Overview

Dataset statistics

Number of variables33
Number of observations500
Missing cells4227
Missing cells (%)25.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory139.8 KiB
Average record size in memory286.3 B

Variable types

Text8
Categorical9
Numeric13
Unsupported3

Dataset

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

Alerts

블록 has constant value ""Constant
새주소_지상지하_코드 has constant value ""Constant
부속_블록 has constant value ""Constant
대장_구분_코드 is highly imbalanced (68.9%)Imbalance
대장_구분_코드_명 is highly imbalanced (72.2%)Imbalance
대장_종류_코드 is highly imbalanced (57.3%)Imbalance
대장_종류_코드_명 is highly imbalanced (61.8%)Imbalance
대지_구분_코드 is highly imbalanced (56.4%)Imbalance
부속_대장_구분_코드 is highly imbalanced (67.0%)Imbalance
부속_대장_구분_코드_명 is highly imbalanced (69.8%)Imbalance
부속_대지_구분_코드 is highly imbalanced (82.3%)Imbalance
도로명_대지_위치 has 104 (20.8%) missing valuesMissing
건물_명 has 299 (59.8%) missing valuesMissing
특수지_명 has 498 (99.6%) missing valuesMissing
블록 has 499 (99.8%) missing valuesMissing
로트 has 500 (100.0%) missing valuesMissing
새주소_도로_코드 has 101 (20.2%) missing valuesMissing
새주소_법정동_코드 has 85 (17.0%) missing valuesMissing
새주소_본_번 has 71 (14.2%) missing valuesMissing
새주소_부_번 has 93 (18.6%) missing valuesMissing
부속_특수지_명 has 500 (100.0%) missing valuesMissing
부속_블록 has 499 (99.8%) missing valuesMissing
부속_로트 has 500 (100.0%) missing valuesMissing
부속_기타_지번_명 has 476 (95.2%) missing valuesMissing
로트 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부속_특수지_명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부속_로트 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지 has 191 (38.2%) zerosZeros
새주소_본_번 has 33 (6.6%) zerosZeros
새주소_부_번 has 310 (62.0%) zerosZeros
부속_번 has 6 (1.2%) zerosZeros
부속_지 has 133 (26.6%) zerosZeros

Reproduction

Analysis started2023-12-10 15:01:23.690450
Analysis finished2023-12-10 15:01:25.282272
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리_건축물대장_PK
Text

Distinct497
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:01:25.631250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length12.542
Min length8

Characters and Unicode

Total characters6271
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

Unique494 ?
Unique (%)98.8%

Sample

1st row41287-226871
2nd row48310-100207754
3rd row30200-15467
4th row41590-100294293
5th row41670-14011
ValueCountFrequency (%)
43760-100193284 2
 
0.4%
31710-100195877 2
 
0.4%
43760-100193251 2
 
0.4%
41650-21958 1
 
0.2%
41570-100173678 1
 
0.2%
45790-11070 1
 
0.2%
48240-23535 1
 
0.2%
46840-100182629 1
 
0.2%
47290-24309 1
 
0.2%
29170-100190538 1
 
0.2%
Other values (487) 487
97.4%
2023-12-11T00:01:26.468805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1137
18.1%
0 1135
18.1%
4 722
11.5%
2 578
9.2%
- 500
8.0%
7 440
 
7.0%
3 403
 
6.4%
8 383
 
6.1%
5 355
 
5.7%
6 320
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5771
92.0%
Dash Punctuation 500
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1137
19.7%
0 1135
19.7%
4 722
12.5%
2 578
10.0%
7 440
 
7.6%
3 403
 
7.0%
8 383
 
6.6%
5 355
 
6.2%
6 320
 
5.5%
9 298
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6271
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1137
18.1%
0 1135
18.1%
4 722
11.5%
2 578
9.2%
- 500
8.0%
7 440
 
7.0%
3 403
 
6.4%
8 383
 
6.1%
5 355
 
5.7%
6 320
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6271
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1137
18.1%
0 1135
18.1%
4 722
11.5%
2 578
9.2%
- 500
8.0%
7 440
 
