Overview

Dataset statistics

Number of variables9
Number of observations218
Missing cells255
Missing cells (%)13.0%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory27.0 KiB
Average record size in memory126.8 B

Variable types

Categorical6
Numeric1
Text1
Unsupported1

Dataset

Description경상남도 창원시의 온실가스배출량 현황(에너지별배출량, 산업공정별배출량, 농축산흡수량, 폐기물별배출량)입니다.
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15036654

Alerts

Dataset has 1 (0.5%) duplicate rowsDuplicates
원단위 is highly overall correlated with 부문 and 2 other fieldsHigh correlation
단위 is highly overall correlated with 부문 and 2 other fieldsHigh correlation
감축기술 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
부문 is highly overall correlated with Unnamed: 1 and 5 other fieldsHigh correlation
Unnamed: 2 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
지표 is highly overall correlated with 부문 and 2 other fieldsHigh correlation
Unnamed: 1 is highly overall correlated with 부문 and 2 other fieldsHigh correlation
부문 is highly imbalanced (92.5%)Imbalance
출처 has 35 (16.1%) missing valuesMissing
Unnamed: 8 has 218 (100.0%) missing valuesMissing
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 1 has 5 (2.3%) zerosZeros

Reproduction

Analysis started2023-12-10 23:59:28.862252
Analysis finished2023-12-10 23:59:30.397426
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

부문
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
0
216 
<NA>
 
2

Length

Max length4
Median length1
Mean length1.0275229
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 216
99.1%
<NA> 2
 
0.9%

Length

2023-12-11T08:59:30.472812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:59:30.581368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 216
99.1%
na 2
 
0.9%

Unnamed: 1
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct169
Distinct (%)78.2%
Missing2
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean228.5171
Minimum0
Maximum32653
Zeros5
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-12-11T08:59:30.697371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.000140625
Q10.018375
median0.2963
Q31.58105
95-th percentile396
Maximum32653
Range32653
Interquartile range (IQR)1.562675

Descriptive statistics

Standard deviation2252.4152
Coefficient of variation (CV)9.8566593
Kurtosis202.42215
Mean228.5171
Median Absolute Deviation (MAD)0.2955
Skewness14.044318
Sum49359.694
Variance5073374.3
MonotonicityNot monotonic
2023-12-11T08:59:30.826795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 8
 
3.7%
0.0 5
 
2.3%
0.63 4
 
1.8%
1.5724 4
 
1.8%
2.06 3
 
1.4%
0.035 3
 
1.4%
0.403 3
 
1.4%
0.0008 3
 
1.4%
5.9 3
 
1.4%
0.0003 3
 
1.4%
Other values (159) 177
81.2%
ValueCountFrequency (%)
0.0 5
2.3%
3.6500000000000006e-06 1
 
0.5%
3.98e-06 1
 
0.5%
8.37e-06 1
 
0.5%
9.02e-06 1
 
0.5%
1.23e-05 1
 
0.5%
2.85e-05 1
 
0.5%
0.000178 1
 
0.5%
0.000192 1
 
0.5%
0.000249 1
 
0.5%
ValueCountFrequency (%)
32653.0 1
0.5%
4648.0 1
0.5%
1775.41 1
0.5%
1763.0 1
0.5%
1530.0 1
0.5%
1329.68 1
0.5%
1188.0 1
0.5%
917.0 1
0.5%
761.0 1
0.5%
647.0 1
0.5%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
tCO2eq/대
52 
tCO2eq/가구
33 
tCO2eq/m2
15 
tCO2eq/톤
12 
tCO2eq/kW
11 
Other values (37)
95 

Length

Max length13
Median length12
Mean length9.0642202
Min length4

Unique

Unique16 ?
Unique (%)7.3%

Sample

1st rowtCO2eq/가구
2nd rowtCO2eq/가구
3rd rowtCO2eq/m3
4th rowtCO2eq/kW
5th rowtCO2eq/가구

Common Values

ValueCountFrequency (%)
tCO2eq/대 52
23.9%
tCO2eq/가구 33
15.1%
tCO2eq/m2 15
 
6.9%
tCO2eq/톤 12
 
5.5%
tCO2eq/kW 11
 
5.0%
tCO2eq/ha/년 10
 
4.6%
tCO2eq/대·년 8
 
3.7%
tCO2eq/km 6
 
2.8%
tCO2eq/m3 6
 
2.8%
tCO2eq/개·년 6
 
2.8%
Other values (32) 59
27.1%

Length

2023-12-11T08:59:30.962225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tco2eq/대 52
23.9%
tco2eq/가구 33
15.1%
tco2eq/m2 15
 
