Overview

Dataset statistics

Number of variables22
Number of observations4004
Missing cells163
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory735.2 KiB
Average record size in memory188.0 B

Variable types

Categorical4
Text5
Numeric12
DateTime1

Dataset

Description기존 공공건축물 성능개선사업을 통해 공공건축물 성공모델 발굴 및 성능개선을 선도하고, 민간건축물로 확산하기 기존 공공건축물의 에너지 소비량에 대한 데이터를 제공합니다. 지역, 용도, 면적, 코드번호, 기관명, 건물명, 소재지, 냉난방면적(㎡), 지하, 지상, 사용승인 연도,연간 단위면적당 1차에너지소비량 3개년평균(kWh/㎡년),연간 단위면적당 1차에너지소비량 3개년평균 중간값(kWh/㎡년), 간절기 대비 소비량 비율[(냉방월 + 난방월)/간절기월] 3개년 평균, 간절기 대비 소비량 비율[(냉방월 + 난방월)/간절기월] 2개년 평균, 간절기 대비 소비량 비율[(냉방월 + 난방월)/간절기월] 1개년 평균, 전기(KWH), 가스(KWH), 유류(KWH), 기타(KWH)을 포함하고 있습니다.
URLhttps://www.data.go.kr/data/3069931/fileData.do

Alerts

지하 has 145 (3.6%) missing valuesMissing
연면적 is highly skewed (γ1 = 36.67059531)Skewed
간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 3개년 평균 is highly skewed (γ1 = 24.60590371)Skewed
간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 2개년 평균 is highly skewed (γ1 = 42.45503425)Skewed
간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 1개년 평균 is highly skewed (γ1 = 46.56742605)Skewed
전기 (KWH) is highly skewed (γ1 = 42.86096801)Skewed
가스 (KWH) is highly skewed (γ1 = 63.202899)Skewed
유류 (KWH) is highly skewed (γ1 = 63.0463003)Skewed
기타 (KWH) is highly skewed (γ1 = 47.11800667)Skewed
지하 has 297 (7.4%) zerosZeros
간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 3개년 평균 has 256 (6.4%) zerosZeros
간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 2개년 평균 has 326 (8.1%) zerosZeros
간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 1개년 평균 has 375 (9.4%) zerosZeros
전기 (KWH) has 268 (6.7%) zerosZeros
가스 (KWH) has 1795 (44.8%) zerosZeros
유류 (KWH) has 3780 (94.4%) zerosZeros
기타 (KWH) has 3994 (99.8%) zerosZeros

Reproduction

Analysis started2023-12-11 23:02:46.491232
Analysis finished2023-12-11 23:02:47.406535
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
중부2지역
2426 
남부지역
1207 
중부1지역
278 
제주도
 
93

Length

Max length5
Median length5
Mean length4.6520979
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중부1지역
2nd row중부1지역
3rd row중부1지역
4th row중부1지역
5th row중부1지역

Common Values

ValueCountFrequency (%)
중부2지역 2426
60.6%
남부지역 1207
30.1%
중부1지역 278
 
6.9%
제주도 93
 
2.3%

Length

2023-12-12T08:02:47.478532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:02:47.580421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중부2지역 2426
60.6%
남부지역 1207
30.1%
중부1지역 278
 
6.9%
제주도 93
 
2.3%

용도
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
업무시설
1535 
교육연구시설
1511 
문화 및 집회시설
538 
의료시설
194 
수련시설
 
123

Length

Max length9
Median length6
Mean length5.4265734
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문화 및 집회시설
2nd row문화 및 집회시설
3rd row문화 및 집회시설
4th row문화 및 집회시설
5th row문화 및 집회시설

Common Values

ValueCountFrequency (%)
업무시설 1535
38.3%
교육연구시설 1511
37.7%
문화 및 집회시설 538
 
13.4%
의료시설 194
 
4.8%
수련시설 123
 
3.1%
운수시설 103
 
2.6%

Length

2023-12-12T08:02:47.671735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:02:47.764870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
업무시설 1535
30.2%
교육연구시설 1511
29.7%
문화 538
 
10.6%
및 538
 
10.6%
집회시설 538
 
10.6%
의료시설 194
 
3.8%
수련시설 123
 
2.4%
운수시설 103
 
2.0%

면적
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
3,000㎡이상~5,000㎡미만
1567 
5,000㎡이상~10,000㎡미만
1548 
10,000㎡이상
889 

Length

Max length18
Median length17
Mean length15.61039
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3,000㎡이상~5,000㎡미만
2nd row3,000㎡이상~5,000㎡미만
3rd row3,000㎡이상~5,000㎡미만
4th row3,000㎡이상~5,000㎡미만
5th row3,000㎡이상~5,000㎡미만

Common Values

ValueCountFrequency (%)
3,000㎡이상~5,000㎡미만 1567
39.1%
5,000㎡이상~10,000㎡미만 1548
38.7%
10,000㎡이상 889
22.2%

Length

2023-12-12T08:02:47.869188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:02:47.978339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3,000㎡이상~5,000㎡미만 1567
39.1%
5,000㎡이상~10,000㎡미만 1548
38.7%
10,000㎡이상 889
22.2%

기관유형
Categorical

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
광역 및 지방자치단체
1244 
국공립대학교
1237 
중앙행정기관 및 소속기관
620 
공공기관
512 
지방공사 및 공단
169 
Other values (2)
222 

Length

Max length14
Median length13
Mean length8.4957542
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광역 및 지방자치단체
2nd row광역 및 지방자치단체
3rd row광역 및 지방자치단체
4th row광역 및 지방자치단체
5th row중앙행정기관 및 소속기관

Common Values

ValueCountFrequency (%)
광역 및 지방자치단체 1244
31.1%
국공립대학교 1237
30.9%
중앙행정기관 및 소속기관 620
15.5%
공공기관 512
12.8%
지방공사 및 공단 169
 
4.2%
교육청 166
 
4.1%
국공립대학병원 및 치대병원 56
 
1.4%

Length

2023-12-12T08:02:48.099274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:02:48.198261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
및 2089
25.5%
광역 1244
15.2%
지방자치단체 1244
15.2%
국공립대학교 1237
15.1%
중앙행정기관 620
 
7.6%
소속기관 620
 
7.6%
공공기관 512
 
6.3%
지방공사 169
 
2.1%
공단 169
 
2.1%
교육청 166
 
2.0%
Other values (2) 112
 
1.4%

코드번호
Text

Distinct3516
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
2023-12-12T08:02:48.482443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.6958042
Min length5

Characters and Unicode

Total characters34818
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3072 ?
Unique (%)76.7%

Sample

1st row1011-0003
2nd row1011-0008
3rd row1011-0022
4th row1011-0027
5th row1011-0031
ValueCountFrequency (%)
2012-100 14
 
