Overview

Dataset statistics

Number of variables75
Number of observations500
Missing cells6000
Missing cells (%)16.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory320.4 KiB
Average record size in memory656.3 B

Variable types

Text10
Categorical28
Numeric33
Unsupported4

Dataset

Description샘플 데이터
Author국토교통부(open.eais.go.kr)
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=28

Alerts

블록 has constant value ""Constant
새주소_지상지하_코드 has constant value ""Constant
친환경_건축물_인증점수 has constant value ""Constant
지능형_건축물_인증점수 has constant value ""Constant
대장_구분_코드 is highly imbalanced (64.9%)Imbalance
대장_구분_코드_명 is highly imbalanced (65.7%)Imbalance
대장_종류_코드 is highly imbalanced (69.7%)Imbalance
대장_종류_코드_명 is highly imbalanced (55.0%)Imbalance
대지_구분_코드 is highly imbalanced (90.8%)Imbalance
주_부속_구분_코드 is highly imbalanced (57.7%)Imbalance
주_부속_구분_코드_명 is highly imbalanced (68.9%)Imbalance
지하_층_수 is highly imbalanced (64.0%)Imbalance
승용_승강기_수 is highly imbalanced (90.3%)Imbalance
비상용_승강기_수 is highly imbalanced (93.3%)Imbalance
부속_건축물_수 is highly imbalanced (69.1%)Imbalance
옥내_기계식_대수(대) is highly imbalanced (96.9%)Imbalance
옥내_기계식_면적(㎡) is highly imbalanced (97.4%)Imbalance
옥외_기계식_대수(대) is highly imbalanced (97.4%)Imbalance
옥외_기계식_면적(㎡) is highly imbalanced (97.9%)Imbalance
허가번호_기관_코드_명 is highly imbalanced (71.0%)Imbalance
허가번호_구분_코드_명 is highly imbalanced (64.6%)Imbalance
호_수(호) is highly imbalanced (93.9%)Imbalance
에너지_절감률 is highly imbalanced (97.9%)Imbalance
EPI_점수 is highly imbalanced (97.9%)Imbalance
도로명_대지_위치 has 90 (18.0%) missing valuesMissing
건물_명 has 434 (86.8%) missing valuesMissing
특수지_명 has 498 (99.6%) missing valuesMissing
블록 has 499 (99.8%) missing valuesMissing
로트 has 500 (100.0%) missing valuesMissing
새주소_도로_코드 has 89 (17.8%) missing valuesMissing
새주소_법정동_코드 has 95 (19.0%) missing valuesMissing
새주소_본_번 has 70 (14.0%) missing valuesMissing
새주소_부_번 has 85 (17.0%) missing valuesMissing
동_명칭 has 422 (84.4%) missing valuesMissing
기타_지붕 has 10 (2.0%) missing valuesMissing
허가_일 has 197 (39.4%) missing valuesMissing
착공_일 has 299 (59.8%) missing valuesMissing
사용승인_일 has 48 (9.6%) missing valuesMissing
허가번호_년 has 379 (75.8%) missing valuesMissing
허가번호_기관_코드 has 385 (77.0%) missing valuesMissing
허가번호_구분_코드 has 391 (78.2%) missing valuesMissing
에너지_효율등급 has 500 (100.0%) missing valuesMissing
친환경_건축물_등급 has 500 (100.0%) missing valuesMissing
지능형_건축물_등급 has 500 (100.0%) missing valuesMissing
부속_건축물_면적(㎡) is highly skewed (γ1 = 22.27874296)Skewed
옥내_자주식_면적(㎡) is highly skewed (γ1 = 21.31595851)Skewed
관리_건축물대장_PK has unique valuesUnique
대지_위치 has unique valuesUnique
로트 is an unsupported type, check if it needs cleaning or further analysisUnsupported
에너지_효율등급 is an unsupported type, check if it needs cleaning or further analysisUnsupported
친환경_건축물_등급 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지능형_건축물_등급 is an unsupported type, check if it needs cleaning or further analysisUnsupported
has 6 (1.2%) zerosZeros
has 151 (30.2%) zerosZeros
외필지_수 has 439 (87.8%) zerosZeros
새주소_본_번 has 12 (2.4%) zerosZeros
새주소_부_번 has 220 (44.0%) zerosZeros
대지_면적(㎡) has 247 (49.4%) zerosZeros
건축_면적(㎡) has 48 (9.6%) zerosZeros
건폐_율(%) has 260 (52.0%) zerosZeros
용적_률_산정_연면적(㎡) has 54 (10.8%) zerosZeros
용적_률(%) has 255 (51.0%) zerosZeros
세대_수(세대) has 450 (90.0%) zerosZeros
가구_수(가구) has 211 (42.2%) zerosZeros
높이(m) has 272 (54.4%) zerosZeros
지상_층_수 has 11 (2.2%) zerosZeros
부속_건축물_면적(㎡) has 436 (87.2%) zerosZeros
총_동_연면적(㎡) has 51 (10.2%) zerosZeros
옥내_자주식_대수(대) has 471 (94.2%) zerosZeros
옥내_자주식_면적(㎡) has 478 (95.6%) zerosZeros
옥외_자주식_대수(대) has 409 (81.8%) zerosZeros
옥외_자주식_면적(㎡) has 427 (85.4%) zerosZeros

Reproduction

Analysis started2023-12-10 15:05:20.580814
Analysis finished2023-12-10 15:05:22.974555
Duration2.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:05:23.275808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length11.524
Min length9

Characters and Unicode

Total characters5762
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

Unique500 ?
Unique (%)100.0%

Sample

1st row46890-16026
2nd row42230-3945
3rd row41820-16564
4th row47130-9552
5th row31110-13718
ValueCountFrequency (%)
46890-16026 1
 
0.2%
48240-8849 1
 
0.2%
48310-7424 1
 
0.2%
11230-30327 1
 
0.2%
11305-19463 1
 
0.2%
11545-11986 1
 
0.2%
46830-8351 1
 
0.2%
11200-7684 1
 
0.2%
47730-5873 1
 
0.2%
41500-100224731 1
 
0.2%
Other values (490) 490
98.0%
2023-12-11T00:05:24.108354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 958
16.6%
0 874
15.2%
4 679
11.8%
2 594
10.3%
- 500
8.7%
3 454
7.9%
7 422
7.3%
8 356
 
6.2%
6 337
 
5.8%
5 319
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5262
91.3%
Dash Punctuation 500
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 958
18.2%
0 874
16.6%
4 679
12.9%
2 594
11.3%
3 454
8.6%
7 422
8.0%
8 356
 
6.8%
6 337
 
6.4%
5 319
 
6.1%
9 269
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5762
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 958
16.6%
0 874
15.2%
4 679
11.8%
2 594
10.3%
- 500
8.7%
3 454
7.9%
7 422
7.3%
8 356
 
6.2%
6 337
 
5.8%
5 319
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5762
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 958
16.6%
0 874
15.2%
4 679
11.8%
2 594
10.3%
- 500
8.7%
3 454
7.9%
7 422
7.3%
8 356
 
6.2%
6 337
 
5.8%
5 319
 
5.5%

대장_구분_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
467 
2
 
33

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 467
93.4%
2 33
 
6.6%

Length

2023-12-11T00:05:24.371932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:24.558674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 467
93.4%
2 33
 
6.6%

대장_구분_코드_명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
일반
468 
집합
 
32

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row일반
3rd row집합
4th row일반
5th row일반

Common Values

ValueCountFrequency (%)
일반 468
93.6%
집합 32
 
6.4%

Length

2023-12-11T00:05:24.790388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:25.072752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 468
93.6%
집합 32
 
6.4%

대장_종류_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
473 
3
 
27

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 473
94.6%
3 27
 
5.4%

Length

2023-12-11T00:05:25.282605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:25.483050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 473
94.6%
3 27
 
5.4%

대장_종류_코드_명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
일반건축물
453 
표제부
47 

Length

Max length5
Median length5
Mean length4.812
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반건축물 453
90.6%
표제부 47
 
9.4%

Length

2023-12-11T00:05:25.725186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:25.946859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반건축물 453
90.6%
표제부 47
 
9.4%

대지_위치
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:05:26.445775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length22.086
Min length16

Characters and Unicode

Total characters11043
Distinct characters266
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st row충청북도 옥천군 이원면 건진리 150번지
2nd row경기도 포천시 이동면 연곡리 597-3번지
3rd row인천광역시 서구 공촌동 313-3번지
4th row인천광역시 중구 전동 26번지
5th row경기도 화성시 향남읍 동오리 32-4번지
ValueCountFrequency (%)
경기도 91
 
3.9%
경상북도 61
 
2.6%
전라남도 53
 
2.3%
서울특별시 40
 
1.7%
전라북도 37
 
1.6%
충청남도 36
 
1.6%
경상남도 33
 
1.4%
강원도 26
 
1.1%
충청북도 24
 
1.0%
부산광역시 23
 
1.0%
Other values (1351) 1880
81.6%
2023-12-11T00:05:27.462786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1808
 
16.4%
517
 
4.7%
500
 
4.5%
406
 
3.7%
384
 
3.5%
1 376
 
3.4%
- 344
 
3.1%
329
 
3.0%
256
 
2.3%
2 249
 
2.3%
Other values (256) 5874
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6922
62.7%
Decimal Number 1969
 
17.8%
Space Separator 1808
 
16.4%
Dash Punctuation 344
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
517
 
7.5%
500
 
7.2%
406
 
5.9%
384
 
5.5%
329
 
4.8%
256
 
3.7%
203
 
2.9%
197
 
2.8%
184
 
2.7%
171
 
2.5%
Other values (244) 3775
54.5%
Decimal Number
ValueCountFrequency (%)
1 376
19.1%
2 249
12.6%
3 241
12.2%
6 202
10.3%
5 188
9.5%
4 166
8.4%
0 145
 
7.4%
8 142
 
7.2%
7 141
 
7.2%
9 119
 
6.0%
Space Separator
ValueCountFrequency (%)
1808
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 344
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6922
62.7%
Common 4121
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
517
 
7.5%
500
 
7.2%
406
 
5.9%
384
 
5.5%
329
 
4.8%
256
 
3.7%
203
 
2.9%
197
 
2.8%
184
 
2.7%
171
 
2.5%
Other values (244) 3775
54.5%
Common
ValueCountFrequency (%)
1808
43.9%
1 376
 
9.1%
- 344
 
8.3%
2 249
 
6.0%
3 241
 
5.8%
6 202
 
4.9%
5 188
 
4.6%
4 166
 
4.0%
0 145
 
3.5%
8 142
 
3.4%
Other values (2) 260
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6922
62.7%
ASCII 4121
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1808
43.9%
1 376
 
9.1%
- 344
 
8.3%
2 249
 
6.0%
3 241
 
5.8%
6 202
 
4.9%
5 188
 
4.6%
4 166
 
4.0%
0 145
 
3.5%
8 142
 
3.4%
Other values (2) 260
 
6.3%
Hangul
ValueCountFrequency (%)
517
 
7.5%
500
 
7.2%
406
 
5.9%
384
 
5.5%
329
 
4.8%
256
 
3.7%
203
 
2.9%
197
 
2.8%
184
 
2.7%
171
 
2.5%
Other values (244) 3775
54.5%
Distinct410
Distinct (%)100.0%
Missing90
Missing (%)18.0%
Memory size4.0 KiB
2023-12-11T00:05:28.035814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length18.985366
Min length13

Characters and Unicode

Total characters7784
Distinct characters270
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique410 ?
Unique (%)100.0%

Sample

1st row충청남도 아산시 남부로350번길 7
2nd row강원도 철원군 명성로125번길 7
3rd row서울특별시 성북구 보문로30가길 17-16
4th row전라남도 나주시 장산길 8-2
5th row경상북도 포항시 남구 대잠길69번길 12-4
ValueCountFrequency (%)
경기도 60
 
3.5%
경상북도 50
 
3.0%
경상남도 48
 
2.8%
서울특별시 43
 
2.5%
전라남도 34
 
2.0%
충청남도 26
 
1.5%
강원도 26
 
1.5%
부산광역시 22
 
1.3%
전라북도 20
 
1.2%
충청북도 19
 
1.1%
Other values (927) 1343
79.4%
2023-12-11T00:05:28.861819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1281
 
16.5%
1 352
 
4.5%
326
 
4.2%
303
 
3.9%
292
 
3.8%
260
 
3.3%
2 249
 
3.2%
- 198
 
2.5%
193
 
2.5%
173
 
2.2%
Other values (260) 4157
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4716
60.6%
Decimal Number 1588
 
20.4%
Space Separator 1281
 
16.5%
Dash Punctuation 198
 
2.5%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
326
 
6.9%
303
 
6.4%
292
 
6.2%
260
 
5.5%
193
 
4.1%
173
 
3.7%
160
 
3.4%
120
 
2.5%
120
 
2.5%
101
 
2.1%
Other values (247) 2668
56.6%
Decimal Number
ValueCountFrequency (%)
1 352
22.2%
2 249
15.7%
3 169
10.6%
4 158
9.9%
5 141
8.9%
6 118
 
7.4%
8 107
 
6.7%
7 104
 
6.5%
9 98
 
6.2%
0 92
 
5.8%
Space Separator
ValueCountFrequency (%)
1281
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 198
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4716
60.6%
Common 3068
39.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
326
 
