Overview

Dataset statistics

Number of variables43
Number of observations947
Missing cells13724
Missing cells (%)33.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory339.5 KiB
Average record size in memory367.1 B

Variable types

Text15
Categorical5
Numeric23

Dataset

Description사업번호,자치구,법정동,사업구분,운영구분,추진위원회/조합명,대표지번,진행단계,상태,정비구역명칭,정비구역위치,정비구역면적(㎡),건축연면적(㎡),용도지역,용도지구,택지면적(㎡),도로면적(㎡),공원면적(㎡),녹지면적(㎡),공공공지면적(㎡),학교면적(㎡),기타면적(㎡),주용도,건폐율,용적률,높이(m),지상층수,지하층수,건설세대총수,60미만건설세대수,60이상85이하건설세대수,85초과건설세대수,건축계획비고,위치도,조감도,배치도
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-2253/S/1/datasetView.do

Alerts

정비구역명칭 has 166 (17.5%) missing valuesMissing
정비구역위치 has 167 (17.6%) missing valuesMissing
정비구역면적(㎡) has 183 (19.3%) missing valuesMissing
건축연면적(㎡) has 303 (32.0%) missing valuesMissing
용도지역 has 241 (25.4%) missing valuesMissing
용도지구 has 465 (49.1%) missing valuesMissing
택지면적(㎡) has 345 (36.4%) missing valuesMissing
도로면적(㎡) has 384 (40.5%) missing valuesMissing
공원면적(㎡) has 492 (52.0%) missing valuesMissing
녹지면적(㎡) has 687 (72.5%) missing valuesMissing
공공공지면적(㎡) has 688 (72.7%) missing valuesMissing
학교면적(㎡) has 742 (78.4%) missing valuesMissing
기타면적(㎡) has 653 (69.0%) missing valuesMissing
주용도 has 255 (26.9%) missing valuesMissing
건폐율 has 234 (24.7%) missing valuesMissing
용적률 has 229 (24.2%) missing valuesMissing
높이(m) has 412 (43.5%) missing valuesMissing
지상층수 has 268 (28.3%) missing valuesMissing
지하층수 has 291 (30.7%) missing valuesMissing
분양세대총수 has 549 (58.0%) missing valuesMissing
60㎡이하 has 306 (32.3%) missing valuesMissing
60㎡초과~85㎡이하 has 302 (31.9%) missing valuesMissing
85㎡초과 has 504 (53.2%) missing valuesMissing
임대세대총수 has 793 (83.7%) missing valuesMissing
(임대)40㎡이하 has 695 (73.4%) missing valuesMissing
(임대)40㎡초과~50㎡이하 has 652 (68.8%) missing valuesMissing
(임대)50㎡초과 has 600 (63.4%) missing valuesMissing
건축계획비고 has 859 (90.7%) missing valuesMissing
위치도 has 200 (21.1%) missing valuesMissing
조감도 has 319 (33.7%) missing valuesMissing
배치도 has 296 (31.3%) missing valuesMissing
조합사무실 주소 has 244 (25.8%) missing valuesMissing
조합사무실 전화번호 has 200 (21.1%) missing valuesMissing
정비구역면적(㎡) is highly skewed (γ1 = 27.51800509)Skewed
건축연면적(㎡) is highly skewed (γ1 = 23.31761252)Skewed
지상층수 is highly skewed (γ1 = 26.02010673)Skewed
60㎡이하 is highly skewed (γ1 = 23.60238185)Skewed
사업번호 has unique valuesUnique
토지등 소유자 수 has 160 (16.9%) zerosZeros
도로면적(㎡) has 32 (3.4%) zerosZeros
공원면적(㎡) has 57 (6.0%) zerosZeros
녹지면적(㎡) has 121 (12.8%) zerosZeros
공공공지면적(㎡) has 121 (12.8%) zerosZeros
학교면적(㎡) has 153 (16.2%) zerosZeros
기타면적(㎡) has 102 (10.8%) zerosZeros
높이(m) has 10 (1.1%) zerosZeros

Reproduction

Analysis started2024-05-11 08:20:34.776235
Analysis finished2024-05-11 08:20:36.213672
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업번호
Text

UNIQUE 

Distinct947
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-05-11T17:20:36.333400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters14205
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

Unique947 ?
Unique (%)100.0%

Sample

1st row11260-900000932
2nd row11380-900000892
3rd row11305-900001150
4th row11290-900000971
5th row11320-900001118
ValueCountFrequency (%)
11260-900000932 1
 
0.1%
11650-100002018 1
 
0.1%
11380-900000018 1
 
0.1%
11590-100002011 1
 
0.1%
11170-100003006 1
 
0.1%
11290-900000803 1
 
0.1%
11440-900000801 1
 
0.1%
11650-900000605 1
 
0.1%
11290-900000159 1
 
0.1%
11215-900000150 1
 
0.1%
Other values (937) 937
98.9%
2024-05-11T17:20:36.630244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6045
42.6%
1 3088
21.7%
9 951
 
6.7%
- 947
 
6.7%
5 641
 
4.5%
2 526
 
3.7%
6 522
 
3.7%
4 413
 
2.9%
3 407
 
2.9%
7 373
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13258
93.3%
Dash Punctuation 947
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6045
45.6%
1 3088
23.3%
9 951
 
7.2%
5 641
 
4.8%
2 526
 
4.0%
6 522
 
3.9%
4 413
 
3.1%
3 407
 
3.1%
7 373
 
2.8%
8 292
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 947
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14205
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6045
42.6%
1 3088
21.7%
9 951
 
6.7%
- 947
 
6.7%
5 641
 
4.5%
2 526
 
3.7%
6 522
 
3.7%
4 413
 
2.9%
3 407
 
2.9%
7 373
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14205
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6045
42.6%
1 3088
21.7%
9 951
 
6.7%
- 947
 
6.7%
5 641
 
4.5%
2 526
 
3.7%
6 522
 
3.7%
4 413
 
2.9%
3 407
 
2.9%
7 373
 
2.6%

자치구
Categorical

Distinct25
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
영등포구
120 
성북구
70 
서초구
65 
송파구
 
53
동작구
 
47
Other values (20)
592 

Length

Max length4
Median length3
Mean length3.2090813
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중랑구
2nd row은평구
3rd row강북구
4th row성북구
5th row도봉구

Common Values

ValueCountFrequency (%)
영등포구 120
 
12.7%
성북구 70
 
7.4%
서초구 65
 
6.9%
송파구 53
 
5.6%
동작구 47
 
5.0%
동대문구 46
 
4.9%
강동구 42
 
4.4%
서대문구 42
 
4.4%
용산구 41
 
4.3%
강남구 41
 
4.3%
Other values (15) 380
40.1%

Length

2024-05-11T17:20:36.761343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영등포구 120
 
12.7%
성북구 70
 
7.4%
서초구 65
 
6.9%
송파구 53
 
5.6%
동작구 47
 
5.0%
동대문구 46
 
4.9%
강동구 42
 
4.4%
서대문구 42
 
4.4%
용산구 41
 
4.3%
강남구 41
 
4.3%
Other values (15) 380
40.1%
Distinct185
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-05-11T17:20:37.019328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.1214361
Min length2

Characters and Unicode

Total characters2956
Distinct characters163
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

Unique44 ?
Unique (%)4.6%

Sample

1st row면목동
2nd row갈현동
3rd row미아동
4th row장위동
5th row쌍문동
ValueCountFrequency (%)
신길동 35
 
3.7%
영등포동 31
 
3.3%
잠원동 22
 
2.3%
장위동 21
 
2.2%
면목동 20
 
2.1%
미아동 20
 
2.1%
여의도동 18
 
1.9%
방배동 18
 
1.9%
천호동 15
 
1.6%
정릉동 14
 
1.5%
Other values (175) 733
77.4%
2024-05-11T17:20:37.390850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
936
31.7%
93
 
3.1%
54
 
1.8%
46
 
1.6%
44
 
1.5%
41
 
1.4%
39
 
1.3%
36
 
1.2%
35
 
1.2%
35
 
1.2%
Other values (153) 1597
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2940
99.5%
Decimal Number 16
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
936
31.8%
93
 
3.2%
54
 
1.8%
46
 
1.6%
44
 
1.5%
41
 
1.4%
39
 
1.3%
36
 
1.2%
35
 
1.2%
35
 
1.2%
Other values (148) 1581
53.8%
Decimal Number
ValueCountFrequency (%)
3 7
43.8%
2 4
25.0%
1 2
 
12.5%
4 2
 
12.5%
6 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2940
99.5%
Common 16
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
936
31.8%
93
 
3.2%
54
 
1.8%
46
 
1.6%
44
 
1.5%
41
 
1.4%
39
 
1.3%
36
 
1.2%
35
 
1.2%
35
 
1.2%
Other values (148) 1581
53.8%
Common
ValueCountFrequency (%)
3 7
43.8%
2 4
25.0%
1 2
 
12.5%
4 2
 
12.5%
6 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2940
99.5%
ASCII 16
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
936
31.8%
93
 
3.2%
54
 
1.8%
46
 
1.6%
44
 
1.5%
41
 
1.4%
39
 
1.3%
36
 
1.2%
35
 
1.2%
35
 
1.2%
Other values (148) 1581
53.8%
ASCII
ValueCountFrequency (%)
3 7
43.8%
2 4
25.0%
1 2
 
12.5%
4 2
 
12.5%
6 1
 
6.2%

사업구분
Categorical

Distinct7
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
재건축
342 
재개발(주택정비형)
260 
가로주택정비
135 
재개발(도시정비형)
115 
지역주택
56 
Other values (2)
39 

Length

Max length10
Median length6
Mean length6.3569166
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가로주택정비
2nd row가로주택정비
3rd row재개발(주택정비형)
4th row가로주택정비
5th row지역주택

Common Values

ValueCountFrequency (%)
재건축 342
36.1%
재개발(주택정비형) 260
27.5%
가로주택정비 135
 
14.3%
재개발(도시정비형) 115
 
12.1%
지역주택 56
 
5.9%
소규모재건축 27
 
2.9%
리모델링 12
 
1.3%

Length

2024-05-11T17:20:37.544883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:20:37.663405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재건축 342
36.1%
재개발(주택정비형 260
27.5%
가로주택정비 135
 
14.3%
재개발(도시정비형 115
 
12.1%
지역주택 56
 
5.9%
소규모재건축 27
 
2.9%
리모델링 12
 
1.3%

운영구분
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
조합
689 
공공지원자
114 
추진위원회
94 
조합청산
 
50

Length

Max length5
Median length2
Mean length2.7645195
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조합
2nd row조합
3rd row공공지원자
4th row조합
5th row조합

Common Values

ValueCountFrequency (%)
조합 689
72.8%
공공지원자 114
 
12.0%
추진위원회 94
 
9.9%
조합청산 50
 
5.3%

Length

2024-05-11T17:20:37.787798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:20:37.880904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조합 689
72.8%
공공지원자 114
 
12.0%
추진위원회 94
 
9.9%
조합청산 50
 
5.3%
Distinct945
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-05-11T17:20:38.054055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length31
Mean length19.462513
Min length4

Characters and Unicode

Total characters18431
Distinct characters302
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique943 ?
Unique (%)99.6%

Sample

1st row면목역6구역 가로주택정비사업
2nd row갈현동 이화연립일원 가로주택정비사업
3rd row미아동 791-2882번지 일대 주택정비형 재개발사업
4th row장위11의4구역 가로주택정비사업조합
5th row쌍문동137번지 지역주택조합
ValueCountFrequency (%)
조합 161
 
6.8%
주택재개발정비사업조합 95
 
4.0%
주택재건축정비사업조합 93
 
3.9%
가로주택정비사업 92
 
3.9%
주택재건축정비사업 66
 
2.8%
재건축정비사업 51
 
2.2%
주택재개발정비사업 48
 
2.0%
일대 44
 
1.9%
조합설립추진위원회 44
 
1.9%
재건축정비사업조합 37
 
1.6%
Other values (1165) 1630
69.0%
2024-05-11T17:20:38.376993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1424
 
7.7%
959
 
5.2%
911
 
4.9%
821
 
4.5%
810
 
4.4%
765
 
4.2%
700
 
3.8%
691
 
3.7%
681
 
3.7%
653
 
3.5%
Other values (292) 10016
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15408
83.6%
Space Separator 1424
 
7.7%
Decimal Number 1239
 
6.7%
Dash Punctuation 114
 
0.6%
Close Punctuation 90
 
0.5%
Open Punctuation 89
 
0.5%
Other Punctuation 54
 
0.3%
Uppercase Letter 9
 
< 0.1%
Other Number 3
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
959
 
6.2%
911
 
5.9%
821
 
5.3%
810
 
5.3%
765
 
5.0%
700
 
4.5%
691
 
4.5%
681
 
4.4%
653
 
4.2%
527
 
3.4%
Other values (264) 7890
51.2%
Decimal Number
ValueCountFrequency (%)
1 361
29.1%
2 209
16.9%
3 162
13.1%
4 121
 
9.8%
5 97
 
7.8%
6 82
 
6.6%
7 65
 
5.2%
8 51
 
4.1%
0 48
 
3.9%
9 43
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
22.2%
A 2
22.2%
E 1
11.1%
S 1
11.1%
H 1
11.1%
L 1
11.1%
B 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 30
55.6%
, 14
25.9%
? 10
 
18.5%
Other Number
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Space Separator
ValueCountFrequency (%)
1424
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 89
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15408
83.6%
Common 3014
 
16.4%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
959
 
6.2%
911
 
5.9%
821
 
5.3%
810
 
5.3%
765
 
5.0%
700
 
4.5%
691
 
4.5%
681
 
4.4%
653
 
4.2%
527
 
3.4%
Other values (264) 7890
51.2%
Common
ValueCountFrequency (%)
1424
47.2%
1 361
 