0.3%
oct-21 11
 
0.3%
1021-10 7
 
0.2%
2011-100 7
 
0.2%
3012-100 4
 
0.1%
2062-0185 3
 
0.1%
2062-0168 3
 
0.1%
2063-0079 3
 
0.1%
2042-0034 3
 
0.1%
2062-0032 3
 
0.1%
Other values (3506) 3946
98.6%
2023-12-12T08:02:48.877466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9800
28.1%
2 5522
15.9%
1 4332
12.4%
- 4004
11.5%
3 3483
 
10.0%
4 2386
 
6.9%
6 2244
 
6.4%
5 854
 
2.5%
7 732
 
2.1%
8 703
 
2.0%
Other values (19) 758
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30727
88.3%
Dash Punctuation 4004
 
11.5%
Lowercase Letter 58
 
0.2%
Uppercase Letter 29
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 13
22.4%
t 13
22.4%
p 6
10.3%
u 5
 
8.6%
r 5
 
8.6%
a 4
 
6.9%
e 4
 
6.9%
g 3
 
5.2%
y 2
 
3.4%
n 1
 
1.7%
Other values (2) 2
 
3.4%
Decimal Number
ValueCountFrequency (%)
0 9800
31.9%
2 5522
18.0%
1 4332
14.1%
3 3483
 
11.3%
4 2386
 
7.8%
6 2244
 
7.3%
5 854
 
2.8%
7 732
 
2.4%
8 703
 
2.3%
9 671
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
O 13
44.8%
A 6
20.7%
M 4
 
13.8%
S 3
 
10.3%
J 2
 
6.9%
F 1
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 4004
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34731
99.8%
Latin 87
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 13
14.9%
c 13
14.9%
t 13
14.9%
p 6
6.9%
A 6
6.9%
u 5
 
5.7%
r 5
 
5.7%
M 4
 
4.6%
a 4
 
4.6%
e 4
 
4.6%
Other values (8) 14
16.1%
Common
ValueCountFrequency (%)
0 9800
28.2%
2 5522
15.9%
1 4332
12.5%
- 4004
11.5%
3 3483
 
10.0%
4 2386
 
6.9%
6 2244
 
6.5%
5 854
 
2.5%
7 732
 
2.1%
8 703
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34818
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9800
28.1%
2 5522
15.9%
1 4332
12.4%
- 4004
11.5%
3 3483
 
10.0%
4 2386
 
6.9%
6 2244
 
6.4%
5 854
 
2.5%
7 732
 
2.1%
8 703
 
2.0%
Other values (19) 758
 
2.2%

기관명
Text

Distinct638
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
2023-12-12T08:02:49.158996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length6.7644855
Min length3

Characters and Unicode

Total characters27085
Distinct characters239
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)4.5%

Sample

1st row강원도 원주시
2nd row경기도 동두천시
3rd row강원도 평창군
4th row경기도 연천군
5th row산림청
ValueCountFrequency (%)
경기도 287
 
5.8%
서울특별시 194
 
3.9%
서울대학교 124
 
2.5%
경상남도 97
 
2.0%
경상북도 95
 
1.9%
전라북도 75
 
1.5%
전라남도 73
 
1.5%
경북대학교 72
 
1.5%
한국전력공사 71
 
1.4%
부산광역시 69
 
1.4%
Other values (607) 3760
76.5%
2023-12-12T08:02:49.559843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 1576
 
5.8%
학 1336
 
4.9%
대 1313
 
4.8%
시 1263
 
4.7%
도 1154
 
4.3%
경 1051
 
3.9%
913
 
3.4%
청 857
 
3.2%
국 764
 
2.8%
한 599
 
2.2%
Other values (229) 16259
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26016
96.1%
Space Separator 913
 
3.4%
Uppercase Letter 105
 
0.4%
Open Punctuation 24
 
0.1%
Close Punctuation 24
 
0.1%
Decimal Number 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 1576
 
6.1%
학 1336
 
5.1%
대 1313
 
5.0%
시 1263
 
4.9%
도 1154
 
4.4%
경 1051
 
4.0%
청 857
 
3.3%
국 764
 
2.9%
한 599
 
2.3%
공 582
 
2.2%
Other values (221) 15521
59.7%
Uppercase Letter
ValueCountFrequency (%)
B 35
33.3%
K 35
33.3%
I 35
33.3%
Space Separator
ValueCountFrequency (%)
913
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Decimal Number
ValueCountFrequency (%)
3 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26017
96.1%
Common 963
 
3.6%
Latin 105
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 1576
 
6.1%
학 1336
 
5.1%
대 1313
 
5.0%
시 1263
 
4.9%
도 1154
 
4.4%
경 1051
 
4.0%
청 857
 
3.3%
국 764
 
2.9%
한 599
 
2.3%
공 582
 
2.2%
Other values (222) 15522
59.7%
Common
ValueCountFrequency (%)
913
94.8%
( 24
 
2.5%
) 24
 
2.5%
3 2
 
0.2%
Latin
ValueCountFrequency (%)
B 35
33.3%
K 35
33.3%
I 35
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26016
96.1%
ASCII 1068
 
3.9%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 1576
 
6.1%
학 1336
 
5.1%
대 1313
 
5.0%
시 1263
 
4.9%
도 1154
 
4.4%
경 1051
 
4.0%
청 857
 
3.3%
국 764
 
2.9%
한 599
 
2.3%
공 582
 
2.2%
Other values (221) 15521
59.7%
ASCII
ValueCountFrequency (%)
913
85.5%
B 35
 
3.3%
K 35
 
3.3%
I 35
 
3.3%
( 24
 
2.2%
) 24
 
2.2%
3 2
 
0.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%

건물명
Text

Distinct3720
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
2023-12-12T08:02:49.819859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length26
Mean length8.3501499
Min length2

Characters and Unicode

Total characters33434
Distinct characters505
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3592 ?
Unique (%)89.7%

Sample

1st row원주역사박물관
2nd row자유수호박물관
3rd row평창문화예술회관
4th row연천군문화체육센터 가동
5th row산림박물관
ValueCountFrequency (%)
본관 103
 
2.0%
한국전력공사 71
 
1.3%
한국폴리텍대학 60
 
1.1%
본관동 53
 
1.0%
기업은행 35
 
0.7%
청사 31
 
0.6%
별관 28
 
0.5%
기숙사 27
 
0.5%
및 23
 
0.4%
학생회관 23
 
0.4%
Other values (3892) 4808
91.4%
2023-12-12T08:02:50.247780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 2015
 
6.0%
1285
 
3.8%
동 1021
 
3.1%
청 827
 
2.5%
사 783
 
2.3%
학 770
 
2.3%
서 748
 
2.2%
) 675
 
2.0%
( 672
 
2.0%
원 599
 
1.8%
Other values (495) 24039
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28727
85.9%
Decimal Number 1598
 
