Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory1.1 MiB
Average record size in memory117.0 B

Variable types

Text3
Categorical4
Numeric5
Unsupported1

Dataset

Description2012년도부터 2020년도까지 환경기업 환경정보 현황(사업장명, 구분, 유형, 업종, 에너지총량, 직접배출량, 간접배출량) 등 제공 (제공요청 데이터)
Author한국환경산업기술원
URLhttps://www.data.go.kr/data/15107680/fileData.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
직접배출량(scope1) is highly overall correlated with 간접배출량(scope2) and 1 other fieldsHigh correlation
간접배출량(scope2) is highly overall correlated with 직접배출량(scope1) and 1 other fieldsHigh correlation
온실가스배출총량 is highly overall correlated with 직접배출량(scope1) and 1 other fieldsHigh correlation
유형 is highly overall correlated with 특성 and 1 other fieldsHigh correlation
특성 is highly overall correlated with 유형High correlation
업종 is highly overall correlated with 유형High correlation
직접배출량(scope1) is highly skewed (γ1 = 43.63050565)Skewed
간접배출량(scope2) is highly skewed (γ1 = 82.621575)Skewed
간접배출량(scope3) is highly skewed (γ1 = 69.11668286)Skewed
온실가스배출총량 is highly skewed (γ1 = 38.20543644)Skewed
에너지총량(TJ) is an unsupported type, check if it needs cleaning or further analysisUnsupported
직접배출량(scope1) has 8139 (81.4%) zerosZeros
간접배출량(scope2) has 8125 (81.2%) zerosZeros
간접배출량(scope3) has 9958 (99.6%) zerosZeros
온실가스배출총량 has 8089 (80.9%) zerosZeros

Reproduction

Analysis started2024-04-20 19:40:48.783391
Analysis finished2024-04-20 19:40:56.553213
Duration7.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대표사업장명
Text

Distinct1449
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T04:40:57.329147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length7.0307
Min length2

Characters and Unicode

Total characters70307
Distinct characters490
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique467 ?
Unique (%)4.7%

Sample

1st row한국수자원공사
2nd row주)벽산익산공장
3rd row한국전력공사
4th row한국가스안전공사
5th row국민체육진흥공단
ValueCountFrequency (%)
주)이마트(본사+성수점 157
 
1.6%
롯데쇼핑(주)본점(본사 105
 
1.1%
홈플러스(주 95
 
0.9%
도로교통공단 65
 
0.7%
삼성생명본사(서초타워 56
 
0.6%
구미시청 51
 
0.5%
김해시청(본청 50
 
0.5%
대한적십자사 49
 
0.5%
대구광역시청 48
 
0.5%
부산광역시청 45
 
0.4%
Other values (1439) 9279
92.8%
2024-04-21T04:40:58.536851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
청 4912
 
7.0%
시 3467
 
4.9%
주 2863
 
4.1%
) 2496
 
3.6%
( 2485
 
3.5%
사 1974
 
2.8%
구 1973
 
2.8%
공 1769
 
2.5%
군 1418
 
2.0%
한 1371
 
2.0%
Other values (480) 45579
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64134
91.2%
Close Punctuation 2496
 
3.6%
Open Punctuation 2485
 
3.5%
Uppercase Letter 703
 
1.0%
Math Symbol 157
 
0.2%
Lowercase Letter 109
 
0.2%
Connector Punctuation 100
 
0.1%
Decimal Number 72
 
0.1%
Other Punctuation 38
 
0.1%
Dash Punctuation 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 4912
 
7.7%
시 3467
 
5.4%
주 2863
 
4.5%
사 1974
 
3.1%
구 1973
 
3.1%
공 1769
 
2.8%
군 1418
 
2.2%
한 1371
 
2.1%
본 1328
 
2.1%
국 1312
 
2.0%
Other values (428) 41747
65.1%
Uppercase Letter
ValueCountFrequency (%)
S 140
19.9%
K 100
14.2%
C 87
12.4%
D 60
8.5%
G 54
 
7.7%
L 47
 
6.7%
I 31
 
4.4%
J 28
 
4.0%
P 27
 
3.8%
E 23
 
3.3%
Other values (13) 106
15.1%
Lowercase Letter
ValueCountFrequency (%)
k 28
25.7%
t 20
18.3%
e 11
 