12.0%
2 209
 
6.9%
3 162
 
5.4%
4 121
 
4.0%
- 114
 
3.8%
5 97
 
3.2%
) 90
 
3.0%
( 89
 
3.0%
6 82
 
2.7%
Other values (11) 265
 
8.8%
Latin
ValueCountFrequency (%)
T 2
22.2%
A 2
22.2%
E 1
11.1%
S 1
11.1%
H 1
11.1%
L 1
11.1%
B 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15408
83.6%
ASCII 3020
 
16.4%
Enclosed Alphanum 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1424
47.2%
1 361
 
12.0%
2 209
 
6.9%
3 162
 
5.4%
4 121
 
4.0%
- 114
 
3.8%
5 97
 
3.2%
) 90
 
3.0%
( 89
 
2.9%
6 82
 
2.7%
Other values (15) 271
 
9.0%
Hangul
ValueCountFrequency (%)
959
 
6.2%
911
 
5.9%
821
 
5.3%
810
 
5.3%
765
 
5.0%
700
 
4.5%
691
 
4.5%
681
 
4.4%
653
 
4.2%
527
 
3.4%
Other values (264) 7890
51.2%
Enclosed Alphanum
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Distinct933
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-05-11T17:20:38.657367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.7961985
Min length5

Characters and Unicode

Total characters8330
Distinct characters170
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

Unique919 ?
Unique (%)97.0%

Sample

1st row면목동 86-19
2nd row갈현동 259-7
3rd row미아동 791-2882
4th row장위동 66-146
5th row쌍문동 137-94
ValueCountFrequency (%)
신길동 35
 
1.8%
잠원동 22
 
1.2%
장위동 21
 
1.1%
면목동 20
 
1.1%
미아동 20
 
1.1%
여의도동 18
 
1.0%
방배동 18
 
1.0%
천호동 15
 
0.8%
반포동 14
 
0.7%
홍은동 14
 
0.7%
Other values (1073) 1697
89.6%
2024-05-11T17:20:39.064917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
948
 
11.4%
936
 
11.2%
1 728
 
8.7%
- 654
 
7.9%
2 489
 
5.9%
3 475
 
5.7%
4 380
 
4.6%
5 330
 
4.0%
6 295
 
3.5%
0 276
 
3.3%
Other values (160) 2819
33.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3701
44.4%
Other Letter 3027
36.3%
Space Separator 948
 
11.4%
Dash Punctuation 654
 
7.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
936
30.9%
133
 
4.4%
93
 
3.1%
54
 
1.8%
44
 
1.5%
41
 
1.4%
39
 
1.3%
36
 
1.2%
35
 
1.2%
35
 
1.2%
Other values (148) 1581
52.2%
Decimal Number
ValueCountFrequency (%)
1 728
19.7%
2 489
13.2%
3 475
12.8%
4 380
10.3%
5 330
8.9%
6 295
8.0%
0 276
 
7.5%
7 252
 
6.8%
8 242
 
6.5%
9 234
 
6.3%
Space Separator
ValueCountFrequency (%)
948
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 654
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5303
63.7%
Hangul 3027
36.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
936
30.9%
133
 
4.4%
93
 
3.1%
54
 
1.8%
44
 
1.5%
41
 
1.4%
39
 
1.3%
36
 
1.2%
35
 
1.2%
35
 
1.2%
Other values (148) 1581
52.2%
Common
ValueCountFrequency (%)
948
17.9%
1 728
13.7%
- 654
12.3%
2 489
9.2%
3 475
9.0%
4 380
7.2%
5 330
 
6.2%
6 295
 
5.6%
0 276
 
5.2%
7 252
 
4.8%
Other values (2) 476
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5303
63.7%
Hangul 3027
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
948
17.9%
1 728
13.7%
- 654
12.3%
2 489
9.2%
3 475
9.0%
4 380
7.2%
5 330
 
6.2%
6 295
 
5.6%
0 276
 
5.2%
7 252
 
4.8%
Other values (2) 476
9.0%
Hangul
ValueCountFrequency (%)
936
30.9%
133
 
4.4%
93
 
3.1%
54
 
1.8%
44
 
1.5%
41
 
1.4%
39
 
1.3%
36
 
1.2%
35
 
1.2%
35
 
1.2%
Other values (148) 1581
52.2%

진행단계
Categorical

Distinct14
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
조합설립인가
335 
조합해산
101 
조합설립추진위원회승인
94 
정비계획 수립
64 
사업시행인가
57 
Other values (9)
296 

Length

Max length11
Median length6
Mean length5.9429778
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조합설립인가
2nd row조합설립인가
3rd row정비계획 수립
4th row조합설립인가
5th row조합설립인가

Common Values

ValueCountFrequency (%)
조합설립인가 335
35.4%
조합해산 101
 
10.7%
조합설립추진위원회승인 94
 
9.9%
정비계획 수립 64
 
6.8%
사업시행인가 57
 
6.0%
관리처분인가 52
 
5.5%
이전고시 52
 
5.5%
조합청산 50
 
5.3%
착공신고 49
 
5.2%
정비구역지정 37
 
3.9%
Other values (4) 56
 
5.9%

Length

2024-05-11T17:20:39.210846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조합설립인가 335
33.1%
조합해산 101
 
10.0%
조합설립추진위원회승인 94
 
9.3%
정비계획 64
 
6.3%
수립 64
 
6.3%
사업시행인가 57
 
5.6%
관리처분인가 52
 
5.1%
이전고시 52
 
5.1%
조합청산 50
 
4.9%
착공신고 49
 
4.8%
Other values (5) 93
 
9.2%

상태
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
운영
822 
일시중단
125 

Length

Max length4
Median length2
Mean length2.2639916
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영 822
86.8%
일시중단 125
 
13.2%

Length

2024-05-11T17:20:39.331003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:20:39.428087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영 822
86.8%
일시중단 125
 
13.2%

토지등 소유자 수
Real number (ℝ)

ZEROS 

Distinct517
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean380.32735
Minimum0
Maximum6875
Zeros160
Zeros (%)16.9%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:39.536516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q141.5
median164
Q3480.5
95-th percentile1452.5
Maximum6875
Range6875
Interquartile range (IQR)439

Descriptive statistics

Standard deviation618.45366
Coefficient of variation (CV)1.6261088
Kurtosis32.118215
Mean380.32735
Median Absolute Deviation (MAD)164
Skewness4.5820242
Sum360170
Variance382484.93
MonotonicityNot monotonic
2024-05-11T17:20:39.673195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 160
 
16.9%
60 7
 
0.7%
66 6
 
0.6%
33 6
 
0.6%
18 6
 
0.6%
95 6
 
0.6%
73 5
 
0.5%
17 5
 
0.5%
106 5
 
0.5%
30 5
 
0.5%
Other values (507) 736
77.7%
ValueCountFrequency (%)
0 160
16.9%
1 3
 
0.3%
6 1
 
0.1%
7 1
 
0.1%
9 1
 
0.1%
10 1
 
0.1%
12 1
 
0.1%
14 2
 
0.2%
15 1
 
0.1%
16 2
 
0.2%
ValueCountFrequency (%)
6875 1
0.1%
6240 1
0.1%
5236 1
0.1%
4830 1
0.1%
4076 1
0.1%
4062 1
0.1%
3887 1
0.1%
2930 1
0.1%
2852 1
0.1%
2676 1
0.1%

정비구역명칭
Text

MISSING 

Distinct776
Distinct (%)99.4%
Missing166
Missing (%)17.5%
Memory size7.5 KiB
2024-05-11T17:20:39.885970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length29
Mean length17.09219
Min length4

Characters and Unicode

Total characters13349
Distinct characters280
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique772 ?
Unique (%)98.8%

Sample

1st row면목역6구역 가로주택정비사업
2nd row갈현동 이화연립일원 가로주택정비사업
3rd row장위11의4구역 가로주택정비사업
4th row쌍문동137번지 지역주택조합
5th row(가칭)신대방역2단지 지역주택조합
ValueCountFrequency (%)
가로주택정비사업 79
 
4.8%
주택재건축정비사업 68
 
4.2%
정비사업 33
 
2.0%
주택재건축 32
 
2.0%
주택재개발정비사업조합 32
 
2.0%
재정비촉진구역 30
 
1.8%
재건축정비사업 27
 
1.6%
주택재개발정비사업 27
 
1.6%
일대 24
 
1.5%
지역주택조합 20
 
1.2%
Other values (959) 1265
77.3%
2024-05-11T17:20:40.269558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
867
 
6.5%
742
 
5.6%
707
 
5.3%
628
 
4.7%
553
 
4.1%
550
 
4.1%
540
 
4.0%
525
 
3.9%
525
 
3.9%
517
 
3.9%
Other values (270) 7195
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11326
84.8%
Decimal Number 949
 
7.1%
Space Separator 867
 
6.5%
Dash Punctuation 86
 
0.6%
Open Punctuation 51
 
0.4%
Close Punctuation 51
 
0.4%
Other Punctuation 12
 
0.1%
Uppercase Letter 3
 
< 0.1%
Other Number 3
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
742
 
6.6%
707
 
6.2%
628
 
5.5%
553
 
4.9%
550
 
4.9%
540
 
4.8%
525
 
4.6%
525
 
4.6%
517
 
4.6%
311
 
2.7%
Other values (244) 5728
50.6%
Decimal Number
ValueCountFrequency (%)
1 303
31.9%
2 156
16.4%
3 125
13.2%
4 90
 
9.5%
5 75
 
7.9%
6 57
 
6.0%
7 44
 
4.6%
8 36
 
3.8%
0 34
 
3.6%
9 29
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 7
58.3%
? 4
33.3%
/ 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
P 1
33.3%
T 1
33.3%
Other Number
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 50
98.0%
[ 1
 
2.0%
Close Punctuation
ValueCountFrequency (%)
) 50
98.0%
] 1
 
2.0%
Space Separator
ValueCountFrequency (%)
867
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11326
84.8%
Common 2020
 
15.1%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
742
 
6.6%
707
 
6.2%
628
 
5.5%
553
 
4.9%
550
 
4.9%
540
 
4.8%
525
 
4.6%
525
 
4.6%
517
 
4.6%
311
 
2.7%
Other values (244) 5728
50.6%
Common
ValueCountFrequency (%)
867
42.9%
1 303
 
15.0%
2 156
 
7.7%
3 125
 
6.2%
4 90
 
4.5%
- 86
 
4.3%
5 75
 
3.7%
6 57
 
2.8%
( 50
 
2.5%
) 50
 
2.5%
Other values (13) 161
 
8.0%
Latin
ValueCountFrequency (%)
A 1
33.3%
P 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11325
84.8%
ASCII 2020
 
15.1%
Enclosed Alphanum 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
867
42.9%
1 303
 
15.0%
2 156
 
7.7%
3 125
 
6.2%
4 90
 
4.5%
- 86
 
4.3%
5 75
 
3.7%
6 57
 
2.8%
( 50
 
2.5%
) 50
 
2.5%
Other values (13) 161
 
8.0%
Hangul
ValueCountFrequency (%)
742
 
6.6%
707
 
6.2%
628
 
5.5%
553
 
4.9%
550
 
4.9%
540
 
4.8%
525
 
4.6%
525
 
4.6%
517
 
4.6%
311
 
2.7%
Other values (243) 5727
50.6%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

정비구역위치
Text

MISSING 

Distinct776
Distinct (%)99.5%
Missing167
Missing (%)17.6%
Memory size7.5 KiB
2024-05-11T17:20:40.613881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length14.40641
Min length5

Characters and Unicode

Total characters11237
Distinct characters212
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

Unique772 ?
Unique (%)99.0%

Sample

1st row중랑구 면목동 86-19
2nd row은평구 갈현동 259-7
3rd row성북구 장위동 66-146
4th row도봉구 쌍문동 137-94외 5필지
5th row관악구 신림동 475-83
ValueCountFrequency (%)
서초구 56
 
2.4%
성북구 55
 
2.3%
영등포구 45
 
1.9%
동대문구 40
 
1.7%
동작구 39
 
1.6%
송파구 37
 
1.6%
강남구 36
 
1.5%
중랑구 35
 
1.5%
서대문구 33
 
1.4%
용산구 33
 
1.4%
Other values (1087) 1961
82.7%
2024-05-11T17:20:41.159132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1627
 
14.5%
906
 
8.1%
741
 
6.6%
1 636
 
5.7%
- 573
 
5.1%
2 446
 
4.0%
3 407
 
3.6%
355
 
3.2%
331
 
2.9%
4 322
 
2.9%
Other values (202) 4893
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5697
50.7%
Decimal Number 3297
29.3%
Space Separator 1627
 
14.5%
Dash Punctuation 573
 
5.1%
Open Punctuation 16
 
0.1%
Close Punctuation 15
 
0.1%
Other Punctuation 8
 
0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
906
 
15.9%
741
 
13.0%
355
 
6.2%
331
 
5.8%
139
 
2.4%
127
 
2.2%
126
 
2.2%
113
 
2.0%
103
 
1.8%
101
 
1.8%
Other values (182) 2655
46.6%
Decimal Number
ValueCountFrequency (%)
1 636
19.3%
2 446
13.5%
3 407
12.3%
4 322
9.8%
0 316
9.6%
5 294
8.9%
6 259
7.9%
7 208
 
6.3%
9 207
 
6.3%
8 202
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
P 1
25.0%
B 1
25.0%
A 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
. 2
 
25.0%
Space Separator
ValueCountFrequency (%)
1627
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 573
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5697
50.7%
Common 5536
49.3%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
906
 
15.9%
741
 
13.0%
355
 
6.2%
331
 
5.8%
139
 
2.4%
127
 
2.2%
126
 
2.2%
113
 
2.0%
103
 
1.8%
101
 
1.8%
Other values (182) 2655
46.6%
Common
ValueCountFrequency (%)
1627
29.4%
1 636
 
