.9260.2060.402
에너지 사용량 원단위 값0.8861.0001.0000.8540.8860.9570.2560.620
매출액(원)0.8861.0001.0000.8540.8860.9570.2560.620
지정구분0.9420.8540.8541.0000.9420.8950.2020.479
에너지 사용량 원단위 단위0.9710.8860.8860.9421.0000.9260.2060.402
온실가스 배출량 원단위 값0.9260.9570.9570.8950.9261.0000.1210.483
검증수행기관0.2060.2560.2560.2020.2060.1211.0000.292
지정업종0.4020.6200.6200.4790.4020.4830.2921.000
2023-12-10T19:40:51.498823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번에너지 사용량지정구분지정업종온실가스 배출량 원단위 값온실가스 배출량 원단위 단위에너지 사용량 원단위 값에너지 사용량 원단위 단위검증수행기관매출액(원)
연번1.0000.0710.0000.0000.0000.0000.0000.0000.1020.000
에너지 사용량0.0711.0000.5810.3340.6320.5630.6460.5630.2910.646
지정구분0.0000.5811.0000.4790.8950.9420.8540.9420.2020.854
지정업종0.0000.3340.4791.0000.4830.4020.6200.4020.2920.620
온실가스 배출량 원단위 값0.0000.6320.8950.4831.0000.9260.9570.9260.1210.957
온실가스 배출량 원단위 단위0.0000.5630.9420.4020.9261.0000.8860.9710.2060.886
에너지 사용량 원단위 값0.0000.6460.8540.6200.9570.8861.0000.8860.2561.000
에너지 사용량 원단위 단위0.0000.5630.9420.4020.9260.9710.8861.0000.2060.886
검증수행기관0.1020.2910.2020.2920.1210.2060.2560.2061.0000.256
매출액(원)0.0000.6460.8540.6200.9570.8861.0000.8860.2561.000

Missing values

2023-12-10T19:40:40.156631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:40:40.565210image/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

연번소관부처법인명주소대상연도지정구분지정업종온실가스 배출량온실가스 배출량 단위온실가스 배출량 원단위 값온실가스 배출량 원단위 단위에너지 사용량에너지 사용량 단위에너지 사용량 원단위 값에너지 사용량 원단위 단위검증수행기관매출액(원)
01국토교통부(유)호남고속전라북도 전주시 덕진구 신복천변로 28 (팔복동1가)2020사업장교통(여객)21,850tCO₂eq--341TJ--(주)한국경영인증원-
12국토교통부(주)경기고속경기도 광주시 광주대로 171 (송정동)2020업체교통(여객)109,380tCO₂eq60tCO₂eq/억원1727TJ0.945353055TJ/억원산림조합중앙회182,683,071,861
23국토교통부(주)경남고속부산광역시 금정구 중앙대로 2008 6층 (남산동)2020사업장교통(여객)14,747tCO₂eq--208TJ--(주)한국경영인증원-
34국토교통부(주)공항리무진서울특별시 강서구 개화동로8길 17 (개화동)2020사업장교통(여객)6,755tCO₂eq--96TJ--(주)한국경영인증원-
45국토교통부(주)국민은행서울특별시 영등포구 국제금융로8길 26 (여의도동)2020업체건물111,653tCO₂eq0tCO₂eq/억원1697TJ0.007230472TJ/억원한국표준협회23,470,113,000,000
56국토교통부(주)금남고속대전광역시 대덕구 대전로 14292020사업장교통(여객)19,848tCO₂eq--282TJ--(주)한국경영인증원-
67국토교통부(주)농협물류서울특별시 서대문구 통일로 87 (미근동)2020사업장교통(화물)30,429tCO₂eq--437TJ--한국표준협회-
78국토교통부(주)대명티피앤이강원도 홍천군 서면 한치골길 2642020사업장건물9,465tCO₂eq--188TJ--(주)한국경영인증원-
89국토교통부(주)대우건설서울특별시 종로구 새문안로 75 대우건설2020업체건설58,969tCO₂eq1tCO₂eq/억원1174TJ0.015372013TJ/억원(주)비에스아이그룹코리아7,637,255,920,891
910국토교통부(주)대원고속경기도 광주시 광주대로 171 (송정동)2020업체교통(여객)115,574tCO₂eq62tCO₂eq/억원1822TJ0.972720462TJ/억원산림조합중앙회187,309,722,609
연번소관부처법인명주소대상연도지정구분지정업종온실가스 배출량온실가스 배출량 단위온실가스 배출량 원단위 값온실가스 배출량 원단위 단위에너지 사용량에너지 사용량 단위에너지 사용량 원단위 값에너지 사용량 원단위 단위검증수행기관매출액(원)
9091국토교통부서울파이낸스센터(주)서울특별시 중구 세종대로 136 (태평로1가)2020사업장건물11,435tCO₂eq--233TJ--한국생산성본부인증원(주)-
9192국토교통부선진버스(주)경기도 김포시 월곶면 김포대로 2600 월곶 공영차고지2020사업장교통(여객)21,475tCO₂eq--396TJ--(주)한국경영인증원-
9293국토교통부성남시내버스(주)경기도 성남시 분당구 판교로 7742020사업장교통(여객)31,011tCO₂eq--545TJ--㈜한국품질보증원-
9394국토교통부세방(주)부산광역시 남구 북항로 140 (감만동)2020사업장교통(화물)28,371tCO₂eq--440TJ--(주)한국경영인증원-
9495국토교통부소신여객자동차(주)경기도 부천시 부일로 490 (심곡동)2020사업장교통(여객)23,340tCO₂eq--424TJ--한국표준협회-
9596국토교통부수원애경역사(주)경기도 수원시 팔달구 덕영대로 924 (매산로1가)2020사업장건물14,844tCO₂eq--302TJ--한국표준협회-
9697국토교통부수원여객운수(주)경기도 수원시 장안구 창훈로60번길 22-2 (연무동)2020사업장교통(여객)37,095tCO₂eq--691TJ--한국표준협회-
9798국토교통부수협노량진수산(주)서울특별시 동작구 노들로 6742020사업장건물15,878tCO₂eq--327TJ--(주)한국경영인증원-
9899국토교통부신도림테크노마트 주식회사서울특별시 구로구 새말로 97 신도림테크노마트2020사업장건물14,640tCO₂eq--299TJ--(주)한국경영인증원-
99100국토교통부신분당선(주)경기도 성남시 분당구 대왕판교로606번길 332020사업장교통(철도)25,125tCO₂eq--517TJ--(주)한국경영인증원-