7.0%
3 403
 
6.4%
8 383
 
6.1%
5 355
 
5.7%
6 320
 
5.1%

대장_구분_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
472 
2
 
28

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 (%)
1 472
94.4%
2 28
 
5.6%

Length

2023-12-11T00:01:26.852991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:27.062787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 472
94.4%
2 28
 
5.6%

대장_구분_코드_명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
일반
476 
집합
 
24

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 476
95.2%
집합 24
 
4.8%

Length

2023-12-11T00:01:27.292601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:27.512401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 476
95.2%
집합 24
 
4.8%

대장_종류_코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
414 
1
49 
3
 
35
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 414
82.8%
1 49
 
9.8%
3 35
 
7.0%
4 2
 
0.4%

Length

2023-12-11T00:01:27.721921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:27.953417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 414
82.8%
1 49
 
9.8%
3 35
 
7.0%
4 2
 
0.4%

대장_종류_코드_명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
일반건축물
430 
총괄표제부
 
37
표제부
 
28
전유부
 
5

Length

Max length5
Median length5
Mean length4.868
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반건축물 430
86.0%
총괄표제부 37
 
7.4%
표제부 28
 
5.6%
전유부 5
 
1.0%

Length

2023-12-11T00:01:28.189445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:28.420475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반건축물 430
86.0%
총괄표제부 37
 
7.4%
표제부 28
 
5.6%
전유부 5
 
1.0%

대지_위치
Text

Distinct450
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:01:29.081263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length22.094
Min length16

Characters and Unicode

Total characters11047
Distinct characters260
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique420 ?
Unique (%)84.0%

Sample

1st row경상북도 청도군 운문면 마일리 125-1번지
2nd row전라북도 임실군 임실읍 이도리 71-3번지
3rd row경상북도 영덕군 영해면 괴시리 128번지
4th row경기도 남양주시 퇴계원면 퇴계원리 218-202번지
5th row경상북도 김천시 구성면 송죽리 606번지
ValueCountFrequency (%)
경기도 98
 
4.1%
경상북도 59
 
2.5%
충청북도 47
 
2.0%
산 43
 
1.8%
전라북도 38
 
1.6%
울산광역시 37
 
1.5%
강원도 35
 
1.5%
충청남도 33
 
1.4%
경상남도 33
 
1.4%
전라남도 32
 
1.3%
Other values (1230) 1946
81.0%
2023-12-11T00:01:30.547064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1904
 
17.2%
지 521
 
4.7%
번 501
 
4.5%
도 405
 
3.7%
1 373
 
3.4%
시 360
 
3.3%
- 296
 
2.7%
리 292
 
2.6%
동 276
 
2.5%
2 239
 
2.2%
Other values (250) 5880
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7096
64.2%
Space Separator 1904
 
17.2%
Decimal Number 1748
 
15.8%
Dash Punctuation 296
 
2.7%
Uppercase Letter 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 521
 
7.3%
번 501
 
7.1%
도 405
 
5.7%
시 360
 
5.1%
리 292
 
4.1%
동 276
 
3.9%
산 209
 
2.9%
경 206
 
2.9%
면 195
 
2.7%
북 192
 
2.7%
Other values (235) 3939
55.5%
Decimal Number
ValueCountFrequency (%)
1 373
21.3%
2 239
13.7%
3 178
10.2%
5 168
9.6%
4 148
 
8.5%
7 139
 
8.0%
6 132
 
7.6%
0 129
 
7.4%
9 123
 
7.0%
8 119
 
6.8%
Space Separator
ValueCountFrequency (%)
1904
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 296
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7094
64.2%
Common 3950
35.8%
Han 2
 
< 0.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 521
 
7.3%
번 501
 
7.1%
도 405
 
5.7%
시 360
 
5.1%
리 292
 
4.1%
동 276
 
3.9%
산 209
 
2.9%
경 206
 
2.9%
면 195
 
2.7%
북 192
 
2.7%
Other values (233) 3937
55.5%
Common
ValueCountFrequency (%)
1904
48.2%
1 373
 