6.9%
tco2eq/톤 12
 
5.5%
tco2eq/kw 11
 
5.0%
tco2eq/ha/년 10
 
4.6%
tco2eq/대·년 8
 
3.7%
tco2eq/km 6
 
2.8%
tco2eq/m3 6
 
2.8%
tco2eq/개·년 6
 
2.8%
Other values (32) 59
27.1%

감축기술
Categorical

HIGH CORRELATION 

Distinct41
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
대
49 
가구
33 
m2
15 
톤
12 
kW
11 
Other values (36)
98 

Length

Max length11
Median length9
Mean length2.0412844
Min length1

Unique

Unique18 ?
Unique (%)8.3%

Sample

1st row가구
2nd row가구
3rd rowm3
4th rowkW
5th row가구

Common Values

ValueCountFrequency (%)
대 49
22.5%
가구 33
15.1%
m2 15
 
6.9%
톤 12
 
5.5%
kW 11
 
5.0%
대수 11
 
5.0%
ha·년 10
 
4.6%
km 9
 
4.1%
개수 6
 
2.8%
m3 6
 
2.8%
Other values (31) 56
25.7%

Length

2023-12-11T08:59:31.090801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대 49
22.5%
가구 33
15.1%
m2 15
 
6.9%
톤 12
 
5.5%
kw 11
 
5.0%
대수 11
 
5.0%
ha·년 10
 
4.6%
km 9
 
4.1%
m3 6
 
2.8%
개수 6
 
2.8%
Other values (31) 56
25.7%

원단위
Categorical

HIGH CORRELATION 

Distinct41
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
지자체 온실가스 통합관리 지침
104 
온실가스 감축을 위한 실천방안 수립연구
14 
농업·농촌 자발적 온실가스 감축사업
13 
교통부문 온실가스 관리 시스템(https://www.kotems.or.kr)
12 
지자체 온실가스 감축 사례집
 
6
Other values (36)
69 

Length

Max length42
Median length41
Mean length18.068807
Min length3

Unique

Unique22 ?
Unique (%)10.1%

Sample

1st row지자체 온실가스 통합관리 지침
2nd row온실가스 감축을 위한 실천방안 수립연구
3rd row온실가스 감축을 위한 실천방안 수립연구
4th row지자체 온실가스 통합관리 지침
5th row지자체 온실가스 통합관리 지침

Common Values

ValueCountFrequency (%)
지자체 온실가스 통합관리 지침 104
47.7%
온실가스 감축을 위한 실천방안 수립연구 14
 
6.4%
농업·농촌 자발적 온실가스 감축사업 13
 
6.0%
교통부문 온실가스 관리 시스템(https://www.kotems.or.kr) 12
 
5.5%
지자체 온실가스 감축 사례집 6
 
2.8%
폐기물 발생 간접배출계수[지자체 온실가스 배출량 산정지침(Ver.4.1 6
 
2.8%
에너지관리공단 6
 
2.8%
한국환경경제학회 5
 
2.3%
녹색기술센터 5
 
2.3%
한국에너지공단 5
 
2.3%
Other values (31) 42
19.3%

Length

2023-12-11T08:59:31.242076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
온실가스 165
20.3%
지자체 110
13.5%
통합관리 104
12.8%
지침 104
12.8%
감축을 17
 
2.1%
위한 17
 
2.1%
실천방안 15
 
1.8%
수립연구 14
 
1.7%
농업·농촌 13
 
1.6%
자발적 13
 
1.6%
Other values (87) 241
29.6%

단위
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
한국환경공단
113 
국립환경과학원
17 
농업기술실용화재단
13 
에너지통계핸드북
 
6
한국환경공단)]
 