4.8%
Space Separator 1285
 
3.8%
Close Punctuation 693
 
2.1%
Open Punctuation 690
 
2.1%
Uppercase Letter 196
 
0.6%
Other Punctuation 167
 
0.5%
Dash Punctuation 59
 
0.2%
Lowercase Letter 14
 
< 0.1%
Connector Punctuation 2
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 2015
 
7.0%
동 1021
 
3.6%
청 827
 
2.9%
사 783
 
2.7%
학 770
 
2.7%
서 748
 
2.6%
원 599
 
2.1%
대 569
 
2.0%
국 519
 
1.8%
시 470
 
1.6%
Other values (436) 20406
71.0%
Uppercase Letter
ValueCountFrequency (%)
A 48
24.5%
B 26
13.3%
C 15
 
7.7%
N 14
 
7.1%
L 13
 
6.6%
E 11
 
5.6%
S 10
 
5.1%
M 8
 
4.1%
I 7
 
3.6%
D 7
 
3.6%
Other values (11) 37
18.9%
Decimal Number
ValueCountFrequency (%)
1 445
27.8%
2 321
20.1%
0 190
11.9%
3 182
11.4%
4 117
 
7.3%
5 104
 
6.5%
6 73
 
4.6%
7 64
 
4.0%
9 54
 
3.4%
8 48
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
a 3
21.4%
b 2
14.3%
c 2
14.3%
n 1
 
7.1%
t 1
 
7.1%
u 1
 
7.1%
o 1
 
7.1%
p 1
 
7.1%
m 1
 
7.1%
r 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 82
49.1%
, 45
26.9%
/ 20
 
12.0%
" 8
 
4.8%
· 6
 
3.6%
& 3
 
1.8%
% 2
 
1.2%
; 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 675
97.4%
] 18
 
2.6%
Open Punctuation
ValueCountFrequency (%)
( 672
97.4%
[ 18
 
2.6%
Space Separator
ValueCountFrequency (%)
1285
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28728
85.9%
Common 4495
 
13.4%
Latin 211
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 2015
 
7.0%
동 1021
 
3.6%
청 827
 
2.9%
사 783
 
2.7%
학 770
 
2.7%
서 748
 
2.6%
원 599
 
2.1%
대 569
 
2.0%
국 519
 
1.8%
시 470
 
1.6%
Other values (437) 20407
71.0%
Latin
ValueCountFrequency (%)
A 48
22.7%
B 26
12.3%
C 15
 
7.1%
N 14
 
6.6%
L 13
 
6.2%
E 11
 
5.2%
S 10
 
4.7%
M 8
 
3.8%
I 7
 
3.3%
D 7
 
3.3%
Other values (22) 52
24.6%
Common
ValueCountFrequency (%)
1285
28.6%
) 675
15.0%
( 672
14.9%
1 445
 
9.9%
2 321
 
7.1%
0 190
 
4.2%
3 182
 
4.0%
4 117
 
2.6%
5 104
 
2.3%
. 82
 
1.8%
Other values (16) 422
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28726
85.9%
ASCII 4699
 
14.1%
None 7
 
< 0.1%
Number Forms 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 2015
 
7.0%
동 1021
 
3.6%
청 827
 
2.9%
사 783
 
2.7%
학 770
 
2.7%
서 748
 
2.6%
원 599
 
2.1%
대 569
 
2.0%
국 519
 
1.8%
시 470
 
1.6%
Other values (435) 20405
71.0%
ASCII
ValueCountFrequency (%)
1285
27.3%
) 675
14.4%
( 672
14.3%
1 445
 
9.5%
2 321
 
6.8%
0 190
 
4.0%
3 182
 
3.9%
4 117
 
2.5%
5 104
 
2.2%
. 82
 
1.7%
Other values (46) 626
13.3%
None
ValueCountFrequency (%)
· 6
85.7%
㈜ 1
 
14.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

소재지
Text

Distinct2937
Distinct (%)73.6%
Missing13
Missing (%)0.3%
Memory size31.4 KiB
2023-12-12T08:02:50.511298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length65
Mean length25.984716
Min length6

Characters and Unicode

Total characters103705
Distinct characters512
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2668 ?
Unique (%)66.9%

Sample

1st row강원도 원주시 봉산동 836-1
2nd row경기도 동두천시 상봉암동 162-10
3rd row강원도 평창군 평창읍 종부리 596-4
4th row경기도 연천군 573
5th row경기도 포천시 소흘읍 직동리 51-7 국립수목원
ValueCountFrequency (%)
1095
 
5.2%
서울특별시 731
 
3.4%
경기도 585
 
2.8%
경상남도 328
 
1.5%
부산광역시 271
 
1.3%
전라북도 226
 
1.1%
강원도 221
 
1.0%
경상북도 209
 
1.0%
충청북도 207
 
1.0%
전라남도 205
 
1.0%
Other values (6576) 17175
80.8%
2023-12-12T08:02:50.928766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19079
 
18.4%
동 4003
 
3.9%
시 3837
 
3.7%
1 3818
 
3.7%
구 2952
 
2.8%
도 2532
 
2.4%
2 2307
 
2.2%
- 2158
 
2.1%
3 1849
 
1.8%
5 1495
 
1.4%
Other values (502) 59675
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61690
59.5%
Space Separator 19079
 
18.4%
Decimal Number 17105
 
16.5%
Dash Punctuation 2158
 
2.1%
Close Punctuation 1220
 
1.2%
Open Punctuation 1219
 
1.2%
Other Punctuation 1086
 
1.0%
Uppercase Letter 123
 
0.1%
Lowercase Letter 21
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4003
 
6.5%
시 3837
 
6.2%
구 2952
 
4.8%
도 2532
 
4.1%
지 1457
 
2.4%
서 1431
 
2.3%
경 1399
 
2.3%
광 1326
 
2.1%
남 1226
 
2.0%
산 1200
 
1.9%
Other values (447) 40327
65.4%
Uppercase Letter
ValueCountFrequency (%)
A 26
21.1%
B 14
11.4%
C 10
 
8.1%
E 9
 
7.3%
L 8
 
6.5%
T 7
 
5.7%
S 6
 
4.9%
G 5
 
4.1%
H 5
 
4.1%
F 5
 
4.1%
Other values (11) 28
22.8%
Decimal Number
ValueCountFrequency (%)
1 3818
22.3%
2 2307
13.5%
3 1849
10.8%
5 1495
 
8.7%
0 1488
 
8.7%
4 1375
 
8.0%
6 1313
 
7.7%
7 1217
 
7.1%
8 1199
 
7.0%
9 1044
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
n 4
19.0%
e 4
19.0%
d 4
19.0%
i 2
9.5%
f 2
9.5%
u 2
9.5%
p 1
 