10.1%
a 10
 
9.2%
b 7
 
6.4%
r 7
 
6.4%
s 7
 
6.4%
p 5
 
4.6%
m 4
 
3.7%
o 3
 
2.8%
Other values (4) 7
 
6.4%
Decimal Number
ValueCountFrequency (%)
1 39
54.2%
3 15
 
20.8%
5 10
 
13.9%
2 4
 
5.6%
8 4
 
5.6%
Other Punctuation
ValueCountFrequency (%)
& 28
73.7%
, 6
 
15.8%
. 3
 
7.9%
/ 1
 
2.6%
Close Punctuation
ValueCountFrequency (%)
) 2496
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2485
100.0%
Math Symbol
ValueCountFrequency (%)
+ 157
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64137
91.2%
Common 5358
 
7.6%
Latin 812
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 4912
 
7.7%
시 3467
 
5.4%
주 2863
 
4.5%
사 1974
 
3.1%
구 1973
 
3.1%
공 1769
 
2.8%
군 1418
 
2.2%
한 1371
 
2.1%
본 1328
 
2.1%
국 1312
 
2.0%
Other values (429) 41750
65.1%
Latin
ValueCountFrequency (%)
S 140
17.2%
K 100
12.3%
C 87
10.7%
D 60
 
7.4%
G 54
 
6.7%
L 47
 
5.8%
I 31
 
3.8%
k 28
 
3.4%
J 28
 
3.4%
P 27
 
3.3%
Other values (27) 210
25.9%
Common
ValueCountFrequency (%)
) 2496
46.6%
( 2485
46.4%
+ 157
 
2.9%
_ 100
 
1.9%
1 39
 
0.7%
& 28
 
0.5%
3 15
 
0.3%
5 10
 
0.2%
- 10
 
0.2%
, 6
 
0.1%
Other values (4) 12
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64134
91.2%
ASCII 6170
 
8.8%
None 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
청 4912
 
7.7%
시 3467
 
5.4%
주 2863
 
4.5%
사 1974
 
3.1%
구 1973
 
3.1%
공 1769
 
2.8%
군 1418
 
2.2%
한 1371
 
2.1%
본 1328
 
2.1%
국 1312
 
2.0%
Other values (428) 41747
65.1%
ASCII
ValueCountFrequency (%)
) 2496
40.5%
( 2485
40.3%
+ 157
 
2.5%
S 140
 
2.3%
_ 100
 
1.6%
K 100
 
1.6%
C 87
 
1.4%
D 60
 
1.0%
G 54
 
0.9%
L 47
 
0.8%
Other values (41) 444
 
7.2%
None
ValueCountFrequency (%)
㈜ 3
100.0%

사업장명
Text

Distinct6466
Distinct (%)64.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T04:40:59.249546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length9.0814
Min length2

Characters and Unicode

Total characters90814
Distinct characters629
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3956 ?
Unique (%)39.6%

Sample

1st row전북지역본부
2nd row(주)벽산음성공장
3rd row한국전력공사_인천지역본부시흥전력지사
4th row한국가스안전공사대구경북지역본부
5th row경륜경정사업본부B
ValueCountFrequency (%)
농업기술센터 63
 
0.6%
보건소 48
 
0.5%
상하수도사업소 30
 
0.3%
차량등록사업소 12
 
0.1%
남면사무소 10
 
0.1%
중앙동주민센터 7
 
0.1%
현대백화점신촌점 6
 
0.1%
방화3동주민센터 6
 
0.1%
수도사업소 6
 
0.1%
비봉면사무소 6
 
0.1%
Other values (6456) 9806
98.1%
2024-04-21T04:41:00.089610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 3672
 
4.0%
사 3232
 
3.6%
소 2318
 
2.6%
동 2303
 
2.5%
공 2062
 
2.3%
) 2002
 
2.2%
( 2002
 
2.2%
터 1785
 
2.0%
센 1769
 
1.9%
시 1702
 
1.9%
Other values (619) 67967
74.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84097
92.6%
Close Punctuation 2006
 
