Overview

Dataset statistics

Number of variables64
Number of observations500
Missing cells6937
Missing cells (%)21.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory274.5 KiB
Average record size in memory562.3 B

Variable types

Text8
Categorical19
Numeric33
Unsupported4

Dataset

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

Alerts

대장_종류_코드 has constant value ""Constant
대장_종류_코드_명 has constant value ""Constant
로트 has constant value ""Constant
새주소_지상지하_코드 has constant value ""Constant
옥외_기계식_대수(대) has constant value ""Constant
옥외_기계식_면적(㎡) has constant value ""Constant
에너지_절감률 has constant value ""Constant
지능형_건축물_인증점수 has constant value ""Constant
대장_구분_코드 is highly imbalanced (67.3%)Imbalance
대장_구분_코드_명 is highly imbalanced (66.5%)Imbalance
신_구_대장_구분_코드 is highly imbalanced (56.1%)Imbalance
신_구_대장_구분_코드_명 is highly imbalanced (58.0%)Imbalance
대지_구분_코드 is highly imbalanced (89.4%)Imbalance
옥내_기계식_대수(대) is highly imbalanced (97.4%)Imbalance
옥내_기계식_면적(㎡) is highly imbalanced (97.9%)Imbalance
허가번호_구분_코드_명 is highly imbalanced (59.1%)Imbalance
EPI_점수 is highly imbalanced (96.4%)Imbalance
친환경_건축물_인증점수 is highly imbalanced (97.9%)Imbalance
도로명_대지_위치 has 188 (37.6%) missing valuesMissing
건물_명 has 429 (85.8%) missing valuesMissing
특수지_명 has 500 (100.0%) missing valuesMissing
블록 has 496 (99.2%) missing valuesMissing
로트 has 499 (99.8%) missing valuesMissing
새주소_도로_코드 has 195 (39.0%) missing valuesMissing
새주소_법정동_코드 has 192 (38.4%) missing valuesMissing
새주소_본_번 has 156 (31.2%) missing valuesMissing
새주소_부_번 has 160 (32.0%) missing valuesMissing
기타_용도 has 46 (9.2%) missing valuesMissing
허가_일 has 367 (73.4%) missing valuesMissing
착공_일 has 361 (72.2%) missing valuesMissing
사용승인_일 has 334 (66.8%) missing valuesMissing
허가번호_년 has 377 (75.4%) missing valuesMissing
허가번호_기관_코드 has 381 (76.2%) missing valuesMissing
허가번호_기관_코드_명 has 364 (72.8%) missing valuesMissing
허가번호_구분_코드 has 392 (78.4%) 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
건축_면적(㎡) is highly skewed (γ1 = 21.49067816)Skewed
관리_건축물대장_PK has unique valuesUnique
대지_위치 has unique valuesUnique
특수지_명 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 191 (38.2%) zerosZeros
외필지_수 has 417 (83.4%) zerosZeros
새주소_본_번 has 25 (5.0%) zerosZeros
새주소_부_번 has 214 (42.8%) zerosZeros
대지_면적(㎡) has 190 (38.0%) zerosZeros
건축_면적(㎡) has 43 (8.6%) zerosZeros
건폐_율(%) has 190 (38.0%) zerosZeros
연면적(㎡) has 24 (4.8%) zerosZeros
용적_률_산정_연면적(㎡) has 31 (6.2%) zerosZeros
용적_률(%) has 189 (37.8%) zerosZeros
세대_수(세대) has 461 (92.2%) zerosZeros
가구_수(가구) has 298 (59.6%) zerosZeros
주_건축물_수 has 28 (5.6%) zerosZeros
부속_건축물_수 has 391 (78.2%) zerosZeros
부속_건축물_면적(㎡) has 381 (76.2%) zerosZeros
총_주차_수 has 366 (73.2%) zerosZeros
옥내_자주식_대수(대) has 471 (94.2%) zerosZeros
옥내_자주식_면적(㎡) has 481 (96.2%) zerosZeros
옥외_자주식_대수(대) has 371 (74.2%) zerosZeros
옥외_자주식_면적(㎡) has 371 (74.2%) zerosZeros
호_수(호) has 492 (98.4%) zerosZeros

Reproduction

Analysis started2024-04-21 07:16:48.281827
Analysis finished2024-04-21 07:16:49.760896
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-21T16:16:50.458656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length11.134
Min length7

Characters and Unicode

Total characters5567
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 row47730-339
2nd row41500-100176908
3rd row11410-489
4th row31710-100194535
5th row42730-100183011
ValueCountFrequency (%)
47730-339 1
 
0.2%
50110-100249814 1
 
0.2%
47190-928 1
 
0.2%
45750-100183442 1
 
0.2%
41500-100207805 1
 
0.2%
41463-100220909 1
 
0.2%
47280-2593 1
 
0.2%
41830-2356 1
 
0.2%
41590-100310512 1
 
0.2%
41480-4023 1
 
0.2%
Other values (490) 490
98.0%
2024-04-21T16:16:51.448079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 978
17.6%
1 905
16.3%
4 677
12.2%
2 541
9.7%
- 500
9.0%
7 411
7.4%
3 385
 
6.9%
8 351
 
6.3%
5 328
 
5.9%
6 277
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5067
91.0%
Dash Punctuation 500
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 978
19.3%
1 905
17.9%
4 677
13.4%
2 541
10.7%
7 411
8.1%
3 385
 
7.6%
8 351
 
6.9%
5 328
 
6.5%
6 277
 
5.5%
9 214
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5567
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 978
17.6%
1 905
16.3%
4 677
12.2%
2 541
9.7%
- 500
9.0%
7 411
7.4%
3 385
 
6.9%
8 351
 
6.3%
5 328
 
5.9%
6 277
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5567
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 978
17.6%
1 905
16.3%
4 677
12.2%
2 541
9.7%
- 500
9.0%
7 411
7.4%
3 385
 
6.9%
8 351
 
6.3%
5 328
 
5.9%
6 277
 
5.0%

대장_구분_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
470 
2
 
30

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 470
94.0%
2 30
 
6.0%

Length

2024-04-21T16:16:51.675108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:16:51.928655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 470
94.0%
2 30
 
6.0%

대장_구분_코드_명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
일반
469 
집합
 
31

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 469
93.8%
집합 31
 
6.2%

Length

2024-04-21T16:16:52.249784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:16:52.551948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 469
93.8%
집합 31
 
6.2%

대장_종류_코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2024-04-21T16:16:52.879744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:16:53.172847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

대장_종류_코드_명
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
총괄표제부 500
100.0%

Length

2024-04-21T16:16:53.484874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:16:53.782999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
총괄표제부 500
100.0%

신_구_대장_구분_코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
415 
0
82 
<NA>
 
3

Length

Max length4
Median length1
Mean length1.018
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 415
83.0%
0 82
 
16.4%
<NA> 3
 
0.6%

Length

2024-04-21T16:16:54.107790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:16:54.437050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 415
83.0%
0 82
 
16.4%
na 3
 
0.6%

신_구_대장_구분_코드_명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
신대장
421 
구대장
76 
<NA>
 
3

Length

Max length4
Median length3
Mean length3.006
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신대장
2nd row신대장
3rd row구대장
4th row신대장
5th row신대장

Common Values

ValueCountFrequency (%)
신대장 421
84.2%
구대장 76
 
15.2%
<NA> 3
 
0.6%

Length

2024-04-21T16:16:54.781248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:16:55.109609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신대장 421
84.2%
구대장 76
 
15.2%
na 3
 
0.6%

대지_위치
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-21T16:16:56.169368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length28
Mean length22.382
Min length15

Characters and Unicode

Total characters11191
Distinct characters261
Distinct categories5 ?
Distinct scripts3 ?
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 row경기도 광명시 노온사동 2-1번지
2nd row제주특별자치도 제주시 영평동 2430-5번지
3rd row경상북도 영덕군 지품면 신안리 산 74번지
4th row경상북도 성주군 성주읍 용산리 191번지
5th row경상남도 하동군 횡천면 횡천리 572-1번지
ValueCountFrequency (%)
경기도 96
 
4.1%
경상북도 63
 
2.7%
경상남도 58
 
2.4%
전라남도 47
 
2.0%
전라북도 39
 
1.6%
충청남도 35
 
1.5%
부산광역시 30
 
1.3%
충청북도 30
 
1.3%
강원도 28
 
1.2%
서울특별시 20
 
0.8%
Other values (1396) 1922
81.2%
2024-04-21T16:16:57.699805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1872
 
16.7%
521
 
4.7%
498
 
4.5%
436
 
3.9%
1 385
 
3.4%
361
 
3.2%
- 326
 
2.9%
313
 
2.8%
2 264
 
2.4%
252
 
2.3%
Other values (251) 5963
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7107
63.5%
Decimal Number 1885
 
16.8%
Space Separator 1872
 
16.7%
Dash Punctuation 326
 
2.9%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
521
 
7.3%
498
 
7.0%
436
 
6.1%
361
 
5.1%
313
 
4.4%
252
 
3.5%
235
 
3.3%
212
 
3.0%
203
 
2.9%
163
 
2.3%
Other values (238) 3913
55.1%
Decimal Number
ValueCountFrequency (%)
1 385
20.4%
2 264
14.0%
3 214
11.4%
5 189
10.0%
4 173
9.2%
9 136
 
7.2%
6 136
 
7.2%
7 133
 
7.1%
8 131
 
6.9%
0 124
 
6.6%
Space Separator
ValueCountFrequency (%)
1872
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 326
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7107
63.5%
Common 4083
36.5%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
521
 
7.3%
498
 
7.0%
436
 
6.1%
361
 
5.1%
313
 
4.4%
252
 
3.5%
235
 
3.3%
212
 
3.0%
203
 
2.9%
163
 
2.3%
Other values (238) 3913
55.1%
Common
ValueCountFrequency (%)
1872
45.8%
1 385
 
9.4%
- 326
 
8.0%
2 264
 
6.5%
3 214
 
5.2%
5 189
 
4.6%
4 173
 
4.2%
9 136
 
3.3%
6 136
 
3.3%
7 133
 
3.3%
Other values (2) 255
 
6.2%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7107
63.5%
ASCII 4084
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1872
45.8%
1 385
 
9.4%
- 326
 
8.0%
2 264
 
6.5%
3 214
 
5.2%
5 189
 
4.6%
4 173
 
4.2%
9 136
 
3.3%
6 136
 
3.3%
7 133
 
3.3%
Other values (3) 256
 
6.3%
Hangul
ValueCountFrequency (%)
521
 
7.3%
498
 
7.0%
436
 
6.1%
361
 
5.1%
313
 
4.4%
252
 
3.5%
235
 
3.3%
212
 
3.0%
203
 
2.9%
163
 
2.3%
Other values (238) 3913
55.1%
Distinct312
Distinct (%)100.0%
Missing188
Missing (%)37.6%
Memory size4.0 KiB
2024-04-21T16:16:58.886761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length18.227564
Min length13