9.4%
- 296
 
7.5%
2 239
 
6.1%
3 178
 
4.5%
5 168
 
4.3%
4 148
 
3.7%
7 139
 
3.5%
6 132
 
3.3%
0 129
 
3.3%
Other values (4) 244
 
6.2%
Han
ValueCountFrequency (%)
花 1
50.0%
山 1
50.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7094
64.2%
ASCII 3951
35.8%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1904
48.2%
1 373
 
9.4%
- 296
 
7.5%
2 239
 
6.0%
3 178
 
4.5%
5 168
 
4.3%
4 148
 
3.7%
7 139
 
3.5%
6 132
 
3.3%
0 129
 
3.3%
Other values (5) 245
 
6.2%
Hangul
ValueCountFrequency (%)
지 521
 
7.3%
번 501
 
7.1%
도 405
 
5.7%
시 360
 
5.1%
리 292
 
4.1%
동 276
 
3.9%
산 209
 
2.9%
경 206
 
2.9%
면 195
 
2.7%
북 192
 
2.7%
Other values (233) 3937
55.5%
CJK
ValueCountFrequency (%)
花 1
50.0%
山 1
50.0%

도로명_대지_위치
Text

MISSING 

Distinct352
Distinct (%)88.9%
Missing104
Missing (%)20.8%
Memory size4.0 KiB
2023-12-11T00:01:31.079761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length17.977273
Min length14

Characters and Unicode

Total characters7119
Distinct characters257
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique329 ?
Unique (%)83.1%

Sample

1st row경기도 포천시 시우동길 110-19
2nd row충청북도 음성군 행제길76번길 97-8
3rd row경기도 화성시 초록로 594-29
4th row충청남도 공주시 고마나루길 30
5th row경상북도 칠곡군 3공단1로 62-6
ValueCountFrequency (%)
경기도 79
 
4.8%
경상북도 60
 
3.7%
경상남도 33
 
2.0%
전라남도 32
 
2.0%
충청남도 30
 
1.8%
강원도 28
 
1.7%
충청북도 23
 
1.4%
전라북도 23
 
1.4%
남구 22
 
1.3%
울산광역시 21
 
1.3%
Other values (767) 1285
78.5%
2023-12-11T00:01:31.791202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1242
 
17.4%
도 332
 
4.7%
시 309
 
4.3%
로 300
 
4.2%
1 275
 
3.9%
2 207
 
2.9%
경 197
 
2.8%
남 147
 
2.1%
길 145
 
2.0%
구 144
 
2.0%
Other values (247) 3821
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4386
61.6%
Decimal Number 1376
 
19.3%
Space Separator 1242
 
17.4%
Dash Punctuation 114
 
1.6%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 332
 
7.6%
시 309
 
7.0%
로 300
 
6.8%
경 197
 
4.5%
남 147
 
3.4%
길 145
 
3.3%
구 144
 
3.3%
북 124
 
2.8%
군 112
 
2.6%
상 102
 
2.3%
Other values (234) 2474
56.4%
Decimal Number
ValueCountFrequency (%)
1 275
20.0%
2 207
15.0%
3 138
10.0%
0 132
9.6%
4 124
9.0%
6 112
8.1%
5 110
 
8.0%
9 95
 
6.9%
8 94
 
6.8%
7 89
 
6.5%
Space Separator
ValueCountFrequency (%)
1242
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4386
61.6%
Common 2733
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 332
 
7.6%
시 309
 
7.0%
로 300
 
6.8%
경 197
 
4.5%
남 147
 
3.4%
길 145
 
3.3%
구 144
 
3.3%
북 124
 
2.8%
군 112
 
2.6%
상 102
 
2.3%
Other values (234) 2474
56.4%
Common
ValueCountFrequency (%)
1242
45.4%
1 275
 
10.1%
2 207
 
7.6%
3 138
 
5.0%
0 132
 
4.8%
4 124
 
4.5%
- 114
 
4.2%
6 112
 
4.1%
5 110
 
4.0%
9 95
 
3.5%
Other values (3) 184
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4386
61.6%
ASCII 2733
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1242
45.4%
1 275
 