2.2%
Open Punctuation 2006
 
2.2%
Decimal Number 1202
 
1.3%
Uppercase Letter 931
 
1.0%
Connector Punctuation 376
 
0.4%
Other Punctuation 86
 
0.1%
Lowercase Letter 84
 
0.1%
Dash Punctuation 17
 
< 0.1%
Other Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3672
 
4.4%
사 3232
 
3.8%
소 2318
 
2.8%
동 2303
 
2.7%
공 2062
 
2.5%
터 1785
 
2.1%
센 1769
 
2.1%
시 1702
 
2.0%
산 1673
 
2.0%
지 1627
 
1.9%
Other values (553) 61954
73.7%
Uppercase Letter
ValueCountFrequency (%)
S 138
14.8%
C 121
13.0%
K 99
10.6%
D 68
 
7.3%
I 62
 
6.7%
T 60
 
6.4%
L 54
 
5.8%
G 54
 
5.8%
N 35
 
3.8%
B 34
 
3.7%
Other values (15) 206
22.1%
Lowercase Letter
ValueCountFrequency (%)
k 21
25.0%
t 14
16.7%
o 10
11.9%
a 8
 
9.5%
b 4
 
4.8%
r 4
 
4.8%
e 4
 
4.8%
l 3
 
3.6%
s 3
 
3.6%
p 3
 
3.6%
Other values (8) 10
11.9%
Decimal Number
ValueCountFrequency (%)
2 419
34.9%
1 397
33.0%
3 187
15.6%
4 87
 
7.2%
5 55
 
4.6%
6 22
 
1.8%
0 13
 
1.1%
8 11
 
0.9%
7 7
 
0.6%
9 4
 
0.3%
Other Punctuation
ValueCountFrequency (%)
& 36
41.9%
. 19
22.1%
· 18
20.9%
, 12
 
14.0%
/ 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 2002
99.8%
] 4
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 2002
99.8%
[ 4
 
0.2%
Connector Punctuation
ValueCountFrequency (%)
_ 376
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84104
92.6%
Common 5695
 
6.3%
Latin 1015
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3672
 
4.4%
사 3232
 
3.8%
소 2318
 
2.8%
동 2303
 
2.7%
공 2062
 
2.5%
터 1785
 
2.1%
센 1769
 
2.1%
시 1702
 
2.0%
산 1673
 
2.0%
지 1627
 
1.9%
Other values (554) 61961
73.7%
Latin
ValueCountFrequency (%)
S 138
13.6%
C 121
11.9%
K 99
 
9.8%
D 68
 
6.7%
I 62
 
6.1%
T 60
 
5.9%
L 54
 
5.3%
G 54
 
5.3%
N 35
 
3.4%
B 34
 
3.3%
Other values (33) 290
28.6%
Common
ValueCountFrequency (%)
) 2002
35.2%
( 2002
35.2%
2 419
 
7.4%
1 397
 
7.0%
_ 376
 
6.6%
3 187
 
3.3%
4 87
 
1.5%
5 55
 
1.0%
& 36
 
0.6%
6 22
 
0.4%
Other values (12) 112
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84093
92.6%
ASCII 6692
 
7.4%
None 25
 
< 0.1%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 3672
 
4.4%
사 3232
 
3.8%
소 2318
 
2.8%
동 2303
 
2.7%
공 2062
 
2.5%
터 1785
 
2.1%
센 1769
 
2.1%
시 1702
 
2.0%
산 1673
 
2.0%
지 1627
 
1.9%
Other values (552) 61950
73.7%
ASCII
ValueCountFrequency (%)
) 2002
29.9%
( 2002
29.9%
2 419
 
6.3%
1 397
 
5.9%
_ 376
 
5.6%
3 187
 
2.8%
S 138
 
2.1%
C 121
 
1.8%
K 99
 
1.5%
4 87
 
1.3%
Other values (54) 864
12.9%
None
ValueCountFrequency (%)
· 18
72.0%
㈜ 7
 
28.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 4
100.0%

사업장구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
사업장
8060 
대표사업장
1940 

Length

Max length5
Median length3
Mean length3.388
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사업장 8060
80.6%
대표사업장 1940
 
19.4%

Length

2024-04-21T04:41:00.322605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T04:41:00.501153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업장 8060
80.6%
대표사업장 1940
 
19.4%

유형
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
공공행정
6454 
제조
1650 
기타서비스
1212 
기타산업
 
303
교육서비스
 
273

Length

Max length5
Median length4
Mean length3.7969
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공공행정
2nd row제조
3rd row공공행정
4th row공공행정
5th row공공행정