6
Other values (43)
63 

Length

Max length43
Median length7
Mean length10.605505
Min length4

Unique

Unique35 ?
Unique (%)16.1%

Sample

1st row 한국환경공단
2nd row 국립환경과학원
3rd row 국립환경과학원
4th row 한국환경공단
5th row 한국환경공단

Common Values

ValueCountFrequency (%)
한국환경공단 113
51.8%
국립환경과학원 17
 
7.8%
농업기술실용화재단 13
 
6.0%
에너지통계핸드북 6
 
2.8%
한국환경공단)] 6
 
2.8%
녹색기후기술의 온실가스 감축 효과 및 육성 방안 5
 
2.3%
주요국 감축수단별 감축잠재량 산정 및 감축목표 달성 가능성 검토 방법 연구 5
 
2.3%
탄소중립 최종보고서 5
 
2.3%
전기차의 평균연비 온실가스 달성 효과 3
 
1.4%
천안시 3
 
1.4%
Other values (38) 42
 
19.3%

Length

2023-12-11T08:59:31.406519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한국환경공단 119
28.9%
국립환경과학원 17
 
4.1%
온실가스 14
 
3.4%
및 14
 
3.4%
농업기술실용화재단 13
 
3.2%
효과 10
 
2.4%
감축 9
 
2.2%
달성 8
 
1.9%
에너지통계핸드북 6
 
1.5%
최종보고서 5
 
1.2%
Other values (104) 197
47.8%

지표
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
2013
110 
<NA>
21 
2017
18 
2012
15 
2014
 
10
Other values (26)
44 

Length

Max length17
Median length5
Mean length5.5
Min length4

Unique

Unique21 ?
Unique (%)9.6%

Sample

1st row 2013
2nd row 2012
3rd row 2012
4th row 2013
5th row 2013

Common Values

ValueCountFrequency (%)
2013 110
50.5%
<NA> 21
 
9.6%
2017 18
 
8.3%
2012 15
 
6.9%
2014 10
 
4.6%
2016 9
 
4.1%
2008 6
 
2.8%
2015 4
 
1.8%
2011 2
 
0.9%
2019 2
 
0.9%
Other values (21) 21
 
9.6%

Length

2023-12-11T08:59:31.563365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2013 110
45.8%
na 21
 
8.8%
2017 18
 
7.5%
2012 15
 
6.2%
2014 10
 
4.2%
2016 9
 
3.8%
2008 6
 
2.5%
2015 4
 
1.7%
저감 3
 
1.2%
소각장 2
 
0.8%
Other values (37) 42
 
17.5%

출처
Text

MISSING 

Distinct162
Distinct (%)88.5%
Missing35
Missing (%)16.1%
Memory size12.7 KiB
2023-12-11T08:59:31.825123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length13.885246
Min length2

Characters and Unicode

Total characters2541
Distinct characters305
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)77.0%

Sample

1st row그린홈 보급
2nd row빗물재이용
3rd row빗물재이용 시설 확대
4th row수소연료전지(발전용)
5th row태양열 온수기 도입
ValueCountFrequency (%)
보급 21
 
3.8%
확대 14
 
2.5%
에너지 11
 
2.0%
고효율 8
 
1.4%
및 8
 
1.4%
친환경 7
 
1.3%
제품 7
 
1.3%
도입 7
 
1.3%
시스템 6
 
1.1%
보일러 6
 
1.1%
Other values (325) 464
83.0%
2023-12-11T08:59:32.330267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
376
 
14.8%
( 64
 
2.5%
) 64
 
2.5%
기 61
 
2.4%
시 46
 
1.8%
이 45
 
1.8%
보 44
 
1.7%
급 44
 
1.7%
용 41
 
1.6%
전 41
 
1.6%
Other values (295) 1715
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1949
76.7%
Space Separator 376
 
14.8%
Open Punctuation 65
 
2.6%
Close Punctuation 65
 
2.6%
Uppercase Letter 30
 
1.2%
Decimal Number 21
 
0.8%
Lowercase Letter 9
 
0.4%
Dash Punctuation 7
 
0.3%
Connector Punctuation 6
 
0.2%
Math Symbol 6
 
0.2%
Other values (2) 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 61
 
3.1%
시 46
 
2.4%
이 45
 
2.3%
보 44
 
2.3%
급 44
 
2.3%
용 41
 
2.1%
전 41
 
2.1%
지 38
 
1.9%
대 33
 
1.7%
수 32
 
1.6%
Other values (254) 1524
78.2%
Uppercase Letter
ValueCountFrequency (%)
L 6
20.0%
D 4
13.3%
E 4
13.3%
G 3
10.0%
C 2
 