11.5%
- 573
 
10.4%
2 446
 
8.1%
3 407
 
7.4%
4 322
 
5.8%
0 316
 
5.7%
5 294
 
5.3%
6 259
 
4.7%
7 208
 
3.8%
Other values (6) 448
 
8.1%
Latin
ValueCountFrequency (%)
T 1
25.0%
P 1
25.0%
B 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5697
50.7%
ASCII 5540
49.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1627
29.4%
1 636
 
11.5%
- 573
 
10.3%
2 446
 
8.1%
3 407
 
7.3%
4 322
 
5.8%
0 316
 
5.7%
5 294
 
5.3%
6 259
 
4.7%
7 208
 
3.8%
Other values (10) 452
 
8.2%
Hangul
ValueCountFrequency (%)
906
 
15.9%
741
 
13.0%
355
 
6.2%
331
 
5.8%
139
 
2.4%
127
 
2.2%
126
 
2.2%
113
 
2.0%
103
 
1.8%
101
 
1.8%
Other values (182) 2655
46.6%

정비구역면적(㎡)
Real number (ℝ)

MISSING  SKEWED 

Distinct758
Distinct (%)99.2%
Missing183
Missing (%)19.3%
Infinite0
Infinite (%)0.0%
Mean81088.759
Minimum128.7
Maximum29884000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:41.339031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.7
5-th percentile2159.015
Q18157
median22829.85
Q354412.375
95-th percentile145282.7
Maximum29884000
Range29883871
Interquartile range (IQR)46255.375

Descriptive statistics

Standard deviation1081248.8
Coefficient of variation (CV)13.334139
Kurtosis759.45856
Mean81088.759
Median Absolute Deviation (MAD)16699.5
Skewness27.518005
Sum61951812
Variance1.1690989 × 1012
MonotonicityNot monotonic
2024-05-11T17:20:41.495297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8486.0 2
 
0.2%
6801.4 2
 
0.2%
45229.0 2
 
0.2%
3437.0 2
 
0.2%
9123.9 2
 
0.2%
11084.0 2
 
0.2%
37334.7 1
 
0.1%
89828.0 1
 
0.1%
102371.6 1
 
0.1%
25109.6 1
 
0.1%
Other values (748) 748
79.0%
(Missing) 183
 
19.3%
ValueCountFrequency (%)
128.7 1
0.1%
182.35 1
0.1%
229.34 1
0.1%
314.65 1
0.1%
316.68 1
0.1%
587.47 1
0.1%
643.4 1
0.1%
789.87 1
0.1%
851.07 1
0.1%
903.0 1
0.1%
ValueCountFrequency (%)
29884000.0 1
0.1%
626232.5 1
0.1%
405782.4 1
0.1%
399741.7 1
0.1%
393729.0 1
0.1%
370484.0 1
0.1%
360187.8 1
0.1%
358077.0 1
0.1%
343266.7 1
0.1%
284637.5 1
0.1%

건축연면적(㎡)
Real number (ℝ)

MISSING  SKEWED 

Distinct639
Distinct (%)99.2%
Missing303
Missing (%)32.0%
Infinite0
Infinite (%)0.0%
Mean3382194.9
Minimum0
Maximum1.4485231 × 109
Zeros3
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:41.657438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7595.521
Q132723.745
median85713.63
Q3183807.27
95-th percentile619073.77
Maximum1.4485231 × 109
Range1.4485231 × 109
Interquartile range (IQR)151083.53

Descriptive statistics

Standard deviation58917170
Coefficient of variation (CV)17.419803
Kurtosis566.76193
Mean3382194.9
Median Absolute Deviation (MAD)62156.655
Skewness23.317613
Sum2.1781335 × 109
Variance3.4712329 × 1015
MonotonicityNot monotonic
2024-05-11T17:20:41.806738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
0.3%
137512.95 2
 
0.2%
23626.33 2
 
0.2%
38550.46 2
 
0.2%
153551.2 1
 
0.1%
158701.3 1
 
0.1%
34415.0 1
 
0.1%
134756.53 1
 
0.1%
72901.14 1
 
0.1%
133959.52 1
 
0.1%
Other values (629) 629
66.4%
(Missing) 303
32.0%
ValueCountFrequency (%)
0.0 3
0.3%
83.25 1
 
0.1%
833.35 1
 
0.1%
878.4 1
 
0.1%
1051.31 1
 
0.1%
2072.58 1
 
0.1%
2260.12 1
 
0.1%
2719.05 1
 
0.1%
3273.98 1
 
0.1%
3274.5 1
 
0.1%
ValueCountFrequency (%)
1448523147.78 1
0.1%
330946838.67 1
0.1%
135077122.97 1
0.1%
113325911.59 1
0.1%
14911391.98 1
0.1%
11418990.28 1
0.1%
6579239.88 1
0.1%
5824773.86 1
0.1%
4777589.18 1
0.1%
3105205.8 1
0.1%

용도지역
Text

MISSING 

Distinct254
Distinct (%)36.0%
Missing241
Missing (%)25.4%
Memory size7.5 KiB
2024-05-11T17:20:42.018478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length44
Mean length11.892351
Min length1

Characters and Unicode

Total characters8396
Distinct characters144
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique212 ?
Unique (%)30.0%

Sample

1st row제2종 일반주거지역(7층 이하)
2nd row제2종일반주거지역
3rd row제2종 일반주거지역
4th row도시지역 - 일반주거지역 - 제23종일반주거지
5th row제2종일반주거지역
ValueCountFrequency (%)
일반주거지역 174
14.8%
제3종일반주거지역 129
 
10.9%
제2종일반주거지역 100
 
8.5%
제2종 87
 
7.4%
제3종 69
 
5.9%
일반상업지역 59
 
5.0%
도시지역 56
 
4.7%
준주거지역 40
 
3.4%
제2종일반주거지역(7층이하 32
 
2.7%
준공업지역 24
 
2.0%
Other values (187) 409
34.7%
2024-05-11T17:20:42.590993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
868
10.3%
858
10.2%
695
 
8.3%
677
 
8.1%
675
 
8.0%
672
 
8.0%
636
 
7.6%
567
 
6.8%
496
 
5.9%
2 356
 
4.2%
Other values (134) 1896
22.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6779
80.7%
Decimal Number 820
 
9.8%
Space Separator 496
 
5.9%
Close Punctuation 117
 
1.4%
Open Punctuation 117
 
1.4%
Other Punctuation 58
 
0.7%
Dash Punctuation 6
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
868
12.8%
858
12.7%
695
10.3%
677
10.0%
675
10.0%
672
9.9%
636
9.4%
567
8.4%
101
 
1.5%
99
 
1.5%
Other values (111) 931
13.7%
Decimal Number
ValueCountFrequency (%)
2 356
43.4%
3 266
32.4%
7 91
 
11.1%
1 88
 
10.7%
8 5
 
0.6%
0 5
 
0.6%
4 4
 
0.5%
5 2
 
0.2%
9 2
 
0.2%
6 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 34
58.6%
. 15
25.9%
/ 8
 
13.8%
: 1
 
1.7%
Math Symbol
ValueCountFrequency (%)
1
33.3%
1
33.3%
+ 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 115
98.3%
] 2
 
1.7%
Open Punctuation
ValueCountFrequency (%)
( 115
98.3%
[ 2
 
1.7%
Space Separator
ValueCountFrequency (%)
496
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6779
80.7%
Common 1617
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
868
12.8%
858
12.7%
695
10.3%
677
10.0%
675
10.0%
672
9.9%
636
9.4%
567
8.4%
101
 
1.5%
99
 
1.5%
Other values (111) 931
13.7%
Common
ValueCountFrequency (%)
496
30.7%
2 356
22.0%
3 266
16.5%
) 115
 
7.1%
( 115
 
7.1%
7 91
 
5.6%
1 88
 
5.4%
, 34
 
2.1%
. 15
 
0.9%
/ 8
 
0.5%
Other values (13) 33
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6778
80.7%
ASCII 1615
 
19.2%
Arrows 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
868
12.8%
858
12.7%
695
10.3%
677
10.0%
675
10.0%
672
9.9%
636
9.4%
567
8.4%
101
 
1.5%
99
 
1.5%
Other values (110) 930
13.7%
ASCII
ValueCountFrequency (%)
496
30.7%
2 356
22.0%
3 266
16.5%
) 115
 
7.1%
( 115
 
7.1%
7 91
 
5.6%
1 88
 
5.4%
, 34
 
2.1%
. 15
 
0.9%
/ 8
 
0.5%
Other values (11) 31
 
1.9%
Arrows
ValueCountFrequency (%)
1
50.0%
1
50.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

용도지구
Text

MISSING 

Distinct225
Distinct (%)46.7%
Missing465
Missing (%)49.1%
Memory size7.5 KiB
2024-05-11T17:20:42.783204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length110
Median length48
Mean length9.7863071
Min length1

Characters and Unicode

Total characters4717
Distinct characters200
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)35.3%

Sample

1st row7층 이하
2nd row과밀억제권역
3rd row재정비촉진지구
4th row미아중심재정비촉진지구준주거지역부설주차장 설치제구역
5th row최고고도지구
ValueCountFrequency (%)
일반미관지구 45
 
6.4%
아파트지구 40
 
5.6%
재정비촉진지구 36
 
5.1%
중심지미관지구 27
 
3.8%
일반주거지역 27
 
3.8%
26
 
3.7%
미관지구 23
 
3.2%
제2종일반주거지역 16
 
2.3%
15
 
2.1%
제2종 14
 
2.0%
Other values (235) 439
62.0%
2024-05-11T17:20:43.125533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
487
 
10.3%
417
 
8.8%
305
 
6.5%
201
 
4.3%
162
 
3.4%
154
 
3.3%
152
 
3.2%
145
 
3.1%
119
 
2.5%
86
 
1.8%
Other values (190) 2489
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4007
84.9%
Space Separator 305
 
6.5%
Decimal Number 185
 
3.9%
Open Punctuation 57
 
1.2%
Close Punctuation 57
 
1.2%
Other Punctuation 44
 
0.9%
Dash Punctuation 31
 
0.7%
Math Symbol 17
 
0.4%
Lowercase Letter 9
 
0.2%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
487
 
12.2%
417
 
10.4%
201
 
5.0%
162
 
4.0%
154
 
3.8%
152
 
3.8%
145
 
3.6%
119
 
3.0%
86
 
2.1%
83
 
2.1%
Other values (161) 2001
49.9%
Decimal Number
ValueCountFrequency (%)
2 68
36.8%
3 40
21.6%
7 26
 
14.1%
1 20
 
10.8%
0 9
 
4.9%
5 8
 
4.3%
8 7
 
3.8%
6 3
 
1.6%
9 3
 
1.6%
4 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 21
47.7%
/ 11
25.0%
. 10
22.7%
: 2
 
4.5%
Math Symbol
ValueCountFrequency (%)
> 7
41.2%
< 7
41.2%
~ 2
 
11.8%
1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
M 2
40.0%
T 1
20.0%
A 1
20.0%
P 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 56
98.2%
[ 1
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 56
98.2%
] 1
 
1.8%
Space Separator
ValueCountFrequency (%)
305
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4007
84.9%
Common 696
 
14.8%
Latin 14
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
487
 
12.2%
417
 
10.4%
201
 
5.0%
162
 
4.0%
154
 
3.8%
152
 
3.8%
145
 
3.6%
119
 
3.0%
86
 
2.1%
83
 
2.1%
Other values (161) 2001
49.9%
Common
ValueCountFrequency (%)
305
43.8%
2 68
 
9.8%
( 56
 
8.0%
) 56
 
8.0%
3 40
 
5.7%
- 31
 
4.5%
7 26
 
3.7%
, 21
 
3.0%
1 20
 
2.9%
/ 11
 
1.6%
Other values (14) 62
 
8.9%
Latin
ValueCountFrequency (%)
m 9
64.3%
M 2
 
14.3%
T 1
 
7.1%
A 1
 
7.1%
P 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4007
84.9%
ASCII 709
 
15.0%
Arrows 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
487
 
12.2%
417
 
10.4%
201
 
5.0%
162
 
4.0%
154
 
3.8%
152
 
3.8%
145
 
3.6%
119
 
3.0%
86
 
2.1%
83
 
2.1%
Other values (161) 2001
49.9%
ASCII
ValueCountFrequency (%)
305
43.0%
2 68
 
9.6%
( 56
 
7.9%
) 56
 
7.9%
3 40
 
5.6%
- 31
 
4.4%
7 26
 
3.7%
, 21
 
3.0%
1 20
 
2.8%
/ 11
 
1.6%
Other values (18) 75
 
10.6%
Arrows
ValueCountFrequency (%)
1
100.0%

택지면적(㎡)
Real number (ℝ)

MISSING 

Distinct600
Distinct (%)99.7%
Missing345
Missing (%)36.4%
Infinite0
Infinite (%)0.0%
Mean44569.919
Minimum0
Maximum3997410.1
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:43.264669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1749.28
Q18824.05
median23293.715
Q346517.8
95-th percentile109583.72
Maximum3997410.1
Range3997410.1
Interquartile range (IQR)37693.75

Descriptive statistics

Standard deviation178944.72
Coefficient of variation (CV)4.0149213
Kurtosis406.54572
Mean44569.919
Median Absolute Deviation (MAD)17017.965
Skewness19.117387
Sum26831091
Variance3.2021212 × 1010
MonotonicityNot monotonic
2024-05-11T17:20:43.413517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10458.1 2
 
0.2%
278.79 2
 
0.2%
74231.8 1
 
0.1%
56270.0 1
 
0.1%
75401.9 1
 
0.1%
20028.9 1
 
0.1%
10339.2 1
 
0.1%
270920.0 1
 
0.1%
54310.0 1
 
0.1%
26401.8 1
 
0.1%
Other values (590) 590
62.3%
(Missing) 345
36.4%
ValueCountFrequency (%)
0.0 1
0.1%
19.43 1
0.1%
89.0 1
0.1%
92.63 1
0.1%
110.04 1
0.1%
164.08 1
0.1%
272.24 1
0.1%
278.79 2
0.2%
300.0 1
0.1%
417.49 1
0.1%
ValueCountFrequency (%)
3997410.07 1
0.1%
1588555.7 1
0.1%
462771.4 1
0.1%
405782.4 1
0.1%
270920.0 1
0.1%
248580.0 1
0.1%
223753.4 1
0.1%
222749.5 1
0.1%
211168.6 1
0.1%
207889.3 1
0.1%