4.8%
m 1
 
4.8%
a 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 1058
97.4%
. 13
 
1.2%
/ 9
 
0.8%
· 3
 
0.3%
& 1
 
0.1%
: 1
 
0.1%
; 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1205
98.8%
] 15
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 1204
98.8%
[ 15
 
1.2%
Space Separator
ValueCountFrequency (%)
19079
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2158
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61690
59.5%
Common 41869
40.4%
Latin 146
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4003
 
6.5%
시 3837
 
6.2%
구 2952
 
4.8%
도 2532
 
4.1%
지 1457
 
2.4%
서 1431
 
2.3%
경 1399
 
2.3%
광 1326
 
2.1%
남 1226
 
2.0%
산 1200
 
1.9%
Other values (447) 40327
65.4%
Latin
ValueCountFrequency (%)
A 26
17.8%
B 14
 
9.6%
C 10
 
6.8%
E 9
 
6.2%
L 8
 
5.5%
T 7
 
4.8%
S 6
 
4.1%
G 5
 
3.4%
H 5
 
3.4%
F 5
 
3.4%
Other values (21) 51
34.9%
Common
ValueCountFrequency (%)
19079
45.6%
1 3818
 
9.1%
2 2307
 
5.5%
- 2158
 
5.2%
3 1849
 
4.4%
5 1495
 
3.6%
0 1488
 
3.6%
4 1375
 
3.3%
6 1313
 
3.1%
7 1217
 
2.9%
Other values (14) 5770
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61689
59.5%
ASCII 42010
40.5%
None 3
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19079
45.4%
1 3818
 
9.1%
2 2307
 
5.5%
- 2158
 
5.1%
3 1849
 
4.4%
5 1495
 
3.6%
0 1488
 
3.5%
4 1375
 
3.3%
6 1313
 
3.1%
7 1217
 
2.9%
Other values (43) 5911
 
14.1%
Hangul
ValueCountFrequency (%)
동 4003
 
6.5%
시 3837
 
6.2%
구 2952
 
4.8%
도 2532
 
4.1%
지 1457
 
2.4%
서 1431
 
2.3%
경 1399
 
2.3%
광 1326
 
2.1%
남 1226
 
2.0%
산 1200
 
1.9%
Other values (446) 40326
65.4%
None
ValueCountFrequency (%)
· 3
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

연면적
Real number (ℝ)

SKEWED 

Distinct3967
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10094.183
Minimum3000
Maximum1466117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:51.063740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000
5-th percentile3243.0765
Q14149.905
median5871.205
Q39391.635
95-th percentile28115.835
Maximum1466117
Range1463117
Interquartile range (IQR)5241.73

Descriptive statistics

Standard deviation28309.914
Coefficient of variation (CV)2.8045771
Kurtosis1783.2251
Mean10094.183
Median Absolute Deviation (MAD)2092.625
Skewness36.670595
Sum40417109
Variance8.0145126 × 108
MonotonicityNot monotonic
2023-12-12T08:02:51.188354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3714.0 2
 
< 0.1%
5181.18 2
 
< 0.1%
6575.52 2
 
< 0.1%
6041.77 2
 
< 0.1%
3668.0 2
 
< 0.1%
5632.2 2
 
< 0.1%
5121.78 2
 
< 0.1%
3367.0 2
 
< 0.1%
4260.0 2
 
< 0.1%
4856.03 2
 
< 0.1%
Other values (3957) 3984
99.5%
ValueCountFrequency (%)
3000.0 1
< 0.1%
3004.0 1
< 0.1%
3004.42 1
< 0.1%
3005.04 1
< 0.1%
3005.2 1
< 0.1%
3006.1 1
< 0.1%
3006.58 1
< 0.1%
3007.11 1
< 0.1%
3014.4 1
< 0.1%
3015.34 1
< 0.1%
ValueCountFrequency (%)
1466117.0 1
< 0.1%
506995.68 1
< 0.1%
387620.68 1
< 0.1%
252668.84 1
< 0.1%
222462.0 1
< 0.1%
191731.0 1
< 0.1%
167192.0 1
< 0.1%
166503.0 1
< 0.1%
142112.5 1
< 0.1%
138302.15 1
< 0.1%

냉난방면적
Real number (ℝ)

Distinct3857
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7639.8971
Minimum2.4
Maximum506995.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:51.316782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.4
5-th percentile2230.878
Q13428.8325
median4800.61
Q37648.9675
95-th percentile20744.209
Maximum506995.68
Range506993.28
Interquartile range (IQR)4220.135

Descriptive statistics

Standard deviation14056.118
Coefficient of variation (CV)1.8398307
Kurtosis565.88347
Mean7639.8971
Median Absolute Deviation (MAD)1700.765
Skewness19.300351
Sum30590148
Variance1.9757444 × 108
MonotonicityNot monotonic
2023-12-12T08:02:51.445475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3500.0 7
 
0.2%
3000.0 6
 
0.1%
2700.0 5
 
0.1%
5500.0 4
 
0.1%
2500.0 4
 
0.1%
6000.0 3
 
0.1%
3744.0 3
 
0.1%
2437.0 3
 
0.1%
3781.0 3
 
0.1%
4000.0 3
 
0.1%
Other values (3847) 3963
99.0%
ValueCountFrequency (%)
2.4 1
< 0.1%
15.0 1
< 0.1%
110.25 1
< 0.1%
116.0 1
< 0.1%
190.0 1
< 0.1%
195.98 1
< 0.1%
242.0 1
< 0.1%
297.46 1
< 0.1%
327.01 1
< 0.1%
334.57 1
< 0.1%
ValueCountFrequency (%)
506995.68 1
< 0.1%
387620.68 1
< 0.1%
252668.84 1
< 0.1%
167192.0 1
< 0.1%
163302.0 1
< 0.1%
116633.0 1
< 0.1%
115022.0 1
< 0.1%
107115.87 1
< 0.1%
102273.83 1
< 0.1%
94728.0 1
< 0.1%

지하
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.3%
Missing145
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean1.16766
Minimum0
Maximum12
Zeros297
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:51.541530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.78749361
Coefficient of variation (CV)0.67442029
Kurtosis27.769329
Mean1.16766
Median Absolute Deviation (MAD)0
Skewness3.7509122
Sum4506
Variance0.62014618
MonotonicityNot monotonic
2023-12-12T08:02:51.635203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 2944
73.5%
2 440
 