6.9%
303
 
6.4%
292
 
6.2%
260
 
5.5%
193
 
4.1%
173
 
3.7%
160
 
3.4%
120
 
2.5%
120
 
2.5%
101
 
2.1%
Other values (247) 2668
56.6%
Common
ValueCountFrequency (%)
1281
41.8%
1 352
 
11.5%
2 249
 
8.1%
- 198
 
6.5%
3 169
 
5.5%
4 158
 
5.1%
5 141
 
4.6%
6 118
 
3.8%
8 107
 
3.5%
7 104
 
3.4%
Other values (3) 191
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4716
60.6%
ASCII 3067
39.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1281
41.8%
1 352
 
11.5%
2 249
 
8.1%
- 198
 
6.5%
3 169
 
5.5%
4 158
 
5.2%
5 141
 
4.6%
6 118
 
3.8%
8 107
 
3.5%
7 104
 
3.4%
Other values (2) 190
 
6.2%
Hangul
ValueCountFrequency (%)
326
 
6.9%
303
 
6.4%
292
 
6.2%
260
 
5.5%
193
 
4.1%
173
 
3.7%
160
 
3.4%
120
 
2.5%
120
 
2.5%
101
 
2.1%
Other values (247) 2668
56.6%
None
ValueCountFrequency (%)
· 1
100.0%

건물_명
Text

MISSING 

Distinct64
Distinct (%)97.0%
Missing434
Missing (%)86.8%
Memory size4.0 KiB
2023-12-11T00:05:29.286638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length6.8636364
Min length1

Characters and Unicode

Total characters453
Distinct characters193
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)93.9%

Sample

1st row주택
2nd row대황교동 가스충전소
3rd row가동
4th row해송고등학교
5th row매화(2)아파트
ValueCountFrequency (%)
주택 2
 
2.2%
아파트 2
 
2.2%
b동 2
 
2.2%
예일주택 1
 
1.1%
신장동 1
 
1.1%
동강재래시장 1
 
1.1%
중앙하이츠 1
 
1.1%
공장동 1
 
1.1%
관광휴게시설 1
 
1.1%
한국민속촌 1
 
1.1%
Other values (76) 76
85.4%
2023-12-11T00:05:30.005552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
 
5.1%
17
 
3.8%
14
 
3.1%
10
 
2.2%
10
 
2.2%
10
 
2.2%
10
 
2.2%
8
 
1.8%
8
 
1.8%
2 7
 
1.5%
Other values (183) 336
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 369
81.5%
Decimal Number 25
 
5.5%
Space Separator 23
 
5.1%
Uppercase Letter 14
 
3.1%
Lowercase Letter 9
 
2.0%
Open Punctuation 4
 
0.9%
Close Punctuation 4
 
0.9%
Dash Punctuation 3
 
0.7%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17
 
4.6%
14
 
3.8%
10
 
2.7%
10
 
2.7%
10
 
2.7%
10
 
2.7%
8
 
2.2%
8
 
2.2%
7
 
1.9%
7
 
1.9%
Other values (151) 268
72.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
14.3%
B 2
14.3%
P 1
7.1%
M 1
7.1%
D 1
7.1%
L 1
7.1%
N 1
7.1%
A 1
7.1%
K 1
7.1%
X 1
7.1%
Other values (2) 2
14.3%
Decimal Number
ValueCountFrequency (%)
2 7
28.0%
1 5
20.0%
0 3
12.0%
6 3
12.0%
4 2
 
8.0%
7 2
 
8.0%
5 2
 
8.0%
3 1
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
22.2%
l 2
22.2%
e 2
22.2%
n 1
11.1%
c 1
11.1%
o 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 368
81.2%
Common 61
 
13.5%
Latin 23
 
5.1%
Han 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17
 
4.6%
14
 
3.8%
10
 
2.7%
10
 
2.7%
10
 
2.7%
10
 
2.7%
8
 
2.2%
8
 
2.2%
7
 
1.9%
7
 
1.9%
Other values (150) 267
72.6%
Latin
ValueCountFrequency (%)
a 2
 
8.7%
l 2
 
8.7%
e 2
 
8.7%
C 2
 
8.7%
B 2
 
8.7%
n 1
 
4.3%
P 1
 
4.3%
M 1
 
4.3%
D 1
 
4.3%
c 1
 
4.3%
Other values (8) 8
34.8%
Common
ValueCountFrequency (%)
23
37.7%
2 7
 
11.5%
1 5
 
8.2%
( 4
 
6.6%
) 4
 
6.6%
0 3
 
4.9%
- 3
 
4.9%
6 3
 
4.9%
4 2
 
3.3%
7 2
 
3.3%
Other values (4) 5
 
8.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 368
81.2%
ASCII 84
 
18.5%
CJK 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23
27.4%
2 7
 
8.3%
1 5
 
6.0%
( 4
 
4.8%
) 4
 
4.8%
0 3
 
3.6%
- 3
 
3.6%
6 3
 
3.6%
a 2
 
2.4%
l 2
 
2.4%
Other values (22) 28
33.3%
Hangul
ValueCountFrequency (%)
17
 
4.6%
14
 
3.8%
10
 
2.7%
10
 
2.7%
10
 
2.7%
10
 
2.7%
8
 
2.2%
8
 
2.2%
7
 
1.9%
7
 
1.9%
Other values (150) 267
72.6%
CJK
ValueCountFrequency (%)
1
100.0%

시군구_코드
Real number (ℝ)

Distinct209
Distinct (%)41.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39119.504
Minimum11110
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:30.266037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11560
Q130890
median42820
Q346830
95-th percentile48740
Maximum50130
Range39020
Interquartile range (IQR)15940

Descriptive statistics

Standard deviation10443.263
Coefficient of variation (CV)0.26695796
Kurtosis1.0306374
Mean39119.504
Median Absolute Deviation (MAD)4085
Skewness-1.3897008
Sum19559752
Variance1.0906174 × 108
MonotonicityNot monotonic
2023-12-11T00:05:30.523638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50110 8
 
1.6%
41480 7
 
1.4%
47170 7
 
1.4%
47250 7
 
1.4%
28710 6
 
1.2%
48880 6
 
1.2%
28260 6
 
1.2%
31140 6
 
1.2%
44270 5
 
1.0%
29170 5
 
1.0%
Other values (199) 437
87.4%
ValueCountFrequency (%)
11110 1
 
0.2%
11140 4
0.8%
11170 2
0.4%
11215 1
 
0.2%
11230 1
 
0.2%
11260 1
 
0.2%
11290 2
0.4%
11305 1
 
0.2%
11320 1
 
0.2%
11350 2
0.4%
ValueCountFrequency (%)
50130 2
 
0.4%
50110 8
1.6%
48880 6
1.2%
48870 1
 
0.2%
48860 3
 
0.6%
48850 1
 
0.2%
48840 1
 
0.2%
48820 2
 
0.4%
48740 3
 
0.6%
48330 1
 
0.2%

법정동_코드
Real number (ℝ)

Distinct190
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22316.272
Minimum10100
Maximum44022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:30.838016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10100
5-th percentile10100
Q110800
median25024
Q333024
95-th percentile38094.75
Maximum44022
Range33922
Interquartile range (IQR)22224

Descriptive statistics

Standard deviation11228.869
Coefficient of variation (CV)0.50316959
Kurtosis-1.6300364
Mean22316.272
Median Absolute Deviation (MAD)12324
Skewness0.1799164
Sum11158136
Variance1.2608751 × 108
MonotonicityNot monotonic
2023-12-11T00:05:31.595057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10100 34
 
6.8%
10200 20
 
4.0%
10300 17
 
3.4%
10500 14
 
2.8%
10600 14
 
2.8%
10900 13
 
2.6%
10400 13
 
2.6%
10700 12
 
2.4%
10800 8
 
1.6%
11000 8
 
1.6%
Other values (180) 347
69.4%
ValueCountFrequency (%)
10100 34
6.8%
10200 20
4.0%
10300 17
3.4%
10400 13
 
2.6%
10500 14
2.8%
10600 14
2.8%
10700 12
 
2.4%
10800 8
 
1.6%
10900 13
 
2.6%
11000 8
 
1.6%
ValueCountFrequency (%)
44022 2
0.4%
43030 1
0.2%
43025 1
0.2%
43024 1
0.2%
42033 1
0.2%
42025 1
0.2%
42022 1
0.2%
41023 1
0.2%
41021 1
0.2%
40031 1
0.2%

대지_구분_코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
491 
1
 
6
2
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 491
98.2%
1 6
 
1.2%
2 3
 
0.6%

Length

2023-12-11T00:05:32.023742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:32.208524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 491
98.2%
1 6
 
1.2%
2 3
 
0.6%


Real number (ℝ)

ZEROS 

Distinct408
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean499.206
Minimum0
Maximum4268
Zeros6
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:32.435011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q1158.75
median410.5
Q3683.75
95-th percentile1394.6
Maximum4268
Range4268
Interquartile range (IQR)525

Descriptive statistics

Standard deviation483.20158
Coefficient of variation (CV)0.96794025
Kurtosis12.591684
Mean499.206
Median Absolute Deviation (MAD)261
Skewness2.5846417
Sum249603
Variance233483.77
MonotonicityNot monotonic
2023-12-11T00:05:32.718170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
1.2%
12 4
 
0.8%
58 3
 
0.6%
465 3
 
0.6%
307 3
 
0.6%
483 3
 
0.6%
162 3
 
0.6%
63 3
 
0.6%
501 3
 
0.6%
507 3
 
0.6%
Other values (398) 466
93.2%
ValueCountFrequency (%)
0 6
1.2%
1 2
 
0.4%
2 1
 
0.2%
3 1
 
0.2%
4 2
 
0.4%
5 1
 
0.2%
8 2
 
0.4%
9 1
 
0.2%
10 2
 
0.4%
12 4
0.8%
ValueCountFrequency (%)
4268 1
0.2%
3815 1
0.2%
2529 1
0.2%
2344 1
0.2%
2257 1
0.2%
2133 1
0.2%
2120 1
0.2%
2086 1
0.2%
2022 1
0.2%
1700 1
0.2%


Real number (ℝ)

ZEROS 

Distinct67
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.014
Minimum0
Maximum379
Zeros151
Zeros (%)30.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:32.983690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q39
95-th percentile58.1
Maximum379
Range379
Interquartile range (IQR)9

Descriptive statistics

Standard deviation43.175851
Coefficient of variation (CV)3.0809085
Kurtosis37.490265
Mean14.014
Median Absolute Deviation (MAD)2
Skewness5.8151694
Sum7007
Variance1864.1541
MonotonicityNot monotonic
2023-12-11T00:05:33.279794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 151
30.2%
1 64
12.8%
2 46
 
9.2%
3 30
 
6.0%
4 21
 
4.2%
5 20
 
4.0%
7 15
 
3.0%
6 12
 
2.4%
9 11
 
2.2%
12 10
 
2.0%
Other values (57) 120
24.0%
ValueCountFrequency (%)
0 151
30.2%
1 64
12.8%
2 46
 
9.2%
3 30
 
6.0%
4 21
 
4.2%
5 20
 
4.0%
6 12
 
2.4%
7 15
 
3.0%
8 6
 
1.2%
9 11
 
2.2%
ValueCountFrequency (%)
379 1
0.2%
367 1
0.2%
320 1
0.2%
307 1
0.2%
287 1
0.2%
280 1
0.2%
267 1
0.2%
245 1
0.2%
181 1
0.2%
161 1
0.2%

특수지_명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing498
Missing (%)99.6%
Memory size4.0 KiB
2023-12-11T00:05:33.440922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters2
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

Unique2 ?
Unique (%)100.0%

Sample

1st row0
2nd row]
ValueCountFrequency (%)
0 1
50.0%
1
50.0%
2023-12-11T00:05:33.801676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1
50.0%
] 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
50.0%
Close Punctuation 1
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1
50.0%
] 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1
50.0%
] 1
50.0%

블록
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing499
Missing (%)99.8%
Memory size4.0 KiB
2023-12-11T00:05:34.023278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
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

Unique1 ?
Unique (%)100.0%

Sample

1st row6-2블록
ValueCountFrequency (%)
6-2블록 1
100.0%
2023-12-11T00:05:34.456401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1
20.0%
- 1
20.0%
2 1
20.0%
1
20.0%
1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
40.0%
Other Letter 2
40.0%
Dash Punctuation 1
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1
50.0%
2 1
50.0%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3
60.0%
Hangul 2
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1
33.3%
- 1
33.3%
2 1
33.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
60.0%
Hangul 2
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1
33.3%
- 1
33.3%
2 1
33.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

로트
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500
Missing (%)100.0%
Memory size4.5 KiB

외필지_수
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.244
Minimum0
Maximum18
Zeros439
Zeros (%)87.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:34.665601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.127389
Coefficient of variation (CV)4.6204468
Kurtosis137.1667
Mean0.244
Median Absolute Deviation (MAD)0
Skewness10.23424
Sum122
Variance1.271006
MonotonicityNot monotonic
2023-12-11T00:05:34.838489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 439
87.8%
1 43
 
8.6%
3 7
 
1.4%
2 6
 
1.2%
9 1
 
0.2%
18 1
 
0.2%
4 1
 
0.2%
7 1
 
0.2%
8 1
 
0.2%
ValueCountFrequency (%)
0 439
87.8%
1 43
 
8.6%
2 6
 
1.2%
3 7
 
1.4%
4 1
 
0.2%
7 1
 
0.2%
8 1
 
0.2%
9 1
 
0.2%
18 1
 
0.2%
ValueCountFrequency (%)
18 1
 
0.2%
9 1
 
0.2%
8 1
 
0.2%
7 1
 
0.2%
4 1
 
0.2%
3 7
 
1.4%
2 6
 
1.2%
1 43
 
8.6%
0 439
87.8%

새주소_도로_코드
Real number (ℝ)