도로면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct527
Distinct (%)93.6%
Missing384
Missing (%)40.5%
Infinite0
Infinite (%)0.0%
Mean5714.2933
Minimum0
Maximum254019
Zeros32
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:43.586603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1580.21
median2334.1
Q36596.75
95-th percentile20684.31
Maximum254019
Range254019
Interquartile range (IQR)6016.54

Descriptive statistics

Standard deviation13165.366
Coefficient of variation (CV)2.3039359
Kurtosis226.90216
Mean5714.2933
Median Absolute Deviation (MAD)2027.1
Skewness12.66178
Sum3217147.1
Variance1.7332685 × 108
MonotonicityNot monotonic
2024-05-11T17:20:43.725273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 32
 
3.4%
392.0 2
 
0.2%
457.3 2
 
0.2%
1505.0 2
 
0.2%
625.9 2
 
0.2%
117.72 2
 
0.2%
1521.0 1
 
0.1%
6988.0 1
 
0.1%
1778.2 1
 
0.1%
18027.0 1
 
0.1%
Other values (517) 517
54.6%
(Missing) 384
40.5%
ValueCountFrequency (%)
0.0 32
3.4%
3.63 1
 
0.1%
5.0 1
 
0.1%
5.99 1
 
0.1%
6.2 1
 
0.1%
6.3 1
 
0.1%
6.7 1
 
0.1%
6.8 1
 
0.1%
8.9 1
 
0.1%
10.0 1
 
0.1%
ValueCountFrequency (%)
254019.0 1
0.1%
72355.7 1
0.1%
55103.0 1
0.1%
43085.1 1
0.1%
42419.0 1
0.1%
39800.0 1
0.1%
39299.0 1
0.1%
38718.5 1
0.1%
36879.0 1
0.1%
33748.0 1
0.1%

공원면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct387
Distinct (%)85.1%
Missing492
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean4146.1375
Minimum0
Maximum52699
Zeros57
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:43.895452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1804
median2099.92
Q34912.5
95-th percentile15223.77
Maximum52699
Range52699
Interquartile range (IQR)4108.5

Descriptive statistics

Standard deviation6033.0504
Coefficient of variation (CV)1.4551014
Kurtosis18.661577
Mean4146.1375
Median Absolute Deviation (MAD)1839.18
Skewness3.6076104
Sum1886492.6
Variance36397697
MonotonicityNot monotonic
2024-05-11T17:20:44.024364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 57
 
6.0%
1508.0 3
 
0.3%
834.0 3
 
0.3%
3000.0 2
 
0.2%
4830.0 2
 
0.2%
1502.0 2
 
0.2%
49.02 2
 
0.2%
1000.0 2
 
0.2%
1618.0 2
 
0.2%
595.0 2
 
0.2%
Other values (377) 378
39.9%
(Missing) 492
52.0%
ValueCountFrequency (%)
0.0 57
6.0%
6.76 1
 
0.1%
11.34 1
 
0.1%
20.0 1
 
0.1%
22.0 1
 
0.1%
26.59 1
 
0.1%
28.62 1
 
0.1%
49.02 2
 
0.2%
57.0 1
 
0.1%
65.68 1
 
0.1%
ValueCountFrequency (%)
52699.0 1
0.1%
46506.0 1
0.1%
36611.1 1
0.1%
33612.0 1
0.1%
31456.2 1
0.1%
30200.0 1
0.1%
27802.0 1
0.1%
22782.0 1
0.1%
20295.0 1
0.1%
19796.4 1
0.1%

녹지면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct140
Distinct (%)53.8%
Missing687
Missing (%)72.5%
Infinite0
Infinite (%)0.0%
Mean2381.6229
Minimum0
Maximum77394.56
Zeros121
Zeros (%)12.8%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:44.148646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median203.75
Q32278.7
95-th percentile9948.1
Maximum77394.56
Range77394.56
Interquartile range (IQR)2278.7

Descriptive statistics

Standard deviation7063.1764
Coefficient of variation (CV)2.9656989
Kurtosis65.076244
Mean2381.6229
Median Absolute Deviation (MAD)203.75
Skewness7.3590675
Sum619221.95
Variance49888461
MonotonicityNot monotonic
2024-05-11T17:20:44.287199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 121
 
12.8%
10.0 1
 
0.1%
1713.0 1
 
0.1%
826.0 1
 
0.1%
3496.0 1
 
0.1%
5719.5 1
 
0.1%
2245.2 1
 
0.1%
1845.0 1
 
0.1%
1347.0 1
 
0.1%
653.0 1
 
0.1%
Other values (130) 130
 
13.7%
(Missing) 687
72.5%
ValueCountFrequency (%)
0.0 121
12.8%
8.52 1
 
0.1%
10.0 1
 
0.1%
30.0 1
 
0.1%
54.4 1
 
0.1%
61.8 1
 
0.1%
83.9 1
 
0.1%
110.0 1
 
0.1%
141.0 1
 
0.1%
180.0 1
 
0.1%
ValueCountFrequency (%)
77394.56 1
0.1%
52416.51 1
0.1%
48919.83 1
0.1%
20038.0 1
0.1%
19159.0 1
0.1%
16278.6 1
0.1%
13056.0 1
0.1%
12150.0 1
0.1%
12085.7 1
0.1%
11586.0 1
0.1%

공공공지면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct137
Distinct (%)52.9%
Missing688
Missing (%)72.7%
Infinite0
Infinite (%)0.0%
Mean1176.0705
Minimum0
Maximum36366
Zeros121
Zeros (%)12.8%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:44.409971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median102
Q31231
95-th percentile4966.73
Maximum36366
Range36366
Interquartile range (IQR)1231

Descriptive statistics

Standard deviation3105.5931
Coefficient of variation (CV)2.6406522
Kurtosis68.332075
Mean1176.0705
Median Absolute Deviation (MAD)102
Skewness7.0626533
Sum304602.25
Variance9644708.3
MonotonicityNot monotonic
2024-05-11T17:20:44.529718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 121
 
12.8%
900.0 2
 
0.2%
1000.0 2
 
0.2%
850.0 1
 
0.1%
632.1 1
 
0.1%
583.0 1
 
0.1%
2799.0 1
 
0.1%
1362.5 1
 
0.1%
1342.0 1
 
0.1%
456.4 1
 
0.1%
Other values (127) 127
 
13.4%
(Missing) 688
72.7%
ValueCountFrequency (%)
0.0 121
12.8%
5.27 1
 
0.1%
5.31 1
 
0.1%
10.0 1
 
0.1%
22.8 1
 
0.1%
26.9 1
 
0.1%
40.0 1
 
0.1%
77.0 1
 
0.1%
86.0 1
 
0.1%
102.0 1
 
0.1%
ValueCountFrequency (%)
36366.0 1
0.1%
18490.8 1
0.1%
12940.0 1
0.1%
11366.0 1
0.1%
9860.0 1
0.1%
9285.0 1
0.1%
8559.0 1
0.1%
7476.0 1
0.1%
7442.3 1
0.1%
7106.9 1
0.1%

학교면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct53
Distinct (%)25.9%
Missing742
Missing (%)78.4%
Infinite0
Infinite (%)0.0%
Mean2225.9239
Minimum0
Maximum71937.1
Zeros153
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:44.652292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q310.3
95-th percentile12804.28
Maximum71937.1
Range71937.1
Interquartile range (IQR)10.3

Descriptive statistics

Standard deviation7053.3511
Coefficient of variation (CV)3.1687297
Kurtosis49.193734
Mean2225.9239
Median Absolute Deviation (MAD)0
Skewness5.9806221
Sum456314.4
Variance49749761
MonotonicityNot monotonic
2024-05-11T17:20:44.778383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 153
 
16.2%
139.0 1
 
0.1%
1015.0 1
 
0.1%
7752.0 1
 
0.1%
5120.0 1
 
0.1%
46.3 1
 
0.1%
12605.0 1
 
0.1%
14729.6 1
 
0.1%
12061.0 1
 
0.1%
2291.0 1
 
0.1%
Other values (43) 43
 
4.5%
(Missing) 742
78.4%
ValueCountFrequency (%)
0.0 153
16.2%
10.3 1
 
0.1%
46.0 1
 
0.1%
46.3 1
 
0.1%
50.0 1
 
0.1%
139.0 1
 
0.1%
334.0 1
 
0.1%
358.3 1
 
0.1%
365.0 1
 
0.1%
456.0 1
 
0.1%
ValueCountFrequency (%)
71937.1 1
0.1%
33710.2 1
0.1%
23894.8 1
0.1%
23780.0 1
0.1%
22892.0 1
0.1%
22414.0 1
0.1%
19464.2 1
0.1%
14729.6 1
0.1%
14331.0 1
0.1%
14328.5 1
0.1%

기타면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct184
Distinct (%)62.6%
Missing653
Missing (%)69.0%
Infinite0
Infinite (%)0.0%
Mean1979.9201
Minimum0
Maximum51031.6
Zeros102
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:44.905931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median645.5
Q31874
95-th percentile7746.475
Maximum51031.6
Range51031.6
Interquartile range (IQR)1874

Descriptive statistics

Standard deviation5196.5724
Coefficient of variation (CV)2.6246374
Kurtosis53.335639
Mean1979.9201
Median Absolute Deviation (MAD)645.5
Skewness6.6023245
Sum582096.52
Variance27004365
MonotonicityNot monotonic
2024-05-11T17:20:45.061517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 102
 
10.8%
1000.0 3
 
0.3%
2560.0 2
 
0.2%
486.0 2
 
0.2%
3290.0 2
 
0.2%
7.0 2
 
0.2%
6.76 2
 
0.2%
1200.0 2
 
0.2%
1300.0 2
 
0.2%
2089.0 1
 
0.1%
Other values (174) 174
 
18.4%
(Missing) 653
69.0%
ValueCountFrequency (%)
0.0 102
10.8%
6.6 1
 
0.1%
6.76 2
 
0.2%
7.0 2
 
0.2%
16.1 1
 
0.1%
40.6 1
 
0.1%
60.0 1
 
0.1%
72.0 1
 
0.1%
76.81 1
 
0.1%
81.1 1
 
0.1%
ValueCountFrequency (%)
51031.6 1
0.1%
49139.4 1
0.1%
31057.5 1
0.1%
20416.3 1
0.1%
20354.5 1
0.1%
16899.3 1
0.1%
14855.9 1
0.1%
11667.0 1
0.1%
10612.0 1
0.1%
10525.0 1
0.1%

주용도
Text

MISSING 

Distinct173
Distinct (%)25.0%
Missing255
Missing (%)26.9%
Memory size7.5 KiB
2024-05-11T17:20:45.243318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length30
Mean length9.1965318
Min length1

Characters and Unicode

Total characters6364
Distinct characters117
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

Unique133 ?
Unique (%)19.2%

Sample

1st row아파트
2nd row제2종 일반주거(7층이하)
3rd row아파트 및 부대복리시설
4th row아파트
5th row공동주택
ValueCountFrequency (%)
공동주택 338
26.8%
211
16.7%
부대복리시설 182
14.4%
아파트 84
 
6.7%
공동주택(아파트 71
 
5.6%
주거 28
 
2.2%
근린생활시설 27
 
2.1%
업무 22
 
1.7%
근린생활 20
 
1.6%
판매 18
 
1.4%
Other values (138) 259
20.6%
2024-05-11T17:20:45.568436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
589
 
9.3%
574
 
9.0%
515
 
8.1%
514
 
8.1%
496
 
7.8%
346
 
5.4%
342
 
5.4%
268
 
4.2%
243
 
3.8%
242
 
3.8%
Other values (107) 2235
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5422
85.2%
Space Separator 574
 
9.0%
Open Punctuation 109
 
1.7%
Close Punctuation 109
 
1.7%
Other Punctuation 103
 
1.6%
Decimal Number 29
 
0.5%
Uppercase Letter 13
 
0.2%
Math Symbol 4
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
589
 
10.9%
515
 
9.5%
514
 
9.5%
496
 
9.1%
346
 
6.4%
342
 
6.3%
268
 
4.9%
243
 
4.5%
242
 
4.5%
238
 
4.4%
Other values (82) 1629
30.0%
Decimal Number
ValueCountFrequency (%)
3 6
20.7%
2 4
13.8%
1 4
13.8%
5 3
10.3%
8 3
10.3%
0 2
 
6.9%
7 2
 
6.9%
4 2
 
6.9%
9 2
 
6.9%
6 1
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
A 3
23.1%
T 3
23.1%
P 3
23.1%
M 1
 
7.7%
I 1
 
7.7%
C 1
 
7.7%
E 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 72
69.9%
/ 23
 
22.3%
. 8
 
7.8%
Space Separator
ValueCountFrequency (%)
574
100.0%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5422
85.2%
Common 929
 