11.0%
0 297
 
7.4%
3 104
 
2.6%
4 38
 
0.9%
6 15
 
0.4%
5 15
 
0.4%
7 2
 
< 0.1%
8 2
 
< 0.1%
12 1
 
< 0.1%
(Missing) 145
 
3.6%
ValueCountFrequency (%)
0 297
 
7.4%
1 2944
73.5%
2 440
 
11.0%
3 104
 
2.6%
4 38
 
0.9%
5 15
 
0.4%
6 15
 
0.4%
7 2
 
< 0.1%
8 2
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
11 1
 
< 0.1%
8 2
 
< 0.1%
7 2
 
< 0.1%
6 15
 
0.4%
5 15
 
0.4%
4 38
 
0.9%
3 104
 
2.6%
2 440
 
11.0%
1 2944
73.5%

지상
Real number (ℝ)

Distinct26
Distinct (%)0.7%
Missing5
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean4.5993998
Minimum0
Maximum28
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:51.731915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q13
median4
Q35
95-th percentile9
Maximum28
Range28
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.569798
Coefficient of variation (CV)0.55872463
Kurtosis13.931618
Mean4.5993998
Median Absolute Deviation (MAD)1
Skewness3.0527299
Sum18393
Variance6.6038616
MonotonicityNot monotonic
2023-12-12T08:02:51.823634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
4 1153
28.8%
3 1008
25.2%
5 744
18.6%
2 296
 
7.4%
6 263
 
6.6%
7 146
 
3.6%
8 94
 
2.3%
10 64
 
1.6%
9 63
 
1.6%
1 44
 
1.1%
Other values (16) 124
 
3.1%
ValueCountFrequency (%)
0 3
 
0.1%
1 44
 
1.1%
2 296
 
7.4%
3 1008
25.2%
4 1153
28.8%
5 744
18.6%
6 263
 
6.6%
7 146
 
3.6%
8 94
 
2.3%
9 63
 
1.6%
ValueCountFrequency (%)
28 1
 
< 0.1%
27 1
 
< 0.1%
23 1
 
< 0.1%
22 1
 
< 0.1%
21 5
0.1%
20 9
0.2%
19 4
 
0.1%
18 11
0.3%
17 3
 
0.1%
16 9
0.2%

사용승인연도
Date

Distinct2839
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
Minimum1926-09-05 00:00:00
Maximum2022-12-12 00:00:00
2023-12-12T08:02:51.920674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:52.046113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

연간 단위면적당 1차 에너지 소비량 3개년 평균
Text

Distinct2836
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
2023-12-12T08:02:52.340950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.766983
Min length1

Characters and Unicode

Total characters19087
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2178 ?
Unique (%)54.4%

Sample

1st row미제출
2nd row33.9
3rd row20.43
4th row16.81
5th row32.39
ValueCountFrequency (%)
미제출 243
 
6.1%
0 29
 
0.7%
18.31 12
 
0.3%
34.67 9
 
0.2%
27.38 7
 
0.2%
47.37 7
 
0.2%
24.65 6
 
0.1%
24.71 6
 
0.1%
19.14 6
 
0.1%
78.96 6
 
0.1%
Other values (2826) 3673
91.7%
2023-12-12T08:02:52.748348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3699
19.4%
1 2018
10.6%
2 2011
10.5%
3 1934
10.1%
4 1564
8.2%
5 1406
 
7.4%
6 1314
 
6.9%
8 1257
 
6.6%
7 1176
 
6.2%
9 1153
 
6.0%
Other values (5) 1555
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14629
76.6%
Other Punctuation 3729
 
19.5%
Other Letter 729
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2018
13.8%
2 2011
13.7%
3 1934
13.2%
4 1564
10.7%
5 1406
9.6%
6 1314
9.0%
8 1257
8.6%
7 1176
8.0%
9 1153
7.9%
0 796
 
5.4%
Other Letter
ValueCountFrequency (%)
미 243
33.3%
제 243
33.3%
출 243
33.3%
Other Punctuation
ValueCountFrequency (%)
. 3699
99.2%
, 30
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 18358
96.2%
Hangul 729
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3699
20.1%
1 2018
11.0%
2 2011
11.0%
3 1934
10.5%
4 1564
8.5%
5 1406
 
7.7%
6 1314
 
7.2%
8 1257
 
6.8%
7 1176
 
6.4%
9 1153
 
6.3%
Other values (2) 826
 
4.5%
Hangul
ValueCountFrequency (%)
미 243
33.3%
제 243
33.3%
출 243
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18358
96.2%
Hangul 729
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3699
20.1%
1 2018
11.0%
2 2011
11.0%
3 1934
10.5%
4 1564
8.5%
5 1406
 
7.7%
6 1314
 
7.2%
8 1257
 
6.8%
7 1176
 
6.4%
9 1153
 
6.3%
Other values (2) 826
 
4.5%
Hangul
ValueCountFrequency (%)
미 243
33.3%
제 243
33.3%
출 243
33.3%

연간 단위면적당 1차 에너지 소비량 3개년 평균 중간값
Real number (ℝ)

Distinct67
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.665697
Minimum13.09
Maximum70.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:52.868510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13.09
5-th percentile22.73
Q128.85
median29.59
Q336.59
95-th percentile52.91
Maximum70.89
Range57.8
Interquartile range (IQR)7.74

Descriptive statistics

Standard deviation9.0035332
Coefficient of variation (CV)0.27562655
Kurtosis4.0256237
Mean32.665697
Median Absolute Deviation (MAD)4.35
Skewness1.6830637
Sum130793.45
Variance81.063609
MonotonicityNot monotonic
2023-12-12T08:02:53.196597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.59 400
 
10.0%
29.59 387
 
9.7%
28.93 351
 
8.8%
37.27 344
 
8.6%
25.24 228
 
5.7%
35.89 225
 
5.6%
22.73 193
 
4.8%
28.85 176
 
4.4%
29.18 160
 
4.0%
33.36 151
 
3.8%
Other values (57) 1389
34.7%
ValueCountFrequency (%)
13.09 17
0.4%
14.51 10
0.2%
17.12 5
 
0.1%
17.2 1
 
< 0.1%
17.59 1
 
< 0.1%
18.31 22
0.5%
18.39 4
 
0.1%
18.78 3
 
0.1%
19.88 6
 
0.1%
20.94 10
0.2%
ValueCountFrequency (%)
70.89 5
 
0.1%
68.12 45
1.1%
66.62 26
0.6%
64.52 6
 
0.1%
60.12 27
0.7%
58.45 1
 
< 0.1%
58.34 15
 
0.4%
58.31 3
 
0.1%
55.69 18
 
0.4%
55.58 22
0.5%

간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 3개년 평균
Real number (ℝ)

SKEWED  ZEROS 

Distinct3745
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1679632
Minimum0
Maximum369.92951
Zeros256
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:53.304249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.1118939
median1.3294556
Q31.6963474
95-th percentile2.7027509
Maximum369.92951
Range369.92951
Interquartile range (IQR)0.58445347