MISSING 

Distinct411
Distinct (%)100.0%
Missing89
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean3.8366786 × 1011
Minimum1.111041 × 1011
Maximum5.0130485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:35.103484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111041 × 1011
5-th percentile1.1395413 × 1011
Q13.014043 × 1011
median4.2170322 × 1011
Q34.6775398 × 1011
95-th percentile4.8330481 × 1011
Maximum5.0130485 × 1011
Range3.9020075 × 1011
Interquartile range (IQR)1.6634968 × 1011

Descriptive statistics

Standard deviation1.131449 × 1011
Coefficient of variation (CV)0.29490325
Kurtosis0.56519043
Mean3.8366786 × 1011
Median Absolute Deviation (MAD)4.7401485 × 1010
Skewness-1.2982667
Sum1.5768749 × 1014
Variance1.2801768 × 1022
MonotonicityNot monotonic
2023-12-11T00:05:35.346671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
277104244415 1
 
0.2%
477304745523 1
 
0.2%
421703221022 1
 
0.2%
442104562196 1
 
0.2%
451904613153 1
 
0.2%
478203319009 1
 
0.2%
478504766230 1
 
0.2%
467803290019 1
 
0.2%
479204772111 1
 
0.2%
461104643107 1
 
0.2%
Other values (401) 401
80.2%
(Missing) 89
 
17.8%
ValueCountFrequency (%)
111104100112 1
0.2%
111104100126 1
0.2%
111104100208 1
0.2%
111104100270 1
0.2%
111404103296 1
0.2%
111404103377 1
0.2%
112154112071 1
0.2%
112304115115 1
0.2%
112604118098 1
0.2%
112903005035 1
0.2%
ValueCountFrequency (%)
501304850352 1
0.2%
501303350234 1
0.2%
501303350119 1
0.2%
501303349229 1
0.2%
501104848950 1
0.2%
501104847279 1
0.2%
501104847251 1
0.2%
501103349167 1
0.2%
488904844239 1
0.2%
488904844012 1
0.2%

새주소_법정동_코드
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)24.9%
Missing95
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean20839.889
Minimum10101
Maximum45001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:35.603202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10101
Q110601
median12701
Q333001
95-th percentile39802
Maximum45001
Range34900
Interquartile range (IQR)22400

Descriptive statistics

Standard deviation11468.668
Coefficient of variation (CV)0.5503229
Kurtosis-1.5048974
Mean20839.889
Median Absolute Deviation (MAD)2600
Skewness0.45476093
Sum8440155
Variance1.3153035 × 108
MonotonicityNot monotonic
2023-12-11T00:05:35.879385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10101 32
 
6.4%
25001 23
 
4.6%
10201 22
 
4.4%
10301 20
 
4.0%
34001 16
 
3.2%
32001 16
 
3.2%
31001 16
 
3.2%
35001 14
 
2.8%
10801 14
 
2.8%
36001 12
 
2.4%
Other values (91) 220
44.0%
(Missing) 95
19.0%
ValueCountFrequency (%)
10101 32
6.4%
10201 22
4.4%
10202 1
 
0.2%
10301 20
4.0%
10303 2
 
0.4%
10401 11
 
2.2%
10501 8
 
1.6%
10502 3
 
0.6%
10601 10
 
2.0%
10602 3
 
0.6%
ValueCountFrequency (%)
45001 1
 
0.2%
43003 1
 
0.2%
43001 2
 
0.4%
42001 4
0.8%
41001 2
 
0.4%
40002 2
 
0.4%
40001 9
1.8%
39006 1
 
0.2%
39001 5
1.0%
38001 5
1.0%

새주소_지상지하_코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-11T00:05:36.107225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:36.261666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

새주소_본_번
Real number (ℝ)

MISSING  ZEROS 

Distinct183
Distinct (%)42.6%
Missing70
Missing (%)14.0%
Infinite0
Infinite (%)0.0%
Mean139.59302
Minimum0
Maximum2979
Zeros12
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:36.469817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q115
median38.5
Q3112.75
95-th percentile656.8
Maximum2979
Range2979
Interquartile range (IQR)97.75

Descriptive statistics

Standard deviation306.04527
Coefficient of variation (CV)2.1924109
Kurtosis27.015075
Mean139.59302
Median Absolute Deviation (MAD)28.5
Skewness4.6019689
Sum60025
Variance93663.706
MonotonicityNot monotonic
2023-12-11T00:05:36.777611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 13
 
2.6%
0 12
 
2.4%
3 11
 
2.2%
23 10
 
2.0%
12 10
 
2.0%
13 9
 
1.8%
10 9
 
1.8%
31 8
 
1.6%
14 8
 
1.6%
38 7
 
1.4%
Other values (173) 333
66.6%
(Missing) 70
 
14.0%
ValueCountFrequency (%)
0 12
2.4%
1 3
 
0.6%
2 2
 
0.4%
3 11
2.2%
4 3
 
0.6%
5 13
2.6%
6 7
1.4%
7 6
1.2%
8 3
 
0.6%
9 5
 
1.0%
ValueCountFrequency (%)
2979 1
0.2%
1905 1
0.2%
1826 1
0.2%
1791 1
0.2%
1567 1
0.2%
1547 1
0.2%
1461 1
0.2%
1260 1
0.2%
1236 1
0.2%
1207 1
0.2%

새주소_부_번
Real number (ℝ)

MISSING  ZEROS 

Distinct48
Distinct (%)11.6%
Missing85
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean7.226506
Minimum0
Maximum321
Zeros220
Zeros (%)44.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:37.088836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q38
95-th percentile31.6
Maximum321
Range321
Interquartile range (IQR)8

Descriptive statistics

Standard deviation22.041283
Coefficient of variation (CV)3.0500608
Kurtosis124.46387
Mean7.226506
Median Absolute Deviation (MAD)0
Skewness9.8801326
Sum2999
Variance485.81814
MonotonicityNot monotonic
2023-12-11T00:05:37.390055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 220
44.0%
1 32
 
6.4%
6 13
 
2.6%
8 13
 
2.6%
7 11
 
2.2%
2 11
 
2.2%
5 9
 
1.8%
15 9
 
1.8%
9 8
 
1.6%
12 8
 
1.6%
Other values (38) 81
 
16.2%
(Missing) 85
 
17.0%
ValueCountFrequency (%)
0 220
44.0%
1 32
 
6.4%
2 11
 
2.2%
3 4
 
0.8%
4 7
 
1.4%
5 9
 
1.8%
6 13
 
2.6%
7 11
 
2.2%
8 13
 
2.6%
9 8
 
1.6%
ValueCountFrequency (%)
321 1
0.2%
231 1
0.2%
77 1
0.2%
67 1
0.2%
60 1
0.2%
59 1
0.2%
55 1
0.2%
49 1
0.2%
46 1
0.2%
44 1
0.2%

동_명칭
Text

MISSING 

Distinct46
Distinct (%)59.0%
Missing422
Missing (%)84.4%
Memory size4.0 KiB
2023-12-11T00:05:37.939216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length3
Min length1

Characters and Unicode

Total characters234
Distinct characters53
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)43.6%

Sample

1st row2
2nd row40호
3rd rowB동
4th rowD동
5th row101동
ValueCountFrequency (%)
2동 7
 
9.0%
나동 6
 
7.7%
가동 5
 
6.4%
주건축물제1동 4
 
5.1%
다동 4
 
5.1%
제1호 3
 
3.8%
3동 3
 
3.8%
1동 3
 
3.8%
제1동 3
 
3.8%
라동 2
 
2.6%
Other values (36) 38
48.7%
2023-12-11T00:05:38.614139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61
26.1%
1 25
 
10.7%
2 13
 
5.6%
12
 
5.1%
11
 
4.7%
0 10
 
4.3%
7
 
3.0%
7
 
3.0%
3 7
 
3.0%
7
 
3.0%
Other values (43) 74
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 160
68.4%
Decimal Number 64
 
27.4%
Uppercase Letter 4
 
1.7%
Open Punctuation 2
 
0.9%
Close Punctuation 2
 
0.9%
Other Punctuation 1
 
0.4%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
61
38.1%
12
 
7.5%
11
 
6.9%
7
 
4.4%
7
 
4.4%
7
 
4.4%
7
 
4.4%
6
 
3.8%
4
 
2.5%
4
 
2.5%
Other values (28) 34
21.2%
Decimal Number
ValueCountFrequency (%)
1 25
39.1%
2 13
20.3%
0 10
 
15.6%
3 7
 
10.9%
4 4
 
6.2%
7 2
 
3.1%
9 2
 
3.1%
6 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
C 1
25.0%
D 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 160
68.4%
Common 70
29.9%
Latin 4
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
61
38.1%
12
 
7.5%
11
 
6.9%
7
 
4.4%
7
 
4.4%
7
 
4.4%
7
 
4.4%
6
 
3.8%
4
 
2.5%
4
 
2.5%
Other values (28) 34
21.2%
Common
ValueCountFrequency (%)
1 25
35.7%
2 13
18.6%
0 10
 
14.3%
3 7
 
10.0%
4 4
 
5.7%
7 2
 
2.9%
( 2
 
2.9%
9 2
 
2.9%
) 2
 
2.9%
6 1
 
1.4%
Other values (2) 2
 
2.9%
Latin
ValueCountFrequency (%)
B 2
50.0%
C 1
25.0%
D 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 160
68.4%
ASCII 74
31.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
61
38.1%
12
 
7.5%
11
 
6.9%
7
 
4.4%
7
 
4.4%
7
 
4.4%
7
 
4.4%
6
 
3.8%
4
 
2.5%
4
 
2.5%
Other values (28) 34
21.2%
ASCII
ValueCountFrequency (%)
1 25
33.8%
2 13
17.6%
0 10
 
13.5%
3 7
 
9.5%
4 4
 
5.4%
7 2
 
2.7%
( 2
 
2.7%
B 2
 
2.7%
9 2
 
2.7%
) 2
 
2.7%
Other values (5) 5
 
6.8%

주_부속_구분_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
457 
1
 
43

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 457
91.4%
1 43
 
8.6%

Length

2023-12-11T00:05:38.879235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:39.074220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 457
91.4%
1 43
 
8.6%

주_부속_구분_코드_명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
주건축물
472 
부속건축물
 
28

Length

Max length5
Median length4
Mean length4.056
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주건축물 472
94.4%
부속건축물 28
 
5.6%

Length

2023-12-11T00:05:39.305865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:39.509315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주건축물 472
94.4%
부속건축물 28
 
5.6%

대지_면적(㎡)
Real number (ℝ)

ZEROS 

Distinct229
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean415.1101
Minimum0
Maximum26192
Zeros247
Zeros (%)49.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:39.806072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median63.15
Q3360.775
95-th percentile1224.9
Maximum26192
Range26192
Interquartile range (IQR)360.775

Descriptive statistics

Standard deviation1600.3051
Coefficient of variation (CV)3.8551341
Kurtosis155.10466
Mean415.1101
Median Absolute Deviation (MAD)63.15
Skewness11.189016
Sum207555.05
Variance2560976.4
MonotonicityNot monotonic
2023-12-11T00:05:40.119155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 247
49.4%
660.0 5
 
1.0%
159.0 3
 
0.6%
330.0 3
 
0.6%
659.0 3
 
0.6%
265.0 2
 
0.4%
200.0 2
 
0.4%
611.0 2
 
0.4%
482.0 2
 
0.4%
182.0 2
 
0.4%
Other values (219) 229
45.8%
ValueCountFrequency (%)
0.0 247
49.4%
39.7 1
 
0.2%
40.0 1
 
0.2%
63.0 1
 
0.2%
63.3 1
 
0.2%
73.0 1
 
0.2%
78.7 1
 
0.2%
91.0 1
 
0.2%
92.34 1
 
0.2%
92.55 1
 
0.2%
ValueCountFrequency (%)
26192.0 1
0.2%
15348.0 1
0.2%
11359.0 1
0.2%
7097.0 1
0.2%
6796.0 1
0.2%
5967.0 1
0.2%
5338.1 1
0.2%
4073.0 1
0.2%
3873.0 1
0.2%
3511.4 1
0.2%

건축_면적(㎡)
Real number (ℝ)

ZEROS 

Distinct435
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140.98416
Minimum0
Maximum2758.63
Zeros48
Zeros (%)9.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:40.381253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q150.33
median83.3
Q3138.23
95-th percentile470.103
Maximum2758.63
Range2758.63
Interquartile range (IQR)87.9

Descriptive statistics

Standard deviation225.68953
Coefficient of variation (CV)1.6008148
Kurtosis47.105547
Mean140.98416
Median Absolute Deviation (MAD)41.02
Skewness5.664558
Sum70492.078
Variance50935.763
MonotonicityNot monotonic
2023-12-11T00:05:40.652262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 48
 