Characters and Unicode

Total characters5687
Distinct characters254
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

Unique312 ?
Unique (%)100.0%

Sample

1st row울산광역시 울주군 공암공단3길 38
2nd row경상남도 남해군 남서대로1202번길 23
3rd row경상남도 밀양시 상동가곡3길 33-4
4th row충청북도 제천시 옥순봉로14길 181
5th row충청남도 서천군 서인로 656-40
ValueCountFrequency (%)
경기도 60
 
4.7%
경상남도 44
 
3.5%
충청남도 36
 
2.8%
경상북도 26
 
2.1%
전라남도 24
 
1.9%
전라북도 18
 
1.4%
부산광역시 18
 
1.4%
충청북도 17
 
1.3%
강원도 14
 
1.1%
밀양시 12
 
0.9%
Other values (712) 997
78.8%
2024-04-21T16:17:00.312624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
958
 
16.8%
261
 
4.6%
1 248
 
4.4%
233
 
4.1%
227
 
4.0%
168
 
3.0%
2 161
 
2.8%
138
 
2.4%
137
 
2.4%
3 127
 
2.2%
Other values (244) 3029
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3494
61.4%
Decimal Number 1118
 
19.7%
Space Separator 958
 
16.8%
Dash Punctuation 117
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
261
 
7.5%
233
 
6.7%
227
 
6.5%
168
 
4.8%
138
 
3.9%
137
 
3.9%
98
 
2.8%
87
 
2.5%
83
 
2.4%
80
 
2.3%
Other values (232) 1982
56.7%
Decimal Number
ValueCountFrequency (%)
1 248
22.2%
2 161
14.4%
3 127
11.4%
4 110
9.8%
5 106
9.5%
6 88
 
7.9%
7 84
 
7.5%
9 81
 
7.2%
8 59
 
5.3%
0 54
 
4.8%
Space Separator
ValueCountFrequency (%)
958
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 117
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3494
61.4%
Common 2193
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
261
 
7.5%
233
 
6.7%
227
 
6.5%
168
 
4.8%
138
 
3.9%
137
 
3.9%
98
 
2.8%
87
 
2.5%
83
 
2.4%
80
 
2.3%
Other values (232) 1982
56.7%
Common
ValueCountFrequency (%)
958
43.7%
1 248
 
11.3%
2 161
 
7.3%
3 127
 
5.8%
- 117
 
5.3%
4 110
 
5.0%
5 106
 
4.8%
6 88
 
4.0%
7 84
 
3.8%
9 81
 
3.7%
Other values (2) 113
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3494
61.4%
ASCII 2193
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
958
43.7%
1 248
 
11.3%
2 161
 
7.3%
3 127
 
5.8%
- 117
 
5.3%
4 110
 
5.0%
5 106
 
4.8%
6 88
 
4.0%
7 84
 
3.8%
9 81
 
3.7%
Other values (2) 113
 
5.2%
Hangul
ValueCountFrequency (%)
261
 
7.5%
233
 
6.7%
227
 
6.5%
168
 
4.8%
138
 
3.9%
137
 
3.9%
98
 
2.8%
87
 
2.5%
83
 
2.4%
80
 
2.3%
Other values (232) 1982
56.7%

건물_명
Text

MISSING 

Distinct69
Distinct (%)97.2%
Missing429
Missing (%)85.8%
Memory size4.0 KiB
2024-04-21T16:17:01.250803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length8.7746479
Min length2

Characters and Unicode

Total characters623
Distinct characters200
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)95.8%

Sample

1st row가평향교
2nd row그린에스앤피
3rd row내기리00창고
4th row명진철강산업(주)
5th row팔영농업협동조합
ValueCountFrequency (%)
주택 3
 
2.8%
공장 2
 
1.9%
단독주택 2
 
1.9%
풍림리 1
 
0.9%
지오로드 1
 
0.9%
초원그린타운 1
 
0.9%
명작빌 1
 
0.9%
서경 1
 
0.9%
가동,나동,다동 1
 
0.9%
천차만차 1
 
0.9%
Other values (93) 93
86.9%
2024-04-21T16:17:02.473623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
 
5.8%
25
 
4.0%
18
 
2.9%
) 14
 
2.2%
( 14
 
2.2%
12
 
1.9%
1 11
 
1.8%
11
 
1.8%
10
 
1.6%
- 10
 
1.6%
Other values (190) 462
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 491
78.8%
Decimal Number 48
 
7.7%
Space Separator 36
 
5.8%
Close Punctuation 14
 
2.2%
Open Punctuation 14
 
2.2%
Dash Punctuation 10
 
1.6%
Other Punctuation 8
 
1.3%
Lowercase Letter 1
 
0.2%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
25
 
5.1%
18
 
3.7%
12
 
2.4%
11
 
2.2%
10
 
2.0%
10
 
2.0%
9
 
1.8%
9
 
1.8%
9
 
1.8%
8
 
1.6%
Other values (172) 370
75.4%
Decimal Number
ValueCountFrequency (%)
1 11
22.9%
2 8
16.7%
6 7
14.6%
3 4
 
8.3%
5 4
 
8.3%
4 4
 
8.3%
9 4
 
8.3%
0 4
 
8.3%
7 1
 
2.1%
8 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 7
87.5%
. 1
 
12.5%
Space Separator
ValueCountFrequency (%)
36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Lowercase Letter
ValueCountFrequency (%)
i 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 491
78.8%
Common 130
 
20.9%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
25
 
5.1%
18
 
3.7%
12
 
2.4%
11
 
2.2%
10
 
2.0%
10
 
2.0%
9
 
1.8%
9
 
1.8%
9
 
1.8%
8
 
1.6%
Other values (172) 370
75.4%
Common
ValueCountFrequency (%)
36
27.7%
) 14
 
10.8%
( 14
 
10.8%
1 11
 
8.5%
- 10
 
7.7%
2 8
 
6.2%
6 7
 
5.4%
, 7
 
5.4%
3 4
 
3.1%
5 4
 
3.1%
Other values (6) 15
11.5%
Latin
ValueCountFrequency (%)
i 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 491
78.8%
ASCII 132
 
21.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
27.3%
) 14
 
10.6%
( 14
 
10.6%
1 11
 
8.3%
- 10
 
7.6%
2 8
 
6.1%
6 7
 
5.3%
, 7
 
5.3%
3 4
 
3.0%
5 4
 
3.0%
Other values (8) 17
12.9%
Hangul
ValueCountFrequency (%)
25
 
5.1%
18
 
3.7%
12
 
2.4%
11
 
2.2%
10
 
2.0%
10
 
2.0%
9
 
1.8%
9
 
1.8%
9
 
1.8%
8
 
1.6%
Other values (172) 370
75.4%

시군구_코드
Real number (ℝ)

Distinct177
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41148.734
Minimum11200
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:02.760219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11200
5-th percentile11707
Q141370
median44210
Q347150
95-th percentile48880
Maximum50130
Range38930
Interquartile range (IQR)5780

Descriptive statistics

Standard deviation9555.4687
Coefficient of variation (CV)0.23221781
Kurtosis2.8912876
Mean41148.734
Median Absolute Deviation (MAD)2903
Skewness-1.8849676
Sum20574367
Variance91306983
MonotonicityNot monotonic
2024-04-21T16:17:03.280527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41590 12
 
2.4%
44270 12
 
2.4%
50130 11
 
2.2%
41360 8
 
1.6%
45140 8
 
1.6%
47250 8
 
1.6%
47900 7
 
1.4%
42770 7
 
1.4%
41650 7
 
1.4%
50110 7
 
1.4%
Other values (167) 413
82.6%
ValueCountFrequency (%)
11200 3
0.6%
11215 2
0.4%
11230 2
0.4%
11290 2
0.4%
11305 1
 
0.2%
11350 1
 
0.2%
11410 2
0.4%
11440 2
0.4%
11530 3
0.6%
11590 2
0.4%
ValueCountFrequency (%)
50130 11
2.2%
50110 7
1.4%
48890 6
1.2%
48880 2
 
0.4%
48870 4
 
0.8%
48860 3
 
0.6%
48850 2
 
0.4%
48840 2
 
0.4%
48820 3
 
0.6%
48740 5
1.0%

법정동_코드
Real number (ℝ)

Distinct204
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25473.118
Minimum10100
Maximum47029
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:03.590441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10100
5-th percentile10200
Q111800
median25481
Q334032.25
95-th percentile40082.4
Maximum47029
Range36929
Interquartile range (IQR)22232.25

Descriptive statistics

Standard deviation10962.817
Coefficient of variation (CV)0.43036809
Kurtosis-1.3841866
Mean25473.118
Median Absolute Deviation (MAD)10544.5
Skewness-0.23279446
Sum12736559
Variance1.2018336 × 108
MonotonicityNot monotonic
2024-04-21T16:17:03.860307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10200 17
 
3.4%
10300 13
 
2.6%
10100 12
 
2.4%
10600 12
 
2.4%
10500 11
 
2.2%
10900 11
 
2.2%
25024 9
 
1.8%
11200 9
 
1.8%
25021 9
 
1.8%
25031 8
 
1.6%
Other values (194) 389
77.8%
ValueCountFrequency (%)
10100 12
2.4%
10200 17
3.4%
10300 13
2.6%
10400 5
 
1.0%
10500 11
2.2%
10600 12
2.4%
10700 6
 
1.2%
10800 3
 
0.6%
10900 11
2.2%
11000 5
 
1.0%
ValueCountFrequency (%)
47029 1
0.2%
46026 1
0.2%
46021 1
0.2%
45029 1
0.2%
44032 1
0.2%
44027 1
0.2%
44022 1
0.2%
43036 1
0.2%
43027 1
0.2%
43025 1
0.2%

대지_구분_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
493 
1
 
7

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 (%)
0 493
98.6%
1 7
 
1.4%

Length

2024-04-21T16:17:04.096745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:04.279077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 493
98.6%
1 7
 
1.4%


Real number (ℝ)

Distinct402
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean490.488
Minimum1
Maximum3782
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:04.514289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile28.85
Q1148.25
median390
Q3691.25
95-th percentile1236.05
Maximum3782
Range3781
Interquartile range (IQR)543

Descriptive statistics

Standard deviation465.58521
Coefficient of variation (CV)0.94922854
Kurtosis12.319836
Mean490.488
Median Absolute Deviation (MAD)259
Skewness2.6240986
Sum245244
Variance216769.59
MonotonicityNot monotonic
2024-04-21T16:17:04.772548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
137 4
 