6.7%
R 2
 
6.7%
N 2
 
6.7%
T 2
 
6.7%
S 1
 
3.3%
H 1
 
3.3%
Other values (3) 3
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
z 1
11.1%
k 1
11.1%
r 1
11.1%
o 1
11.1%
w 1
11.1%
l 1
11.1%
t 1
11.1%
Decimal Number
ValueCountFrequency (%)
0 6
28.6%
2 4
19.0%
1 4
19.0%
4 3
14.3%
6 2
 
9.5%
5 2
 
9.5%
Other Punctuation
ValueCountFrequency (%)
% 2
50.0%
/ 1
25.0%
· 1
25.0%
Math Symbol
ValueCountFrequency (%)
+ 2
33.3%
→ 2
33.3%
> 2
33.3%
Open Punctuation
ValueCountFrequency (%)
( 64
98.5%
[ 1
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 64
98.5%
] 1
 
1.5%
Space Separator
ValueCountFrequency (%)
376
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1949
76.7%
Common 553
 
21.8%
Latin 39
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 61
 
3.1%
시 46
 
2.4%
이 45
 
2.3%
보 44
 
2.3%
급 44
 
2.3%
용 41
 
2.1%
전 41
 
2.1%
지 38
 
1.9%
대 33
 
1.7%
수 32
 
1.6%
Other values (254) 1524
78.2%
Latin
ValueCountFrequency (%)
L 6
15.4%
D 4
 
10.3%
E 4
 
10.3%
G 3
 
7.7%
C 2
 
5.1%
R 2
 
5.1%
N 2
 
5.1%
e 2
 
5.1%
T 2
 
5.1%
S 1
 
2.6%
Other values (11) 11
28.2%
Common
ValueCountFrequency (%)
376
68.0%
( 64
 
11.6%
) 64
 
11.6%
- 7
 
1.3%
_ 6
 
1.1%
0 6
 
1.1%
2 4
 
0.7%
1 4
 
0.7%
4 3
 
0.5%
℃ 3
 
0.5%
Other values (10) 16
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1949
76.7%
ASCII 586
 
23.1%
Letterlike Symbols 3
 
0.1%
Arrows 2
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
376
64.2%
( 64
 
10.9%
) 64
 
10.9%
- 7
 
1.2%
_ 6
 
1.0%
0 6
 
1.0%
L 6
 
1.0%
D 4
 
0.7%
E 4
 
0.7%
2 4
 
0.7%
Other values (28) 45
 
7.7%
Hangul
ValueCountFrequency (%)
기 61
 
3.1%
시 46
 
2.4%
이 45
 
2.3%
보 44
 
2.3%
급 44
 
2.3%
용 41
 
2.1%
전 41
 
2.1%
지 38
 
1.9%
대 33
 
1.7%
수 32
 
1.6%
Other values (254) 1524
78.2%
Letterlike Symbols
ValueCountFrequency (%)
℃ 3
100.0%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing218
Missing (%)100.0%
Memory size12.9 KiB

Interactions

2023-12-11T08:59:29.563962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:59:32.441623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2감축기술원단위단위지표
Unnamed: 11.0000.8890.8890.0000.0000.000
Unnamed: 20.8891.0000.9990.9420.9450.908
감축기술0.8890.9991.0000.9720.9400.917
원단위0.0000.9420.9721.0000.9970.989
단위0.0000.9450.9400.9971.0000.985
지표0.0000.9080.9170.9890.9851.000
2023-12-11T08:59:32.564477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
원단위단위감축기술부문Unnamed: 2지표
원단위1.0000.8790.4721.0000.4610.782
단위0.8791.0000.4351.0000.4480.772
감축기술0.4720.4351.0001.0000.9500.427
부문1.0001.0001.0001.0001.0001.000
Unnamed: 20.4610.4480.9501.0001.0000.413
지표0.7820.7720.4271.0000.4131.000
2023-12-11T08:59:32.670219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1부문Unnamed: 2감축기술원단위단위지표
Unnamed: 11.0001.0000.6450.6490.0000.0000.000
부문1.0001.0001.0001.0001.0001.0001.000
Unnamed: 20.6451.0001.0000.9500.4610.4480.413
감축기술0.6491.0000.9501.0000.4720.4350.427
원단위0.0001.0000.4610.4721.0000.8790.782
단위0.0001.0000.4480.4350.8791.0000.772
지표0.0001.0000.4130.4270.7820.7721.000