9.6%
99.0 3
 
0.6%
28.0 2
 
0.4%
88.0 2
 
0.4%
192.0 2
 
0.4%
79.2 2
 
0.4%
36.36 2
 
0.4%
23.0 2
 
0.4%
198.0 2
 
0.4%
65.0 2
 
0.4%
Other values (425) 433
86.6%
ValueCountFrequency (%)
0.0 48
9.6%
2.0 1
 
0.2%
2.88 1
 
0.2%
4.2 1
 
0.2%
6.82 1
 
0.2%
7.56 1
 
0.2%
9.18 1
 
0.2%
11.261 1
 
0.2%
12.0 1
 
0.2%
12.42 1
 
0.2%
ValueCountFrequency (%)
2758.63 1
0.2%
1735.42 1
0.2%
1506.69 1
0.2%
1473.18 1
0.2%
1061.44 1
0.2%
1058.0 1
0.2%
1005.89 1
0.2%
962.98 1
0.2%
825.0 1
0.2%
793.7 1
0.2%

건폐_율(%)
Real number (ℝ)

ZEROS 

Distinct232
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.929
Minimum0
Maximum89.46
Zeros260
Zeros (%)52.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:40.947978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q333.9975
95-th percentile59.8505
Maximum89.46
Range89.46
Interquartile range (IQR)33.9975

Descriptive statistics

Standard deviation23.628339
Coefficient of variation (CV)1.3178838
Kurtosis-0.31025403
Mean17.929
Median Absolute Deviation (MAD)0
Skewness1.0241748
Sum8964.5001
Variance558.2984
MonotonicityNot monotonic
2023-12-11T00:05:41.683868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 260
52.0%
59.1 3
 
0.6%
52.65 2
 
0.4%
21.71 2
 
0.4%
59.63 2
 
0.4%
59.24 2
 
0.4%
15.78 2
 
0.4%
57.88 2
 
0.4%
59.7 2
 
0.4%
24.18 1
 
0.2%
Other values (222) 222
44.4%
ValueCountFrequency (%)
0.0 260
52.0%
2.35 1
 
0.2%
2.93 1
 
0.2%
2.9411674 1
 
0.2%
3.84 1
 
0.2%
4.71 1
 
0.2%
5.06 1
 
0.2%
5.31 1
 
0.2%
5.4 1
 
0.2%
5.46 1
 
0.2%
ValueCountFrequency (%)
89.46 1
0.2%
89.43 1
0.2%
89.14 1
0.2%
82.05 1
0.2%
79.78 1
0.2%
78.21 1
0.2%
77.15 1
0.2%
75.01 1
0.2%
69.03 1
0.2%
68.53 1
0.2%

연면적(㎡)
Real number (ℝ)

Distinct481
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean448.03957
Minimum0
Maximum20862.76
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:41.979458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20.8275
Q157.7975
median106.7
Q3242.305
95-th percentile1605.438
Maximum20862.76
Range20862.76
Interquartile range (IQR)184.5075

Descriptive statistics

Standard deviation1551.8099
Coefficient of variation (CV)3.4635555
Kurtosis84.097454
Mean448.03957
Median Absolute Deviation (MAD)67.85
Skewness8.2888895
Sum224019.79
Variance2408114.1
MonotonicityNot monotonic
2023-12-11T00:05:42.272366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48.0 4
 
0.8%
184.5 3
 
0.6%
52.89 2
 
0.4%
64.8 2
 
0.4%
192.0 2
 
0.4%
90.48 2
 
0.4%
99.0 2
 
0.4%
62.81 2
 
0.4%
10.2 2
 
0.4%
168.0 2
 
0.4%
Other values (471) 477
95.4%
ValueCountFrequency (%)
0.0 1
0.2%
0.81 1
0.2%
0.9 1
0.2%
0.99 1
0.2%
1.71 1
0.2%
2.4 1
0.2%
2.95 1
0.2%
3.0 1
0.2%
3.31 1
0.2%
5.06 1
0.2%
ValueCountFrequency (%)
20862.76 1
0.2%
13680.08 1
0.2%
12387.2282 1
0.2%
11716.08 1
0.2%
7797.46 1
0.2%
6671.16 1
0.2%
6243.9 1
0.2%
6184.38 1
0.2%
5628.0 1
0.2%
4589.66 1
0.2%

용적_률_산정_연면적(㎡)
Real number (ℝ)

ZEROS 

Distinct431
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean279.34162
Minimum0
Maximum14430.42
Zeros54
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:42.701109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q143.7025
median94.78
Q3197.0225
95-th percentile875.6025
Maximum14430.42
Range14430.42
Interquartile range (IQR)153.32

Descriptive statistics

Standard deviation888.00459
Coefficient of variation (CV)3.1789197
Kurtosis140.89103
Mean279.34162
Median Absolute Deviation (MAD)69.96
Skewness10.35834
Sum139670.81
Variance788552.15
MonotonicityNot monotonic
2023-12-11T00:05:43.011486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 54
 
10.8%
52.89 3
 
0.6%
93.8 2
 
0.4%
33.06 2
 
0.4%
49.0 2
 
0.4%
71.0 2
 
0.4%
40.0 2
 
0.4%
86.58 2
 
0.4%
150.0 2
 
0.4%
84.0 2
 
0.4%
Other values (421) 427
85.4%
ValueCountFrequency (%)
0.0 54
10.8%
1.87 1
 
0.2%
2.1 1
 
0.2%
5.57 1
 
0.2%
6.0 1
 
0.2%
6.25 1
 
0.2%
6.5 1
 
0.2%
6.6 1
 
0.2%
7.56 1
 
0.2%
9.9 1
 
0.2%
ValueCountFrequency (%)
14430.42 1
0.2%
7102.5 1
0.2%
5407.3 1
0.2%
4561.96 1
0.2%
4487.46 1
0.2%
4239.5 1
0.2%
3329.22 1
0.2%
2964.0 1
0.2%
2869.26 1
0.2%
2814.0 1
0.2%

용적_률(%)
Real number (ℝ)

ZEROS 

Distinct243
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.951493
Minimum0
Maximum358.91
Zeros255
Zeros (%)51.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:43.351776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q336.405
95-th percentile199.4935
Maximum358.91
Range358.91
Interquartile range (IQR)36.405

Descriptive statistics

Standard deviation70.762816
Coefficient of variation (CV)1.8166907
Kurtosis5.0052975
Mean38.951493
Median Absolute Deviation (MAD)0
Skewness2.2978532
Sum19475.746
Variance5007.3761
MonotonicityNot monotonic
2023-12-11T00:05:43.677839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 255
51.0%
3.28 2
 
0.4%
2.33 2
 
0.4%
14.09 2
 
0.4%
14.75 1
 
0.2%
6.15 1
 
0.2%
8.64 1
 
0.2%
59.79 1
 
0.2%
21.85 1
 
0.2%
30.49 1
 
0.2%
Other values (233) 233
46.6%
ValueCountFrequency (%)
0.0 255
51.0%
0.6 1
 
0.2%
1.14 1
 
0.2%
1.27 1
 
0.2%
1.35 1
 
0.2%
1.85 1
 
0.2%
2.01 1
 
0.2%
2.1039 1
 
0.2%
2.2 1
 
0.2%
2.33 2
 
0.4%
ValueCountFrequency (%)
358.91 1
0.2%
357.8 1
0.2%
351.61 1
0.2%
346.96 1
0.2%
327.51 1
0.2%
302.47 1
0.2%
299.33 1
0.2%
299.09 1
0.2%
290.92 1
0.2%
276.31 1
0.2%

구조_코드
Real number (ℝ)

Distinct14
Distinct (%)2.8%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean24.182731
Minimum10
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:43.943172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile11
Q111
median21
Q332
95-th percentile51
Maximum99
Range89
Interquartile range (IQR)21

Descriptive statistics

Standard deviation14.648145
Coefficient of variation (CV)0.60572749
Kurtosis1.7737113
Mean24.182731
Median Absolute Deviation (MAD)10
Skewness1.2461292
Sum12043
Variance214.56815
MonotonicityNot monotonic
2023-12-11T00:05:44.213969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
11 132
26.4%
21 111
22.2%
51 76
15.2%
12 65
13.0%
32 44
 
8.8%
31 43
 
8.6%
19 10
 
2.0%
33 10
 
2.0%
99 2
 
0.4%
50 1
 
0.2%
Other values (4) 4
 
0.8%
(Missing) 2
 
0.4%
ValueCountFrequency (%)
10 1
 
0.2%
11 132
26.4%
12 65
13.0%
13 1
 
0.2%
19 10
 
2.0%
21 111
22.2%
30 1
 
0.2%
31 43
 
8.6%
32 44
 
8.8%
33 10
 
2.0%
ValueCountFrequency (%)
99 2
 
0.4%
51 76
15.2%
50 1
 
0.2%
42 1
 
0.2%
33 10
 
2.0%
32 44
 
8.8%
31 43
 
8.6%
30 1
 
0.2%
21 111
22.2%
19 10
 
2.0%
Distinct13
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
철근콘크리트구조
125 
벽돌구조
113 
일반목구조
81 
블록구조
55 
일반철골구조
48 
Other values (8)
78 

Length

Max length11
Median length8
Mean length5.652
Min length3

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row벽돌구조
2nd row벽돌구조
3rd row철근콘크리트구조
4th row일반목구조
5th row철근콘크리트구조

Common Values

ValueCountFrequency (%)
철근콘크리트구조 125
25.0%
벽돌구조 113
22.6%
일반목구조 81
16.2%
블록구조 55
11.0%
일반철골구조 48
 
9.6%
경량철골구조 45
 
9.0%
강파이프구조 11
 
2.2%
기타조적구조 10
 
2.0%
조적구조 5
 
1.0%
기타강구조 3
 
0.6%
Other values (3) 4
 
0.8%

Length

2023-12-11T00:05:44.576172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철근콘크리트구조 125
25.0%
벽돌구조 113
22.6%
일반목구조 81
16.2%
블록구조 55
11.0%
일반철골구조 48
 
9.6%
경량철골구조 45
 
9.0%
강파이프구조 11
 
2.2%
기타조적구조 10
 
2.0%
조적구조 5
 
1.0%
기타강구조 3
 
0.6%
Other values (3) 4
 
0.8%
Distinct145
Distinct (%)29.1%
Missing2
Missing (%)0.4%
Memory size4.0 KiB
2023-12-11T00:05:45.023905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length5.2871486
Min length2

Characters and Unicode

Total characters2633
Distinct characters82
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

Unique106 ?
Unique (%)21.3%

Sample

1st row연와조
2nd row일반철골구조
3rd row목조
4th row벽돌구조
5th row블록구조
ValueCountFrequency (%)
목조 92
16.9%
철근콘크리트조 41
 
7.5%
철근콘크리트구조 39
 
7.2%
조적조 32
 
5.9%
일반철골구조 31
 
5.7%
연와조 31
 
5.7%
경량철골구조 22
 
4.0%
시멘트벽돌조 18
 
3.3%
벽돌조 14
 
2.6%
일반목구조 12
 
2.2%
Other values (106) 212
39.0%
2023-12-11T00:05:45.827234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
528
20.1%
204
 
7.7%
145
 
5.5%
138
 
5.2%
113
 
4.3%
109
 
4.1%
109
 
4.1%
109
 
4.1%
108
 
4.1%
90
 
3.4%
Other values (72) 980
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2497
94.8%
Other Punctuation 66
 
2.5%
Space Separator 46
 
1.7%
Uppercase Letter 9
 
0.3%
Open Punctuation 6
 
0.2%
Close Punctuation 6
 
0.2%
Decimal Number 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
528
21.1%
204
 
8.2%
145
 
5.8%
138
 
5.5%
113
 
4.5%
109
 
4.4%
109
 
4.4%
109
 
4.4%
108
 
4.3%
90
 
3.6%
Other values (58) 844
33.8%
Uppercase Letter
ValueCountFrequency (%)
R 3
33.3%
C 3
33.3%
B 1
 
11.1%
P 1
 
11.1%
E 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 55
83.3%
. 8
 
12.1%
/ 3
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2497
94.8%
Common 127
 
4.8%
Latin 9
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
528
21.1%
204
 
8.2%
145
 
5.8%
138
 
5.5%
113
 
4.5%
109
 
4.4%
109
 
4.4%
109
 
4.4%
108
 
4.3%
90
 
3.6%
Other values (58) 844
33.8%
Common
ValueCountFrequency (%)
, 55
43.3%
46
36.2%
. 8
 
6.3%
( 6
 
4.7%
) 6
 
4.7%
/ 3
 
2.4%
+ 1
 
0.8%
1 1
 
0.8%
2 1
 
0.8%
Latin
ValueCountFrequency (%)
R 3
33.3%
C 3
33.3%
B 1
 
11.1%
P 1
 
11.1%
E 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2497
94.8%
ASCII 136
 
5.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
528
21.1%
204
 
8.2%
145
 
5.8%
138
 
5.5%
113
 
4.5%
109
 
4.4%
109
 
4.4%
109
 
4.4%
108
 
4.3%
90
 
3.6%
Other values (58) 844
33.8%
ASCII
ValueCountFrequency (%)
, 55
40.4%
46
33.8%
. 8
 
5.9%
( 6
 
4.4%
) 6
 
4.4%
R 3
 
2.2%
C 3
 
2.2%
/ 3
 
2.2%
+ 1
 
0.7%
B 1
 
0.7%
Other values (4) 4
 
2.9%
Distinct21
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
01000
298 
04000
40 
03000
34 
21000
 
27
18000
 
25
Other values (16)
76 

Length

Max length5
Median length5
Mean length4.982
Min length4

Unique

Unique8 ?
Unique (%)1.6%

Sample

1st row01000
2nd row01000
3rd row01000
4th row02000
5th row01000

Common Values

ValueCountFrequency (%)
01000 298
59.6%
04000 40
 
8.0%
03000 34
 
6.8%
21000 27
 
5.4%
18000 25
 
5.0%
02000 25
 
5.0%
17000 20
 
4.0%
<NA> 9
 
1.8%
15000 4
 
0.8%
20000 3
 
0.6%
Other values (11) 15
 
3.0%

Length

2023-12-11T00:05:46.209459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
01000 298
59.6%
04000 40
 