10.1%
2 207
 
7.6%
3 138
 
5.0%
0 132
 
4.8%
4 124
 
4.5%
- 114
 
4.2%
6 112
 
4.1%
5 110
 
4.0%
9 95
 
3.5%
Other values (3) 184
 
6.7%
Hangul
ValueCountFrequency (%)
도 332
 
7.6%
시 309
 
7.0%
로 300
 
6.8%
경 197
 
4.5%
남 147
 
3.4%
길 145
 
3.3%
구 144
 
3.3%
북 124
 
2.8%
군 112
 
2.6%
상 102
 
2.3%
Other values (234) 2474
56.4%

건물_명
Text

MISSING 

Distinct169
Distinct (%)84.1%
Missing299
Missing (%)59.8%
Memory size4.0 KiB
2023-12-11T00:01:32.176715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length7.5671642
Min length1

Characters and Unicode

Total characters1521
Distinct characters298
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

Unique157 ?
Unique (%)78.1%

Sample

1st row(주)중앙고속
2nd row학생군사학교
3rd row서남대학교
4th row학생군사학교
5th row신천초등학교(8동)
ValueCountFrequency (%)
현대자동차 10
 
3.8%
학생군사학교 9
 
3.4%
대구경북과학기술원 7
 
2.7%
학생중앙군사학교 6
 
2.3%
b동 6
 
2.3%
육군기계화학교 3
 
1.1%
s/y 3
 
1.1%
한국청소년안전체험관 2
 
0.8%
한국도로공사 2
 
0.8%
롯데캐슬 2
 
0.8%
Other values (202) 211
80.8%
2023-12-11T00:01:32.939225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 74
 
4.9%
60
 
3.9%
교 56
 
3.7%
대 45
 
3.0%
동 44
 
2.9%
사 35
 
2.3%
원 27
 
1.8%
장 26
 
1.7%
( 22
 
1.4%
주 22
 
1.4%
Other values (288) 1110
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1308
86.0%
Space Separator 60
 
3.9%
Decimal Number 46
 
3.0%
Uppercase Letter 37
 
2.4%
Open Punctuation 22
 
1.4%
Close Punctuation 22
 
1.4%
Other Punctuation 16
 
1.1%
Dash Punctuation 6
 
0.4%
Lowercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 74
 
5.7%
교 56
 
4.3%
대 45
 
3.4%
동 44
 
3.4%
사 35
 
2.7%
원 27
 
2.1%
장 26
 
2.0%
주 22
 
1.7%
군 20
 
1.5%
공 19
 
1.5%
Other values (258) 940
71.9%
Uppercase Letter
ValueCountFrequency (%)
C 7
18.9%
B 7
18.9%
S 5
13.5%
Y 3
8.1%
V 3
8.1%
A 3
8.1%
G 2
 
5.4%
L 1
 
2.7%
P 1
 
2.7%
I 1
 
2.7%
Other values (4) 4
10.8%
Decimal Number
ValueCountFrequency (%)
2 12
26.1%
1 9
19.6%
5 7
15.2%
8 6
13.0%
3 5
10.9%
6 4
 
8.7%
7 2
 
4.3%
9 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 9
56.2%
/ 5
31.2%
' 2
 
12.5%
Space Separator
ValueCountFrequency (%)
60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1308
86.0%
Common 172
 
11.3%
Latin 41
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 74
 
5.7%
교 56
 
4.3%
대 45
 
3.4%
동 44
 
3.4%
사 35
 
2.7%
원 27
 
2.1%
장 26
 
2.0%
주 22
 
1.7%
군 20
 
1.5%
공 19
 
1.5%
Other values (258) 940
71.9%
Common
ValueCountFrequency (%)
60
34.9%
( 22
 
12.8%
) 22
 
12.8%
2 12
 
7.0%
1 9
 
5.2%
. 9
 
5.2%
5 7
 
4.1%
8 6
 
3.5%
- 6
 
3.5%
3 5
 
2.9%
Other values (5) 14
 
8.1%
Latin
ValueCountFrequency (%)
C 7
17.1%
B 7
17.1%
S 5
12.2%
k 4
9.8%
Y 3
7.3%
V 3
7.3%
A 3
7.3%
G 2
 