14.6%
Latin 13
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
589
 
10.9%
515
 
9.5%
514
 
9.5%
496
 
9.1%
346
 
6.4%
342
 
6.3%
268
 
4.9%
243
 
4.5%
242
 
4.5%
238
 
4.4%
Other values (82) 1629
30.0%
Common
ValueCountFrequency (%)
574
61.8%
( 109
 
11.7%
) 109
 
11.7%
, 72
 
7.8%
/ 23
 
2.5%
. 8
 
0.9%
3 6
 
0.6%
2 4
 
0.4%
1 4
 
0.4%
+ 4
 
0.4%
Other values (8) 16
 
1.7%
Latin
ValueCountFrequency (%)
A 3
23.1%
T 3
23.1%
P 3
23.1%
M 1
 
7.7%
I 1
 
7.7%
C 1
 
7.7%
E 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5422
85.2%
ASCII 942
 
14.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
589
 
10.9%
515
 
9.5%
514
 
9.5%
496
 
9.1%
346
 
6.4%
342
 
6.3%
268
 
4.9%
243
 
4.5%
242
 
4.5%
238
 
4.4%
Other values (82) 1629
30.0%
ASCII
ValueCountFrequency (%)
574
60.9%
( 109
 
11.6%
) 109
 
11.6%
, 72
 
7.6%
/ 23
 
2.4%
. 8
 
0.8%
3 6
 
0.6%
2 4
 
0.4%
1 4
 
0.4%
+ 4
 
0.4%
Other values (15) 29
 
3.1%

건폐율
Real number (ℝ)

MISSING 

Distinct587
Distinct (%)82.3%
Missing234
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean31.303689
Minimum1.81
Maximum350.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:45.688768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.81
5-th percentile17.12
Q120.92
median25.98
Q335.21
95-th percentile59.934
Maximum350.25
Range348.44
Interquartile range (IQR)14.29

Descriptive statistics

Standard deviation20.112589
Coefficient of variation (CV)0.64249903
Kurtosis123.25036
Mean31.303689
Median Absolute Deviation (MAD)6.03
Skewness8.7376423
Sum22319.53
Variance404.51626
MonotonicityNot monotonic
2024-05-11T17:20:45.812878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60.0 23
 
2.4%
30.0 11
 
1.2%
50.0 8
 
0.8%
33.9 5
 
0.5%
19.43 3
 
0.3%
23.15 3
 
0.3%
20.0 3
 
0.3%
52.0 3
 
0.3%
22.06 3
 
0.3%
25.18 3
 
0.3%
Other values (577) 648
68.4%
(Missing) 234
 
24.7%
ValueCountFrequency (%)
1.81 1
0.1%
11.6 1
0.1%
12.55 1
0.1%
13.48 1
0.1%
13.49 1
0.1%
14.26 1
0.1%
14.44 1
0.1%
14.91 1
0.1%
15.02 1
0.1%
15.03 1
0.1%
ValueCountFrequency (%)
350.25 1
 
0.1%
285.35 1
 
0.1%
85.25 1
 
0.1%
85.18 1
 
0.1%
75.9 1
 
0.1%
65.0 2
 
0.2%
63.0 1
 
0.1%
61.0 1
 
0.1%
60.54 1
 
0.1%
60.0 23
2.4%

용적률
Real number (ℝ)

MISSING 

Distinct610
Distinct (%)85.0%
Missing229
Missing (%)24.2%
Infinite0
Infinite (%)0.0%
Mean293.65312
Minimum2
Maximum2492.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:45.947086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile173.442
Q1229.545
median249.89
Q3299.7
95-th percentile649.8
Maximum2492.68
Range2490.68
Interquartile range (IQR)70.155

Descriptive statistics

Standard deviation173.4422
Coefficient of variation (CV)0.59063633
Kurtosis41.981316
Mean293.65312
Median Absolute Deviation (MAD)33.37
Skewness4.6944469
Sum210842.94
Variance30082.197
MonotonicityNot monotonic
2024-05-11T17:20:46.071739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
299.99 19
 
2.0%
249.98 13
 
1.4%
299.98 9
 
1.0%
249.99 8
 
0.8%
249.96 5
 
0.5%
299.94 5
 
0.5%
299.7 5
 
0.5%
249.86 4
 
0.4%
299.95 4
 
0.4%
250.0 3
 
0.3%
Other values (600) 643
67.9%
(Missing) 229
 
24.2%
ValueCountFrequency (%)
2.0 1
0.1%
2.1 1
0.1%
2.4 1
0.1%
3.7 1
0.1%
3.9 2
0.2%
4.0 1
0.1%
4.6 1
0.1%
4.8 1
0.1%
5.4 1
0.1%
6.2 1
0.1%
ValueCountFrequency (%)
2492.68 1
0.1%
1559.96 1
0.1%
1000.0 1
0.1%
991.37 1
0.1%
962.25 1
0.1%
959.26 1
0.1%
950.0 1
0.1%
891.12 1
0.1%
869.84 1
0.1%
859.0 1
0.1%

높이(m)
Real number (ℝ)

MISSING  ZEROS 

Distinct181
Distinct (%)33.8%
Missing412
Missing (%)43.5%
Infinite0
Infinite (%)0.0%
Mean1279.0093
Minimum0
Maximum118400
Zeros10
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:46.191580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19.7
Q155
median80
Q3109
95-th percentile5989.5
Maximum118400
Range118400
Interquartile range (IQR)54

Descriptive statistics

Standard deviation8229.7981
Coefficient of variation (CV)6.4345098
Kurtosis140.23031
Mean1279.0093
Median Absolute Deviation (MAD)27
Skewness11.300725
Sum684270
Variance67729577
MonotonicityNot monotonic
2024-05-11T17:20:46.583895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 18
 
1.9%
100 17
 
1.8%
75 13
 
1.4%
70 13
 
1.4%
60 12
 
1.3%
0 10
 
1.1%
90 10
 
1.1%
72 10
 
1.1%
40 9
 
1.0%
43 9
 
1.0%
Other values (171) 414
43.7%
(Missing) 412
43.5%
ValueCountFrequency (%)
0 10
1.1%
1 1
 
0.1%
6 1
 
0.1%
7 1
 
0.1%
9 2
 
0.2%
11 1
 
0.1%
13 2
 
0.2%
14 1
 
0.1%
15 6
0.6%
16 1
 
0.1%
ValueCountFrequency (%)
118400 1
0.1%
105200 1
0.1%
78250 1
0.1%
50200 1
0.1%
34550 1
0.1%
15570 1
0.1%
14255 1
0.1%
11926 1
0.1%
9755 1
0.1%
9640 1
0.1%

지상층수
Real number (ℝ)

MISSING  SKEWED 

Distinct52
Distinct (%)7.7%
Missing268
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean36.005891
Minimum1
Maximum8600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:46.724948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q115
median23
Q330.5
95-th percentile39
Maximum8600
Range8599
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation329.29837
Coefficient of variation (CV)9.1456803
Kurtosis677.69453
Mean36.005891
Median Absolute Deviation (MAD)8
Skewness26.020107
Sum24448
Variance108437.42
MonotonicityNot monotonic
2024-05-11T17:20:46.868359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 88
 
9.3%
15 73
 
7.7%
20 59
 
6.2%
25 57
 
6.0%
7 31
 
3.3%
29 30
 
3.2%
30 26
 
2.7%
28 21
 
2.2%
18 20
 
2.1%
22 19
 
2.0%
Other values (42) 255
26.9%
(Missing) 268
28.3%
ValueCountFrequency (%)
1 2
 
0.2%
2 8
 
0.8%
3 3
 
0.3%
4 3
 
0.3%
5 1
 
0.1%
6 7
 
0.7%
7 31
3.3%
8 2
 
0.2%
9 3
 
0.3%
10 14
1.5%
ValueCountFrequency (%)
8600 1
 
0.1%
65 1
 
0.1%
56 1
 
0.1%
55 1
 
0.1%
50 4
0.4%
49 4
0.4%
48 1
 
0.1%
47 1
 
0.1%
46 1
 
0.1%
45 2
0.2%

지하층수
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)2.6%
Missing291
Missing (%)30.7%
Infinite0
Infinite (%)0.0%
Mean3.347561
Minimum0
Maximum35
Zeros2
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:46.974158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q12
median3
Q34
95-th percentile6
Maximum35
Range35
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.6908826
Coefficient of variation (CV)0.80383377
Kurtosis60.327422
Mean3.347561
Median Absolute Deviation (MAD)1
Skewness6.6163126
Sum2196
Variance7.240849
MonotonicityNot monotonic
2024-05-11T17:20:47.094346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2 219
23.1%
3 213
22.5%
4 96
 
10.1%
5 44
 
4.6%
1 29
 
3.1%
6 23
 
2.4%
7 14
 
1.5%
8 4
 
0.4%
9 3
 
0.3%
25 2
 
0.2%
Other values (7) 9
 
1.0%
(Missing) 291
30.7%
ValueCountFrequency (%)
0 2
 
0.2%
1 29
 
3.1%
2 219
23.1%
3 213
22.5%
4 96
10.1%
5 44
 
4.6%
6 23
 
2.4%
7 14
 
1.5%
8 4
 
0.4%
9 3
 
0.3%
ValueCountFrequency (%)
35 1
 
0.1%
30 1
 
0.1%
25 2
 
0.2%
23 1
 
0.1%
15 2
 
0.2%
13 1
 
0.1%
10 1
 
0.1%
9 3
 
0.3%
8 4
 
0.4%
7 14
1.5%

분양세대총수
Real number (ℝ)

MISSING 

Distinct361
Distinct (%)90.7%
Missing549
Missing (%)58.0%
Infinite0
Infinite (%)0.0%
Mean1439.7965
Minimum26
Maximum93000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:47.221307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile138.3
Q1415.5
median781.5
Q31297
95-th percentile2831.4
Maximum93000
Range92974
Interquartile range (IQR)881.5

Descriptive statistics

Standard deviation5624.6667
Coefficient of variation (CV)3.9065707
Kurtosis210.5995
Mean1439.7965
Median Absolute Deviation (MAD)406
Skewness14.074143
Sum573039
Variance31636876
MonotonicityNot monotonic
2024-05-11T17:20:47.351102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
421 3
 
0.3%
915 3
 
0.3%
827 3
 
0.3%
260 3
 
0.3%
276 2
 
0.2%
185 2
 
0.2%
497 2
 
0.2%
490 2
 
0.2%
2326 2
 
0.2%
92 2
 
0.2%
Other values (351) 374
39.5%
(Missing) 549
58.0%
ValueCountFrequency (%)
26 1
0.1%
28 1
0.1%
45 1
0.1%
47 1
0.1%
48 1
0.1%
49 1
0.1%
54 1
0.1%
59 1
0.1%
60 1
0.1%
63 1
0.1%
ValueCountFrequency (%)
93000 1
0.1%
61854 1
0.1%
10060 1
0.1%
8109 1
0.1%
6309 1
0.1%
6033 1
0.1%
5100 1
0.1%
5002 1
0.1%
4792 1
0.1%
4778 1
0.1%

60㎡이하
Real number (ℝ)

MISSING  SKEWED 

Distinct381
Distinct (%)59.4%
Missing306
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean333.67395
Minimum2
Maximum35900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:47.472977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile23
Q184
median178
Q3357
95-th percentile878
Maximum35900
Range35898
Interquartile range (IQR)273

Descriptive statistics

Standard deviation1440.7486
Coefficient of variation (CV)4.3178337
Kurtosis582.74096
Mean333.67395
Median Absolute Deviation (MAD)115
Skewness23.602382
Sum213885
Variance2075756.5
MonotonicityNot monotonic
2024-05-11T17:20:47.604029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70 7
 
0.7%
166 6
 
0.6%
150 6
 
0.6%
42 6
 
0.6%
28 6
 
0.6%
84 6
 
0.6%
40 5
 
0.5%
196 5
 
0.5%
140 5
 
0.5%
15 5
 
0.5%
Other values (371) 584
61.7%
(Missing) 306
32.3%
ValueCountFrequency (%)
2 2
 
0.2%
3 1
 
0.1%
5 2
 
0.2%
6 1
 
0.1%
9 4
0.4%
11 1
 
0.1%
13 1
 
0.1%
14 1
 
0.1%
15 5
0.5%
16 1
 
0.1%
ValueCountFrequency (%)
35900 1
0.1%
2746 1
0.1%
2106 1
0.1%
2005 1
0.1%
1824 1
0.1%
1682 1
0.1%
1652 1
0.1%
1453 1
0.1%
1443 1
0.1%
1350 1
0.1%

60㎡초과~85㎡이하
Real number (ℝ)

MISSING 

Distinct441
Distinct (%)68.4%
Missing302
Missing (%)31.9%
Infinite0
Infinite (%)0.0%
Mean523.5814
Minimum1
Maximum47600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:47.730408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25
Q197
median254
Q3492
95-th percentile1173.2
Maximum47600
Range47599
Interquartile range (IQR)395

Descriptive statistics

Standard deviation2556.4159
Coefficient of variation (CV)4.8825567
Kurtosis301.61246
Mean523.5814
Median Absolute Deviation (MAD)179
Skewness17.108763
Sum337710
Variance6535262
MonotonicityNot monotonic
2024-05-11T17:20:47.856512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56 9
 
1.0%
28 8
 
0.8%
48 5
 
0.5%
30 5
 
0.5%
82 5
 
0.5%
42 4
 
0.4%
128 4
 
0.4%
25 4
 
0.4%
10 4
 
0.4%
629 4
 
0.4%
Other values (431) 593
62.6%
(Missing) 302
31.9%
ValueCountFrequency (%)
1 2
0.2%
3 1
 
0.1%
4 1
 
0.1%
5 1
 
0.1%
9 2
0.2%
10 4
0.4%
11 1
 
0.1%
12 1
 
0.1%
13 1
 
0.1%
14 4
0.4%
ValueCountFrequency (%)
47600 1
0.1%
43429 1
0.1%
5132 1
0.1%
3948 1
0.1%
3000 1
0.1%
2676 1
0.1%
2598 1
0.1%
2522 1
0.1%
2483 1
0.1%
2038 1
0.1%

85㎡초과
Real number (ℝ)

MISSING 

Distinct266
Distinct (%)60.0%
Missing504
Missing (%)53.2%
Infinite0
Infinite (%)0.0%
Mean271.72235
Minimum0
Maximum18362
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:47.980206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q140
median98
Q3250
95-th percentile736.4
Maximum18362
Range18362
Interquartile range (IQR)210