Descriptive statistics

Standard deviation10.549514
Coefficient of variation (CV)4.8660944
Kurtosis764.46983
Mean2.1679632
Median Absolute Deviation (MAD)0.28451502
Skewness24.605904
Sum8680.5248
Variance111.29224
MonotonicityNot monotonic
2023-12-12T08:02:53.421976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 256
 
6.4%
1.833359125 3
 
0.1%
0.658948061 2
 
< 0.1%
0.66135921 2
 
< 0.1%
369.9295089 1
 
< 0.1%
1.23077499 1
 
< 0.1%
1.295851451 1
 
< 0.1%
0.023290854 1
 
< 0.1%
2.276196079 1
 
< 0.1%
1.435623481 1
 
< 0.1%
Other values (3735) 3735
93.3%
ValueCountFrequency (%)
0.0 256
6.4%
0.00636572 1
 
< 0.1%
0.006551153 1
 
< 0.1%
0.006993539 1
 
< 0.1%
0.009376788 1
 
< 0.1%
0.009719863 1
 
< 0.1%
0.010107462 1
 
< 0.1%
0.010108582 1
 
< 0.1%
0.010477454 1
 
< 0.1%
0.01076092 1
 
< 0.1%
ValueCountFrequency (%)
369.9295089 1
< 0.1%
365.7736816 1
< 0.1%
169.7344349 1
< 0.1%
163.0794731 1
< 0.1%
122.9132102 1
< 0.1%
102.6583315 1
< 0.1%
100.6522792 1
< 0.1%
96.90670117 1
< 0.1%
88.41107673 1
< 0.1%
85.36453993 1
< 0.1%

간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 2개년 평균
Real number (ℝ)

SKEWED  ZEROS 

Distinct3671
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0424061
Minimum0
Maximum869.1714
Zeros326
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:53.549113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.1013459
median1.3161937
Q31.6905321
95-th percentile2.6552316
Maximum869.1714
Range869.1714
Interquartile range (IQR)0.58918623

Descriptive statistics

Standard deviation16.940815
Coefficient of variation (CV)8.294538
Kurtosis1992.9022
Mean2.0424061
Median Absolute Deviation (MAD)0.28515099
Skewness42.455034
Sum8177.7942
Variance286.99123
MonotonicityNot monotonic
2023-12-12T08:02:53.668481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 326
 
8.1%
1.771312473 3
 
0.1%
1.379918495 2
 
< 0.1%
1.493717117 2
 
< 0.1%
0.746965283 2
 
< 0.1%
1.185952933 2
 
< 0.1%
0.695553741 2
 
< 0.1%
1.128343285 2
 
< 0.1%
1.940756031 1
 
< 0.1%
1.467620541 1
 
< 0.1%
Other values (3661) 3661
91.4%
ValueCountFrequency (%)
0.0 326
8.1%
0.003334227 1
 
< 0.1%
0.003901046 1
 
< 0.1%
0.004253147 1
 
< 0.1%
0.00426508 1
 
< 0.1%
0.004304035 1
 
< 0.1%
0.004345102 1
 
< 0.1%
0.005601563 1
 
< 0.1%
0.009854352 1
 
< 0.1%
0.01076092 1
 
< 0.1%
ValueCountFrequency (%)
869.1714008 1
< 0.1%
550.9737931 1
< 0.1%
151.5434505 1
< 0.1%
94.72926302 1
< 0.1%
93.4255903 1
< 0.1%
88.65289457 1
< 0.1%
84.68376818 1
< 0.1%
83.34619776 1
< 0.1%
76.00922096 1
< 0.1%
72.84073129 1
< 0.1%

간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 1개년 평균
Real number (ℝ)

SKEWED  ZEROS 

Distinct3618
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6111967
Minimum0
Maximum387.08225
Zeros375
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:53.780895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.06269
median1.2970846
Q31.7002131
95-th percentile2.8375772
Maximum387.08225
Range387.08225
Interquartile range (IQR)0.63752313

Descriptive statistics

Standard deviation6.8993002
Coefficient of variation (CV)4.2820967
Kurtosis2482.7096
Mean1.6111967
Median Absolute Deviation (MAD)0.30555603
Skewness46.567426
Sum6451.2317
Variance47.600343
MonotonicityNot monotonic
2023-12-12T08:02:53.906802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 375
 
9.4%
1.272482511 3
 
0.1%
1.6396716 3
 
0.1%
1.0 3
 
0.1%
1.137248649 2
 
< 0.1%
1.473366122 2
 
< 0.1%
1.445024864 2
 
< 0.1%
1.256072188 2
 
< 0.1%
1.431586177 2
 
< 0.1%
0.933818595 2
 
< 0.1%
Other values (3608) 3608
90.1%
ValueCountFrequency (%)
0.0 375
9.4%
0.004806283 1
 
< 0.1%
0.011183924 1
 
< 0.1%
0.014464428 1
 
< 0.1%
0.021790072 1
 
< 0.1%
0.027031228 1
 
< 0.1%
0.040983452 1
 
< 0.1%
0.054677276 1
 
< 0.1%
0.056265822 1
 
< 0.1%
0.176903261 1
 
< 0.1%
ValueCountFrequency (%)
387.0822509 1
< 0.1%
132.6186874 1
< 0.1%
97.07640852 1
< 0.1%
80.41908114 1
< 0.1%
64.59547689 1
< 0.1%
30.42041805 1
< 0.1%
26.59346622 1
< 0.1%
16.21031212 1
< 0.1%
14.17853902 1
< 0.1%
13.67877107 1
< 0.1%

전기 (KWH)
Real number (ℝ)

SKEWED  ZEROS 

Distinct3681
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean847128.74
Minimum0
Maximum8.17146 × 108
Zeros268
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:54.032917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q173194.25
median134690
Q3260778.75
95-th percentile824498.25
Maximum8.17146 × 108
Range8.17146 × 108
Interquartile range (IQR)187584.5

Descriptive statistics

Standard deviation15452010
Coefficient of variation (CV)18.24045
Kurtosis2095.8509
Mean847128.74
Median Absolute Deviation (MAD)77436.5
Skewness42.860968
Sum3.3919035 × 109
Variance2.3876461 × 1014
MonotonicityNot monotonic
2023-12-12T08:02:54.160480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 268
 
6.7%
31155.83333 6
 
0.1%
67320.0 4
 
0.1%
64000.0 3
 
0.1%
665460.0 2
 
< 0.1%
69071.0 2
 
< 0.1%
54529.0 2
 
< 0.1%
155239.3067 2
 
< 0.1%
186000.0 2
 
< 0.1%
184871.0 2
 
< 0.1%
Other values (3671) 3711
92.7%
ValueCountFrequency (%)
0.0 268
6.7%
3.74917 1
 