4.9%
L 1
 
2.4%
P 1
 
2.4%
Other values (5) 5
12.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1308
86.0%
ASCII 213
 
14.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 74
 
5.7%
교 56
 
4.3%
대 45
 
3.4%
동 44
 
3.4%
사 35
 
2.7%
원 27
 
2.1%
장 26
 
2.0%
주 22
 
1.7%
군 20
 
1.5%
공 19
 
1.5%
Other values (258) 940
71.9%
ASCII
ValueCountFrequency (%)
60
28.2%
( 22
 
10.3%
) 22
 
10.3%
2 12
 
5.6%
1 9
 
4.2%
. 9
 
4.2%
C 7
 
3.3%
B 7
 
3.3%
5 7
 
3.3%
8 6
 
2.8%
Other values (20) 52
24.4%

시군구_코드
Real number (ℝ)

Distinct178
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40567.878
Minimum11110
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:33.436636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11680
Q141360
median43113
Q346830
95-th percentile48330
Maximum50130
Range39020
Interquartile range (IQR)5470

Descriptive statistics

Standard deviation9162.5389
Coefficient of variation (CV)0.22585699
Kurtosis3.1713855
Mean40567.878
Median Absolute Deviation (MAD)2627
Skewness-1.9067681
Sum20283939
Variance83952120
MonotonicityNot monotonic
2023-12-11T00:01:33.943011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47111 14
 
2.8%
41461 13
 
2.6%
46880 11
 
2.2%
31200 9
 
1.8%
47290 9
 
1.8%
31140 8
 
1.6%
41590 8
 
1.6%
41500 7
 
1.4%
48250 7
 
1.4%
43130 6
 
1.2%
Other values (168) 408
81.6%
ValueCountFrequency (%)
11110 2
0.4%
11140 2
0.4%
11170 4
0.8%
11215 3
0.6%
11230 1
 
0.2%
11260 1
 
0.2%
11290 2
0.4%
11380 2
0.4%
11440 1
 
0.2%
11500 1
 
0.2%
ValueCountFrequency (%)
50130 1
 
0.2%
50110 4
0.8%
48870 3
0.6%
48860 4
0.8%
48850 2
0.4%
48740 4
0.8%
48730 4
0.8%
48720 2
0.4%
48330 2
0.4%
48310 2
0.4%

법정동_코드
Real number (ℝ)

Distinct178
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22616.624
Minimum10100
Maximum46038
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:34.283849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10100
5-th percentile10200
Q111200
median25029
Q333025
95-th percentile39024
Maximum46038
Range35938
Interquartile range (IQR)21825

Descriptive statistics

Standard deviation10843.633
Coefficient of variation (CV)0.47945409
Kurtosis-1.5920137
Mean22616.624
Median Absolute Deviation (MAD)11993
Skewness0.13296809
Sum11308312
Variance1.1758437 × 108
MonotonicityNot monotonic
2023-12-11T00:01:34.584713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10200 17
 
3.4%
11100 16
 
3.2%
10900 15
 
3.0%
11500 15
 
3.0%
10100 14
 
2.8%
10400 13
 
2.6%
10800 12
 
2.4%
10500 11
 
2.2%
11200 10
 
2.0%
25321 10
 
2.0%
Other values (168) 367
73.4%
ValueCountFrequency (%)
10100 14
2.8%
10200 17
3.4%
10300 5
 
1.0%
10400 13
2.6%
10500 11
2.2%
10600 4
 
0.8%
10700 7
1.4%
10800 12
2.4%
10900 15
3.0%
11000 6
 
1.2%
ValueCountFrequency (%)
46038 1
0.2%
44049 1
0.2%
41031 1
0.2%
41028 1
0.2%
41022 1
0.2%
41021 1
0.2%
40032 1
0.2%
40029 1
0.2%
40027 2
0.4%
40025 1
0.2%