Descriptive statistics

Standard deviation1026.5967
Coefficient of variation (CV)3.7781092
Kurtosis233.47079
Mean271.72235
Median Absolute Deviation (MAD)73
Skewness14.242743
Sum120373
Variance1053900.8
MonotonicityNot monotonic
2024-05-11T17:20:48.141486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 8
 
0.8%
88 7
 
0.7%
40 6
 
0.6%
14 6
 
0.6%
35 6
 
0.6%
12 6
 
0.6%
4 5
 
0.5%
42 5
 
0.5%
52 5
 
0.5%
44 5
 
0.5%
Other values (256) 384
40.5%
(Missing) 504
53.2%
ValueCountFrequency (%)
0 1
 
0.1%
1 2
 
0.2%
2 8
0.8%
3 3
 
0.3%
4 5
0.5%
5 2
 
0.2%
6 1
 
0.1%
7 2
 
0.2%
8 3
 
0.3%
9 2
 
0.2%
ValueCountFrequency (%)
18362 1
0.1%
9500 1
0.1%
3366 1
0.1%
2835 1
0.1%
2391 1
0.1%
2144 1
0.1%
1994 1
0.1%
1524 1
0.1%
1522 1
0.1%
1180 1
0.1%

임대세대총수
Real number (ℝ)

MISSING 

Distinct132
Distinct (%)85.7%
Missing793
Missing (%)83.7%
Infinite0
Infinite (%)0.0%
Mean253.23377
Minimum22
Maximum1401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:48.266635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile58
Q1132
median183.5
Q3304
95-th percentile625.7
Maximum1401
Range1379
Interquartile range (IQR)172

Descriptive statistics

Standard deviation217.11392
Coefficient of variation (CV)0.85736561
Kurtosis9.4133529
Mean253.23377
Median Absolute Deviation (MAD)77
Skewness2.6848501
Sum38998
Variance47138.455
MonotonicityNot monotonic
2024-05-11T17:20:48.395308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
168 4
 
0.4%
174 3
 
0.3%
51 2
 
0.2%
179 2
 
0.2%
292 2
 
0.2%
208 2
 
0.2%
198 2
 
0.2%
161 2
 
0.2%
58 2
 
0.2%
111 2
 
0.2%
Other values (122) 131
 
13.8%
(Missing) 793
83.7%
ValueCountFrequency (%)
22 1
0.1%
31 1
0.1%
51 2
0.2%
55 1
0.1%
56 1
0.1%
57 1
0.1%
58 2
0.2%
60 1
0.1%
63 1
0.1%
65 1
0.1%
ValueCountFrequency (%)
1401 1
0.1%
1308 1
0.1%
1046 1
0.1%
979 1
0.1%
928 1
0.1%
750 1
0.1%
681 1
0.1%
640 1
0.1%
618 1
0.1%
550 1
0.1%

(임대)40㎡이하
Real number (ℝ)

MISSING 

Distinct152
Distinct (%)60.3%
Missing695
Missing (%)73.4%
Infinite0
Infinite (%)0.0%
Mean105.4127
Minimum4
Maximum1065
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:48.534635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile15.55
Q140
median74.5
Q3124.25
95-th percentile297.8
Maximum1065
Range1061
Interquartile range (IQR)84.25

Descriptive statistics

Standard deviation116.96479
Coefficient of variation (CV)1.1095892
Kurtosis23.111409
Mean105.4127
Median Absolute Deviation (MAD)38.5
Skewness3.9423887
Sum26564
Variance13680.761
MonotonicityNot monotonic
2024-05-11T17:20:48.651032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 7
 
0.7%
20 7
 
0.7%
70 6
 
0.6%
52 6
 
0.6%
45 5
 
0.5%
42 5
 
0.5%
84 4
 
0.4%
39 4
 
0.4%
105 4
 
0.4%
24 4
 
0.4%
Other values (142) 200
 
21.1%
(Missing) 695
73.4%
ValueCountFrequency (%)
4 1
 
0.1%
5 2
0.2%
6 1
 
0.1%
9 1
 
0.1%
10 1
 
0.1%
12 3
0.3%
14 2
0.2%
15 2
0.2%
16 1
 
0.1%
18 1
 
0.1%
ValueCountFrequency (%)
1065 1
0.1%
726 1
0.1%
657 1
0.1%
553 1
0.1%
538 1
0.1%
402 1
0.1%
349 1
0.1%
348 1
0.1%
333 1
0.1%
327 1
0.1%

(임대)40㎡초과~50㎡이하
Real number (ℝ)

MISSING 

Distinct149
Distinct (%)50.5%
Missing652
Missing (%)68.8%
Infinite0
Infinite (%)0.0%
Mean79.908475
Minimum3
Maximum628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:48.769693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile11.7
Q129.5
median57
Q3104
95-th percentile218.3
Maximum628
Range625
Interquartile range (IQR)74.5

Descriptive statistics

Standard deviation78.218526
Coefficient of variation (CV)0.97885145
Kurtosis13.964821
Mean79.908475
Median Absolute Deviation (MAD)33
Skewness2.9465859
Sum23573
Variance6118.1379
MonotonicityNot monotonic
2024-05-11T17:20:48.889740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 7
 
0.7%
28 7
 
0.7%
35 6
 
0.6%
12 6
 
0.6%
20 6
 
0.6%
33 5
 
0.5%
42 5
 
0.5%
30 5
 
0.5%
76 5
 
0.5%
14 4
 
0.4%
Other values (139) 239
 
25.2%
(Missing) 652
68.8%
ValueCountFrequency (%)
3 3
0.3%
4 2
 
0.2%
5 1
 
0.1%
6 1
 
0.1%
7 2
 
0.2%
9 2
 
0.2%
10 2
 
0.2%
11 2
 
0.2%
12 6
0.6%
13 3
0.3%
ValueCountFrequency (%)
628 1
0.1%
572 1
0.1%
402 1
0.1%
352 1
0.1%
331 1
0.1%
316 1
0.1%
270 1
0.1%
265 1
0.1%
262 1
0.1%
249 1
0.1%

(임대)50㎡초과
Real number (ℝ)

MISSING 

Distinct147
Distinct (%)42.4%
Missing600
Missing (%)63.4%
Infinite0
Infinite (%)0.0%
Mean65.429395
Minimum1
Maximum737
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-11T17:20:49.020094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q119
median36
Q388
95-th percentile205.1
Maximum737
Range736
Interquartile range (IQR)69

Descriptive statistics

Standard deviation76.684117
Coefficient of variation (CV)1.1720132
Kurtosis18.918999
Mean65.429395
Median Absolute Deviation (MAD)24
Skewness3.3052844
Sum22704
Variance5880.4538
MonotonicityNot monotonic
2024-05-11T17:20:49.145063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 13
 
1.4%
21 10
 
1.1%
15 9
 
1.0%
17 9
 
1.0%
28 9
 
1.0%
16 8
 
0.8%
20 8
 
0.8%
30 7
 
0.7%
10 6
 
0.6%
23 6
 
0.6%
Other values (137) 262
27.7%
(Missing) 600
63.4%
ValueCountFrequency (%)
1 1
 
0.1%
2 1
 
0.1%
3 3
0.3%
4 3
0.3%
5 5
0.5%
6 4
0.4%
7 3
0.3%
8 6
0.6%
9 3
0.3%
10 6
0.6%
ValueCountFrequency (%)
737 1
0.1%
423 1
0.1%
333 1
0.1%
320 1
0.1%
313 1
0.1%
310 1
0.1%
298 1
0.1%
294 2
0.2%
282 1
0.1%
266 1
0.1%

건축계획비고
Text

MISSING 

Distinct66
Distinct (%)75.0%
Missing859
Missing (%)90.7%
Memory size7.5 KiB
2024-05-11T17:20:49.410152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length28
Mean length10.522727
Min length1

Characters and Unicode

Total characters926
Distinct characters161
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)68.2%

Sample

1st rowSH신속사업성 기준
2nd row임대224세대
3rd row대지면적통합
4th row부대시설 포함
5th row임대27포함
ValueCountFrequency (%)
임대포함 11
 
5.8%
포함 8
 
4.2%
0 8
 
4.2%
기준 5
 
2.6%
없음 4
 
2.1%
미정 4
 
2.1%
sh신속사업성 3
 
1.6%
있음 3
 
1.6%
3
 
1.6%
변경될 3
 
1.6%
Other values (122) 139
72.8%
2024-05-11T17:20:49.826267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
103
 
11.1%
60
 
6.5%
34
 
3.7%
33
 
3.6%
33
 
3.6%
23
 
2.5%
1 18
 
1.9%
16
 
1.7%
16
 
1.7%
2 15
 
1.6%
Other values (151) 575
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 661
71.4%
Decimal Number 109
 
11.8%
Space Separator 103
 
11.1%
Other Punctuation 17
 
1.8%
Lowercase Letter 9
 
1.0%
Uppercase Letter 8
 
0.9%
Close Punctuation 7
 
0.8%
Open Punctuation 7
 
0.8%
Other Symbol 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
60
 
9.1%
34
 
5.1%
33
 
5.0%
33
 
5.0%
23
 
3.5%
16
 
2.4%
16
 
2.4%
15
 
2.3%
15
 
2.3%
14
 
2.1%
Other values (121) 402
60.8%
Decimal Number
ValueCountFrequency (%)
1 18
16.5%
2 15
13.8%
5 14
12.8%
0 13
11.9%
8 12
11.0%
6 10
9.2%
3 9
8.3%
9 8
7.3%
4 6
 
5.5%
7 4
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
s 2
22.2%
h 2
22.2%
m 1
11.1%
t 1
11.1%
y 1
11.1%
p 1
11.1%
e 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 8
47.1%
: 4
23.5%
/ 4
23.5%
, 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
H 3
37.5%
S 3
37.5%
A 1
 
12.5%
B 1
 
12.5%
Other Symbol
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Space Separator
ValueCountFrequency (%)
103
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 661
71.4%
Common 248
 
26.8%
Latin 17
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
60
 
9.1%
34
 
5.1%
33
 
5.0%
33
 
5.0%
23
 
3.5%
16
 
2.4%
16
 
2.4%
15
 
2.3%
15
 
2.3%
14
 
2.1%
Other values (121) 402
60.8%
Common
ValueCountFrequency (%)
103
41.5%
1 18
 
7.3%
2 15
 
6.0%
5 14
 
5.6%
0 13
 
5.2%
8 12
 
4.8%
6 10
 
4.0%
3 9
 
3.6%
9 8
 
3.2%
. 8
 
3.2%
Other values (9) 38
 
15.3%
Latin
ValueCountFrequency (%)
H 3
17.6%
S 3
17.6%
s 2
11.8%
h 2
11.8%
m 1
 
5.9%
A 1
 
5.9%
B 1
 
5.9%
t 1
 
5.9%
y 1
 
5.9%
p 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 661
71.4%
ASCII 260
 
28.1%
CJK Compat 5
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
103
39.6%
1 18
 
6.9%
2 15
 
5.8%
5 14
 
5.4%
0 13
 
5.0%
8 12
 
4.6%
6 10
 
3.8%
3 9
 
3.5%
9 8
 
3.1%
. 8
 
3.1%
Other values (18) 50
19.2%
Hangul
ValueCountFrequency (%)
60
 
9.1%
34
 
5.1%
33
 
5.0%
33
 
5.0%
23
 
3.5%
16
 
2.4%
16
 
2.4%
15
 
2.3%
15
 
2.3%
14
 
2.1%
Other values (121) 402
60.8%
CJK Compat
ValueCountFrequency (%)
4
80.0%
1
 
20.0%

위치도
Text

MISSING 

Distinct747
Distinct (%)100.0%
Missing200
Missing (%)21.1%
Memory size7.5 KiB
2024-05-11T17:20:50.073038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length70
Mean length64.222222
Min length51

Characters and Unicode

Total characters47974
Distinct characters37
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique747 ?
Unique (%)100.0%

Sample

1st row/servlet/image?url=images/assc/2022/08/202208031710201659514220659.png
2nd row/servlet/image?url=images/assc/2024/05/202405091740221715244022793.jpg
3rd row/servlet/image?url=images/assc/2023/06/202306291608021688022482243.jpg
4th row/servlet/image?url=images/assc/2023/12/202312171624271702797867846.jpg
5th row/servlet/image?url=images/assc/2023/10/202310041155181696388118624.jpg
ValueCountFrequency (%)
servlet/image?url=images/assc/2022/01/202201131615141642058114215.jpg 1
 
0.1%
servlet/image/assc/2011/12/201112071402131323234133382.jpg 1
 
0.1%
servlet/image/assc/2010/11/201011091357401289278660369.bmp 1
 
0.1%
servlet/image/assc/2010/09/201009301010261285809026309.jpg 1
 
0.1%
servlet/image?url=images/assc/2022/07/202207161525381657952738744.jpg 1
 
0.1%
servlet/image/assc/2011/09/201109011717361314865056529.jpg 1
 
0.1%
servlet/image/assc/2010/10/201010181249021287373742789.jpg 1
 
0.1%
servlet/image/assc/2010/10/201010071436401286429800021.jpg 1
 
0.1%
servlet/image/assc/2011/11/201111221548541321944534662.gif 1
 
0.1%
servlet/image/assc/2010/03/201003291331431269837103126.jpg 1
 
0.1%
Other values (737) 737
98.7%
2024-05-11T17:20:50.419580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5021
 
10.5%
0 4656
 
9.7%
/ 4404
 
9.2%
2 4246
 
8.9%
e 2624
 
5.5%
s 2624
 
5.5%
a 1877
 
3.9%
g 1819
 
3.8%
3 1815
 
3.8%
4 1700
 
3.5%
Other values (27) 17188
35.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24417
50.9%
Lowercase Letter 17634
36.8%
Other Punctuation 5534
 
11.5%
Math Symbol 383
 
0.8%
Uppercase Letter 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2624
14.9%
s 2624
14.9%
a 1877
10.6%
g 1819
10.3%
m 1179
6.7%
i 1145
6.5%
l 1130
6.4%
r 1130
6.4%
v 747
 