< 0.1%
89.364 1
 
< 0.1%
117.0 1
 
< 0.1%
120.278 1
 
< 0.1%
139.195 1
 
< 0.1%
199.586 1
 
< 0.1%
212.12033 1
 
< 0.1%
274.0 1
 
< 0.1%
346.067 1
 
< 0.1%
ValueCountFrequency (%)
817146000.0 1
< 0.1%
426622722.0 1
< 0.1%
148505376.0 1
< 0.1%
127221200.0 1
< 0.1%
121578104.0 1
< 0.1%
112036262.0 1
< 0.1%
101254497.0 1
< 0.1%
99416136.0 1
< 0.1%
88398500.0 1
< 0.1%
53609225.0 1
< 0.1%

가스 (KWH)
Real number (ℝ)

SKEWED  ZEROS 

Distinct2163
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2295524.4
Minimum0
Maximum6.4623524 × 109
Zeros1795
Zeros (%)44.8%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:54.300473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median43349.124
Q3518410.58
95-th percentile2497985.7
Maximum6.4623524 × 109
Range6.4623524 × 109
Interquartile range (IQR)518410.58

Descriptive statistics

Standard deviation1.0215705 × 108
Coefficient of variation (CV)44.502709
Kurtosis3997.7099
Mean2295524.4
Median Absolute Deviation (MAD)43349.124
Skewness63.202899
Sum9.1912797 × 109
Variance1.0436064 × 1016
MonotonicityNot monotonic
2023-12-12T08:02:54.452077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1795
44.8%
180651.6 4
 
0.1%
1124525.0 3
 
0.1%
285603.8 3
 
0.1%
187614.7 2
 
< 0.1%
512176.85 2
 
< 0.1%
460576.0 2
 
< 0.1%
1384334.3 2
 
< 0.1%
889315.2 2
 
< 0.1%
675809.7 2
 
< 0.1%
Other values (2153) 2187
54.6%
ValueCountFrequency (%)
0.0 1795
44.8%
1.0 1
 
< 0.1%
33.592 1
 
< 0.1%
38.9 1
 
< 0.1%
56.09 1
 
< 0.1%
76.81972 1
 
< 0.1%
88.2424 1
 
< 0.1%
106.484 1
 
< 0.1%
197.0 1
 
< 0.1%
255.918 1
 
< 0.1%
ValueCountFrequency (%)
6462352393.0 1
< 0.1%
64632225.52 1
< 0.1%
61059070.08 1
< 0.1%
54912134.7 1
< 0.1%
46520653.4 1
< 0.1%
43521358.9 1
< 0.1%
41010908.5 1
< 0.1%
34127748.0 2
< 0.1%
33306218.9 1
< 0.1%
32526079.4 1
< 0.1%

유류 (KWH)
Real number (ℝ)

SKEWED  ZEROS 

Distinct223
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110767.13
Minimum0
Maximum3.6013601 × 108
Zeros3780
Zeros (%)94.4%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:54.572431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile181.825
Maximum3.6013601 × 108
Range3.6013601 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5698121.9
Coefficient of variation (CV)51.442355
Kurtosis3984.2243
Mean110767.13
Median Absolute Deviation (MAD)0
Skewness63.0463
Sum4.4351157 × 108
Variance3.2468593 × 1013
MonotonicityNot monotonic
2023-12-12T08:02:54.690807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3780
94.4%
202243.842 2
 
< 0.1%
72927.0 2
 
< 0.1%
61020.0 1
 
< 0.1%
55.33 1
 
< 0.1%
182.5 1
 
< 0.1%
1492.31 1
 
< 0.1%
105700.0 1
 
< 0.1%
15300.0 1
 
< 0.1%
131.91 1
 
< 0.1%
Other values (213) 213
 
5.3%
ValueCountFrequency (%)
0.0 3780
94.4%
0.2 1
 
< 0.1%
25.04759 1
 
< 0.1%
42.0 1
 
< 0.1%
42.72227 1
 
< 0.1%
46.4 1
 
< 0.1%
53.0 1
 
< 0.1%
55.33 1
 
< 0.1%
59.61596 1
 
< 0.1%
59.73597 1
 
< 0.1%
ValueCountFrequency (%)
360136010.0 1
< 0.1%
10666546.0 1
< 0.1%
10564825.0 1
< 0.1%
6105887.0 1
< 0.1%
3591090.0 1
< 0.1%
2695000.0 1
< 0.1%
2647625.6 1
< 0.1%
2646100.0 1
< 0.1%
1596000.0 1
< 0.1%
1423558.0 1
< 0.1%

기타 (KWH)
Real number (ℝ)

SKEWED  ZEROS 

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1038.4063
Minimum0
Maximum2400098.4
Zeros3994
Zeros (%)99.8%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2023-12-12T08:02:54.793277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2400098.4
Range2400098.4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation45618.883
Coefficient of variation (CV)43.931633
Kurtosis2288.2132
Mean1038.4063
Median Absolute Deviation (MAD)0
Skewness47.118007
Sum4157778.7
Variance2.0810825 × 109
MonotonicityNot monotonic
2023-12-12T08:02:54.897823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 3994
99.8%
4590.0 1
 
< 0.1%
1608.0 1
 
< 0.1%
2223.9 1
 
< 0.1%
6989.4 1
 
< 0.1%
3334.0 1
 
< 0.1%
120.0 1
 
< 0.1%
2400098.4 1
 
< 0.1%
1599998.4 1
 
< 0.1%
20932.2 1
 
< 0.1%
ValueCountFrequency (%)
0.0 3994
99.8%
120.0 1
 
< 0.1%
1608.0 1
 
< 0.1%
2223.9 1
 
< 0.1%
3334.0 1
 
< 0.1%
4590.0 1
 
< 0.1%
6989.4 1
 
< 0.1%
20932.2 1
 
< 0.1%
117884.4 1
 
< 0.1%
1599998.4 1
 
< 0.1%
ValueCountFrequency (%)
2400098.4 1
< 0.1%
1599998.4 1
< 0.1%
117884.4 1
< 0.1%
20932.2 1
< 0.1%
6989.4 1
< 0.1%
4590.0 1
< 0.1%
3334.0 1
< 0.1%
2223.9 1
< 0.1%
1608.0 1
< 0.1%
120.0 1
< 0.1%