대지_구분_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
455 
1
 
45

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 (%)
0 455
91.0%
1 45
 
9.0%

Length

2023-12-11T00:01:35.012167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:35.327088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 455
91.0%
1 45
 
9.0%

번
Real number (ℝ)

Distinct324
Distinct (%)64.9%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean422.47295
Minimum1
Maximum3184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:35.690821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.9
Q193.5
median307
Q3634.5
95-th percentile1279.8
Maximum3184
Range3183
Interquartile range (IQR)541

Descriptive statistics

Standard deviation432.76939
Coefficient of variation (CV)1.0243718
Kurtosis6.0054431
Mean422.47295
Median Absolute Deviation (MAD)249
Skewness1.9280441
Sum210814
Variance187289.35
MonotonicityNot monotonic
2023-12-11T00:01:36.010059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 12
 
2.4%
687 12
 
2.4%
214 10
 
2.0%
12 8
 
1.6%
100 8
 
1.6%
166 8
 
1.6%
55 5
 
1.0%
27 5
 
1.0%
506 5
 
1.0%
2 4
 
0.8%
Other values (314) 422
84.4%
ValueCountFrequency (%)
1 12
2.4%
2 4
 
0.8%
3 4
 
0.8%
5 1
 
0.2%
6 3
 
0.6%
7 1
 
0.2%
8 1
 
0.2%
10 1
 
0.2%
11 3
 
0.6%
12 8
1.6%
ValueCountFrequency (%)
3184 1
 
0.2%
2876 1
 
0.2%
2050 1
 
0.2%
1870 1
 
0.2%
1858 2
0.4%
1741 3
0.6%
1718 1
 
0.2%
1680 1
 
0.2%
1656 1
 
0.2%
1645 1
 
0.2%

지
Real number (ℝ)

ZEROS 

Distinct45
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.408
Minimum0
Maximum496
Zeros191
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:36.377830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile23
Maximum496
Range496
Interquartile range (IQR)4

Descriptive statistics

Standard deviation27.989862
Coefficient of variation (CV)4.3679561
Kurtosis201.14761
Mean6.408
Median Absolute Deviation (MAD)1
Skewness12.756746
Sum3204
Variance783.4324
MonotonicityNot monotonic
2023-12-11T00:01:36.716743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 191
38.2%
1 112
22.4%
2 35
 
7.0%
3 27
 
5.4%
4 18
 
3.6%
5 18
 
3.6%
6 15
 
3.0%
14 10
 
2.0%
7 9
 
1.8%
9 8
 
1.6%
Other values (35) 57
 
11.4%
ValueCountFrequency (%)
0 191
38.2%
1 112
22.4%
2 35
 
7.0%
3 27
 
5.4%
4 18
 
3.6%
5 18
 
3.6%
6 15
 
3.0%
7 9
 
1.8%
8 3
 
0.6%
9 8
 
1.6%
ValueCountFrequency (%)
496 1
0.2%
248 1
0.2%
166 1
0.2%
105 1
0.2%
96 1
0.2%
80 1
0.2%
75 1
0.2%
73 1
0.2%
65 1
0.2%
58 1
0.2%

특수지_명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing498
Missing (%)99.6%
Memory size4.0 KiB
2023-12-11T00:01:37.102664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8
Min length5

Characters and Unicode

Total characters16
Distinct characters13
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row21B2L
2nd rowKCC울산일반산업단지
ValueCountFrequency (%)
21b2l 1
50.0%
kcc울산일반산업단지 1
50.0%
2023-12-11T00:01:37.774784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
12.5%
C 2
12.5%
산 2
12.5%
1 1
 
6.2%
B 1
 
6.2%
L 1
 
6.2%
K 1
 
6.2%
울 1
 
6.2%
일 1
 
6.2%
반 1
 
6.2%
Other values (3) 3
18.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
50.0%
Uppercase Letter 5
31.2%
Decimal Number 3
 