0.8%
20 4
 
0.8%
29 4
 
0.8%
92 3
 
0.6%
675 3
 
0.6%
143 3
 
0.6%
450 3
 
0.6%
657 3
 
0.6%
458 3
 
0.6%
214 3
 
0.6%
Other values (392) 467
93.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
5 2
0.4%
6 2
0.4%
7 1
0.2%
8 1
0.2%
9 2
0.4%
10 1
0.2%
12 1
0.2%
14 1
0.2%
ValueCountFrequency (%)
3782 1
0.2%
3543 1
0.2%
3392 1
0.2%
2762 1
0.2%
2162 1
0.2%
2080 1
0.2%
2020 1
0.2%
1985 1
0.2%
1934 1
0.2%
1904 1
0.2%


Real number (ℝ)

ZEROS 

Distinct59
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.662
Minimum0
Maximum1209
Zeros191
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:05.061047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile43.3
Maximum1209
Range1209
Interquartile range (IQR)5

Descriptive statistics

Standard deviation69.610884
Coefficient of variation (CV)5.0952191
Kurtosis187.58477
Mean13.662
Median Absolute Deviation (MAD)1
Skewness12.285437
Sum6831
Variance4845.6751
MonotonicityNot monotonic
2024-04-21T16:17:05.355771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 191
38.2%
1 86
17.2%
2 47
 
9.4%
3 34
 
6.8%
5 16
 
3.2%
4 15
 
3.0%
7 12
 
2.4%
10 9
 
1.8%
9 7
 
1.4%
6 6
 
1.2%
Other values (49) 77
15.4%
ValueCountFrequency (%)
0 191
38.2%
1 86
17.2%
2 47
 
9.4%
3 34
 
6.8%
4 15
 
3.0%
5 16
 
3.2%
6 6
 
1.2%
7 12
 
2.4%
8 4
 
0.8%
9 7
 
1.4%
ValueCountFrequency (%)
1209 1
0.2%
587 1
0.2%
468 1
0.2%
283 1
0.2%
244 1
0.2%
217 1
0.2%
211 1
0.2%
198 1
0.2%
155 1
0.2%
139 1
0.2%

특수지_명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

블록
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing496
Missing (%)99.2%
Memory size4.0 KiB
2024-04-21T16:17:05.810989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3.5
Mean length3.5
Min length3

Characters and Unicode

Total characters14
Distinct characters9
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowA3블럭
2nd rowi16B
3rd row1블럭
4th row3블록
ValueCountFrequency (%)
a3블럭 1
25.0%
i16b 1
25.0%
1블럭 1
25.0%
3블록 1
25.0%
2024-04-21T16:17:06.527215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
21.4%
3 2
14.3%
2
14.3%
1 2
14.3%
A 1
 
7.1%
i 1
 
7.1%
6 1
 
7.1%
B 1
 
7.1%
1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
42.9%
Decimal Number 5
35.7%
Uppercase Letter 2
 
14.3%
Lowercase Letter 1
 
7.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
50.0%
2
33.3%
1
 
16.7%
Decimal Number
ValueCountFrequency (%)
3 2
40.0%
1 2
40.0%
6 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
i 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
42.9%
Common 5
35.7%
Latin 3
21.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
50.0%
2
33.3%
1
 
16.7%
Common
ValueCountFrequency (%)
3 2
40.0%
1 2
40.0%
6 1
20.0%
Latin
ValueCountFrequency (%)
A 1
33.3%
i 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
57.1%
Hangul 6
42.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3
50.0%
2
33.3%
1
 
16.7%
ASCII
ValueCountFrequency (%)
3 2
25.0%
1 2
25.0%
A 1
12.5%
i 1
12.5%
6 1
12.5%
B 1
12.5%

로트
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing499
Missing (%)99.8%
Memory size4.0 KiB
2024-04-21T16:17:06.807760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 row13-3L
ValueCountFrequency (%)
13-3l 1
100.0%
2024-04-21T16:17:07.380761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2
40.0%
1 1
20.0%
- 1
20.0%
L 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
60.0%
Dash Punctuation 1
 
20.0%
Uppercase Letter 1
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2
66.7%
1 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
80.0%
Latin 1
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 2
50.0%
1 1
25.0%
- 1
25.0%
Latin
ValueCountFrequency (%)
L 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2
40.0%
1 1
20.0%
- 1
20.0%
L 1
20.0%

외필지_수
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.458
Minimum0
Maximum39
Zeros417
Zeros (%)83.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:07.570846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum39
Range39
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4339442
Coefficient of variation (CV)5.3142886
Kurtosis161.96126
Mean0.458
Median Absolute Deviation (MAD)0
Skewness11.864128
Sum229
Variance5.9240842
MonotonicityNot monotonic
2024-04-21T16:17:07.768642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 417
83.4%
1 46
 
9.2%
2 19
 
3.8%
3 8
 
1.6%
4 5
 
1.0%
22 1
 
0.2%
5 1
 
0.2%
26 1
 
0.2%
9 1
 
0.2%
39 1
 
0.2%
ValueCountFrequency (%)
0 417
83.4%
1 46
 
9.2%
2 19
 
3.8%
3 8
 
1.6%
4 5
 
1.0%
5 1
 
0.2%
9 1
 
0.2%
22 1
 
0.2%
26 1
 
0.2%
39 1
 
0.2%
ValueCountFrequency (%)
39 1
 
0.2%
26 1
 
0.2%
22 1
 
0.2%
9 1
 
0.2%
5 1
 
0.2%
4 5
 
1.0%
3 8
 
1.6%
2 19
 
3.8%
1 46
 
9.2%
0 417
83.4%

새주소_도로_코드
Real number (ℝ)

MISSING 

Distinct301
Distinct (%)98.7%
Missing195
Missing (%)39.0%
Infinite0
Infinite (%)0.0%
Mean4.1210656 × 1011
Minimum1.111041 × 1011
Maximum5.0130485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:08.015135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111041 × 1011
5-th percentile2.6272334 × 1011
Q14.1287438 × 1011
median4.4131455 × 1011
Q34.7150472 × 1011
95-th percentile4.8848338 × 1011
Maximum5.0130485 × 1011
Range3.9020075 × 1011
Interquartile range (IQR)5.8630336 × 1010

Descriptive statistics

Standard deviation9.0431025 × 1010
Coefficient of variation (CV)0.21943603
Kurtosis2.9898621
Mean4.1210656 × 1011
Median Absolute Deviation (MAD)2.9110183 × 1010
Skewness-1.8410911
Sum1.256925 × 1014
Variance8.1777703 × 1021
MonotonicityNot monotonic
2024-04-21T16:17:08.287602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
416503000136 2
 
0.4%
437503245021 2
 
0.4%
416503213050 2
 
0.4%
482404802466 2
 
0.4%
111403005010 1
 
0.2%
451404607040 1
 
0.2%
317103173003 1
 
0.2%
427704487164 1
 
0.2%
457404628165 1
 
0.2%
416504439027 1
 
0.2%
Other values (291) 291
58.2%
(Missing) 195
39.0%
ValueCountFrequency (%)
111104100542 1
0.2%
111403005010 1
0.2%
111404103205 1
0.2%
112154112066 1
0.2%
112154112502 1
0.2%
112304115100 1
0.2%
112304115380 1
0.2%
112604118052 1
0.2%
112604118430 1
0.2%
114104136050 1
0.2%
ValueCountFrequency (%)
501304850807 1
0.2%
501303350155 1
0.2%
501104848564 1
0.2%
501104848406 1
0.2%
501104848276 1
0.2%
501103349235 1
0.2%
501103349184 1
0.2%
501103349156 1
0.2%
501103349056 1
0.2%
488904844246 1
0.2%

새주소_법정동_코드
Real number (ℝ)

MISSING 

Distinct91
Distinct (%)29.5%
Missing192
Missing (%)38.4%
Infinite0
Infinite (%)0.0%
Mean25131.519
Minimum10101
Maximum46001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:08.554142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10301
Q111976
median25601
Q334001
95-th percentile39002
Maximum46001
Range35900
Interquartile range (IQR)22025

Descriptive statistics

Standard deviation10805.136
Coefficient of variation (CV)0.42994361
Kurtosis-1.48715
Mean25131.519
Median Absolute Deviation (MAD)10400
Skewness-0.25678146
Sum7740508
Variance1.1675097 × 108
MonotonicityNot monotonic
2024-04-21T16:17:08.840357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25001 35
 
7.0%
32001 20
 
4.0%
31001 19
 
3.8%
33001 17
 
3.4%
34001 16
 
3.2%
35001 11
 
2.2%
36001 10
 
2.0%
37001 10
 
2.0%
25301 10
 
2.0%
10601 9
 
1.8%
Other values (81) 151
30.2%
(Missing) 192
38.4%
ValueCountFrequency (%)
10101 8
1.6%
10201 4
0.8%
10202 1
 
0.2%
10301 4
0.8%
10302 1
 
0.2%
10303 1
 
0.2%
10401 5
1.0%
10403 1
 
0.2%
10501 1
 
0.2%
10601 9
1.8%
ValueCountFrequency (%)
46001 1
 
0.2%
43001 1
 
0.2%
42001 2
 
0.4%
41001 3
0.6%
40002 3
0.6%
40001 4
0.8%
39501 1
 
0.2%
39002 2
 
0.4%
39001 7
1.4%
38003 1
 
0.2%

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

2024-04-21T16:17:09.085071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:09.241658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

새주소_본_번
Real number (ℝ)

MISSING  ZEROS 

Distinct181
Distinct (%)52.6%
Missing156
Missing (%)31.2%
Infinite0
Infinite (%)0.0%
Mean243.38663
Minimum0
Maximum4767
Zeros25
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:09.450913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116
median53.5
Q3145
95-th percentile1379.7
Maximum4767
Range4767
Interquartile range (IQR)129

Descriptive statistics

Standard deviation611.8081
Coefficient of variation (CV)2.5137293
Kurtosis23.784393
Mean243.38663
Median Absolute Deviation (MAD)43.5
Skewness4.5526553
Sum83725
Variance374309.15
MonotonicityNot monotonic
2024-04-21T16:17:09.742284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25
 
5.0%
9 7
 
1.4%
10 7
 
1.4%
11 6
 
1.2%
16 6
 
1.2%
23 6
 
1.2%
26 6
 
1.2%
13 5
 
1.0%
15 5
 
1.0%
27 5
 
1.0%
Other values (171) 266
53.2%
(Missing) 156
31.2%
ValueCountFrequency (%)
0 25
5.0%
1 2
 
0.4%
2 2
 
0.4%
3 5
 
1.0%
4 3
 
0.6%
5 2
 
0.4%
6 3
 
0.6%
7 4
 
0.8%
9 7
 
1.4%
10 7
 
1.4%
ValueCountFrequency (%)
4767 1
0.2%
4633 1
0.2%
3414 1
0.2%
3304 1
0.2%
3270 1
0.2%
3121 1
0.2%
3077 1
0.2%
2068 1
0.2%
2013 1
0.2%
1954 1
0.2%