Sample

지역용도면적기관유형코드번호기관명건물명소재지연면적냉난방면적지하지상사용승인연도연간 단위면적당 1차 에너지 소비량 3개년 평균연간 단위면적당 1차 에너지 소비량 3개년 평균 중간값간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 3개년 평균간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 2개년 평균간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 1개년 평균전기 (KWH)가스 (KWH)유류 (KWH)기타 (KWH)
0중부1지역문화 및 집회시설3,000㎡이상~5,000㎡미만광역 및 지방자치단체1011-0003강원도 원주시원주역사박물관강원도 원주시 봉산동 836-13060.572312.0121999-12-23미제출21.441.9943151.713121.7470260.0362236.80.00.0
1중부1지역문화 및 집회시설3,000㎡이상~5,000㎡미만광역 및 지방자치단체1011-0008경기도 동두천시자유수호박물관경기도 동두천시 상봉암동 162-103331.813162.0142001-12-2433.921.441.7345971.9009612.014257116510.00.00.00.0
2중부1지역문화 및 집회시설3,000㎡이상~5,000㎡미만광역 및 지방자치단체1011-0022강원도 평창군평창문화예술회관강원도 평창군 평창읍 종부리 596-44168.173558.6121999-09-2020.4321.441.2563531.1066431.0752881733.00.00.00.0
3중부1지역문화 및 집회시설3,000㎡이상~5,000㎡미만광역 및 지방자치단체1011-0027경기도 연천군연천군문화체육센터 가동경기도 연천군 5734496.054496.05132001-07-2916.8121.4456.2830691.0190951.84620984973.00.00.00.0
4중부1지역문화 및 집회시설3,000㎡이상~5,000㎡미만중앙행정기관 및 소속기관1011-0031산림청산림박물관경기도 포천시 소흘읍 직동리 51-7 국립수목원4798.284439.75121986-10-3032.3921.442.1000922.2930182.562821130200.00.00.00.0
5중부1지역문화 및 집회시설3,000㎡이상~5,000㎡미만지방공사 및 공단1011-0032가평군시설관리공단문화예술회관경기도 가평군 가평읍 대곡리 3374801.224801.22131998-06-059.3521.441.6199481.5466251.61849450471.00.00.00.0
6중부1지역문화 및 집회시설3,000㎡이상~5,000㎡미만광역 및 지방자치단체1011-0055강원도 양양군오산리선사유적박물관강원도 양양군 손양면 오산리 513197.253197.25112005-09-2521.4421.4430.1018484.4945324.84849948756.00.00.00.0
7중부1지역문화 및 집회시설3,000㎡이상~5,000㎡미만광역 및 지방자치단체1011-100경상북도 봉화군청량산박물관, 인물역사관, 농경문화전시관경상북도 봉화군 0(명호면 관창리 1726-6번지, 청량산박물관,인물역사관, 농경문화전시관 )3061.03061.0032001-07-2818.2321.442.2934131.1656270.062722.00.00.00.0
8중부1지역문화 및 집회시설3,000㎡이상~5,000㎡미만중앙행정기관 및 소속기관1011-57산림청열대식물경기도 포천시 광릉수목원로 415(소흘읍 직동리 51-10번지, 열대식물자원연구센터 )3833.73004.0112008-08-0190.7521.441.5961671.4297431.41138690680.00.00.00.0
9중부1지역문화 및 집회시설3,000㎡이상~5,000㎡미만광역 및 지방자치단체1011-65경기도 동두천시평생학습관경기도 동두천시 중앙로 110-18(지행동 722-1번지, 아름다운문화센터 )3716.383716.38132007-10-3024.8621.441.4524221.4351191.42671884725.0183685.80.00.0
지역용도면적기관유형코드번호기관명건물명소재지연면적냉난방면적지하지상사용승인연도연간 단위면적당 1차 에너지 소비량 3개년 평균연간 단위면적당 1차 에너지 소비량 3개년 평균 중간값간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 3개년 평균간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 2개년 평균간절기 대비 소비량 비율[(냉방월 +난방월)/간절기월] 1개년 평균전기 (KWH)가스 (KWH)유류 (KWH)기타 (KWH)
3994제주도업무시설5,000㎡이상~10,000㎡미만광역 및 지방자치단체4062-0001제주특별자치도제주특별자치도(제1청사 본관)제주특별자치도 제주시 연동 312-18101.494952.92141994-02-2171.6339.21.1275621.1284251.13702398804.00.00.00.0
3995제주도업무시설5,000㎡이상~10,000㎡미만교육청4062-0002제주특별자치도교육청제주도교육청제주특별자치도 제주시 연동 311-468937.848602.94141979-08-1823.2439.21.1204361.1645461.196872224726.00.00.00.0
3996제주도업무시설5,000㎡이상~10,000㎡미만광역 및 지방자치단체4062-0003제주특별자치도제주특별자치도(제1청사 별관)제주특별자치도 제주시 연동 312-19686.266685.48142002-01-2463.4539.21.1276491.128321.137042476815.00.00.00.0
3997제주도업무시설5,000㎡이상~10,000㎡미만중앙행정기관 및 소속기관4062-0006제주지방해양경찰청제주해양경찰서 본관제주특별자치도 제주시 건입동 9085103.03613.28151998-08-1229.5539.21.1527421.1575131.147866120005.00.00.00.0
3998제주도업무시설5,000㎡이상~10,000㎡미만광역 및 지방자치단체4062-0013제주특별자치도인재개발원 본관제주특별자치도 제주시 아라동 368-205436.113696.61131993-05-1735.9339.21.2908421.2404661.307957149294.00.00.00.0
3999제주도업무시설5,000㎡이상~10,000㎡미만중앙행정기관 및 소속기관4062-14제주특별자치도경찰청제주서부경찰서제주특별자치도 제주시 애조로 215(애월읍 상귀리 416번지, 제1호 )5775.85775.8142007-12-2042.4639.21.3774711.4458351.227662268534.00.00.00.0
4000제주도업무시설10,000㎡이상중앙행정기관 및 소속기관4063-0001제주지방우정청제주우편집중국제주특별자치도 제주시 노형동 70710688.737986.92132000-01-2417.1318.390.9462390.8225430.877962121918.0289299.30.00.0
4001제주도업무시설10,000㎡이상중앙행정기관 및 소속기관4063-0002제주지방검찰청제주지방검찰청제주특별자치도 제주시 이도이동 950-1 제주지방검찰청11134.929431.91161999-11-2816.5618.392.9178922.5761562.504908133113.00.00.00.0
4002제주도업무시설10,000㎡이상광역 및 지방자치단체4063-0004제주특별자치도 서귀포시서귀포시1청사 본관제주특별자치도 서귀포시 서홍동 440-115284.8210720.51251999-12-1026.4618.391.5717491.7576071.825573318830.650.00.00.0
4003제주도업무시설10,000㎡이상광역 및 지방자치단체4063-0005제주특별자치도 서귀포시서귀포시청 제2청사제주특별자치도 서귀포시 법환동 73110155.767319.02141994-03-2419.6418.391.5043651.4692451.537649158193.390.00.00.0