Common Values

ValueCountFrequency (%)
공공행정 6454
64.5%
제조 1650
 
16.5%
기타서비스 1212
 
12.1%
기타산업 303
 
3.0%
교육서비스 273
 
2.7%
보건 108
 
1.1%

Length

2024-04-21T04:41:00.683553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T04:41:00.871809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공행정 6454
64.5%
제조 1650
 
16.5%
기타서비스 1212
 
12.1%
기타산업 303
 
3.0%
교육서비스 273
 
2.7%
보건 108
 
1.1%

특성
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
지방자치단체
4820 
공공기관
1410 
온실가스목표관리업체
1397 
배출권할당대상업체
1196 
중앙행정기관
 
446
Other values (6)
731 

Length

Max length10
Median length6
Mean length6.5202
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공공기관
2nd row온실가스목표관리업체
3rd row배출권할당대상업체
4th row공공기관
5th row공공기관

Common Values

ValueCountFrequency (%)
지방자치단체 4820
48.2%
공공기관 1410
 
14.1%
온실가스목표관리업체 1397
 
14.0%
배출권할당대상업체 1196
 
12.0%
중앙행정기관 446
 
4.5%
지방공단 272
 
2.7%
국공립대학 138
 
1.4%
녹색기업 135
 
1.4%
지방공사 95
 
0.9%
지방공사공단 79
 
0.8%

Length

2024-04-21T04:41:01.088854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지방자치단체 4820
48.2%
공공기관 1410
 
14.1%
온실가스목표관리업체 1397
 
14.0%
배출권할당대상업체 1196
 
12.0%
중앙행정기관 446
 
4.5%
지방공단 272
 
2.7%
국공립대학 138
 
1.4%
녹색기업 135
 
1.4%
지방공사 95
 
0.9%
지방공사공단 79
 
0.8%

업종
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
공공행정,국방및사회보장행정
5109 
제조업
1612 
도매및소매업
 
481
보건업및사회복지서비스업
 
364
교육서비스업
 
346
Other values (15)
2088 

Length

Max length19
Median length14
Mean length11.0449
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전기,가스,증기및수도사업
2nd row제조업
3rd row전기,가스,증기및수도사업
4th row전문,과학및기술서비스업
5th row공공행정,국방및사회보장행정

Common Values

ValueCountFrequency (%)
공공행정,국방및사회보장행정 5109
51.1%
제조업 1612
 
16.1%
도매및소매업 481
 
4.8%
보건업및사회복지서비스업 364
 
3.6%
교육서비스업 346
 
3.5%
전기,가스,증기및수도사업 337
 
3.4%
전문,과학및기술서비스업 269
 
2.7%
예술,스포츠및여가관련서비스업 259
 
2.6%
사업시설관리및사업지원서비스업 249
 
2.5%
금융및보험업 228
 
2.3%
Other values (10) 746
 
7.5%

Length

2024-04-21T04:41:01.315648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공공행정,국방및사회보장행정 5109
51.1%
제조업 1612
 
16.1%
도매및소매업 481
 
4.8%
보건업및사회복지서비스업 364
 
3.6%
교육서비스업 346
 
3.5%
전기,가스,증기및수도사업 337
 
3.4%
전문,과학및기술서비스업 269
 
2.7%
예술,스포츠및여가관련서비스업 259
 
2.6%
사업시설관리및사업지원서비스업 249
 
2.5%
금융및보험업 228
 
2.3%
Other values (10) 746
 
7.5%

세부업종
Text

Distinct65
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T04:41:02.090274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length11.9052
Min length2

Characters and Unicode

Total characters119052
Distinct characters161
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row수도사업
2nd row기타제품제조업
3rd row전기,가스,증기및공기조절공급업
4th row기타전문,과학및기술서비스업
5th row공공행정,국방및사회보장행정
ValueCountFrequency (%)
공공행정,국방및사회보장행정 5109
51.1%
소매업;자동차제외 439
 
4.4%
교육서비스업 346
 
3.5%
보건업 304
 
3.0%
화학물질및화학제품제조업;의약품제외 297
 
3.0%
전기,가스,증기및공기조절공급업 227
 
2.3%
금융업 190
 
1.9%
사업시설관리및조경서비스업 189
 
1.9%
비금속광물제품제조업 176
 
1.8%
1차금속제조업 171
 
1.7%
Other values (55) 2552
25.5%
2024-04-21T04:41:03.140685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 10745
 