새주소_부_번
Real number (ℝ)

MISSING  ZEROS 

Distinct43
Distinct (%)12.6%
Missing160
Missing (%)32.0%
Infinite0
Infinite (%)0.0%
Mean6.25
Minimum0
Maximum192
Zeros214
Zeros (%)42.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:09.980851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile29.05
Maximum192
Range192
Interquartile range (IQR)6

Descriptive statistics

Standard deviation16.120467
Coefficient of variation (CV)2.5792748
Kurtosis56.139025
Mean6.25
Median Absolute Deviation (MAD)0
Skewness6.1185492
Sum2125
Variance259.86947
MonotonicityNot monotonic
2024-04-21T16:17:10.523037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 214
42.8%
1 15
 
3.0%
6 9
 
1.8%
10 8
 
1.6%
3 7
 
1.4%
5 7
 
1.4%
13 6
 
1.2%
8 5
 
1.0%
18 5
 
1.0%
2 5
 
1.0%
Other values (33) 59
 
11.8%
(Missing) 160
32.0%
ValueCountFrequency (%)
0 214
42.8%
1 15
 
3.0%
2 5
 
1.0%
3 7
 
1.4%
4 5
 
1.0%
5 7
 
1.4%
6 9
 
1.8%
8 5
 
1.0%
9 3
 
0.6%
10 8
 
1.6%
ValueCountFrequency (%)
192 1
0.2%
87 1
0.2%
78 1
0.2%
71 1
0.2%
70 1
0.2%
67 1
0.2%
60 1
0.2%
50 1
0.2%
45 1
0.2%
44 1
0.2%

대지_면적(㎡)
Real number (ℝ)

ZEROS 

Distinct295
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7570.9759
Minimum0
Maximum1517070
Zeros190
Zeros (%)38.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:10.969859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median571.85
Q31743.75
95-th percentile8784.55
Maximum1517070
Range1517070
Interquartile range (IQR)1743.75

Descriptive statistics

Standard deviation79007.094
Coefficient of variation (CV)10.435523
Kurtosis296.84095
Mean7570.9759
Median Absolute Deviation (MAD)571.85
Skewness16.728313
Sum3785487.9
Variance6.242121 × 109
MonotonicityNot monotonic
2024-04-21T16:17:11.443317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 190
38.0%
998.0 3
 
0.6%
833.0 3
 
0.6%
1041.0 3
 
0.6%
661.0 2
 
0.4%
497.0 2
 
0.4%
1037.0 2
 
0.4%
602.0 2
 
0.4%
3307.0 2
 
0.4%
1985.0 2
 
0.4%
Other values (285) 289
57.8%
ValueCountFrequency (%)
0.0 190
38.0%
49.6 1
 
0.2%
76.0 1
 
0.2%
81.07 1
 
0.2%
116.0 1
 
0.2%
153.92 1
 
0.2%
157.0 1
 
0.2%
178.0 1
 
0.2%
185.0 1
 
0.2%
186.0 1
 
0.2%
ValueCountFrequency (%)
1517070.0 1
0.2%
875587.0 1
0.2%
157777.0 1
0.2%
115702.0 1
0.2%
109241.7 1
0.2%
103016.0 1
0.2%
58279.0 1
0.2%
52474.0 1
0.2%
36290.0 1
0.2%
35937.0 1
0.2%

건축_면적(㎡)
Real number (ℝ)

SKEWED  ZEROS 

Distinct448
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3815.3091
Minimum0
Maximum1265224.6
Zeros43
Zeros (%)8.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:11.767430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1112.76
median197.065
Q3589.535
95-th percentile4349.4972
Maximum1265224.6
Range1265224.6
Interquartile range (IQR)476.775

Descriptive statistics

Standard deviation57361.64
Coefficient of variation (CV)15.034598
Kurtosis471.62762
Mean3815.3091
Median Absolute Deviation (MAD)139.99
Skewness21.490678
Sum1907654.6
Variance3.2903577 × 109
MonotonicityNot monotonic
2024-04-21T16:17:12.071986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 43
 
8.6%
396.0 3
 
0.6%
69.6 2
 
0.4%
223.08 2
 
0.4%
148.64 2
 
0.4%
63.3 2
 
0.4%
152.42 2
 
0.4%
52.9 2
 
0.4%
368.0 2
 
0.4%
68.0 2
 
0.4%
Other values (438) 438
87.6%
ValueCountFrequency (%)
0.0 43
8.6%
30.0 1
 
0.2%
32.66 1
 
0.2%
36.6 1
 
0.2%
37.02 1
 
0.2%
40.25 1
 
0.2%
45.88 1
 
0.2%
46.28 1
 
0.2%
46.57 1
 
0.2%
47.0 1
 
0.2%
ValueCountFrequency (%)
1265224.6 1
0.2%
209964.449 1
0.2%
43842.67 1
0.2%
32831.52 1
0.2%
11218.86 1
0.2%
10140.69 1
0.2%
8586.8 1
0.2%
7943.8747 1
0.2%
7867.6 1
0.2%
7358.002 1
0.2%

건폐_율(%)
Real number (ℝ)

ZEROS 

Distinct299
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.228607
Minimum0
Maximum79.81
Zeros190
Zeros (%)38.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:12.369934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median17.17
Q334.2275
95-th percentile54.907
Maximum79.81
Range79.81
Interquartile range (IQR)34.2275

Descriptive statistics

Standard deviation19.494724
Coefficient of variation (CV)1.0138396
Kurtosis-0.44337816
Mean19.228607
Median Absolute Deviation (MAD)17.17
Skewness0.68460858
Sum9614.3037
Variance380.04426
MonotonicityNot monotonic
2024-04-21T16:17:12.671518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 190
38.0%
31.15 2
 
0.4%
29.62 2
 
0.4%
17.98 2
 
0.4%
39.45 2
 
0.4%
39.61 2
 
0.4%
35.42 2
 
0.4%
19.97 2
 
0.4%
20.93 2
 
0.4%
35.71 2
 
0.4%
Other values (289) 292
58.4%
ValueCountFrequency (%)
0.0 190
38.0%
0.71 1
 
0.2%
0.86 1
 
0.2%
2.08 1
 
0.2%
2.73 1
 
0.2%
3.03 1
 
0.2%
3.08 1
 
0.2%
3.33 1
 
0.2%
4.61 1
 
0.2%
5.83 1
 
0.2%
ValueCountFrequency (%)
79.81 1
0.2%
78.88 1
0.2%
78.83 1
0.2%
75.79 1
0.2%
70.94 1
0.2%
70.44 1
0.2%
69.7731 1
0.2%
62.75 1
0.2%
59.83 1
0.2%
59.66 1
0.2%

연면적(㎡)
Real number (ℝ)

ZEROS 

Distinct471
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4317.1633
Minimum0
Maximum539090.47
Zeros24
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:12.975582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25.968
Q1131.7975
median280.395
Q31006.7575
95-th percentile9437.711
Maximum539090.47
Range539090.47
Interquartile range (IQR)874.96

Descriptive statistics

Standard deviation27728.135
Coefficient of variation (CV)6.4227673
Kurtosis281.20385
Mean4317.1633
Median Absolute Deviation (MAD)198.895
Skewness15.29439
Sum2158581.6
Variance7.6884948 × 108
MonotonicityNot monotonic
2024-04-21T16:17:13.272456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 24
 
4.8%
396.0 3
 
0.6%
174.89 2
 
0.4%
165.28 2
 
0.4%
138.2 2
 
0.4%
109.2 2
 
0.4%
1611.76 1
 
0.2%
63.0 1
 
0.2%
1223.56 1
 
0.2%
214.0 1
 
0.2%
Other values (461) 461
92.2%
ValueCountFrequency (%)
0.0 24
4.8%
17.76 1
 
0.2%
26.4 1
 
0.2%
26.44 1
 
0.2%
39.0 1
 
0.2%
41.2 1
 
0.2%
41.32 1
 
0.2%
42.44 1
 
0.2%
46.2 1
 
0.2%
46.28 1
 
0.2%
ValueCountFrequency (%)
539090.47 1
0.2%
146271.3679 1
0.2%
139964.3778 1
0.2%
110753.518 1
0.2%
86801.67 1
0.2%
83483.676 1
0.2%
78123.04 1
0.2%
76176.923 1
0.2%
59937.0817 1
0.2%
57403.0 1
0.2%

용적_률_산정_연면적(㎡)
Real number (ℝ)

ZEROS 

Distinct465
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1091.1381
Minimum0
Maximum37724.359
Zeros31
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:13.543582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1112.61
median226.3
Q3620.065
95-th percentile4020.26
Maximum37724.359
Range37724.359
Interquartile range (IQR)507.455

Descriptive statistics

Standard deviation3470.9492
Coefficient of variation (CV)3.1810355
Kurtosis51.499063
Mean1091.1381
Median Absolute Deviation (MAD)140.955
Skewness6.5938469
Sum545569.07
Variance12047488
MonotonicityNot monotonic
2024-04-21T16:17:13.838746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 31
 
6.2%
231.0 2
 
0.4%
112.38 2
 
0.4%
115.62 2
 
0.4%
950.0 2
 
0.4%
396.0 2
 
0.4%
216.07 1
 
0.2%
109.13 1
 
0.2%
348.0 1
 
0.2%
1548.9 1
 
0.2%
Other values (455) 455
91.0%
ValueCountFrequency (%)
0.0 31
6.2%
23.4 1
 
0.2%
35.84 1
 
0.2%
40.7 1
 
0.2%
42.97 1
 
0.2%
42.98 1
 
0.2%
43.84 1
 
0.2%
45.0 1
 
0.2%
45.05 1
 
0.2%
46.11 1
 
0.2%
ValueCountFrequency (%)
37724.3592 1
0.2%
32722.44 1
0.2%
27235.16 1
0.2%
22931.47 1
0.2%
18683.91 1
0.2%
18089.52 1
0.2%
15683.54 1
0.2%
15623.184 1
0.2%
14550.97 1
0.2%
14426.49 1
0.2%

용적_률(%)
Real number (ℝ)

ZEROS 

Distinct303
Distinct (%)60.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.13303
Minimum0
Maximum524.95
Zeros189
Zeros (%)37.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:14.132223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median19.94
Q339.1425
95-th percentile98.1485
Maximum524.95
Range524.95
Interquartile range (IQR)39.1425

Descriptive statistics

Standard deviation50.943767
Coefficient of variation (CV)1.6363254
Kurtosis27.004508
Mean31.13303
Median Absolute Deviation (MAD)19.94
Skewness4.2752766
Sum15566.515
Variance2595.2674
MonotonicityNot monotonic
2024-04-21T16:17:14.390244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 189
37.8%
57.54 2
 