4.2%
t 747
 
4.2%
Other values (10) 2612
14.8%
Decimal Number
ValueCountFrequency (%)
1 5021
20.6%
0 4656
19.1%
2 4246
17.4%
3 1815
 
7.4%
4 1700
 
7.0%
5 1655
 
6.8%
6 1428
 
5.8%
8 1374
 
5.6%
7 1316
 
5.4%
9 1206
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/ 4404
79.6%
. 747
 
13.5%
? 383
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
J 2
33.3%
P 2
33.3%
G 2
33.3%
Math Symbol
ValueCountFrequency (%)
= 383
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30334
63.2%
Latin 17640
36.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2624
14.9%
s 2624
14.9%
a 1877
10.6%
g 1819
10.3%
m 1179
6.7%
i 1145
6.5%
l 1130
6.4%
r 1130
6.4%
v 747
 
4.2%
t 747
 
4.2%
Other values (13) 2618
14.8%
Common
ValueCountFrequency (%)
1 5021
16.6%
0 4656
15.3%
/ 4404
14.5%
2 4246
14.0%
3 1815
 
6.0%
4 1700
 
5.6%
5 1655
 
5.5%
6 1428
 
4.7%
8 1374
 
4.5%
7 1316
 
4.3%
Other values (4) 2719
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47974
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5021
 
10.5%
0 4656
 
9.7%
/ 4404
 
9.2%
2 4246
 
8.9%
e 2624
 
5.5%
s 2624
 
5.5%
a 1877
 
3.9%
g 1819
 
3.8%
3 1815
 
3.8%
4 1700
 
3.5%
Other values (27) 17188
35.8%

조감도
Text

MISSING 

Distinct628
Distinct (%)100.0%
Missing319
Missing (%)33.7%
Memory size7.5 KiB
2024-05-11T17:20:50.658377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length59
Mean length63.835987
Min length59

Characters and Unicode

Total characters40089
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique628 ?
Unique (%)100.0%

Sample

1st row/servlet/image?url=images/assc/2022/08/202208031710201659514220842.jpg
2nd row/servlet/image?url=images/assc/2023/06/202306291610241688022624810.jpg
3rd row/servlet/image?url=images/assc/2023/12/202312171624281702797868712.jpg
4th row/servlet/image?url=images/assc/2023/10/202310041155191696388119035.jpg
5th row/servlet/image?url=images/assc/2023/12/202312291209581703819398540.jpg
ValueCountFrequency (%)
servlet/image?url=images/assc/2016/06/201606071346481465274808558.jpg 1
 
0.2%
servlet/image?url=images/assc/2018/04/201804261125141524709514794.jpg 1
 
0.2%
servlet/image?url=images/assc/2024/04/202404291757511714381071956.png 1
 
0.2%
servlet/image?url=images/assc/2016/01/201601081427481452230868847.jpg 1
 
0.2%
servlet/image/assc/2011/11/201111280953011322441581857.jpg 1
 
0.2%
servlet/image?url=images/assc/2023/10/202310111541591697006519952.jpg 1
 
0.2%
servlet/image/assc/2017/06/201706130932191497313939131.jpg 1
 
0.2%
servlet/image?url=images/assc/2016/07/201607191835501468920950006.jpg 1
 
0.2%
servlet/image?url=images/assc/2016/02/201602171717441455697064073.jpg 1
 
0.2%
servlet/image?url=images/assc/2019/11/201911101512331573366353966.jpg 1
 
0.2%
Other values (618) 618
98.4%
2024-05-11T17:20:51.034373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3951
 
9.9%
0 3874
 
9.7%
/ 3768
 
9.4%
2 3655
 
9.1%
e 2161
 
5.4%
s 2160
 
5.4%
4 1584
 
4.0%
a 1532
 
3.8%
3 1522
 
3.8%
g 1516
 
3.8%
Other values (24) 14366
35.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20724
51.7%
Lowercase Letter 14417
36.0%
Other Punctuation 4672
 
11.7%
Math Symbol 276
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2161
15.0%
s 2160
15.0%
a 1532
10.6%
g 1516
10.5%
m 915
6.3%
i 906
6.3%
r 904
6.3%
l 904
6.3%
v 628
 
4.4%
c 628
 
4.4%
Other values (10) 2163
15.0%
Decimal Number
ValueCountFrequency (%)
1 3951
19.1%
0 3874
18.7%
2 3655
17.6%
4 1584
7.6%
3 1522
 
7.3%
5 1496
 
7.2%
6 1286
 
6.2%
8 1194
 
5.8%
9 1089
 
5.3%
7 1073
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/ 3768
80.7%
. 628
 
13.4%
? 276
 
5.9%
Math Symbol
ValueCountFrequency (%)
= 276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25672
64.0%
Latin 14417
36.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2161
15.0%
s 2160
15.0%
a 1532
10.6%
g 1516
10.5%
m 915
6.3%
i 906
6.3%
r 904
6.3%
l 904
6.3%
v 628
 
4.4%
c 628
 
4.4%
Other values (10) 2163
15.0%
Common
ValueCountFrequency (%)
1 3951
15.4%
0 3874
15.1%
/ 3768
14.7%
2 3655
14.2%
4 1584
6.2%
3 1522
 
5.9%
5 1496
 
5.8%
6 1286
 
5.0%
8 1194
 
4.7%
9 1089
 
4.2%
Other values (4) 2253
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40089
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3951
 
9.9%
0 3874
 
9.7%
/ 3768
 
9.4%
2 3655
 
9.1%
e 2161
 
5.4%
s 2160
 
5.4%
4 1584
 
4.0%
a 1532
 
3.8%
3 1522
 
3.8%
g 1516
 
3.8%
Other values (24) 14366
35.8%

배치도
Text

MISSING 

Distinct651
Distinct (%)100.0%
Missing296
Missing (%)31.3%
Memory size7.5 KiB
2024-05-11T17:20:51.293991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length59
Mean length64.018433
Min length59

Characters and Unicode

Total characters41676
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique651 ?
Unique (%)100.0%

Sample

1st row/servlet/image?url=images/assc/2023/06/202306291610241688022624857.jpg
2nd row/servlet/image?url=images/assc/2023/12/202312171624291702797869657.jpg
3rd row/servlet/image?url=images/assc/2023/10/202310041155191696388119151.jpg
4th row/servlet/image?url=images/assc/2023/04/202304041054091680573249270.jpg
5th row/servlet/image?url=images/assc/2023/04/202304190855521681862152328.jpg
ValueCountFrequency (%)
servlet/image?url=images/assc/2023/04/202304051339001680669540129.pdf 1
 
0.2%
servlet/image/assc/2016/11/201611081043291478569409301.jpg 1
 
0.2%
servlet/image/assc/2010/07/201007131550041279003804496.jpg 1
 
0.2%
servlet/image?url=images/assc/2016/07/201607191835501468920950587.jpg 1
 
0.2%
servlet/image/assc/2017/09/201709291434281506663268592.jpg 1
 
0.2%
servlet/image/assc/2023/05/202305031714211683101661138.jpg 1
 
0.2%
servlet/image?url=images/assc/2024/04/202404291757531714381073785.png 1
 
0.2%
servlet/image?url=images/assc/2016/01/201601081427521452230872118.jpg 1
 
0.2%
servlet/image/assc/2012/01/201201251515201327472120278.jpg 1
 
0.2%
servlet/image?url=images/assc/2023/10/202310121651551697097115117.jpg 1
 
0.2%
Other values (641) 641
98.5%
2024-05-11T17:20:51.663901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4127
 
9.9%
0 4030
 
9.7%
/ 3906
 
9.4%
2 3806
 
9.1%
e 2250
 
5.4%
s 2250
 
5.4%
4 1665
 
4.0%
3 1603
 
3.8%
a 1599
 
3.8%
g 1578
 
3.8%
Other values (24) 14862
35.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21483
51.5%
Lowercase Letter 15042
36.1%
Other Punctuation 4854
 
11.6%
Math Symbol 297
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2250
15.0%
s 2250
15.0%
a 1599
10.6%
g 1578
10.5%
m 957
6.4%
i 951
6.3%
r 948
6.3%
l 948
6.3%
t 651
 
4.3%
v 651
 
4.3%
Other values (10) 2259
15.0%
Decimal Number
ValueCountFrequency (%)
1 4127
19.2%
0 4030
18.8%
2 3806
17.7%
4 1665
7.8%
3 1603
 
7.5%
5 1464
 
6.8%
6 1406
 
6.5%
8 1133
 
5.3%
7 1132
 
5.3%
9 1117
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/ 3906
80.5%
. 651
 
13.4%
? 297
 
6.1%
Math Symbol
ValueCountFrequency (%)
= 297
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26634
63.9%
Latin 15042
36.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2250
15.0%
s 2250
15.0%
a 1599
10.6%
g 1578
10.5%
m 957
6.4%
i 951
6.3%
r 948
6.3%
l 948
6.3%
t 651
 
4.3%
v 651
 
4.3%
Other values (10) 2259
15.0%
Common
ValueCountFrequency (%)
1 4127
15.5%
0 4030
15.1%
/ 3906
14.7%
2 3806
14.3%
4 1665
6.3%
3 1603
 
6.0%
5 1464
 
5.5%
6 1406
 
5.3%
8 1133
 
4.3%
7 1132
 
4.3%
Other values (4) 2362
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4127
 
9.9%
0 4030
 
9.7%
/ 3906
 
9.4%
2 3806
 
9.1%
e 2250
 
5.4%
s 2250
 
5.4%
4 1665
 
4.0%
3 1603
 
3.8%
a 1599
 
3.8%
g 1578
 
3.8%
Other values (24) 14862
35.7%
Distinct574
Distinct (%)81.7%
Missing244
Missing (%)25.8%
Memory size7.5 KiB
2024-05-11T17:20:51.982791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length55
Mean length21.227596
Min length2

Characters and Unicode

Total characters14923
Distinct characters359
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique553 ?
Unique (%)78.7%

Sample

1st row서울특별시 중랑구 상봉로 75, 301호 (면목동)
2nd row서울특별시 은평구 갈현로33길 4, 2층 (갈현동)
3rd row서울특별시 성북구 화랑로33길 14, 1층 (장위동)
4th row서울특별시 도봉구 도봉로110다길 6, 1층 부동산1번지 (창동)
5th row서울특별시 관악구 신사로 150, 2층 (신림동)
ValueCountFrequency (%)
서울특별시 359
 
12.0%
2층 137
 
4.6%
3층 101
 
3.4%
1층 61
 
2.0%
4층 42
 
1.4%
성북구 35
 
1.2%
201호 32
 
1.1%
서초구 31
 
1.0%
영등포구 28
 
0.9%
중랑구 26
 
0.9%
Other values (1212) 2138
71.5%
2024-05-11T17:20:52.740678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2289
 
15.3%
2 567
 
3.8%
553
 
3.7%
1 508
 
3.4%
459
 
3.1%
, 447
 
3.0%
422
 
2.8%
) 420
 
2.8%
( 420
 
2.8%
392
 
2.6%
Other values (349) 8446
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8629
57.8%
Decimal Number 2633
 
17.6%
Space Separator 2289
 
15.3%
Other Punctuation 449
 
3.0%
Close Punctuation 421
 
2.8%
Open Punctuation 421
 
2.8%
Dash Punctuation 56
 
0.4%
Uppercase Letter 25
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
553
 
6.4%
459
 
5.3%
422
 
4.9%
392
 
4.5%
389
 
4.5%
383
 
4.4%
367
 
4.3%
359
 
4.2%
359
 
4.2%
291
 
3.4%
Other values (324) 4655
53.9%
Decimal Number
ValueCountFrequency (%)
2 567
21.5%
1 508
19.3%
3 387
14.7%
0 343
13.0%
4 242
9.2%
5 169
 
6.4%
6 127
 
4.8%
7 106
 
4.0%
8 93
 
3.5%
9 91
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
B 15
60.0%
A 5
 
20.0%
S 2
 
8.0%
M 1
 
4.0%
C 1
 
4.0%
H 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 447
99.6%
1
 
0.2%
1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 420
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 420
99.8%
[ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2289
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8629
57.8%
Common 6269
42.0%
Latin 25
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
553
 
6.4%
459
 
5.3%
422
 
4.9%
392
 
4.5%
389
 
4.5%
383
 
4.4%
367
 
4.3%
359
 
4.2%
359
 
4.2%
291
 
3.4%
Other values (324) 4655
53.9%
Common
ValueCountFrequency (%)
2289
36.5%
2 567
 
9.0%
1 508
 
8.1%
, 447
 
7.1%
) 420
 
6.7%
( 420
 
6.7%
3 387
 
6.2%
0 343
 
5.5%
4 242
 
3.9%
5 169
 
2.7%
Other values (9) 477
 
7.6%
Latin
ValueCountFrequency (%)
B 15
60.0%
A 5
 
20.0%
S 2
 
8.0%
M 1
 
4.0%
C 1
 
4.0%
H 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8629
57.8%
ASCII 6292
42.2%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2289
36.4%
2 567
 
9.0%
1 508
 
8.1%
, 447
 
7.1%
) 420
 
6.7%
( 420
 
6.7%
3 387
 
6.2%
0 343
 
5.5%
4 242
 
3.8%
5 169
 
2.7%
Other values (13) 500
 
7.9%
Hangul
ValueCountFrequency (%)
553
 
6.4%
459
 
5.3%
422
 
4.9%
392
 
4.5%
389
 
4.5%
383
 
4.4%
367
 
4.3%
359
 
4.2%
359
 
4.2%
291
 
3.4%
Other values (324) 4655
53.9%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct735
Distinct (%)98.4%
Missing200
Missing (%)21.1%
Memory size7.5 KiB
2024-05-11T17:20:52.978711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length11.381526
Min length11