18.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 2
25.0%
울 1
12.5%
일 1
12.5%
반 1
12.5%
업 1
12.5%
단 1
12.5%
지 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
C 2
40.0%
B 1
20.0%
L 1
20.0%
K 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
50.0%
Latin 5
31.2%
Common 3
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 2
25.0%
울 1
12.5%
일 1
12.5%
반 1
12.5%
업 1
12.5%
단 1
12.5%
지 1
12.5%
Latin
ValueCountFrequency (%)
C 2
40.0%
B 1
20.0%
L 1
20.0%
K 1
20.0%
Common
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
50.0%
Hangul 8
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
25.0%
C 2
25.0%
1 1
12.5%
B 1
12.5%
L 1
12.5%
K 1
12.5%
Hangul
ValueCountFrequency (%)
산 2
25.0%
울 1
12.5%
일 1
12.5%
반 1
12.5%
업 1
12.5%
단 1
12.5%
지 1
12.5%

블록
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing499
Missing (%)99.8%
Memory size4.0 KiB
2023-12-11T00:01:38.014588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories2 ?
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 row4B
ValueCountFrequency (%)
4b 1
100.0%
2023-12-11T00:01:38.468639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
50.0%
B 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
50.0%
Uppercase Letter 1
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
50.0%
Latin 1
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
50.0%
B 1
50.0%

로트
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

새주소_도로_코드
Real number (ℝ)

MISSING 

Distinct358
Distinct (%)89.7%
Missing101
Missing (%)20.2%
Infinite0
Infinite (%)0.0%
Mean4.0552097 × 1011
Minimum1.111041 × 1011
Maximum5.0130335 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:38.866938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111041 × 1011
5-th percentile2.6317223 × 1011
Q14.112526 × 1011
median4.3130324 × 1011
Q34.6810468 × 1011
95-th percentile4.8840234 × 1011
Maximum5.0130335 × 1011
Range3.9019925 × 1011
Interquartile range (IQR)5.6852083 × 1010

Descriptive statistics

Standard deviation8.7348761 × 1010
Coefficient of variation (CV)0.21539888
Kurtosis2.0347264
Mean4.0552097 × 1011
Median Absolute Deviation (MAD)3.6801441 × 1010
Skewness-1.5281086
Sum1.6180287 × 1014
Variance7.6298061 × 1021
MonotonicityNot monotonic
2023-12-11T00:01:39.296149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
312003169028 9
 
1.8%
471113303050 9
 
1.8%
311403170009 5
 
1.0%
472903313081 4
 
0.8%
414613203081 4
 
0.8%
479303325022 3
 
0.6%
317103173096 3
 
0.6%
431144520120 2
 
0.4%
457503277037 2
 
0.4%
277102148003 2
 
0.4%
Other values (348) 356
71.2%
(Missing) 101
 
20.2%
ValueCountFrequency (%)
111104100236 1
0.2%
111104100478 1
0.2%
111704106159 1
0.2%
112153104009 1
0.2%
112604118110 1
0.2%
112604118329 1
0.2%
112604118341 1
0.2%
113804133241 1
0.2%
114104136322 1
0.2%
115603118024 1
0.2%
ValueCountFrequency (%)
501303350332 1
0.2%
501303349239 1
0.2%
501303349235 1
0.2%
501104849157 1
0.2%
501104848739 1
0.2%
501104848337 1
0.2%
501104847114 1
0.2%
501103349124 1
0.2%
501103349079 1
0.2%
501103349016 1
0.2%

새주소_법정동_코드
Real number (ℝ)

MISSING 

Distinct132
Distinct (%)31.8%
Missing85
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean22321.986
Minimum10101
Maximum47001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:39.717341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10301
Q111201.5
median25001
Q333001
95-th percentile38003.2
Maximum47001
Range36900
Interquartile range (IQR)21799.5

Descriptive statistics

Standard deviation10827.336
Coefficient of variation (CV)0.48505256
Kurtosis-1.5837653
Mean22321.986
Median Absolute Deviation (MAD)12000
Skewness0.19031064
Sum9263624
Variance1.1723121 × 108
MonotonicityNot monotonic
2023-12-11T00:01:40.042225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25001 26
 