9.0%
정 10264
 
8.6%
행 10218
 
8.6%
및 7198
 
6.0%
, 6613
 
5.6%
사 5529
 
4.6%
보 5468
 
4.6%
장 5369
 
4.5%
회 5175
 
4.3%
방 5132
 
4.3%
Other values (151) 47341
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111381
93.6%
Other Punctuation 7500
 
6.3%
Decimal Number 171
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 10745
 
9.6%
정 10264
 
9.2%
행 10218
 
9.2%
및 7198
 
6.5%
사 5529
 
5.0%
보 5468
 
4.9%
장 5369
 
4.8%
회 5175
 
4.6%
방 5132
 
4.6%
업 5131
 
4.6%
Other values (147) 41152
36.9%
Other Punctuation
ValueCountFrequency (%)
, 6613
88.2%
; 883
 
11.8%
· 4
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111381
93.6%
Common 7671
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 10745
 
9.6%
정 10264
 
9.2%
행 10218
 
9.2%
및 7198
 
6.5%
사 5529
 
5.0%
보 5468
 
4.9%
장 5369
 
4.8%
회 5175
 
4.6%
방 5132
 
4.6%
업 5131
 
4.6%
Other values (147) 41152
36.9%
Common
ValueCountFrequency (%)
, 6613
86.2%
; 883
 
11.5%
1 171
 
2.2%
· 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111381
93.6%
ASCII 7667
 
6.4%
None 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 10745
 
9.6%
정 10264
 
9.2%
행 10218
 
9.2%
및 7198
 
6.5%
사 5529
 
5.0%
보 5468
 
4.9%
장 5369
 
4.8%
회 5175
 
4.6%
방 5132
 
4.6%
업 5131
 
4.6%
Other values (147) 41152
36.9%
ASCII
ValueCountFrequency (%)
, 6613
86.3%
; 883
 
11.5%
1 171
 
2.2%
None
ValueCountFrequency (%)
· 4
100.0%

년도
Real number (ℝ)

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.5624
Minimum2012
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T04:41:03.379536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12014
median2016
Q32017
95-th percentile2020
Maximum2020
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3406525
Coefficient of variation (CV)0.00116129
Kurtosis-1.0186049
Mean2015.5624
Median Absolute Deviation (MAD)2
Skewness0.099335221
Sum20155624
Variance5.4786541
MonotonicityNot monotonic
2024-04-21T04:41:03.587777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2018 1355
13.6%
2016 1330
13.3%
2017 1330
13.3%
2015 1267
12.7%
2014 1229
12.3%
2012 1220
12.2%
2013 1194
11.9%
2020 546
5.5%
2019 529
 
5.3%
ValueCountFrequency (%)
2012 1220
12.2%
2013 1194
11.9%
2014 1229
12.3%
2015 1267
12.7%
2016 1330
13.3%
2017 1330
13.3%
2018 1355
13.6%
2019 529
 
5.3%
2020 546
5.5%
ValueCountFrequency (%)
2020 546
5.5%
2019 529
 
5.3%
2018 1355
13.6%
2017 1330
13.3%
2016 1330
13.3%
2015 1267
12.7%
2014 1229
12.3%
2013 1194
11.9%
2012 1220
12.2%

에너지총량(TJ)
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

직접배출량(scope1)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1824
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45012.136
Minimum0
Maximum69773644
Zeros8139
Zeros (%)81.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T04:41:03.920320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile11729.446
Maximum69773644
Range69773644
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1056855.3
Coefficient of variation (CV)23.47934
Kurtosis2341.0357
Mean45012.136
Median Absolute Deviation (MAD)0
Skewness43.630506
Sum4.5012136 × 108
Variance1.116943 × 1012
MonotonicityNot monotonic
2024-04-21T04:41:04.367832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8139
81.4%
3384.91 5
 