0.4%
59.17 2
 
0.4%
29.92 2
 
0.4%
39.84 2
 
0.4%
18.94 2
 
0.4%
21.64 2
 
0.4%
40.01 2
 
0.4%
15.72 2
 
0.4%
31.72 2
 
0.4%
Other values (293) 293
58.6%
ValueCountFrequency (%)
0.0 189
37.8%
0.85 1
 
0.2%
3.06 1
 
0.2%
3.5 1
 
0.2%
4.72 1
 
0.2%
5.04 1
 
0.2%
5.4696 1
 
0.2%
5.72 1
 
0.2%
5.86 1
 
0.2%
6.064192273 1
 
0.2%
ValueCountFrequency (%)
524.95 1
0.2%
373.66 1
0.2%
305.23 1
0.2%
286.57 1
0.2%
275.82 1
0.2%
273.42 1
0.2%
226.1 1
0.2%
224.33 1
0.2%
223.97 1
0.2%
205.88 1
0.2%
Distinct21
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
01000
180 
21000
55 
17000
50 
04000
40 
02000
34 
Other values (16)
141 

Length

Max length5
Median length5
Mean length4.948
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row01000
2nd row02000
3rd row01000
4th row18000
5th row17000

Common Values

ValueCountFrequency (%)
01000 180
36.0%
21000 55
 
11.0%
17000 50
 
10.0%
04000 40
 
8.0%
02000 34
 
6.8%
18000 33
 
6.6%
03000 29
 
5.8%
<NA> 26
 
5.2%
10000 13
 
2.6%
19000 6
 
1.2%
Other values (11) 34
 
6.8%

Length

2024-04-21T16:17:14.614058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
01000 180
36.0%
21000 55
 
11.0%
17000 50
 
10.0%
04000 40
 
8.0%
02000 34
 
6.8%
18000 33
 
6.6%
03000 29
 
5.8%
na 26
 
5.2%
10000 13
 
2.6%
20000 6
 
1.2%
Other values (11) 34
 
6.8%
Distinct23
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
단독주택
170 
공장
60 
제2종근린생활시설
48 
동.식물관련시설
46 
창고시설
35 
Other values (18)
141 

Length

Max length10
Median length4
Mean length5.136
Min length2

Unique

Unique3 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
단독주택 170
34.0%
공장 60
 
12.0%
제2종근린생활시설 48
 
9.6%
동.식물관련시설 46
 
9.2%
창고시설 35
 
7.0%
공동주택 32
 
6.4%
제1종근린생활시설 29
 
5.8%
<NA> 27
 
5.4%
자동차관련시설 8
 
1.6%
노유자시설 7
 
1.4%
Other values (13) 38
 
7.6%

Length

2024-04-21T16:17:14.863989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 170
34.0%
공장 60
 
12.0%
제2종근린생활시설 48
 
9.6%
동.식물관련시설 46
 
9.2%
창고시설 35
 
7.0%
공동주택 32
 
6.4%
제1종근린생활시설 29
 
5.8%
na 27
 
5.4%
자동차관련시설 8
 
1.6%
노유자시설 7
 
1.4%
Other values (13) 38
 
7.6%

기타_용도
Text

MISSING 

Distinct127
Distinct (%)28.0%
Missing46
Missing (%)9.2%
Memory size4.0 KiB
2024-04-21T16:17:15.622618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length23
Mean length6.5550661
Min length2

Characters and Unicode

Total characters2976
Distinct characters119
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

Unique94 ?
Unique (%)20.7%

Sample

1st row버섯재배사
2nd row공장
3rd row주택
4th row단독주택
5th row다가구주택 및 창고
ValueCountFrequency (%)
단독주택 144
27.2%
공장 42
 
7.9%
주택 37
 
7.0%
제2종근린생활시설 27
 
5.1%
창고시설 27
 
5.1%
동.식물관련시설 24
 
4.5%
제1종근린생활시설 18
 
3.4%
근린생활시설 12
 
2.3%
동물및식물관련시설 11
 
2.1%
11
 
2.1%
Other values (105) 177
33.4%
2024-04-21T16:17:16.652993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
241
 
8.1%
239
 
8.0%
213
 
7.2%
212
 
7.1%
161
 
5.4%
159
 
5.3%
90
 
3.0%
, 89
 
3.0%
86
 
2.9%
85
 
2.9%
Other values (109) 1401
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2645
88.9%
Other Punctuation 120
 
4.0%
Decimal Number 89
 
3.0%
Space Separator 76
 
2.6%
Open Punctuation 23
 
0.8%
Close Punctuation 23
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
241
 
9.1%
239
 
9.0%
213
 
8.1%
212
 
8.0%
161
 
6.1%
159
 
6.0%
90
 
3.4%
86
 
3.3%
85
 
3.2%
84
 
3.2%
Other values (101) 1075
40.6%
Other Punctuation
ValueCountFrequency (%)
, 89
74.2%
. 29
 
24.2%
/ 2
 
1.7%
Decimal Number
ValueCountFrequency (%)
2 48
53.9%
1 41
46.1%
Space Separator
ValueCountFrequency (%)
76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2645
88.9%
Common 331
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
241
 
9.1%
239
 
9.0%
213
 
8.1%
212
 
8.0%
161
 
6.1%
159
 
6.0%
90
 
3.4%
86
 
3.3%
85
 
3.2%
84
 
3.2%
Other values (101) 1075
40.6%
Common
ValueCountFrequency (%)
, 89
26.9%
76
23.0%
2 48
14.5%
1 41
12.4%
. 29
 
8.8%
( 23
 
6.9%
) 23
 
6.9%
/ 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2645
88.9%
ASCII 331
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
241
 
9.1%
239
 
9.0%
213
 
8.1%
212
 
8.0%
161
 
6.1%
159
 
6.0%
90
 
3.4%
86
 
3.3%
85
 
3.2%
84
 
3.2%
Other values (101) 1075
40.6%
ASCII
ValueCountFrequency (%)
, 89
26.9%
76
23.0%
2 48
14.5%
1 41
12.4%
. 29
 
8.8%
( 23
 
6.9%
) 23
 
6.9%
/ 2
 
0.6%

세대_수(세대)
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.342
Minimum0
Maximum690
Zeros461
Zeros (%)92.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:16.863176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12
Maximum690
Range690
Interquartile range (IQR)0

Descriptive statistics

Standard deviation54.566216
Coefficient of variation (CV)7.4320644
Kurtosis102.29955
Mean7.342
Median Absolute Deviation (MAD)0
Skewness9.7914147
Sum3671
Variance2977.472
MonotonicityNot monotonic
2024-04-21T16:17:17.074688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 461
92.2%
1 8
 
1.6%
16 3
 
0.6%
12 3
 
0.6%
40 2
 
0.4%
19 2
 
0.4%
48 2
 
0.4%
8 2
 
0.4%
690 1
 
0.2%
36 1
 
0.2%
Other values (15) 15
 
3.0%
ValueCountFrequency (%)
0 461
92.2%
1 8
 
1.6%
3 1
 
0.2%
5 1
 
0.2%
8 2
 
0.4%
12 3
 
0.6%
15 1
 
0.2%
16 3
 
0.6%
19 2
 
0.4%
22 1
 
0.2%
ValueCountFrequency (%)
690 1
0.2%
612 1
0.2%
482 1
0.2%
470 1
0.2%
332 1
0.2%
194 1
0.2%
153 1
0.2%
96 1
0.2%
89 1
0.2%
66 1
0.2%

가구_수(가구)
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.002
Minimum0
Maximum45
Zeros298
Zeros (%)59.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:17.280097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3
Maximum45
Range45
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.578234
Coefficient of variation (CV)2.5730878
Kurtosis173.95555
Mean1.002
Median Absolute Deviation (MAD)0
Skewness11.066146
Sum501
Variance6.6472906
MonotonicityNot monotonic
2024-04-21T16:17:17.463621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 298
59.6%
2 100
 
20.0%
1 61
 
12.2%
3 20
 
4.0%
4 6
 
1.2%
5 6
 
1.2%
8 2
 
0.4%
13 2
 
0.4%
16 1
 
0.2%
45 1
 
0.2%
Other values (3) 3
 
0.6%
ValueCountFrequency (%)
0 298
59.6%
1 61
 
12.2%
2 100
 
20.0%
3 20
 
4.0%
4 6
 
1.2%
5 6
 
1.2%
6 1
 
0.2%
7 1
 
0.2%
8 2
 
0.4%
10 1
 
0.2%
ValueCountFrequency (%)
45 1
 
0.2%
16 1
 
0.2%
13 2
 
0.4%
10 1
 
0.2%
8 2
 
0.4%
7 1
 
0.2%
6 1
 
0.2%
5 6
 
1.2%
4 6
 
1.2%
3 20
4.0%

주_건축물_수
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.146
Minimum0
Maximum159
Zeros28
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:17.661448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q33
95-th percentile7
Maximum159
Range159
Interquartile range (IQR)1

Descriptive statistics

Standard deviation7.7439409
Coefficient of variation (CV)2.4615197
Kurtosis333.29844
Mean3.146
Median Absolute Deviation (MAD)0
Skewness17.072445
Sum1573
Variance59.968621
MonotonicityNot monotonic
2024-04-21T16:17:17.899858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2 309
61.8%
3 79
 
15.8%
0 28
 
5.6%
4 28
 
5.6%
5 14
 
2.8%
1 9
 
1.8%
6 7
 
1.4%
8 7
 
1.4%
7 5
 
1.0%
15 4
 
0.8%
Other values (7) 10
 
2.0%
ValueCountFrequency (%)
0 28
 
5.6%
1 9
 
1.8%
2 309
61.8%
3 79
 
15.8%
4 28
 
5.6%
5 14
 
2.8%
6 7
 
1.4%
7 5
 
1.0%
8 7
 
1.4%
11 2
 
0.4%
ValueCountFrequency (%)
159 1
 
0.2%
50 1
 
0.2%
37 1
 
0.2%
16 1
 
0.2%
15 4
0.8%
13 2
 
0.4%
12 2
 
0.4%
11 2
 
0.4%
8 7
1.4%
7 5
1.0%

부속_건축물_수
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.512
Minimum0
Maximum20
Zeros391
Zeros (%)78.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:18.125056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.6183616
Coefficient of variation (CV)3.1608625
Kurtosis57.137326
Mean0.512
Median Absolute Deviation (MAD)0
Skewness6.4878519
Sum256
Variance2.6190942
MonotonicityNot monotonic
2024-04-21T16:17:18.334038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 391
78.2%
1 60
 