8.0%
03000 34
 
6.8%
21000 27
 
5.4%
18000 25
 
5.0%
02000 25
 
5.0%
17000 20
 
4.0%
na 9
 
1.8%
15000 4
 
0.8%
06000 3
 
0.6%
Other values (11) 15
 
3.0%
Distinct17
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
단독주택
289 
제2종근린생활시설
39 
공장
34 
제1종근린생활시설
34 
창고시설
30 
Other values (12)
74 

Length

Max length10
Median length4
Mean length4.856
Min length2

Unique

Unique4 ?
Unique (%)0.8%

Sample

1st row단독주택
2nd row공동주택
3rd row단독주택
4th row단독주택
5th row공장

Common Values

ValueCountFrequency (%)
단독주택 289
57.8%
제2종근린생활시설 39
 
7.8%
공장 34
 
6.8%
제1종근린생활시설 34
 
6.8%
창고시설 30
 
6.0%
동.식물관련시설 27
 
5.4%
공동주택 27
 
5.4%
노유자시설 5
 
1.0%
업무시설 3
 
0.6%
교육연구시설 2
 
0.4%
Other values (7) 10
 
2.0%

Length

2023-12-11T00:05:46.501883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 289
57.8%
제2종근린생활시설 39
 
7.8%
공장 34
 
6.8%
제1종근린생활시설 34
 
6.8%
창고시설 30
 
6.0%
동.식물관련시설 27
 
5.4%
공동주택 27
 
5.4%
노유자시설 5
 
1.0%
업무시설 3
 
0.6%
교육연구시설 2
 
0.4%
Other values (7) 10
 
2.0%
Distinct137
Distinct (%)27.6%
Missing4
Missing (%)0.8%
Memory size4.0 KiB
2023-12-11T00:05:46.894720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length22
Mean length5.3064516
Min length2

Characters and Unicode

Total characters2632
Distinct characters132
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)21.0%

Sample

1st row배저장창고
2nd row지하주차장
3rd row주택
4th row주택
5th row주택
ValueCountFrequency (%)
주택 162
29.2%
단독주택 104
18.8%
근린생활시설 33
 
6.0%
창고시설 17
 
3.1%
공장 14
 
2.5%
제1종근린생활시설 13
 
2.3%
공동주택 11
 
2.0%
제2종근린생활시설 11
 
2.0%
창고 10
 
1.8%
동물및식물관련시설 8
 
1.4%
Other values (111) 171
30.9%
2023-12-11T00:05:47.612051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
358
 
13.6%
350
 
13.3%
144
 
5.5%
139
 
5.3%
129
 
4.9%
127
 
4.8%
76
 
2.9%
75
 
2.8%
75
 
2.8%
75
 
2.8%
Other values (122) 1084
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2333
88.6%
Other Punctuation 84
 
3.2%
Space Separator 62
 
2.4%
Decimal Number 61
 
2.3%
Open Punctuation 45
 
1.7%
Close Punctuation 45
 
1.7%
Dash Punctuation 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
358
15.3%
350
15.0%
144
 
6.2%
139
 
6.0%
129
 
5.5%
127
 
5.4%
76
 
3.3%
75
 
3.2%
75
 
3.2%
75
 
3.2%
Other values (103) 785
33.6%
Decimal Number
ValueCountFrequency (%)
2 20
32.8%
1 20
32.8%
3 6
 
9.8%
8 3
 
4.9%
4 3
 
4.9%
7 3
 
4.9%
6 3
 
4.9%
5 2
 
3.3%
9 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 69
82.1%
. 11
 
13.1%
/ 4
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 44
97.8%
[ 1
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 44
97.8%
] 1
 
2.2%
Space Separator
ValueCountFrequency (%)
62
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2333
88.6%
Common 299
 
11.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
358
15.3%
350
15.0%
144
 
6.2%
139
 
6.0%
129
 
5.5%
127
 
5.4%
76
 
3.3%
75
 
3.2%
75
 
3.2%
75
 
3.2%
Other values (103) 785
33.6%
Common
ValueCountFrequency (%)
, 69
23.1%
62
20.7%
( 44
14.7%
) 44
14.7%
2 20
 
6.7%
1 20
 
6.7%
. 11
 
3.7%
3 6
 
2.0%
/ 4
 
1.3%
8 3
 
1.0%
Other values (9) 16
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2333
88.6%
ASCII 298
 
11.3%
CJK Compat 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
358
15.3%
350
15.0%
144
 
6.2%
139
 
6.0%
129
 
5.5%
127
 
5.4%
76
 
3.3%
75
 
3.2%
75
 
3.2%
75
 
3.2%
Other values (103) 785
33.6%
ASCII
ValueCountFrequency (%)
, 69
23.2%
62
20.8%
( 44
14.8%
) 44
14.8%
2 20
 
6.7%
1 20
 
6.7%
. 11
 
3.7%
3 6
 
2.0%
/ 4
 
1.3%
8 3
 
1.0%
Other values (8) 15
 
5.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%

지붕_코드
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
10
220 
90
113 
20
85 
30
80 
<NA>
 
2

Length

Max length4
Median length2
Mean length2.008
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row10
3rd row10
4th row20
5th row20

Common Values

ValueCountFrequency (%)
10 220
44.0%
90 113
22.6%
20 85
 
17.0%
30 80
 
16.0%
<NA> 2
 
0.4%

Length

2023-12-11T00:05:47.917111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:48.174081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 220
44.0%
90 113
22.6%
20 85
 
17.0%
30 80
 
16.0%
na 2
 
0.4%
Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
(철근)콘크리트
219 
기타지붕
126 
슬레이트
83 
기와
71 
<NA>
 
1

Length

Max length8
Median length4
Mean length5.468
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row(철근)콘크리트
2nd row슬레이트
3rd row기타지붕
4th row기타지붕
5th row기타지붕

Common Values

ValueCountFrequency (%)
(철근)콘크리트 219
43.8%
기타지붕 126
25.2%
슬레이트 83
 
16.6%
기와 71
 
14.2%
<NA> 1
 
0.2%

Length

2023-12-11T00:05:48.466695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:48.671217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근)콘크리트 219
43.8%
기타지붕 126
25.2%
슬레이트 83
 
16.6%
기와 71
 
14.2%
na 1
 
0.2%

기타_지붕
Text

MISSING 

Distinct131
Distinct (%)26.7%
Missing10
Missing (%)2.0%
Memory size4.0 KiB
2023-12-11T00:05:48.951030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length4.3510204
Min length2

Characters and Unicode

Total characters2132
Distinct characters97
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)16.7%

Sample

1st row슬라브
2nd row기타지붕(글라스울판넬경사지붕)
3rd row기와
4th row슬라브
5th row슬래브
ValueCountFrequency (%)
스라브 84
16.5%
슬라브 40
 
7.8%
스레트 40
 
7.8%
철근)콘크리트 32
 
6.3%
기와 32
 
6.3%
평스라브 23
 
4.5%
스레이트 17
 
3.3%
판넬 13
 
2.5%
슬레이트 12
 
2.4%
샌드위치판넬 11
 
2.2%
Other values (114) 206
40.4%
2023-12-11T00:05:49.553931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
200
 
9.4%
185
 
8.7%
183
 
8.6%
144
 
6.8%
87
 
4.1%
83
 
3.9%
76
 
3.6%
72
 
3.4%
70
 
3.3%
54
 
2.5%
Other values (87) 978
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1994
93.5%
Close Punctuation 46
 
2.2%
Open Punctuation 46
 
2.2%
Other Punctuation 25
 
1.2%
Space Separator 20
 
0.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
200
 
10.0%
185
 
9.3%
183
 
9.2%
144
 
7.2%
87
 
4.4%
83
 
4.2%
76
 
3.8%
72
 
3.6%
70
 
3.5%
54
 
2.7%
Other values (81) 840
42.1%
Other Punctuation
ValueCountFrequency (%)
, 24
96.0%
. 1
 
4.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1994
93.5%
Common 138
 
6.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
200
 
10.0%
185
 
9.3%
183
 
9.2%
144
 
7.2%
87
 
4.4%
83
 
4.2%
76
 
3.8%
72
 
3.6%
70
 
3.5%
54
 
2.7%
Other values (81) 840
42.1%
Common
ValueCountFrequency (%)
) 46
33.3%
( 46
33.3%
, 24
17.4%
20
14.5%
- 1
 
0.7%
. 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1994
93.5%
ASCII 138
 
6.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
200
 
10.0%
185
 
9.3%
183
 
9.2%
144
 
7.2%
87
 
4.4%
83
 
4.2%
76
 
3.8%
72
 
3.6%
70
 
3.5%
54
 
2.7%
Other values (81) 840
42.1%
ASCII
ValueCountFrequency (%)
) 46
33.3%
( 46
33.3%
, 24
17.4%
20
14.5%
- 1
 
0.7%
. 1
 
0.7%

세대_수(세대)
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.724
Minimum0
Maximum210
Zeros450
Zeros (%)90.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:49.804031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5.1
Maximum210
Range210
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.092083
Coefficient of variation (CV)7.5940155
Kurtosis157.54143
Mean1.724
Median Absolute Deviation (MAD)0
Skewness11.761426
Sum862
Variance171.40263
MonotonicityNot monotonic
2023-12-11T00:05:50.030661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 450
90.0%
1 19
 
3.8%
8 8
 
1.6%
2 3
 
0.6%
7 2
 
0.4%
12 2
 
0.4%
10 2
 
0.4%
210 1
 
0.2%
84 1
 
0.2%
13 1
 
0.2%
Other values (11) 11
 
2.2%
ValueCountFrequency (%)
0 450
90.0%
1 19
 
3.8%
2 3
 
0.6%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
7 2
 
0.4%
8 8
 
1.6%
9 1
 
0.2%
10 2
 
0.4%
ValueCountFrequency (%)
210 1
0.2%
120 1
0.2%
119 1
0.2%
84 1
0.2%
60 1
0.2%
36 1
0.2%
23 1
0.2%
18 1
0.2%
13 1
0.2%
12 2
0.4%

가구_수(가구)
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.016
Minimum0
Maximum20
Zeros211
Zeros (%)42.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:50.357085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.1374943
Coefficient of variation (CV)2.1038329
Kurtosis36.522805
Mean1.016
Median Absolute Deviation (MAD)1
Skewness5.5195935
Sum508
Variance4.5688818
MonotonicityNot monotonic
2023-12-11T00:05:50.613149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 241
48.2%
0 211
42.2%
2 16
 
3.2%
3 8
 
1.6%
4 6
 
1.2%
11 4
 
0.8%
6 3
 
0.6%
7 2
 
0.4%
5 2
 
0.4%
15 1
 
0.2%
Other values (6) 6
 
1.2%
ValueCountFrequency (%)
0 211
42.2%
1 241
48.2%
2 16
 
3.2%
3 8
 
1.6%
4 6
 
1.2%
5 2
 
0.4%
6 3
 
0.6%
7 2
 
0.4%
8 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
20 1
 
0.2%
19 1
 
0.2%
17 1
 
0.2%
15 1
 
0.2%
12 1
 
0.2%
11 4
0.8%
10 1
 
0.2%
8 1
 
0.2%
7 2
0.4%
6 3
0.6%

높이(m)
Real number (ℝ)

ZEROS 

Distinct134
Distinct (%)26.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.63294
Minimum0
Maximum189.48
Zeros272
Zeros (%)54.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:50.905688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36.25
95-th percentile14.01
Maximum189.48
Range189.48
Interquartile range (IQR)6.25

Descriptive statistics

Standard deviation11.659324
Coefficient of variation (CV)2.5166145
Kurtosis133.73525
Mean4.63294
Median Absolute Deviation (MAD)0
Skewness9.6933326
Sum2316.47
Variance135.93983
MonotonicityNot monotonic
2023-12-11T00:05:51.187272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 272
54.4%
4.5 11
 
2.2%
4.0 9
 
1.8%
4.8 7
 
1.4%
6.0 6
 
1.2%
7.2 5
 
1.0%
5.5 5
 
1.0%
4.7 5
 
1.0%
4.4 4
 
0.8%
3.0 4
 
0.8%
Other values (124) 172
34.4%
ValueCountFrequency (%)
0.0 272
54.4%
2.4 1
 
0.2%
2.5 1
 
0.2%
3.0 4
 
0.8%
3.3 2
 
0.4%
3.4 2
 
0.4%
3.45 2
 
0.4%
3.5 4
 
0.8%
3.6 3
 
0.6%
3.63 1
 
0.2%
ValueCountFrequency (%)
189.48 1
0.2%
73.11 1
0.2%
71.0 1
0.2%
66.06 1
0.2%
65.1 1
0.2%
46.5 1
0.2%
43.5 1
0.2%
40.9 1
0.2%
40.0 1
0.2%
25.8 1
0.2%

지상_층_수
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.762
Minimum0
Maximum20
Zeros11
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:51.485604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.9731047
Coefficient of variation (CV)1.1198097
Kurtosis41.068024
Mean1.762
Median Absolute Deviation (MAD)0
Skewness5.5783314
Sum881
Variance3.8931423
MonotonicityNot monotonic
2023-12-11T00:05:51.730383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 323
64.6%
2 84
 