0.1%
16.0 3
 
< 0.1%
383.0 3
 
< 0.1%
187.0 3
 
< 0.1%
140.0 3
 
< 0.1%
102.0 2
 
< 0.1%
189.0 2
 
< 0.1%
229.0 2
 
< 0.1%
121.0 2
 
< 0.1%
Other values (1814) 1836
 
18.4%
ValueCountFrequency (%)
0.0 8139
81.4%
0.042 1
 
< 0.1%
0.043 1
 
< 0.1%
0.166 1
 
< 0.1%
0.421 1
 
< 0.1%
0.481 1
 
< 0.1%
0.5 1
 
< 0.1%
0.921 1
 
< 0.1%
0.94 1
 
< 0.1%
0.945 1
 
< 0.1%
ValueCountFrequency (%)
69773644.0 1
< 0.1%
41750612.0 1
< 0.1%
28627592.0 1
< 0.1%
27457208.0 1
< 0.1%
26712013.0 1
< 0.1%
22864962.0 1
< 0.1%
21993780.0 1
< 0.1%
21786657.0 1
< 0.1%
14849733.0 1
< 0.1%
12600587.0 1
< 0.1%

간접배출량(scope2)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1865
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19342.455
Minimum0
Maximum62216366
Zeros8125
Zeros (%)81.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T04:41:04.785624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20118.2
Maximum62216366
Range62216366
Interquartile range (IQR)0

Descriptive statistics

Standard deviation669523.5
Coefficient of variation (CV)34.614195
Kurtosis7500.634
Mean19342.455
Median Absolute Deviation (MAD)0
Skewness82.621575
Sum1.9342455 × 108
Variance4.4826171 × 1011
MonotonicityNot monotonic
2024-04-21T04:41:05.426782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8125
81.2%
12281.92 5
 
0.1%
3307.477 2
 
< 0.1%
219.0 2
 
< 0.1%
2215.0 2
 
< 0.1%
1150.0 2
 
< 0.1%
18278.0 2
 
< 0.1%
4068.0 2
 
< 0.1%
2546.0 2
 
< 0.1%
6992.212 1
 
< 0.1%
Other values (1855) 1855
 
18.6%
ValueCountFrequency (%)
0.0 8125
81.2%
2.164 1
 
< 0.1%
2.576 1
 
< 0.1%
2.75 1
 
< 0.1%
2.861 1
 
< 0.1%
3.345 1
 
< 0.1%
3.361 1
 
< 0.1%
3.39 1
 
< 0.1%
3.517 1
 
< 0.1%
4.0 1
 
< 0.1%
ValueCountFrequency (%)
62216366.0 1
< 0.1%
16431059.0 1
< 0.1%
12353449.0 1
< 0.1%
7787367.0 1
< 0.1%
6786584.0 1
< 0.1%
3776558.0 1
< 0.1%
3662757.0 1
< 0.1%
3624342.0 1
< 0.1%
2811680.0 1
< 0.1%
1795931.0 1
< 0.1%

간접배출량(scope3)
Real number (ℝ)

SKEWED  ZEROS 

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean198.57304
Minimum0
Maximum852616
Zeros9958
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T04:41:05.835704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum852616
Range852616
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10517.753
Coefficient of variation (CV)52.966671
Kurtosis5130.8104
Mean198.57304
Median Absolute Deviation (MAD)0
Skewness69.116683
Sum1985730.4
Variance1.1062312 × 108
MonotonicityNot monotonic
2024-04-21T04:41:06.233851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.0 9958
99.6%
6066.96 1
 
< 0.1%
1.0 1
 
< 0.1%
336.0 1
 
< 0.1%
1797.844 1
 
< 0.1%
7826.04 1
 
< 0.1%
4819.0 1
 
< 0.1%
560619.0 1
 
< 0.1%
8.313 1
 
< 0.1%
77.365 1
 
< 0.1%
Other values (33) 33
 
0.3%
ValueCountFrequency (%)
0.0 9958
99.6%
0.21 1
 
< 0.1%
0.33 1
 
< 0.1%
1.0 1
 
< 0.1%
2.986 1
 
< 0.1%
4.0 1
 
< 0.1%
8.313 1
 
< 0.1%
9.0 1
 
< 0.1%
9.678 1
 
< 0.1%
10.233 1
 
< 0.1%
ValueCountFrequency (%)
852616.0 1
< 0.1%
560619.0 1
< 0.1%
167327.0 1
< 0.1%
118238.0 1
< 0.1%
110801.0 1
< 0.1%
91073.0 1
< 0.1%
50506.0 1
< 0.1%
7826.04 1
< 0.1%
6066.96 1
< 0.1%
4819.0 1
< 0.1%