12.0%
2 25
 
5.0%
3 8
 
1.6%
4 4
 
0.8%
6 3
 
0.6%
5 2
 
0.4%
10 1
 
0.2%
9 1
 
0.2%
11 1
 
0.2%
Other values (4) 4
 
0.8%
ValueCountFrequency (%)
0 391
78.2%
1 60
 
12.0%
2 25
 
5.0%
3 8
 
1.6%
4 4
 
0.8%
5 2
 
0.4%
6 3
 
0.6%
7 1
 
0.2%
8 1
 
0.2%
9 1
 
0.2%
ValueCountFrequency (%)
20 1
 
0.2%
13 1
 
0.2%
11 1
 
0.2%
10 1
 
0.2%
9 1
 
0.2%
8 1
 
0.2%
7 1
 
0.2%
6 3
0.6%
5 2
0.4%
4 4
0.8%

부속_건축물_면적(㎡)
Real number (ℝ)

ZEROS 

Distinct116
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean315.41557
Minimum0
Maximum40667.695
Zeros381
Zeros (%)76.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:18.617108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile149.841
Maximum40667.695
Range40667.695
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2903.416
Coefficient of variation (CV)9.2050498
Kurtosis142.2239
Mean315.41557
Median Absolute Deviation (MAD)0
Skewness11.652831
Sum157707.78
Variance8429824.4
MonotonicityNot monotonic
2024-04-21T16:17:19.132097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 381
76.2%
18.0 4
 
0.8%
4.0 2
 
0.4%
685.74 1
 
0.2%
209.42 1
 
0.2%
290.78 1
 
0.2%
2.4 1
 
0.2%
25.26 1
 
0.2%
5.4 1
 
0.2%
26.44 1
 
0.2%
Other values (106) 106
 
21.2%
ValueCountFrequency (%)
0.0 381
76.2%
1.32 1
 
0.2%
1.44 1
 
0.2%
2.0 1
 
0.2%
2.25 1
 
0.2%
2.4 1
 
0.2%
2.52 1
 
0.2%
4.0 2
 
0.4%
4.13 1
 
0.2%
4.2 1
 
0.2%
ValueCountFrequency (%)
40667.6951 1
0.2%
34156.4794 1
0.2%
32545.324 1
0.2%
14360.474 1
0.2%
8889.07 1
0.2%
6883.28 1
0.2%
4991.98 1
0.2%
3538.58 1
0.2%
1451.26 1
0.2%
1056.3 1
0.2%

총_주차_수
Real number (ℝ)

ZEROS 

Distinct43
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.29
Minimum0
Maximum1008
Zeros366
Zeros (%)73.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:19.428405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile23.1
Maximum1008
Range1008
Interquartile range (IQR)1

Descriptive statistics

Standard deviation94.389834
Coefficient of variation (CV)5.4592154
Kurtosis55.36946
Mean17.29
Median Absolute Deviation (MAD)0
Skewness7.1074912
Sum8645
Variance8909.4408
MonotonicityNot monotonic
2024-04-21T16:17:19.710412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 366
73.2%
2 21
 
4.2%
4 13
 
2.6%
6 12
 
2.4%
8 11
 
2.2%
3 11
 
2.2%
1 10
 
2.0%
9 6
 
1.2%
5 5
 
1.0%
7 4
 
0.8%
Other values (33) 41
 
8.2%
ValueCountFrequency (%)
0 366
73.2%
1 10
 
2.0%
2 21
 
4.2%
3 11
 
2.2%
4 13
 
2.6%
5 5
 
1.0%
6 12
 
2.4%
7 4
 
0.8%
8 11
 
2.2%
9 6
 
1.2%
ValueCountFrequency (%)
1008 1
0.2%
896 1
0.2%
677 1
0.2%
660 1
0.2%
617 1
0.2%
532 1
0.2%
460 1
0.2%
449 1
0.2%
432 1
0.2%
411 1
0.2%

옥내_기계식_대수(대)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
498 
8
 
1
22
 
1

Length

Max length2
Median length1
Mean length1.002
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%
8 1
 
0.2%
22 1
 
0.2%

Length

2024-04-21T16:17:19.936079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:20.121637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 498
99.6%
8 1
 
0.2%
22 1
 
0.2%

옥내_기계식_면적(㎡)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0.0
499 
11.5
 
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%
11.5 1
 
0.2%

Length

2024-04-21T16:17:20.329518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:20.512851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 499
99.8%
11.5 1
 
0.2%

옥외_기계식_대수(대)
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

2024-04-21T16:17:20.684355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:20.861004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

옥외_기계식_면적(㎡)
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

2024-04-21T16:17:21.054272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:21.215111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

옥내_자주식_대수(대)
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.444
Minimum0
Maximum701
Zeros471
Zeros (%)94.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:21.369457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum701
Range701
Interquartile range (IQR)0

Descriptive statistics

Standard deviation51.585589
Coefficient of variation (CV)8.0052125
Kurtosis134.00212
Mean6.444
Median Absolute Deviation (MAD)0
Skewness11.013834
Sum3222
Variance2661.073
MonotonicityNot monotonic
2024-04-21T16:17:21.585721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 471
94.2%
3 3
 
0.6%
2 2
 
0.4%
281 1
 
0.2%
11 1
 
0.2%
96 1
 
0.2%
13 1
 
0.2%
12 1
 
0.2%
103 1
 
0.2%
4 1
 
0.2%
Other values (17) 17
 
3.4%
ValueCountFrequency (%)
0 471
94.2%
1 1
 
0.2%
2 2
 
0.4%
3 3
 
0.6%
4 1
 
0.2%
5 1
 
0.2%
7 1
 
0.2%
9 1
 
0.2%
10 1
 
0.2%
11 1
 
0.2%
ValueCountFrequency (%)
701 1
0.2%
685 1
0.2%
396 1
0.2%
281 1
0.2%
256 1
0.2%
156 1
0.2%
134 1
0.2%
114 1
0.2%
103 1
0.2%
96 1
0.2%

옥내_자주식_면적(㎡)
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean223.60763
Minimum0
Maximum38621.814
Zeros481
Zeros (%)96.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:21.834729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum38621.814
Range38621.814
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2212.098
Coefficient of variation (CV)9.8927662
Kurtosis201.03748
Mean223.60763
Median Absolute Deviation (MAD)0
Skewness13.223427
Sum111803.82
Variance4893377.7
MonotonicityNot monotonic
2024-04-21T16:17:22.053432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 481
96.2%
3989.15 1
 
0.2%
13400.686 1
 
0.2%
2638.35 1
 
0.2%
33.0 1
 
0.2%
219.2 1
 
0.2%
89.76 1
 
0.2%
11.5 1
 
0.2%
67.2 1
 
0.2%
767.48 1
 
0.2%
Other values (10) 10
 
2.0%
ValueCountFrequency (%)
0.0 481
96.2%
11.5 1
 
0.2%
33.0 1
 
0.2%
67.2 1
 
0.2%
80.5 1
 
0.2%
89.76 1
 
0.2%
92.0 1
 
0.2%
219.2 1
 
0.2%
241.5 1
 
0.2%
687.25 1
 
0.2%
ValueCountFrequency (%)
38621.8141 1
0.2%
19301.458 1
0.2%
14755.4077 1
0.2%
13400.686 1
0.2%
13114.84 1
0.2%
3989.15 1
0.2%
2945.59 1
0.2%
2638.35 1
0.2%
767.48 1
0.2%
747.13 1
0.2%

옥외_자주식_대수(대)
Real number (ℝ)

ZEROS 

Distinct38
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.436
Minimum0
Maximum641
Zeros371
Zeros (%)74.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:22.306147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile18
Maximum641
Range641
Interquartile range (IQR)1

Descriptive statistics

Standard deviation41.101442
Coefficient of variation (CV)6.3861781
Kurtosis154.81144
Mean6.436
Median Absolute Deviation (MAD)0
Skewness11.632241
Sum3218
Variance1689.3286
MonotonicityNot monotonic
2024-04-21T16:17:22.561515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 371
74.2%
1 21
 
4.2%
3 17
 
3.4%
2 17
 
3.4%
4 11
 
2.2%
5 7
 
1.4%
7 6
 
1.2%
6 4
 
0.8%
18 4
 
0.8%
8 4
 
0.8%
Other values (28) 38
 
7.6%
ValueCountFrequency (%)
0 371
74.2%
1 21
 
4.2%
2 17
 
3.4%
3 17
 
3.4%
4 11
 
2.2%
5 7
 
1.4%
6 4
 
0.8%
7 6
 
1.2%
8 4
 
0.8%
9 2
 
0.4%
ValueCountFrequency (%)
641 1
0.2%
482 1
0.2%
289 1
0.2%
191 1
0.2%
158 1
0.2%
145 1
0.2%
120 1
0.2%
118 1
0.2%
64 1
0.2%
55 1
0.2%

옥외_자주식_면적(㎡)
Real number (ℝ)

ZEROS 

Distinct48
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.764656
Minimum0
Maximum5980
Zeros371
Zeros (%)74.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:22.832399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q311.5
95-th percentile195.55
Maximum5980
Range5980
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation338.31884
Coefficient of variation (CV)6.0669045
Kurtosis203.67136
Mean55.764656
Median Absolute Deviation (MAD)0
Skewness12.962087
Sum27882.328
Variance114459.64
MonotonicityNot monotonic
2024-04-21T16:17:23.101087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0.0 371
74.2%
23.0 22
 
4.4%
34.5 19
 
3.8%
11.5 18
 
3.6%
57.5 10
 
2.0%
46.0 8
 
1.6%
69.0 4
 
0.8%
92.0 3
 
0.6%
80.5 2
 
0.4%
115.0 2
 
0.4%
Other values (38) 41
 
8.2%
ValueCountFrequency (%)
0.0 371
74.2%
11.5 18
 
3.6%
12.0 2
 
0.4%
12.5 1
 
0.2%
16.0 1
 
0.2%
23.0 22
 
4.4%
34.5 19
 
3.8%
46.0 8
 
1.6%
50.0 1
 
0.2%
57.5 10
 
2.0%
ValueCountFrequency (%)
5980.0 1
0.2%
3093.5 1
0.2%
1699.018 1
0.2%
1584.0 1
0.2%
1198.0 1
0.2%
1173.5 1
0.2%
1023.5 1
0.2%
920.0 1
0.2%
862.5 1
0.2%
661.4 1
0.2%

허가_일
Real number (ℝ)

MISSING 

Distinct131
Distinct (%)98.5%
Missing367
Missing (%)73.4%
Infinite0
Infinite (%)0.0%
Mean20074393
Minimum19690901
Maximum20150909
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:23.385962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19690901
5-th percentile19946757
Q120050930
median20090330
Q320120409
95-th percentile20141056
Maximum20150909
Range460008
Interquartile range (IQR)69479

Descriptive statistics

Standard deviation64866.636
Coefficient of variation (CV)0.0032313124
Kurtosis8.9777887
Mean20074393
Median Absolute Deviation (MAD)30782
Skewness-2.270403
Sum2.6698943 × 109
Variance4.2076805 × 109
MonotonicityNot monotonic
2024-04-21T16:17:23.684532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131126 2
 