Missing values

2023-12-11T08:59:29.700176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:59:29.852763image/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.
2023-12-11T08:59:30.305946image/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

부문Unnamed: 1Unnamed: 2감축기술원단위단위지표출처Unnamed: 8
1.0에너지건물02.06tCO2eq/가구가구지자체 온실가스 통합관리 지침한국환경공단2013그린홈 보급<NA>
2.0에너지건물00.0342tCO2eq/가구가구온실가스 감축을 위한 실천방안 수립연구국립환경과학원2012빗물재이용<NA>
3.0에너지건물00.0003tCO2eq/m3m3온실가스 감축을 위한 실천방안 수립연구국립환경과학원2012빗물재이용 시설 확대<NA>
4.0에너지건물02.569tCO2eq/kWkW지자체 온실가스 통합관리 지침한국환경공단2013수소연료전지(발전용)<NA>
5.0에너지건물00.0024tCO2eq/가구가구지자체 온실가스 통합관리 지침한국환경공단2013태양열 온수기 도입<NA>
6.0에너지건물01.0546tCO2eq/kWkW온실가스 감축을 위한 실천방안 수립연구국립환경과학원2012지열 냉난방 시스템 보급(가정)<NA>
10.0에너지건물01.5724tCO2eq/가구가구온실가스 감축을 위한 실천방안 수립연구국립환경과학원2012태양광 주택보급<NA>
11.0에너지건물00.5174tCO2eq/m2m2온실가스 감축을 위한 실천방안 수립연구국립환경과학원2012태양광 시스템 보급 확대<NA>
12.0에너지건물00.0024tCO2eq/가구가구온실가스 감축을 위한 실천방안 수립연구국립환경과학원2012태양열 온수기 도입<NA>
13.0에너지건물00.1134tCO2eq/m2m2온실가스 감축을 위한 실천방안 수립연구국립환경과학원2012태양열 시스템 보급 확대<NA>
부문Unnamed: 1Unnamed: 2감축기술원단위단위지표출처Unnamed: 8
227.0비에너지폐기물00.003998tCO2eq/m3/년m3(송풍량)·년폐기물부문 온실가스 감축 적용 사례집한국환경공단2014하수처리장 생물반응조 송풍량 조정<NA>
228.0비에너지폐기물0152.0tCO2eq/년년폐기물부문 온실가스 감축 적용 사례집한국환경공단2014탈취팬 인버터 주파수 제어(60→45Hz)<NA>
229.0비에너지폐기물019.0tCO2eq/℃/년℃·년폐기물부문 온실가스 감축 적용 사례집한국환경공단2014소각처리시 SCR 저온촉매 사용(220→200℃)<NA>
230.0비에너지토지/녹지010.4tCO2eq/haha지자체 온실가스 통합관리 지침한국환경공단2013탄소중립공원 및 숲가꾸기(조성면적)<NA>
231.0비에너지토지/녹지00.0091tCO2eq/그루그루지자체 온실가스 통합관리 지침한국환경공단2013탄소중립공원 및 숲가꾸기(보급나무)<NA>
232.0비에너지토지/녹지00.043tCO2eq/그루그루지자체 온실가스 통합관리 지침한국환경공단2013가로수 심기<NA>
233.0비에너지토지/녹지00.015tCO2eq/m2m2지자체 온실가스 통합관리 지침한국환경공단2013옥상녹화사업<NA>
234.0비에너지토지/녹지0257.0tCO2eq/haha지자체 온실가스 통합관리 지침한국환경공단2013바다숲 조성<NA>
235.0비에너지토지/녹지04.5tCO2eq/대대수충청남도충청남도 2015년도 온실가스 감축 이행평가 및 2016년도 감축계획 수립2016산림바이오매스 생산 및 보급<NA>
236.0비에너지토지/녹지00.0037tCO2eq/m3/년m3(목재사용량)·년충남 금산군 목재문화체험장 사업계획보고서(산림탄소등록부)금산군청2017목조건축물 신축<NA>

Duplicate rows

Most frequently occurring

부문Unnamed: 1Unnamed: 2감축기술원단위단위지표출처# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA>2