온실가스배출총량
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1905
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64553.114
Minimum0
Maximum72585324
Zeros8089
Zeros (%)80.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T04:41:06.629817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile41686.993
Maximum72585324
Range72585324
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1304890.4
Coefficient of variation (CV)20.214214
Kurtosis1741.223
Mean64553.114
Median Absolute Deviation (MAD)0
Skewness38.205436
Sum6.4553114 × 108
Variance1.702739 × 1012
MonotonicityNot monotonic
2024-04-21T04:41:07.073653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8089
80.9%
15666.83 5
 
0.1%
167058.632 2
 
< 0.1%
3434.0 2
 
< 0.1%
2939.0 2
 
< 0.1%
16980.0 1
 
< 0.1%
41675.0 1
 
< 0.1%
7160.348 1
 
< 0.1%
294916.258 1
 
< 0.1%
42110.737 1
 
< 0.1%
Other values (1895) 1895
 
18.9%
ValueCountFrequency (%)
0.0 8089
80.9%
1.0 1
 
< 0.1%
2.164 1
 
< 0.1%
2.75 1
 
< 0.1%
2.89 1
 
< 0.1%
3.345 1
 
< 0.1%
3.6 1
 
< 0.1%
4.0 1
 
< 0.1%
5.041 1
 
< 0.1%
7.93 1
 
< 0.1%
ValueCountFrequency (%)
72585324.0 1
< 0.1%
63491875.0 1
< 0.1%
41760132.0 1
< 0.1%
34243792.0 1
< 0.1%
28654364.0 1
< 0.1%
26729548.0 1
< 0.1%
22870267.47 1
< 0.1%
22028309.0 1
< 0.1%
21794572.0 1
< 0.1%
20019375.0 1
< 0.1%

Interactions

2024-04-21T04:40:55.152638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:51.485228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:52.379794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:53.461709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:54.323108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:55.339199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:51.670253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:52.567532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:53.644094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:54.500045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:55.516843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:51.852816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:52.745569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:53.819484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:54.671573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:55.691107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:52.032497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:52.917077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:53.987900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:54.834922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:55.849789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:52.194456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:53.286030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:54.145477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:40:54.984921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T04:41:07.363895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장구분유형특성업종세부업종년도직접배출량(scope1)간접배출량(scope2)간접배출량(scope3)온실가스배출총량
사업장구분1.0000.5120.3720.4790.4980.3510.0000.0360.0420.032
유형0.5121.0000.7890.9280.9620.2260.0880.0320.0510.108
특성0.3720.7891.0000.7950.8520.4430.0180.0300.0250.030
업종0.4790.9280.7951.0001.0000.3180.0580.0000.3530.076
세부업종0.4980.9620.8521.0001.0000.3690.1440.1710.3490.182
년도0.3510.2260.4430.3180.3691.0000.0420.0750.0370.083
직접배출량(scope1)0.0000.0880.0180.0580.1440.0421.0000.2120.0000.918
간접배출량(scope2)0.0360.0320.0300.0000.1710.0750.2121.0000.0000.981
간접배출량(scope3)0.0420.0510.0250.3530.3490.0370.0000.0001.0000.000
온실가스배출총량0.0320.1080.0300.0760.1820.0830.9180.9810.0001.000
2024-04-21T04:41:07.688588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특성유형사업장구분업종
특성1.0000.5600.3570.439
유형0.5601.0000.3700.761
사업장구분0.3570.3701.0000.379
업종0.4390.7610.3791.000
2024-04-21T04:41:07.967139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도직접배출량(scope1)간접배출량(scope2)간접배출량(scope3)온실가스배출총량사업장구분유형특성업종
년도1.0000.1500.1500.0050.1490.2570.1230.2150.120
직접배출량(scope1)0.1501.0000.9680.1110.9840.0000.0520.0090.025
간접배출량(scope2)0.1500.9681.0000.1290.9870.0240.0200.0180.000
간접배출량(scope3)0.0050.1110.1291.0000.1360.0280.0330.0150.173
온실가스배출총량0.1490.9840.9870.1361.0000.0240.0600.0140.030
사업장구분0.2570.0000.0240.0280.0241.0000.3700.3570.379
유형0.1230.0520.0200.0330.0600.3701.0000.5600.761
특성0.2150.0090.0180.0150.0140.3570.5601.0000.439
업종0.1200.0250.0000.1730.0300.3790.7610.4391.000

Missing values

2024-04-21T04:40:56.097210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T04:40:56.414511image/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