16.8%
3 38
 
7.6%
4 20
 
4.0%
5 13
 
2.6%
0 11
 
2.2%
6 3
 
0.6%
20 2
 
0.4%
10 2
 
0.4%
15 1
 
0.2%
Other values (3) 3
 
0.6%
ValueCountFrequency (%)
0 11
 
2.2%
1 323
64.6%
2 84
 
16.8%
3 38
 
7.6%
4 20
 
4.0%
5 13
 
2.6%
6 3
 
0.6%
8 1
 
0.2%
10 2
 
0.4%
14 1
 
0.2%
ValueCountFrequency (%)
20 2
 
0.4%
16 1
 
0.2%
15 1
 
0.2%
14 1
 
0.2%
10 2
 
0.4%
8 1
 
0.2%
6 3
 
0.6%
5 13
 
2.6%
4 20
4.0%
3 38
7.6%

지하_층_수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
419 
1
74 
2
 
5
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 419
83.8%
1 74
 
14.8%
2 5
 
1.0%
3 2
 
0.4%

Length

2023-12-11T00:05:52.017052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:52.276727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 419
83.8%
1 74
 
14.8%
2 5
 
1.0%
3 2
 
0.4%

승용_승강기_수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
487 
1
 
11
2
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 487
97.4%
1 11
 
2.2%
2 1
 
0.2%
4 1
 
0.2%

Length

2023-12-11T00:05:52.544841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:52.763574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 487
97.4%
1 11
 
2.2%
2 1
 
0.2%
4 1
 
0.2%

비상용_승강기_수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
494 
2
 
3
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 494
98.8%
2 3
 
0.6%
1 3
 
0.6%

Length

2023-12-11T00:05:52.968005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:53.182739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 494
98.8%
2 3
 
0.6%
1 3
 
0.6%

부속_건축물_수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
427 
1
60 
2
 
11
3
 
1
7
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 427
85.4%
1 60
 
12.0%
2 11
 
2.2%
3 1
 
0.2%
7 1
 
0.2%

Length

2023-12-11T00:05:53.402577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:53.602639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 427
85.4%
1 60
 
12.0%
2 11
 
2.2%
3 1
 
0.2%
7 1
 
0.2%

부속_건축물_면적(㎡)
Real number (ℝ)

SKEWED  ZEROS 

Distinct60
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.522212
Minimum0
Maximum28049.278
Zeros436
Zeros (%)87.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:53.834086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20.001
Maximum28049.278
Range28049.278
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1255.683
Coefficient of variation (CV)20.08379
Kurtosis497.49224
Mean62.522212
Median Absolute Deviation (MAD)0
Skewness22.278743
Sum31261.106
Variance1576739.7
MonotonicityNot monotonic
2023-12-11T00:05:54.130246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 436
87.2%
1.0 4
 
0.8%
4.32 2
 
0.4%
3.3 2
 
0.4%
21.16 1
 
0.2%
39.61 1
 
0.2%
16.96 1
 
0.2%
3.9 1
 
0.2%
1.62 1
 
0.2%
99.0 1
 
0.2%
Other values (50) 50
 
10.0%
ValueCountFrequency (%)
0.0 436
87.2%
0.8 1
 
0.2%
0.81 1
 
0.2%
1.0 4
 
0.8%
1.44 1
 
0.2%
1.62 1
 
0.2%
2.0 1
 
0.2%
2.15 1
 
0.2%
2.52 1
 
0.2%
2.86 1
 
0.2%
ValueCountFrequency (%)
28049.278 1
0.2%
1227.35 1
0.2%
641.07 1
0.2%
103.4 1
0.2%
99.0 1
0.2%
86.77 1
0.2%
86.34 1
0.2%
67.43 1
0.2%
63.72 1
0.2%
56.9 1
0.2%

총_동_연면적(㎡)
Real number (ℝ)

ZEROS 

Distinct430
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean495.95704
Minimum0
Maximum37202.33
Zeros51
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:54.414499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q142.9225
median89.14
Q3224.1525
95-th percentile1723.475
Maximum37202.33
Range37202.33
Interquartile range (IQR)181.23

Descriptive statistics

Standard deviation2204.0896
Coefficient of variation (CV)4.4441141
Kurtosis167.55825
Mean495.95704
Median Absolute Deviation (MAD)66.9
Skewness11.534305
Sum247978.52
Variance4858011.2
MonotonicityNot monotonic
2023-12-11T00:05:54.769606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 51
 
10.2%
198.0 3
 
0.6%
49.95 2
 
0.4%
49.6 2
 
0.4%
82.5 2
 
0.4%
92.76 2
 
0.4%
16.5 2
 
0.4%
96.0 2
 
0.4%
66.12 2
 
0.4%
84.66 2
 
0.4%
Other values (420) 430
86.0%
ValueCountFrequency (%)
0.0 51
10.2%
0.99 1
 
0.2%
1.0 1
 
0.2%
1.2 1
 
0.2%
1.8 1
 
0.2%
2.0 1
 
0.2%
2.4 1
 
0.2%
6.85 1
 
0.2%
7.2 1
 
0.2%
8.0 1
 
0.2%
ValueCountFrequency (%)
37202.33 1
0.2%
17817.79 1
0.2%
15526.5852 1
0.2%
11886.172 1
0.2%
7876.56 1
0.2%
7681.16 1
0.2%
7664.93 1
0.2%
6104.42 1
0.2%
5391.62 1
0.2%
5332.26 1
0.2%

옥내_기계식_대수(대)
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
497 
145
 
1
34
 
1
52
 
1

Length

Max length3
Median length1
Mean length1.008
Min length1

Unique

Unique3 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 497
99.4%
145 1
 
0.2%
34 1
 
0.2%
52 1
 
0.2%

Length

2023-12-11T00:05:55.085967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:55.309778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 497
99.4%
145 1
 
0.2%
34 1
 
0.2%
52 1
 
0.2%

옥내_기계식_면적(㎡)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0.0
498 
52.9
 
1
48.55
 
1

Length

Max length5
Median length3
Mean length3.006
Min length3

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 498
99.6%
52.9 1
 
0.2%
48.55 1
 
0.2%

Length

2023-12-11T00:05:56.034837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:56.270780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 498
99.6%
52.9 1
 
0.2%
48.55 1
 
0.2%

옥외_기계식_대수(대)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
498 
10
 
1
13
 
1

Length

Max length2
Median length1
Mean length1.004
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 498
99.6%
10 1
 
0.2%
13 1
 
0.2%

Length

2023-12-11T00:05:56.514308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:56.786887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 498
99.6%
10 1
 
0.2%
13 1
 
0.2%

옥외_기계식_면적(㎡)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0.0
499 
34.5
 
1

Length

Max length4
Median length3
Mean length3.002
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 499
99.8%
34.5 1
 
0.2%

Length

2023-12-11T00:05:57.059646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:57.340156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 499
99.8%
34.5 1
 
0.2%

옥내_자주식_대수(대)
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.56
Minimum0
Maximum781
Zeros471
Zeros (%)94.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:57.559242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.05
Maximum781
Range781
Interquartile range (IQR)0

Descriptive statistics

Standard deviation47.372679
Coefficient of variation (CV)10.388745
Kurtosis179.90409
Mean4.56
Median Absolute Deviation (MAD)0
Skewness12.840383
Sum2280
Variance2244.1707
MonotonicityNot monotonic
2023-12-11T00:05:57.816517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 471
94.2%
3 4
 
0.8%
1 4
 
0.8%
4 3
 
0.6%
8 3
 
0.6%
5 2
 
0.4%
2 2
 
0.4%
474 1
 
0.2%
6 1
 
0.2%
113 1
 
0.2%
Other values (8) 8
 
1.6%
ValueCountFrequency (%)
0 471
94.2%
1 4
 
0.8%
2 2
 
0.4%
3 4
 
0.8%
4 3
 
0.6%
5 2
 
0.4%
6 1
 
0.2%
8 3
 
0.6%
9 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
781 1
0.2%
474 1
0.2%
436 1
0.2%
298 1
0.2%
113 1
0.2%
52 1
0.2%
23 1
0.2%
12 1
0.2%
10 1
0.2%
9 1
0.2%

옥내_자주식_면적(㎡)
Real number (ℝ)

SKEWED  ZEROS 

Distinct22
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.67817
Minimum0
Maximum29670.525
Zeros478
Zeros (%)95.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:58.072701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum29670.525
Range29670.525
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1350.6704
Coefficient of variation (CV)18.332029
Kurtosis465.22794
Mean73.67817
Median Absolute Deviation (MAD)0
Skewness21.315959
Sum36839.085
Variance1824310.5
MonotonicityNot monotonic
2023-12-11T00:05:58.343687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 478
95.6%
69.0 2
 
0.4%
5704.0 1
 
0.2%
54.22 1
 
0.2%
34.5 1
 
0.2%
74.0 1
 
0.2%
45.03 1
 
0.2%
111.81 1
 
0.2%
92.0 1
 
0.2%
276.0 1
 
0.2%
Other values (12) 12
 
2.4%
ValueCountFrequency (%)
0.0 478
95.6%
11.5 1
 
0.2%
23.0 1
 
0.2%
26.68 1
 
0.2%
29.87 1
 
0.2%
34.5 1
 
0.2%
40.87 1
 
0.2%
45.03 1
 
0.2%
53.2 1
 
0.2%
54.22 1
 
0.2%
ValueCountFrequency (%)
29670.525 1
0.2%
5704.0 1
0.2%
276.0 1
0.2%
137.46 1
0.2%
111.81 1
0.2%
95.58 1
0.2%
92.0 1
0.2%
82.0 1
0.2%
74.0 1
0.2%
73.84 1
0.2%

옥외_자주식_대수(대)
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.544
Minimum0
Maximum642
Zeros409
Zeros (%)81.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:58.576867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.05
Maximum642
Range642
Interquartile range (IQR)0

Descriptive statistics

Standard deviation41.201544
Coefficient of variation (CV)9.0672411
Kurtosis191.77036
Mean4.544
Median Absolute Deviation (MAD)0
Skewness13.40107
Sum2272
Variance1697.5672
MonotonicityNot monotonic
2023-12-11T00:05:58.826162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 409
81.8%
2 20
 
4.0%
1 15
 
3.0%
4 14
 
2.8%
3 14
 
2.8%
7 5
 
1.0%
8 4
 
0.8%
5 2
 
0.4%
13 2
 
0.4%
20 1
 
0.2%
Other values (14) 14
 
2.8%
ValueCountFrequency (%)
0 409
81.8%
1 15
 
3.0%
2 20
 
4.0%
3 14
 
2.8%
4 14
 
2.8%
5 2
 
0.4%
6 1
 
0.2%
7 5
 
1.0%
8 4
 
0.8%
9 1
 
0.2%
ValueCountFrequency (%)
642 1
0.2%
578 1
0.2%
209 1
0.2%
203 1
0.2%
119 1
0.2%
63 1
0.2%
56 1
0.2%
39 1
0.2%
33 1
0.2%
20 1
0.2%

옥외_자주식_면적(㎡)
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)4.4%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean9.6073146
Minimum0
Maximum1315.5
Zeros427
Zeros (%)85.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:59.077610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile46
Maximum1315.5
Range1315.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation64.718209
Coefficient of variation (CV)6.7363474
Kurtosis337.22973
Mean9.6073146
Median Absolute Deviation (MAD)0
Skewness17.187972
Sum4794.05
Variance4188.4465
MonotonicityNot monotonic
2023-12-11T00:05:59.331587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 427
85.4%
23.0 16
 
3.2%
11.5 15
 
3.0%
34.5 11
 
2.2%
46.0 7
 
1.4%
57.5 4
 
0.8%
126.5 3
 
0.6%
69.0 2
 
0.4%
81.5 1
 
0.2%
105.5 1
 
0.2%
Other values (12) 12
 
2.4%
ValueCountFrequency (%)
0.0 427
85.4%
11.5 15
 
3.0%
23.0 16
 
3.2%
23.5 1
 
0.2%
24.0 1
 
0.2%
34.5 11
 
2.2%
41.7 1
 
0.2%
46.0 7
 
1.4%
57.5 4
 
0.8%
69.0 2
 
0.4%
ValueCountFrequency (%)
1315.5 1
 
0.2%
412.5 1
 
0.2%
184.0 1
 
0.2%
152.5 1
 
0.2%
126.5 3
0.6%
115.0 1
 
0.2%
105.5 1
 
0.2%
103.5 1
 
0.2%
96.0 1
 
0.2%
81.5 1
 
0.2%

허가_일
Real number (ℝ)

MISSING 

Distinct294
Distinct (%)97.0%
Missing197
Missing (%)39.4%
Infinite0
Infinite (%)0.0%
Mean19054700
Minimum1920
Maximum20160427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:59.662306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1920
5-th percentile19700663
Q119875762
median19971028
Q320070464
95-th percentile20139857
Maximum20160427
Range20158507
Interquartile range (IQR)194702

Descriptive statistics

Standard deviation4198806.7
Coefficient of variation (CV)0.22035544
Kurtosis16.962801
Mean19054700
Median Absolute Deviation (MAD)99497
Skewness-4.3399041
Sum5.773574 × 109
Variance1.7629977 × 1013
MonotonicityNot monotonic
2023-12-11T00:05:59.991841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1940 2
 