0.4%
20051230 2
 
0.4%
20080804 1
 
0.2%
20140415 1
 
0.2%
19970916 1
 
0.2%
20141016 1
 
0.2%
20091014 1
 
0.2%
20040621 1
 
0.2%
20150904 1
 
0.2%
20130828 1
 
0.2%
Other values (121) 121
 
24.2%
(Missing) 367
73.4%
ValueCountFrequency (%)
19690901 1
0.2%
19890718 1
0.2%
19891011 1
0.2%
19930315 1
0.2%
19930525 1
0.2%
19940201 1
0.2%
19940503 1
0.2%
19950927 1
0.2%
19960515 1
0.2%
19960821 1
0.2%
ValueCountFrequency (%)
20150909 1
0.2%
20150904 1
0.2%
20150716 1
0.2%
20150410 1
0.2%
20150123 1
0.2%
20141121 1
0.2%
20141117 1
0.2%
20141016 1
0.2%
20141014 1
0.2%
20140415 1
0.2%

착공_일
Real number (ℝ)

MISSING 

Distinct137
Distinct (%)98.6%
Missing361
Missing (%)72.2%
Infinite0
Infinite (%)0.0%
Mean20091425
Minimum19950502
Maximum20160406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:23.993456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950502
5-th percentile19980884
Q120070410
median20101018
Q320130412
95-th percentile20150715
Maximum20160406
Range209904
Interquartile range (IQR)60002

Descriptive statistics

Standard deviation48394.917
Coefficient of variation (CV)0.0024087349
Kurtosis0.94047378
Mean20091425
Median Absolute Deviation (MAD)29891
Skewness-1.1397544
Sum2.7927081 × 109
Variance2.342068 × 109
MonotonicityNot monotonic
2024-04-21T16:17:24.281853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150827 2
 
0.4%
20090427 2
 
0.4%
20100330 1
 
0.2%
19980915 1
 
0.2%
20110905 1
 
0.2%
19980602 1
 
0.2%
20100621 1
 
0.2%
20130904 1
 
0.2%
20140822 1
 
0.2%
20130307 1
 
0.2%
Other values (127) 127
 
25.4%
(Missing) 361
72.2%
ValueCountFrequency (%)
19950502 1
0.2%
19950503 1
0.2%
19960202 1
0.2%
19961116 1
0.2%
19961211 1
0.2%
19970109 1
0.2%
19980602 1
0.2%
19980915 1
0.2%
19990127 1
0.2%
19991130 1
0.2%
ValueCountFrequency (%)
20160406 1
0.2%
20151203 1
0.2%
20151023 1
0.2%
20150827 2
0.4%
20150811 1
0.2%
20150728 1
0.2%
20150714 1
0.2%
20150710 1
0.2%
20150422 1
0.2%
20150121 1
0.2%

사용승인_일
Real number (ℝ)

MISSING 

Distinct159
Distinct (%)95.8%
Missing334
Missing (%)66.8%
Infinite0
Infinite (%)0.0%
Mean20065324
Minimum19320101
Maximum20160201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:24.538048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19320101
5-th percentile19900687
Q120041150
median20081070
Q320120814
95-th percentile20150184
Maximum20160201
Range840100
Interquartile range (IQR)79664

Descriptive statistics

Standard deviation94281.118
Coefficient of variation (CV)0.0046987091
Kurtosis25.045256
Mean20065324
Median Absolute Deviation (MAD)39755
Skewness-3.9777748
Sum3.3308437 × 109
Variance8.8889292 × 109
MonotonicityNot monotonic
2024-04-21T16:17:24.789904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080123 2
 
0.4%
20130710 2
 
0.4%
20141030 2
 
0.4%
20071207 2
 
0.4%
20140108 2
 
0.4%
20150213 2
 
0.4%
20110422 2
 
0.4%
20091008 1
 
0.2%
20091012 1
 
0.2%
20090710 1
 
0.2%
Other values (149) 149
29.8%
(Missing) 334
66.8%
ValueCountFrequency (%)
19320101 1
0.2%
19700920 1
0.2%
19701110 1
0.2%
19870101 1
0.2%
19881215 1
0.2%
19890712 1
0.2%
19900120 1
0.2%
19900608 1
0.2%
19900615 1
0.2%
19900903 1
0.2%
ValueCountFrequency (%)
20160201 1
0.2%
20151113 1
0.2%
20151023 1
0.2%
20150921 1
0.2%
20150630 1
0.2%
20150312 1
0.2%
20150213 2
0.4%
20150210 1
0.2%
20150105 1
0.2%
20141114 1
0.2%

허가번호_년
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)14.6%
Missing377
Missing (%)75.4%
Infinite0
Infinite (%)0.0%
Mean2009.2927
Minimum1992
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:25.008270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1992
5-th percentile2003.1
Q12007
median2010
Q32012.5
95-th percentile2015
Maximum2015
Range23
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation4.3263048
Coefficient of variation (CV)0.0021531481
Kurtosis2.230564
Mean2009.2927
Median Absolute Deviation (MAD)3
Skewness-1.1104872
Sum247143
Variance18.716913
MonotonicityNot monotonic
2024-04-21T16:17:25.232404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2012 16
 
3.2%
2014 13
 
2.6%
2009 12
 
2.4%
2008 11
 
2.2%
2004 10
 
2.0%
2015 10
 
2.0%
2007 9
 
1.8%
2013 8
 
1.6%
2010 8
 
1.6%
2006 8
 
1.6%
Other values (8) 18
 
3.6%
(Missing) 377
75.4%
ValueCountFrequency (%)
1992 1
 
0.2%
1994 1
 
0.2%
1996 1
 
0.2%
2001 1
 
0.2%
2002 1
 
0.2%
2003 2
 
0.4%
2004 10
2.0%
2005 4
 
0.8%
2006 8
1.6%
2007 9
1.8%
ValueCountFrequency (%)
2015 10
2.0%
2014 13
2.6%
2013 8
1.6%
2012 16
3.2%
2011 7
1.4%
2010 8
1.6%
2009 12
2.4%
2008 11
2.2%
2007 9
1.8%
2006 8
1.6%

허가번호_기관_코드
Real number (ℝ)

MISSING 

Distinct105
Distinct (%)88.2%
Missing381
Missing (%)76.2%
Infinite0
Infinite (%)0.0%
Mean4667571.8
Minimum3040087
Maximum6510033
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:25.489896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3040087
5-th percentile3596019.1
Q14080103.5
median4580075
Q35360086
95-th percentile5620008.8
Maximum6510033
Range3469946
Interquartile range (IQR)1279982.5

Descriptive statistics

Standard deviation718077.04
Coefficient of variation (CV)0.15384381
Kurtosis-0.81550893
Mean4667571.8
Median Absolute Deviation (MAD)589827
Skewness-0.033328463
Sum5.5544105 × 108
Variance5.1563463 × 1011
MonotonicityNot monotonic
2024-04-21T16:17:25.763828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5600104 4
 
0.8%
5530191 4
 
0.8%
5660007 3
 
0.6%
5360086 2
 
0.4%
3990248 2
 
0.4%
5540077 2
 
0.4%
3990184 2
 
0.4%
4580075 2
 
0.4%
3990155 2
 
0.4%
4280041 1
 
0.2%
Other values (95) 95
 
19.0%
(Missing) 381
76.2%
ValueCountFrequency (%)
3040087 1
0.2%
3110120 1
0.2%
3170148 1
0.2%
3390051 1
0.2%
3530106 1
0.2%
3560038 1
0.2%
3600017 1
0.2%
3620076 1
0.2%
3630127 1
0.2%
3640081 1
0.2%
ValueCountFrequency (%)
6510033 1
 
0.2%
5720011 1
 
0.2%
5660007 3
0.6%
5620025 1
 
0.2%
5620007 1
 
0.2%
5600104 4
0.8%
5600069 1
 
0.2%
5600055 1
 
0.2%
5590190 1
 
0.2%
5590146 1
 
0.2%
Distinct55
Distinct (%)40.4%
Missing364
Missing (%)72.8%
Memory size4.0 KiB
2024-04-21T16:17:26.465580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.9338235
Min length2

Characters and Unicode

Total characters535
Distinct characters68
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)28.7%

Sample

1st row허가민원과
2nd row건축과
3rd row민원봉사과
4th row도시건축과
5th row도시건축과
ValueCountFrequency (%)
건축과 45
33.1%
도시건축과 12
 
8.8%
허가민원과 6
 
4.4%
종합민원과 6
 
4.4%
민원봉사과 4
 
2.9%
지역개발과 3
 
2.2%
허가과 3
 
2.2%
민원처리과 2
 
1.5%
건축녹지과 2
 
1.5%
생태개발과 2
 
1.5%
Other values (45) 51
37.5%
2024-04-21T16:17:27.366559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
108
20.2%
68
12.7%
68
12.7%
28
 
5.2%
27
 
5.0%
17
 
3.2%
17
 
3.2%
15
 
2.8%
13
 
2.4%
12
 
2.2%
Other values (58) 162
30.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 532
99.4%
Decimal Number 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
108
20.3%
68
12.8%
68
12.8%
28
 
5.3%
27
 
5.1%
17
 
3.2%
17
 
3.2%
15
 
2.8%
13
 
2.4%
12
 
2.3%
Other values (56) 159
29.9%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 532
99.4%
Common 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
108
20.3%
68
12.8%
68
12.8%
28
 
5.3%
27
 
5.1%
17
 
3.2%
17
 
3.2%
15
 
2.8%
13
 
2.4%
12
 
2.3%
Other values (56) 159
29.9%
Common
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 532
99.4%
ASCII 3
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
108
20.3%
68
12.8%
68
12.8%
28
 
5.3%
27
 
5.1%
17
 
3.2%
17
 
3.2%
15
 
2.8%
13
 
2.4%
12
 
2.3%
Other values (56) 159
29.9%
ASCII
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%

허가번호_구분_코드
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)7.4%
Missing392
Missing (%)78.4%
Infinite0
Infinite (%)0.0%
Mean1308.6667
Minimum1101
Maximum5200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:27.564561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1101
5-th percentile1101
Q11101
median1102
Q31201
95-th percentile1786.35
Maximum5200
Range4099
Interquartile range (IQR)100

Descriptive statistics

Standard deviation764.59708
Coefficient of variation (CV)0.58425655
Kurtosis21.499902
Mean1308.6667
Median Absolute Deviation (MAD)1
Skewness4.7469451
Sum141336
Variance584608.69
MonotonicityNot monotonic
2024-04-21T16:17:27.750736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1101 47
 