대표사업장명사업장명사업장구분유형특성업종세부업종년도에너지총량(TJ)직접배출량(scope1)간접배출량(scope2)간접배출량(scope3)온실가스배출총량
15014한국수자원공사전북지역본부사업장공공행정공공기관전기,가스,증기및수도사업수도사업2013469.66140.022645.00.022785.0
28708주)벽산익산공장(주)벽산음성공장사업장제조온실가스목표관리업체제조업기타제품제조업201553.220.00.00.00.0
63300한국전력공사한국전력공사_인천지역본부시흥전력지사사업장공공행정배출권할당대상업체전기,가스,증기및수도사업전기,가스,증기및공기조절공급업20198.2511600.761866.3730.013467.133
33585한국가스안전공사한국가스안전공사대구경북지역본부사업장공공행정공공기관전문,과학및기술서비스업기타전문,과학및기술서비스업20150.450.00.00.00.0
66712국민체육진흥공단경륜경정사업본부B사업장공공행정공공기관공공행정,국방및사회보장행정공공행정,국방및사회보장행정202036.460.00.00.00.0
53889세방전지(주)창원생산본부세방전지(주)사업장제조배출권할당대상업체제조업전기장비제조업20184.430.00.00.00.0
27429(주)이랜드리테일NC백화점커낼워크점사업장기타서비스온실가스목표관리업체도매및소매업소매업;자동차제외201567.960.00.00.00.0
26347도로교통공단전남운전면허시험장사업장공공행정공공기관공공행정,국방및사회보장행정공공행정,국방및사회보장행정20153.930.00.00.00.0
43414인천중구시설관리공단짜장면박물관사업장공공행정지방공단공공행정,국방및사회보장행정공공행정,국방및사회보장행정20161.040.00.00.00.0
68398경인환경에너지(주)경인환경에너지(주)대표사업장기타산업배출권할당대상업체하수·폐기물처리,원료재생및환경복원업폐기물수집운반,처리및원료재생업2020174.9865118.02560.00.067678.0
대표사업장명사업장명사업장구분유형특성업종세부업종년도에너지총량(TJ)직접배출량(scope1)간접배출량(scope2)간접배출량(scope3)온실가스배출총량
14670인천광역시남동구청구월3동행정복지센터사업장공공행정지방자치단체공공행정,국방및사회보장행정공공행정,국방및사회보장행정20131.080.00.00.00.0
68052강동구청강동구청대표사업장공공행정지방자치단체공공행정,국방및사회보장행정공공행정,국방및사회보장행정202021.2447.325697.050.01144.375
23526통영시청도천동주민센터사업장공공행정지방자치단체공공행정,국방및사회보장행정공공행정,국방및사회보장행정20140.210.00.00.00.0
19268부산광역시청부산광역시서울본부사업장공공행정지방자치단체공공행정,국방및사회보장행정공공행정,국방및사회보장행정20140.520.00.00.00.0
46376광주광역시청동부소방서사업장공공행정지방자치단체공공행정,국방및사회보장행정공공행정,국방및사회보장행정20174.420.00.00.00.0
59902부산진구청부산진구청부전2동사업장공공행정지방자치단체공공행정,국방및사회보장행정공공행정,국방및사회보장행정20180.290.00.00.00.0
50741구미시청노인종합복지회관사업장공공행정지방자치단체보건업및사회복지서비스업사회복지서비스업20175.370.00.00.00.0
14781경찰청부산지방경찰청사업장공공행정중앙행정기관공공행정,국방및사회보장행정공공행정,국방및사회보장행정201364.890.00.00.00.0
6747법무부인천공항출입국ㆍ외국인청사업장공공행정중앙행정기관공공행정,국방및사회보장행정공공행정,국방및사회보장행정201214.360.00.00.00.0
54944부산광역시청부산광역시체육시설관리사업소사업장공공행정지방자치단체공공행정,국방및사회보장행정공공행정,국방및사회보장행정2018101.790.00.00.00.0

Duplicate rows

Most frequently occurring

대표사업장명사업장명사업장구분유형특성업종세부업종년도직접배출량(scope1)간접배출량(scope2)간접배출량(scope3)온실가스배출총량# duplicates
0충청남도청충청남도수산자원연구소사업장공공행정지방자치단체공공행정,국방및사회보장행정공공행정,국방및사회보장행정20140.00.00.00.02