Characters and Unicode

Total characters8502
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

Unique729 ?
Unique (%)97.6%

Sample

1st row02-2208-2224
2nd row02-353-3538
3rd row02-3292-1181
4th row010-8131-6754
5th row02-869-3450
ValueCountFrequency (%)
02-434-2260 5
 
0.7%
02-2209-9455 4
 
0.5%
02-919-4016 3
 
0.4%
02-6369-5070 2
 
0.3%
02-986-0888 2
 
0.3%
02-2190-7664 2
 
0.3%
02-535-7745 1
 
0.1%
02-3477-7812 1
 
0.1%
02-2659-0051 1
 
0.1%
02-385-0050 1
 
0.1%
Other values (725) 725
97.1%
2024-05-11T17:20:53.340753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1494
17.6%
0 1401
16.5%
2 1363
16.0%
3 632
7.4%
1 562
 
6.6%
5 536
 
6.3%
4 508
 
6.0%
8 506
 
6.0%
6 503
 
5.9%
9 500
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7008
82.4%
Dash Punctuation 1494
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1401
20.0%
2 1363
19.4%
3 632
9.0%
1 562
8.0%
5 536
 
7.6%
4 508
 
7.2%
8 506
 
7.2%
6 503
 
7.2%
9 500
 
7.1%
7 497
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 1494
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8502
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1494
17.6%
0 1401
16.5%
2 1363
16.0%
3 632
7.4%
1 562
 
6.6%
5 536
 
6.3%
4 508
 
6.0%
8 506
 
6.0%
6 503
 
5.9%
9 500
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8502
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1494
17.6%
0 1401
16.5%
2 1363
16.0%
3 632
7.4%
1 562
 
6.6%
5 536
 
6.3%
4 508
 
6.0%
8 506
 
6.0%
6 503
 
5.9%
9 500
 
5.9%

Sample

사업번호자치구법정동사업구분운영구분추진위원회/조합명대표지번진행단계상태토지등 소유자 수정비구역명칭정비구역위치정비구역면적(㎡)건축연면적(㎡)용도지역용도지구택지면적(㎡)도로면적(㎡)공원면적(㎡)녹지면적(㎡)공공공지면적(㎡)학교면적(㎡)기타면적(㎡)주용도건폐율용적률높이(m)지상층수지하층수분양세대총수60㎡이하60㎡초과~85㎡이하85㎡초과임대세대총수(임대)40㎡이하(임대)40㎡초과~50㎡이하(임대)50㎡초과건축계획비고위치도조감도배치도조합사무실 주소조합사무실 전화번호
011260-900000932중랑구면목동가로주택정비조합면목역6구역 가로주택정비사업면목동 86-19조합설립인가운영96면목역6구역 가로주택정비사업중랑구 면목동 86-197658.9523925.61<NA><NA><NA><NA><NA><NA><NA><NA><NA>아파트37.48199.94<NA>27<NA>8491<NA><NA><NA><NA><NA>SH신속사업성 기준/servlet/image?url=images/assc/2022/08/202208031710201659514220659.png/servlet/image?url=images/assc/2022/08/202208031710201659514220842.jpg<NA>서울특별시 중랑구 상봉로 75, 301호 (면목동)02-2208-2224
111380-900000892은평구갈현동가로주택정비조합갈현동 이화연립일원 가로주택정비사업갈현동 259-7조합설립인가운영68갈현동 이화연립일원 가로주택정비사업은평구 갈현동 259-75351.019046.87제2종 일반주거지역(7층 이하)<NA><NA><NA><NA><NA><NA><NA><NA>제2종 일반주거(7층이하)47.47249.12<NA>210<NA>4069<NA><NA><NA>28<NA><NA>/servlet/image?url=images/assc/2024/05/202405091740221715244022793.jpg<NA><NA>서울특별시 은평구 갈현로33길 4, 2층 (갈현동)02-353-3538
211305-900001150강북구미아동재개발(주택정비형)공공지원자미아동 791-2882번지 일대 주택정비형 재개발사업미아동 791-2882정비계획 수립운영0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
311290-900000971성북구장위동가로주택정비조합장위11의4구역 가로주택정비사업조합장위동 66-146조합설립인가운영133장위11의4구역 가로주택정비사업성북구 장위동 66-1467189.7223540.19제2종일반주거지역7층 이하<NA>0.00.00.00.00.0<NA>아파트 및 부대복리시설36.2219.27<NA>72<NA>12142<NA><NA><NA>47<NA><NA>/servlet/image?url=images/assc/2023/06/202306291608021688022482243.jpg/servlet/image?url=images/assc/2023/06/202306291610241688022624810.jpg/servlet/image?url=images/assc/2023/06/202306291610241688022624857.jpg서울특별시 성북구 화랑로33길 14, 1층 (장위동)02-3292-1181
411320-900001118도봉구쌍문동지역주택조합쌍문동137번지 지역주택조합쌍문동 137-94조합설립인가운영0쌍문동137번지 지역주택조합도봉구 쌍문동 137-94외 5필지1662.1<NA>제2종 일반주거지역<NA>1662.1<NA><NA><NA><NA><NA><NA>아파트<NA><NA><NA>131<NA>52<NA><NA><NA><NA><NA><NA><NA>/servlet/image?url=images/assc/2023/12/202312171624271702797867846.jpg/servlet/image?url=images/assc/2023/12/202312171624281702797868712.jpg/servlet/image?url=images/assc/2023/12/202312171624291702797869657.jpg서울특별시 도봉구 도봉로110다길 6, 1층 부동산1번지 (창동)010-8131-6754
511620-900001117관악구신림동지역주택조합(가칭)신대방역2단지 지역주택조합 추진위원회신림동 475-83조합설립인가운영1481(가칭)신대방역2단지 지역주택조합관악구 신림동 475-83122610.0192475.37도시지역 - 일반주거지역 - 제23종일반주거지과밀억제권역122610.07277.06560.00.00.00.01000.0공동주택18.21121.2970125<NA>1188306<NA><NA><NA><NA><NA><NA>/servlet/image?url=images/assc/2023/10/202310041155181696388118624.jpg/servlet/image?url=images/assc/2023/10/202310041155191696388119035.jpg/servlet/image?url=images/assc/2023/10/202310041155191696388119151.jpg서울특별시 관악구 신사로 150, 2층 (신림동)02-869-3450
611710-900000876송파구거여동지역주택조합(가칭)거여파크지역주택조합거여동 6조합설립인가운영0지역주택조합송파구 거여동 6-022362.6178108.63제2종일반주거지역<NA><NA>1345.41508.1<NA><NA><NA><NA>공동주택21.67237.3<NA>253<NA>321172<NA><NA><NA><NA><NA><NA>/servlet/image?url=images/assc/2023/04/202304041051031680573063215.png/servlet/image?url=images/assc/2023/12/202312291209581703819398540.jpg/servlet/image?url=images/assc/2023/04/202304041054091680573249270.jpg서울특별시 송파구 동남로 282, 2층 202호(오금동, 재상빌딩) (오금동)02-6212-1021
711710-900000875송파구거여동지역주택조합거여역2 지역주택조합거여동 173-3조합설립인가운영0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
811710-900000874송파구거여동지역주택조합(가칭)거여역1지역주택조합거여동 17-9조합설립인가운영0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
911710-900000873송파구가락동지역주택조합(가칭)가락2지역주택조합가락동 32조합설립인가운영0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
사업번호자치구법정동사업구분운영구분추진위원회/조합명대표지번진행단계상태토지등 소유자 수정비구역명칭정비구역위치정비구역면적(㎡)건축연면적(㎡)용도지역용도지구택지면적(㎡)도로면적(㎡)공원면적(㎡)녹지면적(㎡)공공공지면적(㎡)학교면적(㎡)기타면적(㎡)주용도건폐율용적률높이(m)지상층수지하층수분양세대총수60㎡이하60㎡초과~85㎡이하85㎡초과임대세대총수(임대)40㎡이하(임대)40㎡초과~50㎡이하(임대)50㎡초과건축계획비고위치도조감도배치도조합사무실 주소조합사무실 전화번호
93711290-100008003성북구보문동재개발(주택정비형)조합보문제4구역 주택재개발정비사업조합보문동3가 225조합해산일시중단254보문제4구역 주택재개발 정비구역보문동3가 225번지 일대31252.9<NA>제2종 일반주거지역제2종 일반주거지역<NA><NA><NA><NA><NA><NA><NA>공동주택(아파트)20.7219.87421544409326186<NA>79<NA><NA><NA>/servlet/image/assc/2010/11/201011191745551290156355567.gif/servlet/image/assc/2010/11/201011101538051289371085319.jpg/servlet/image/assc/2010/11/201011101538091289371089030.jpg201호02-953-2039
93811290-100014000성북구정릉동재개발(주택정비형)조합정릉길음제9구역 주택재개발정비사업조합정릉동 10조합해산일시중단714정릉길음제9구역성북구 정릉동 1069998.6<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1254520484250<NA><NA><NA><NA><NA><NA>/servlet/image/assc/2010/03/201003121656191268380579953.jpg/servlet/image/assc/2010/03/201003121659071268380747476.jpg2층02-915-7710
93911290-100005003성북구석관동재개발(주택정비형)조합석관제3구역 주택재개발정비사업조합석관동 338-540조합해산일시중단142석관 제 3구역성북구 석관동338-540번지15232.033678.57제 2동 및 제 3종 일반 주거 지역<NA>11148.01505.01047.01532.0<NA><NA><NA>공동주택(아파트)23.96202.57<NA>15319934128371993412837<NA>/servlet/image/assc/201003081619281268032768944.jpg/servlet/image/assc/2009/12/200912301640331262158833781.jpg/servlet/image/assc/2009/12/200912301640331262158833390.jpg용호빌딩 4층 402호02-963-8835
94011290-100002003성북구돈암동재개발(주택정비형)조합돈암제5구역 주택재개발정비사업조합돈암동 13-7조합해산일시중단326돈암제5구역주택배개발정비사업조합성북구 돈암동 13-7 일대20990.0<NA>제3종일반주거지역18648.81272.3<NA>1069.0<NA><NA><NA>아파트17.49242.07<NA><NA><NA>40617619040<NA>84<NA><NA><NA>/servlet/image/assc/201002241021311266974491143.png/servlet/image/assc/2011/11/201111081557101320735430854.jpg/servlet/image/assc/2011/11/201111081557101320735430970.bmp103동 관리사무소 2층 조합사무실02-925-9002
94111140-100006000중구중림동재개발(도시정비형)추진위원회마포로5-10구역도시환경정비사업조합설립추진위원회중림동 186-1조합설립추진위원회승인일시중단109마포로 5-10구역 도시환경정비사업중구 중림동 186-1번지8646.348297.05업무,공동주택,판매시설도시환경정비사업6943.0<NA>1283.3<NA>420.0<NA><NA>주상복합56.98459.1<NA>193<NA><NA>1162<NA><NA><NA><NA><NA>/servlet/image/assc/201002221447271266817647160.jpg<NA><NA>2동 202호 상가02-364-3385
94211110-100003019종로구내자동재개발(도시정비형)추진위원회내자동 도시환경정비사업 조합설립추진위원회내자동 81조합설립추진위원회승인일시중단106내자.필운구역 도시환경정비사업종로구 내자동 81번지20877.063897.71제1종3종 일반주거지역 준주거지역 일반상업지역중심지 및 역사문화미관지구18941.561246.14385.0304.3<NA><NA><NA>공동주택 및 근린생활시설47.09334.0370193266421547055222211<NA>/servlet/image/assc/2013/02/201302282003181362049398377.jpg/servlet/image/assc/2013/02/201302282003181362049398686.jpg/servlet/image/assc/2013/03/201303022004451362222285681.jpg오피스텔1615호 내자동도시환경정비사업조합설립추진위원회02-725-5600
94311500-100002008강서구등촌동재건축조합태원연립주택재건축정비사업조합등촌동 651이전고시일시중단24태원연립 주택 재건축 정비사업 신축공사강서구 등촌동 651번지1080.73358.58제3종일반주거지역<NA>1070.7<NA><NA><NA><NA><NA><NA>공동주택37.35229.72<NA>91<NA><NA><NA><NA><NA><NA><NA><NA><NA>/servlet/image/assc/2010/08/201008271152551282877575583.jpg/servlet/image/assc/2010/08/201008271152561282877576038.jpg/servlet/image/assc/2010/08/201008271152571282877577184.jpg<NA><NA>
94411500-100002005강서구화곡동재건축추진위원회유풍연립주택재건축정비사업조합설립추진위원회화곡동 1040-24조합설립추진위원회승인일시중단18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
94511470-100001009양천구신월동재건축조합신월4동431번지일대 주택재건축정비사업조합신월동 432-6이전고시일시중단231양천구 신월4동 주택재건축정비구역양천구 신월동 432-618214.948837.3일반주거지역<NA>15365.11409.6<NA><NA>695.5<NA>744.7공동주택및근린생활시설26.02210.02<NA>152<NA>82235<NA><NA><NA><NA>11<NA>/servlet/image/assc/201003111038511268271531714.jpg/servlet/image/assc/2009/12/200912301640441262158844156.jpg/servlet/image/assc/2009/12/200912301640431262158843515.jpg<NA><NA>
94611440-100006009마포구염리동재개발(주택정비형)추진위원회염리5구역 주택재개발 조합설립추진위원회(뉴타운)염리동 105조합설립추진위원회승인일시중단574염리5구역 주택재개발정비사업 조합설립추진위원회마포구 염리동 10581426.0187796.73제3종일반주거지역대흥로변 일반미관지구57164.016439.05823.0<NA>2000.0<NA><NA>공동주택25.06239.9575<NA><NA>1041439435167178767626<NA>/servlet/image/assc/2010/07/201007271119301280197170628.jpg/servlet/image/assc/2010/07/201007271046091280195169822.jpg/servlet/image/assc/2010/04/201004020948001270169280040.jpg<NA>02-716-8896