9.4%
1201 29
 
5.8%
1202 14
 
2.8%
1102 11
 
2.2%
5100 3
 
0.6%
2101 2
 
0.4%
1108 1
 
0.2%
5200 1
 
0.2%
(Missing) 392
78.4%
ValueCountFrequency (%)
1101 47
9.4%
1102 11
 
2.2%
1108 1
 
0.2%
1201 29
5.8%
1202 14
 
2.8%
2101 2
 
0.4%
5100 3
 
0.6%
5200 1
 
0.2%
ValueCountFrequency (%)
5200 1
 
0.2%
5100 3
 
0.6%
2101 2
 
0.4%
1202 14
 
2.8%
1201 29
5.8%
1108 1
 
0.2%
1102 11
 
2.2%
1101 47
9.4%

허가번호_구분_코드_명
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
376 
신축허가
49 
신축신고
 
34
증축신고
 
22
증축허가
 
9
Other values (5)
 
10

Length

Max length12
Median length4
Mean length4.062
Min length4

Unique

Unique3 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 376
75.2%
신축허가 49
 
9.8%
신축신고 34
 
6.8%
증축신고 22
 
4.4%
증축허가 9
 
1.8%
협의건축물 4
 
0.8%
주택건설사업계획승인 3
 
0.6%
공용건축물 1
 
0.2%
개발제한구역내 건축허가 1
 
0.2%
개축신고 1
 
0.2%

Length

2024-04-21T16:17:27.997148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:28.218472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
75.0%
신축허가 49
 
9.8%
신축신고 34
 
6.8%
증축신고 22
 
4.4%
증축허가 9
 
1.8%
협의건축물 4
 
0.8%
주택건설사업계획승인 3
 
0.6%
공용건축물 1
 
0.2%
개발제한구역내 1
 
0.2%
건축허가 1
 
0.2%

호_수(호)
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.268
Minimum0
Maximum68
Zeros492
Zeros (%)98.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:28.685979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum68
Range68
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.2896534
Coefficient of variation (CV)12.274826
Kurtosis363.86982
Mean0.268
Median Absolute Deviation (MAD)0
Skewness18.135317
Sum134
Variance10.82182
MonotonicityNot monotonic
2024-04-21T16:17:28.884160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 492
98.4%
10 1
 
0.2%
14 1
 
0.2%
3 1
 
0.2%
68 1
 
0.2%
1 1
 
0.2%
16 1
 
0.2%
9 1
 
0.2%
13 1
 
0.2%
ValueCountFrequency (%)
0 492
98.4%
1 1
 
0.2%
3 1
 
0.2%
9 1
 
0.2%
10 1
 
0.2%
13 1
 
0.2%
14 1
 
0.2%
16 1
 
0.2%
68 1
 
0.2%
ValueCountFrequency (%)
68 1
 
0.2%
16 1
 
0.2%
14 1
 
0.2%
13 1
 
0.2%
10 1
 
0.2%
9 1
 
0.2%
3 1
 
0.2%
1 1
 
0.2%
0 492
98.4%

에너지_효율등급
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

에너지_절감률
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

2024-04-21T16:17:29.110683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:29.289464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

EPI_점수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
496 
73
 
1
72
 
1
63
 
1
69
 
1

Length

Max length2
Median length1
Mean length1.008
Min length1

Unique

Unique4 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 496
99.2%
73 1
 
0.2%
72 1
 
0.2%
63 1
 
0.2%
69 1
 
0.2%

Length

2024-04-21T16:17:29.484035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:29.675169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 496
99.2%
73 1
 
0.2%
72 1
 
0.2%
63 1
 
0.2%
69 1
 
0.2%

친환경_건축물_등급
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

친환경_건축물_인증점수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
499 
80
 
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%
80 1
 
0.2%

Length

2024-04-21T16:17:29.879037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:30.065078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 499
99.8%
80 1
 
0.2%

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

2024-04-21T16:17:30.259234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:17:30.414001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

생성_일자
Real number (ℝ)

Distinct194
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20118168
Minimum20090320
Maximum20160528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-21T16:17:30.612770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090320
5-th percentile20100417
Q120111021
median20111021
Q320130648
95-th percentile20150929
Maximum20160528
Range70208
Interquartile range (IQR)19626.75

Descriptive statistics

Standard deviation16867.251
Coefficient of variation (CV)0.00083840893
Kurtosis-0.12803121
Mean20118168
Median Absolute Deviation (MAD)9490.5
Skewness0.92843508
Sum1.0059084 × 1010
Variance2.8450417 × 108
MonotonicityNot monotonic
2024-04-21T16:17:30.913023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111021 137
27.4%
20100417 34
 
6.8%
20111117 31
 
6.2%
20111103 21
 
4.2%
20100421 9
 
1.8%
20111022 9
 
1.8%
20100105 8
 
1.6%
20140805 7
 
1.4%
20140731 7
 
1.4%
20100420 6
 
1.2%
Other values (184) 231
46.2%
ValueCountFrequency (%)
20090320 1
 
0.2%
20090321 1
 
0.2%
20090323 1
 
0.2%
20090325 3
0.6%
20090507 1
 
0.2%
20090711 1
 
0.2%
20090909 1
 
0.2%
20090926 1
 
0.2%
20091120 1
 
0.2%
20091126 1
 
0.2%
ValueCountFrequency (%)
20160528 1
0.2%
20160520 1
0.2%
20160518 1
0.2%
20160512 1
0.2%
20160511 1
0.2%
20160506 1
0.2%
20160428 1
0.2%
20160413 1
0.2%
20160401 1
0.2%
20160322 1
0.2%

Sample

관리_건축물대장_PK대장_구분_코드대장_구분_코드_명대장_종류_코드대장_종류_코드_명신_구_대장_구분_코드신_구_대장_구분_코드_명대지_위치도로명_대지_위치건물_명시군구_코드법정동_코드대지_구분_코드특수지_명블록로트외필지_수새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번대지_면적(㎡)건축_면적(㎡)건폐_율(%)연면적(㎡)용적_률_산정_연면적(㎡)용적_률(%)주_용도_코드주_용도_코드_명기타_용도세대_수(세대)가구_수(가구)주_건축물_수부속_건축물_수부속_건축물_면적(㎡)총_주차_수옥내_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
047730-3391일반1총괄표제부1신대장경기도 광명시 노온사동 2-1번지<NA><NA>282601050006483<NA><NA><NA>044133455056911301000546.0171.950.0184.14486.0257.5401000단독주택버섯재배사00200.0000.00000.0034.5<NA><NA>20030902<NA><NA>허가민원과<NA><NA>0<NA>00<NA>0<NA>020141013
141500-1001769081일반1총괄표제부1신대장제주특별자치도 제주시 영평동 2430-5번지울산광역시 울주군 공암공단3길 38<NA>4313010600017711<NA><NA><NA>0272603146009<NA>00420.0267.240.046.283977.4832.6702000공장<NA>013100.0000.00000.010.020140331<NA><NA><NA><NA>건축과1201<NA>0<NA>00<NA>0<NA>020111021
211410-4891일반1총괄표제부1구대장경상북도 영덕군 지품면 신안리 산 74번지<NA>가평향교43150310280365587<NA><NA><NA>0414804418122<NA>0322<NA>0.02338.4458.6648.271033.9920.274601000단독주택공장3320200.0000.00000.000.0<NA><NA><NA><NA><NA><NA>1102신축허가0<NA>00<NA>0<NA>020151219
331710-1001945351일반1총괄표제부1신대장경상북도 성주군 성주읍 용산리 191번지<NA><NA>415903803005801<NA><NA><NA>0487404823474370020<NA>00.0148.370.0338.0378.7831.7218000단독주택주택00208.643200.00000.00356.52006071120071120<NA><NA><NA>민원봉사과<NA><NA>0<NA>00<NA>0<NA>020111021
442730-1001830111일반1총괄표제부1신대장경상남도 하동군 횡천면 횡천리 572-1번지경상남도 남해군 남서대로1202번길 23<NA>11650109000935<NA><NA><NA>0415904430021<NA>0107201693.0170.69.7198.36120.240.017000단독주택단독주택002151.3000.00000.000.0<NA><NA><NA><NA><NA><NA><NA><NA>0<NA>00<NA>0<NA>020111021
511545-5241집합1총괄표제부1신대장전라남도 목포시 석현동 562-1번지<NA><NA>277103302202640<NA><NA><NA>4264103006032<NA>0111300.0723.8635.1955.595.6123.8402000창고시설다가구주택 및 창고03220.0000.00000.000.0<NA><NA>201509212002<NA><NA>1101신축신고0<NA>00<NA>0<NA>020100417
643130-8461일반1총괄표제부0신대장서울특별시 영등포구 신길동 산 109-1번지<NA><NA>4613034023011237<NA><NA><NA>0441504553575320010<NA><NA>0.0113.9825.94209.2542.970.004000동.식물관련시설노유자시설, 주택00202.0000.00000.02346.020150909<NA>20141114<NA><NA><NA>5100<NA>0<NA>00<NA>0<NA>020111021
727710-1001924261일반1총괄표제부0구대장전라남도 영광군 법성면 덕흥리 649-1번지경상남도 밀양시 상동가곡3길 33-4<NA>431303202301290<NA><NA><NA>0<NA><NA>0<NA>00.08586.80.0190.47105.790.0<NA>동.식물관련시설공장00090.0000.000480.000.0<NA>20130527<NA><NA><NA><NA>2101<NA>0<NA>00<NA>0<NA>020151130
826380-13681집합1총괄표제부1<NA>경상남도 진주시 일반성면 운천리 527번지충청북도 제천시 옥순봉로14길 181<NA>4421013800084415<NA><NA><NA>3<NA>3500203800.097.860.0109.29147.62143.7201000창고시설제2종근린생활시설,단독주택0050061.65000.00000.000.020110208<NA><NA><NA>5720011도시건축과1201신축신고0<NA>00<NA>0<NA>020140403
941220-13482일반1총괄표제부1구대장대구광역시 동구 방촌동 1119-1번지충청남도 서천군 서인로 656-40<NA>272603602808560<NA><NA><NA>028200425958033001060<NA>0.02113.077.064.26481.00.021000공장공장0115053.511700.00002945.5900.0<NA><NA>20090618<NA><NA><NA><NA>신축허가0<NA>00<NA>0<NA>020111021
관리_건축물대장_PK대장_구분_코드대장_구분_코드_명대장_종류_코드대장_종류_코드_명신_구_대장_구분_코드신_구_대장_구분_코드_명대지_위치도로명_대지_위치건물_명시군구_코드법정동_코드대지_구분_코드특수지_명블록로트외필지_수새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번대지_면적(㎡)건축_면적(㎡)건폐_율(%)연면적(㎡)용적_률_산정_연면적(㎡)용적_률(%)주_용도_코드주_용도_코드_명기타_용도세대_수(세대)가구_수(가구)주_건축물_수부속_건축물_수부속_건축물_면적(㎡)총_주차_수옥내_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
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