0.4%
1953 2
 
0.4%
19941229 2
 
0.4%
20021021 2
 
0.4%
20100309 2
 
0.4%
1950 2
 
0.4%
20110128 2
 
0.4%
20060711 2
 
0.4%
19970512 2
 
0.4%
20100920 1
 
0.2%
Other values (284) 284
56.8%
(Missing) 197
39.4%
ValueCountFrequency (%)
1920 1
0.2%
1933 1
0.2%
1940 2
0.4%
1941 1
0.2%
1948 1
0.2%
1950 2
0.4%
1953 2
0.4%
1965 1
0.2%
1974 1
0.2%
1997 1
0.2%
ValueCountFrequency (%)
20160427 1
0.2%
20151204 1
0.2%
20150924 1
0.2%
20150818 1
0.2%
20150730 1
0.2%
20150722 1
0.2%
20150528 1
0.2%
20150515 1
0.2%
20150417 1
0.2%
20150306 1
0.2%

착공_일
Real number (ℝ)

MISSING 

Distinct197
Distinct (%)98.0%
Missing299
Missing (%)59.8%
Infinite0
Infinite (%)0.0%
Mean19719937
Minimum1946
Maximum20160922
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:06:00.343390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1946
5-th percentile19880906
Q119950214
median20010903
Q320080827
95-th percentile20141124
Maximum20160922
Range20158976
Interquartile range (IQR)130613

Descriptive statistics

Standard deviation2426399.2
Coefficient of variation (CV)0.12304295
Kurtosis63.478489
Mean19719937
Median Absolute Deviation (MAD)69888
Skewness-8.0480422
Sum3.9637073 × 109
Variance5.8874129 × 1012
MonotonicityNot monotonic
2023-12-11T00:06:00.729917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110315 2
 
0.4%
20100409 2
 
0.4%
20150611 2
 
0.4%
20050801 2
 
0.4%
20090710 1
 
0.2%
19930324 1
 
0.2%
19920421 1
 
0.2%
20110601 1
 
0.2%
20120210 1
 
0.2%
19970816 1
 
0.2%
Other values (187) 187
37.4%
(Missing) 299
59.8%
ValueCountFrequency (%)
1946 1
0.2%
1996 1
0.2%
199202 1
0.2%
19840601 1
0.2%
19850413 1
0.2%
19870602 1
0.2%
19870814 1
0.2%
19871104 1
0.2%
19880506 1
0.2%
19880715 1
0.2%
ValueCountFrequency (%)
20160922 1
0.2%
20160119 1
0.2%
20151007 1
0.2%
20150819 1
0.2%
20150717 1
0.2%
20150611 2
0.4%
20150423 1
0.2%
20150403 1
0.2%
20150325 1
0.2%
20141124 1
0.2%

사용승인_일
Real number (ℝ)

MISSING 

Distinct421
Distinct (%)93.1%
Missing48
Missing (%)9.6%
Infinite0
Infinite (%)0.0%
Mean17148271
Minimum19
Maximum20160524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:06:01.086183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile1947
Q119770682
median19930674
Q320030908
95-th percentile20120408
Maximum20160524
Range20160505
Interquartile range (IQR)260226.75

Descriptive statistics

Standard deviation6909725.6
Coefficient of variation (CV)0.40294008
Kurtosis2.3708869
Mean17148271
Median Absolute Deviation (MAD)120152
Skewness-2.0871441
Sum7.7510184 × 109
Variance4.7744308 × 1013
MonotonicityNot monotonic
2023-12-11T00:06:01.408426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1950 7
 
1.4%
1958 3
 
0.6%
1940 3
 
0.6%
1955 3
 
0.6%
1945 3
 
0.6%
20050705 2
 
0.4%
1974 2
 
0.4%
1937 2
 
0.4%
1947 2
 
0.4%
1970 2
 
0.4%
Other values (411) 423
84.6%
(Missing) 48
 
9.6%
ValueCountFrequency (%)
19 1
0.2%
1875 1
0.2%
1894 1
0.2%
1905 1
0.2%
1920 1
0.2%
1921 1
0.2%
1934 1
0.2%
1935 2
0.4%
1936 1
0.2%
1937 2
0.4%
ValueCountFrequency (%)
20160524 1
0.2%
20160330 1
0.2%
20160321 1
0.2%
20151022 1
0.2%
20150921 1
0.2%
20150615 1
0.2%
20150317 1
0.2%
20150107 1
0.2%
20141002 1
0.2%
20140829 1
0.2%

허가번호_년
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)19.8%
Missing379
Missing (%)75.8%
Infinite0
Infinite (%)0.0%
Mean1991.5289
Minimum78
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:06:01.727024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum78
5-th percentile1982
Q12006
median2009
Q32013
95-th percentile2015
Maximum2016
Range1938
Interquartile range (IQR)7

Descriptive statistics

Standard deviation175.60548
Coefficient of variation (CV)0.088176214
Kurtosis120.43955
Mean1991.5289
Median Absolute Deviation (MAD)3
Skewness-10.96234
Sum240975
Variance30837.285
MonotonicityNot monotonic
2023-12-11T00:06:02.021035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2008 15
 
3.0%
2015 14
 
2.8%
2009 10
 
2.0%
2013 9
 
1.8%
2007 9
 
1.8%
2014 9
 
1.8%
2010 9
 
1.8%
2006 8
 
1.6%
2012 7
 
1.4%
2011 5
 
1.0%
Other values (14) 26
 
5.2%
(Missing) 379
75.8%
ValueCountFrequency (%)
78 1
0.2%
1976 1
0.2%
1977 2
0.4%
1978 2
0.4%
1982 1
0.2%
1984 1
0.2%
1993 1
0.2%
1995 1
0.2%
2000 1
0.2%
2001 1
0.2%
ValueCountFrequency (%)
2016 1
 
0.2%
2015 14
2.8%
2014 9
1.8%
2013 9
1.8%
2012 7
1.4%
2011 5
 
1.0%
2010 9
1.8%
2009 10
2.0%
2008 15
3.0%
2007 9
1.8%

허가번호_기관_코드
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)87.8%
Missing385
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean4561521.3
Minimum3010094
Maximum5735009
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:06:02.367508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3010094
5-th percentile3160117.6
Q14040137.5
median4650060
Q35185052.5
95-th percentile5600056.4
Maximum5735009
Range2724915
Interquartile range (IQR)1144915

Descriptive statistics

Standard deviation752514.05
Coefficient of variation (CV)0.16496997
Kurtosis-0.84701384
Mean4561521.3
Median Absolute Deviation (MAD)559968
Skewness-0.39218453
Sum5.2457495 × 108
Variance5.662774 × 1011
MonotonicityNot monotonic
2023-12-11T00:06:02.716881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4360021 4
 
0.8%
5030046 3
 
0.6%
4180111 2
 
0.4%
4830123 2
 
0.4%
4380029 2
 
0.4%
4660055 2
 
0.4%
4650060 2
 
0.4%
4540175 2
 
0.4%
3360115 2
 
0.4%
3110120 2
 
0.4%
Other values (91) 92
 
18.4%
(Missing) 385
77.0%
ValueCountFrequency (%)
3010094 1
0.2%
3060117 1
0.2%
3110120 2
0.4%
3130085 1
0.2%
3160077 1
0.2%
3160135 1
0.2%
3200025 1
0.2%
3240079 1
0.2%
3360115 2
0.4%
3390048 1
0.2%
ValueCountFrequency (%)
5735009 1
0.2%
5660007 1
0.2%
5650007 1
0.2%
5620025 1
0.2%
5600121 1
0.2%
5600104 1
0.2%
5600036 1
0.2%
5590202 1
0.2%
5590146 1
0.2%
5570034 1
0.2%

허가번호_기관_코드_명
Categorical

IMBALANCE 

Distinct37
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
400 
건축과
 
37
허가민원과
 
8
도시건축과
 
7
허가과
 
3
Other values (32)
45 

Length

Max length7
Median length4
Mean length4.016
Min length3

Unique

Unique23 ?
Unique (%)4.6%

Sample

1st row<NA>
2nd row<NA>
3rd row영흥면
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 400
80.0%
건축과 37
 
7.4%
허가민원과 8
 
1.6%
도시건축과 7
 
1.4%
허가과 3
 
0.6%
종합민원처리과 3
 
0.6%
민원봉사과 3
 
0.6%
민원과 3
 
0.6%
종합민원실 3
 
0.6%
건축디자인과 2
 
0.4%
Other values (27) 31
 
6.2%

Length

2023-12-11T00:06:03.075576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 400
80.0%
건축과 37
 
7.4%
허가민원과 8
 
1.6%
도시건축과 7
 
1.4%
허가과 3
 
0.6%
종합민원처리과 3
 
0.6%
민원봉사과 3
 
0.6%
민원과 3
 
0.6%
종합민원실 3
 
0.6%
지역개발과 2
 
0.4%
Other values (27) 31
 
6.2%

허가번호_구분_코드
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)9.2%
Missing391
Missing (%)78.2%
Infinite0
Infinite (%)0.0%
Mean1405.1101
Minimum1101
Maximum5810
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:06:03.348074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1101
5-th percentile1101
Q11101
median1102
Q31201
95-th percentile3900.4
Maximum5810
Range4709
Interquartile range (IQR)100

Descriptive statistics

Standard deviation969.85441
Coefficient of variation (CV)0.69023375
Kurtosis12.918575
Mean1405.1101
Median Absolute Deviation (MAD)1
Skewness3.7642902
Sum153157
Variance940617.58
MonotonicityNot monotonic
2023-12-11T00:06:03.582376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1101 54
 
10.8%
1201 31
 
6.2%
1102 7
 
1.4%
1202 7
 
1.4%
2101 4
 
0.8%
5200 2
 
0.4%
5310 1
 
0.2%
5810 1
 
0.2%
5320 1
 
0.2%
5100 1
 
0.2%
(Missing) 391
78.2%
ValueCountFrequency (%)
1101 54
10.8%
1102 7
 
1.4%
1201 31
6.2%
1202 7
 
1.4%
2101 4
 
0.8%
5100 1
 
0.2%
5200 2
 
0.4%
5310 1
 
0.2%
5320 1
 
0.2%
5810 1
 
0.2%
ValueCountFrequency (%)
5810 1
 
0.2%
5320 1
 
0.2%
5310 1
 
0.2%
5200 2
 
0.4%
5100 1
 
0.2%
2101 4
 
0.8%
1202 7
 
1.4%
1201 31
6.2%
1102 7
 
1.4%
1101 54
10.8%

허가번호_구분_코드_명
Categorical

IMBALANCE 

Distinct11
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
392 
신축허가
52 
신축신고
 
30
증축신고
 
6
주택건설사업계획승인
 
5
Other values (6)
 
15

Length

Max length12
Median length4
Mean length4.098
Min length2

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 392
78.4%
신축허가 52
 
10.4%
신축신고 30
 
6.0%
증축신고 6
 
1.2%
주택건설사업계획승인 5
 
1.0%
증축허가 4
 
0.8%
공용건축물 4
 
0.8%
협의건축물 3
 
0.6%
기타 2
 
0.4%
임대주택건설사업계획승인 1
 
0.2%

Length

2023-12-11T00:06:03.859741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 392
78.2%
신축허가 52
 
10.4%
신축신고 30
 
6.0%
증축신고 6
 
1.2%
주택건설사업계획승인 5
 
1.0%
증축허가 4
 
0.8%
공용건축물 4
 
0.8%
협의건축물 3
 
0.6%
기타 2
 
0.4%
임대주택건설사업계획승인 1
 
0.2%
Other values (2) 2
 
0.4%

호_수(호)
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
493 
1
 
5
5
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 493
98.6%
1 5
 
1.0%
5 1
 
0.2%
2 1
 
0.2%

Length

2023-12-11T00:06:04.109374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:06:04.330628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 493
98.6%
1 5
 
1.0%
5 1
 
0.2%
2 1
 
0.2%

에너지_효율등급
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500
Missing (%)100.0%
Memory size4.5 KiB

에너지_절감률
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
499 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.006
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 499
99.8%
<NA> 1
 
0.2%

Length

2023-12-11T00:06:04.602954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:06:04.865436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 499
99.8%
na 1
 
0.2%

EPI_점수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
499 
62
 
1

Length

Max length2
Median length1
Mean length1.002
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 499
99.8%
62 1
 
0.2%

Length

2023-12-11T00:06:05.108386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:06:05.300271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 499
99.8%
62 1
 
0.2%

친환경_건축물_등급
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500
Missing (%)100.0%
Memory size4.5 KiB

친환경_건축물_인증점수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-11T00:06:05.507626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:06:05.709251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

지능형_건축물_등급
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500
Missing (%)100.0%
Memory size4.5 KiB

지능형_건축물_인증점수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-11T00:06:05.884700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:06:06.099540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

생성_일자
Real number (ℝ)

Distinct219
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20120305
Minimum20090318
Maximum20160526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:06:06.320248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090318
5-th percentile20090321
Q120110420
median20111123
Q320131116
95-th percentile20151118
Maximum20160526
Range70208
Interquartile range (IQR)20696

Descriptive statistics

Standard deviation18258.561
Coefficient of variation (CV)0.0009074694
Kurtosis-0.48648134
Mean20120305
Median Absolute Deviation (MAD)9492.5
Skewness0.57814422
Sum1.0060152 × 1010
Variance3.3337506 × 108
MonotonicityNot monotonic
2023-12-11T00:06:06.579934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110420 50
 
10.0%
20111117 36
 
7.2%
20110415 28
 
5.6%
20111124 25
 
5.0%
20111123 24
 
4.8%
20110418 16
 
3.2%
20111125 9
 
1.8%
20140703 9
 
1.8%
20090321 9
 
1.8%
20110417 8
 
1.6%
Other values (209) 286
57.2%
ValueCountFrequency (%)
20090318 7
1.4%
20090319 6
1.2%
20090320 4
0.8%
20090321 9
1.8%
20090325 1
 
0.2%
20090611 1
 
0.2%
20090616 2
 
0.4%
20090714 1
 
0.2%
20090724 1
 
0.2%
20090805 1
 
0.2%
ValueCountFrequency (%)
20160526 2
0.4%
20160514 2
0.4%
20160512 1
0.2%
20160511 1
0.2%
20160422 1
0.2%
20160419 1
0.2%
20160415 1
0.2%
20160407 2
0.4%
20160329 1
0.2%
20160322 1
0.2%

Sample

관리_건축물대장_PK대장_구분_코드대장_구분_코드_명대장_종류_코드대장_종류_코드_명대지_위치도로명_대지_위치건물_명시군구_코드법정동_코드대지_구분_코드특수지_명블록로트외필지_수새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번동_명칭주_부속_구분_코드주_부속_구분_코드_명대지_면적(㎡)건축_면적(㎡)건폐_율(%)연면적(㎡)용적_률_산정_연면적(㎡)용적_률(%)구조_코드구조_코드_명기타_구조주_용도_코드주_용도_코드_명기타_용도지붕_코드지붕_코드_명기타_지붕세대_수(세대)가구_수(가구)높이(m)지상_층_수지하_층_수승용_승강기_수비상용_승강기_수부속_건축물_수부속_건축물_면적(㎡)총_동_연면적(㎡)옥내_기계식_대수(대)옥내_기계식_면적(㎡)옥외_기계식_대수(대)옥외_기계식_면적(㎡)옥내_자주식_대수(대)옥내_자주식_면적(㎡)옥외_자주식_대수(대)옥외_자주식_면적(㎡)허가_일착공_일사용승인_일허가번호_년허가번호_기관_코드허가번호_기관_코드_명허가번호_구분_코드허가번호_구분_코드_명호_수(호)에너지_효율등급에너지_절감률EPI_점수친환경_건축물_등급친환경_건축물_인증점수지능형_건축물_등급지능형_건축물_인증점수생성_일자
046890-160262일반2일반건축물충청북도 옥천군 이원면 건진리 150번지충청남도 아산시 남부로350번길 7<NA>2653010800044317<NA><NA><NA>0411114322190330010280020주건축물324.0688.00.0308.071.670.021벽돌구조연와조01000단독주택배저장창고20(철근)콘크리트슬라브000.0100000.049.700.000.000.000.020021231<NA>20100614<NA><NA><NA><NA><NA>0<NA>00<NA>0<NA>020151215
142230-39451일반2일반건축물경기도 포천시 이동면 연곡리 597-3번지<NA><NA>416702532308289<NA><NA><NA>0272904241369101010208<NA>0주건축물0.00.00.0240.016.00.051벽돌구조일반철골구조01000공동주택지하주차장10슬레이트기타지붕(글라스울판넬경사지붕)0419.4100000.00.000.000.000.0023.0<NA><NA>200109282014<NA><NA><NA><NA>0<NA>00<NA>0<NA>020110715
241820-165641집합2일반건축물인천광역시 서구 공촌동 313-3번지강원도 철원군 명성로125번길 7주택421301100002560<NA><NA><NA>0451134601224350010119740호0주건축물506.065.920.067.11102.326.219철근콘크리트구조목조01000단독주택주택10기타지붕<NA>080.0000000.066.0400.000.000.000.0<NA>20060430<NA><NA>3360115영흥면<NA><NA>0<NA>00<NA>0<NA>020130219
347130-95521일반2일반건축물인천광역시 중구 전동 26번지서울특별시 성북구 보문로30가길 17-16대황교동 가스충전소431303602802872<NA><NA><NA>050110484895010501060<NA>0주건축물103.096.216.6993.830.03.2821일반목구조벽돌구조02000단독주택주택20기타지붕기와0111.95100000.066.1500.000.000.000.02001080919950512197708032007<NA><NA><NA><NA>0<NA>00<NA>0<NA>020110420
431110-137181일반2일반건축물경기도 화성시 향남읍 동오리 32-4번지전라남도 나주시 장산길 8-2<NA>4888010300015240<NA><NA><NA>0481253329017<NA>088<NA><NA>0주건축물366.163.70.097.555.350.011철근콘크리트구조블록구조01000공장주택20기타지붕슬라브810.0500000.096.5500.000.000.000.0201109061994092819830613<NA><NA><NA><NA><NA>0<NA>00<NA>0<NA>020110418
541360-246871일반2일반건축물서울특별시 은평구 진관동 27번지경상북도 포항시 남구 대잠길69번길 12-4<NA>468103702402793<NA><NA><NA>141150434314037001023<NA><NA>0주건축물0.098.1858.9248.1877.020.011일반철골구조철골조, 조적조01000단독주택공장10(철근)콘크리트슬래브9171.02000010.211886.17200.000.000.000.019851118<NA><NA><NA>5410004함열민원과<NA><NA>0<NA>00<NA>0<NA>020110128
648240-266271일반2일반건축물강원도 강릉시 교동 183-231번지<NA><NA>277102563207390<NA><NA><NA>047130471601510801012070B동0주건축물104.055.380.0360.076.540.7511기타조적구조일반철골구조01000단독주택주택90기타지붕(철근)콘크리트014.5100000.0198.000.000.000.000.0<NA>1992090819690531<NA>3670110<NA><NA><NA>0<NA>00<NA>0<NA>020110420
747230-350052일반2일반건축물전라남도 장흥군 회진면 회진리 2143-11번지서울특별시 금천구 벚꽃로 158-1<NA>111701270008671<NA><NA><NA>02771042444612500102356<NA>0주건축물1196.2119.00.0109.34109.950.021벽돌구조일반목구조15000단독주택창고20기와스라브114.0100000.026.4400.000.000.000.0<NA>200707121920<NA><NA><NA><NA><NA>0<NA>00<NA>0<NA>020110113
811305-278081일반2표제부경기도 포천시 내촌면 음현리 337번지<NA><NA>113501010009910<NA><NA><NA>0291103009007330010<NA>11<NA>0주건축물304.07.560.0154.50.00.011철근콘크리트구조철근콘크리트 연와조04000단독주택단독주택(5가구)90슬레이트스페니쉬기와014.02000000.055.5700.000.000.000.020080423<NA>19971127<NA><NA><NA><NA><NA>0<NA>00<NA>0<NA>020110418
946800-11381일반2일반건축물경상남도 함안군 칠서면 구포리 202-6번지경기도 성남시 수정구 산성대로225번길 16-8<NA>411353203204937<NA><NA><NA>0301703166037250010736D동1주건축물0.0113.6160.59196.0268.8175.1121경량철골구조브럭01000단독주택단독주택10(철근)콘크리트평슬라브030.0100000.02234.7600.000.000.000.019970512<NA>19971028<NA><NA><NA><NA><NA>0<NA>062<NA>0<NA>020110420
관리_건축물대장_PK대장_구분_코드대장_구분_코드_명대장_종류_코드대장_종류_코드_명대지_위치도로명_대지_위치건물_명시군구_코드법정동_코드대지_구분_코드특수지_명블록로트외필지_수새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번동_명칭주_부속_구분_코드주_부속_구분_코드_명대지_면적(㎡)건축_면적(㎡)건폐_율(%)연면적(㎡)용적_률_산정_연면적(㎡)용적_률(%)구조_코드구조_코드_명기타_구조주_용도_코드주_용도_코드_명기타_용도지붕_코드지붕_코드_명기타_지붕세대_수(세대)가구_수(가구)높이(m)지상_층_수지하_층_수승용_승강기_수비상용_승강기_수부속_건축물_수부속_건축물_면적(㎡)총_동_연면적(㎡)옥내_기계식_대수(대)옥내_기계식_면적(㎡)옥외_기계식_대수(대)옥외_기계식_면적(㎡)옥내_자주식_대수(대)옥내_자주식_면적(㎡)옥외_자주식_대수(대)옥외_자주식_면적(㎡)허가_일착공_일사용승인_일허가번호_년허가번호_기관_코드허가번호_기관_코드_명허가번호_구분_코드허가번호_구분_코드_명호_수(호)에너지_효율등급에너지_절감률EPI_점수친환경_건축물_등급친환경_건축물_인증점수지능형_건축물_등급지능형_건축물_인증점수생성_일자
49044810-320741일반2일반건축물전라남도 담양군 금성면 석현리 466-7번지경상남도 남해군 망운로10번가길 50-5<NA>482701010001701<NA><NA><NA>1264403136032134010<NA><NA><NA>0주건축물212.042.60.0116.73427.50.031경량철골구조콘크리트구조02000단독주택축분건조장10기타지붕시멘와즙평가건010.01000012.48108.8200.000.000.040.020061124<NA>19500101<NA><NA><NA><NA><NA>0<NA>00<NA>0<NA>020110420
49141820-175011일반2일반건축물울산광역시 울주군 언양읍 직동리 251번지울산광역시 중구 학성공원10안길 21<NA>482203302302851<NA><NA><NA>0421304457563<NA>0520<NA>0주건축물210.033.059.6479.017.51.8512벽돌구조철근콘크리트조, 연와조18000공장주택, 소매점90(철근)콘크리트샌드위치판넬010.0110000.01420.400.000.000.000.0<NA><NA>19961209<NA><NA>금가면1101<NA>0<NA>00<NA>0<NA>020121227
49211110-148721일반2일반건축물경기도 이천시 호법면 매곡리 980번지전라북도 익산시 남전길 75-8<NA>302301030003510<NA><NA><NA>0<NA>117010261다동1주건축물0.0124.4415.183549.0501.3623.0851블록구조흙벽돌01000단독주택단독주택10(철근)콘크리트기타(판넬경사)지붕000.0400000.057.7500.000.000.000.0<NA><NA><NA><NA><NA>도시건축과<NA><NA>0<NA>00<NA>0<NA>020110415
49311440-248821일반2일반건축물대구광역시 중구 종로2가 60-2번지경상북도 상주시 왕산로 82-4<NA>471111290009580<NA><NA><NA>0471704721826<NA>0920<NA>1주건축물0.0174.9618.94233.53175.0223.9851일반목구조철근콘크리트구조01000단독주택동물및식물관련시설10슬레이트스라브6010.0100000.090.7200.000.000.000.0200710292011031520000414<NA><NA><NA><NA>신축허가0<NA>00<NA>0<NA>020110415
49428185-22652일반2일반건축물부산광역시 남구 우암동 12-13번지<NA><NA>441804202522270<NA><NA><NA>04113343370421010103080<NA>0부속건축물426.00.031.1568.260.00.012철근콘크리트구조세멘브럭구조,연와구조01000단독주택주택10(철근)콘크리트스레트010.0200020.0509.3500.000.000.0079.3520100309<NA>20030220<NA><NA><NA>1201<NA>0<NA>00<NA>0<NA>020160526
49546800-154041일반2일반건축물경기도 동두천시 생연동 625-21번지경상남도 창녕군 노리2길 25-15<NA>112901230001064<NA><NA><NA>0458003280068115010660<NA>0주건축물1860.0115.730.035.6742.9183.012블록구조연와조17000단독주택동물및식물관련시설10기타지붕기와0207.75100000.01027.9600.000.000.00103.5<NA>200207081957<NA><NA><NA><NA><NA>0<NA>00<NA>0<NA>020111206
49643130-181091일반2일반건축물경상북도 영천시 청통면 계지리 548번지경기도 부천시 원미구 계남로242번길 33<NA>112153403306005<NA><NA><NA>026260419001410201045<NA><NA>0주건축물0.0428.1820.6572331632.171.00.011벽돌구조경량철골구조01000단독주택창고시설10(철근)콘크리트(철근)콘크리트015.0110000.0130.5100.000.000.000.0200606211998091819980703<NA><NA><NA><NA><NA>0<NA>00<NA>0<NA>020111124
49748250-217521일반2일반건축물충청북도 충주시 산척면 영덕리 32번지<NA><NA>111403302105666<NA><NA><NA>041550442411610201007<NA>0주건축물0.069.120.0482.63314.40.021일반목구조목조02000단독주택주택10(철근)콘크리트스라브010.0100000.095.0400.000.000.000.0200711202016092219940910<NA><NA><NA>1202<NA>0<NA>00<NA>0<NA>020111124
49811680-199641집합3일반건축물경상남도 김해시 대동면 초정리 13-386번지강원도 삼척시 강원남부로 1408-16<NA>4713012300052622<NA><NA><NA>0272904241428109010<NA>44<NA>1주건축물0.060.130.096.044.668.212일반목구조경량철골조01000단독주택주택,점포20기타지붕슬레이트009.8200000.064.400.000.000.000.020010512<NA>198612261976<NA><NA>5200<NA>0<NA>00<NA>0<NA>020111117
49946770-1002101241일반2일반건축물전라남도 해남군 계곡면 당산리 384-2번지전라남도 순천시 농곡길 1-4<NA>437601120001761<NA><NA><NA>0<NA>253010<NA>0<NA>0주건축물0.098.970.093.29316.80.011일반목구조일반철골구조01000단독주택동.식물관련시설10(철근)콘크리트평스라브016.0300010.049.9500.000.000.030.019930331<NA>19950629<NA><NA><NA>1101신축허가0<NA>00<NA>0<NA>020160329