5.2%
25301 25
 
5.0%
31001 20
 
4.0%
32001 13
 
2.6%
34001 13
 
2.6%
35001 12
 
2.4%
33001 12
 
2.4%
37001 11
 
2.2%
36001 10
 
2.0%
10701 9
 
1.8%
Other values (122) 264
52.8%
(Missing) 85
 
17.0%
ValueCountFrequency (%)
10101 7
1.4%
10201 8
1.6%
10202 5
1.0%
10301 6
1.2%
10302 5
1.0%
10303 1
 
0.2%
10401 5
1.0%
10402 3
 
0.6%
10404 1
 
0.2%
10501 5
1.0%
ValueCountFrequency (%)
47001 1
 
0.2%
44001 1
 
0.2%
42001 1
 
0.2%
41003 1
 
0.2%
41001 2
 
0.4%
40001 7
1.4%
39006 1
 
0.2%
39004 1
 
0.2%
39003 1
 
0.2%
39001 4
0.8%

새주소_지상지하_코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-11T00:01:40.408842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:40.603664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

새주소_본_번
Real number (ℝ)

MISSING  ZEROS 

Distinct240
Distinct (%)55.9%
Missing71
Missing (%)14.2%
Infinite0
Infinite (%)0.0%
Mean366.40093
Minimum0
Maximum6262
Zeros33
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:40.841018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q129
median100
Q3318
95-th percentile1683.4
Maximum6262
Range6262
Interquartile range (IQR)289

Descriptive statistics

Standard deviation767.46839
Coefficient of variation (CV)2.0946136
Kurtosis27.499395
Mean366.40093
Median Absolute Deviation (MAD)91
Skewness4.6340861
Sum157186
Variance589007.72
MonotonicityNot monotonic
2023-12-11T00:01:41.167425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 33
 
6.6%
700 10
 
2.0%
30 9
 
1.8%
280 9
 
1.8%
1 6
 
1.2%
24 6
 
1.2%
32 6
 
1.2%
20 6
 
1.2%
658 5
 
1.0%
7 5
 
1.0%
Other values (230) 334
66.8%
(Missing) 71
 
14.2%
ValueCountFrequency (%)
0 33
6.6%
1 6
 
1.2%
2 2
 
0.4%
3 2
 
0.4%
4 2
 
0.4%
5 1
 
0.2%
6 3
 
0.6%
7 5
 
1.0%
8 1
 
0.2%
9 1
 
0.2%
ValueCountFrequency (%)
6262 3
0.6%
4673 1
 
0.2%
4001 1
 
0.2%
3197 1
 
0.2%
2940 1
 
0.2%
2715 1
 
0.2%
2543 1
 
0.2%
2406 2
0.4%
2396 1
 
0.2%
2365 1
 
0.2%

새주소_부_번
Real number (ℝ)

MISSING  ZEROS 

Distinct46
Distinct (%)11.3%
Missing93
Missing (%)18.6%
Infinite0
Infinite (%)0.0%
Mean7.4422604
Minimum0
Maximum313
Zeros310
Zeros (%)62.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:41.507004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile45.7
Maximum313
Range313
Interquartile range (IQR)0

Descriptive statistics

Standard deviation24.724412
Coefficient of variation (CV)3.3221643
Kurtosis63.18297
Mean7.4422604
Median Absolute Deviation (MAD)0
Skewness6.5899702
Sum3029
Variance611.29653
MonotonicityNot monotonic
2023-12-11T00:01:41.811821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 310
62.0%
1 9
 
1.8%
8 8
 
1.6%
91 4
 
0.8%
2 4
 
0.8%
16 4
 
0.8%
12 4
 
0.8%
7 4
 
0.8%
11 3
 
0.6%
30 3
 
0.6%
Other values (36) 54
 
10.8%
(Missing) 93
 
18.6%
ValueCountFrequency (%)
0 310
62.0%
1 9
 
1.8%
2 4
 
0.8%
3 2
 
0.4%
4 3
 
0.6%
5 3
 
0.6%
6 1
 
0.2%
7 4
 
0.8%
8 8
 
1.6%
9 2
 
0.4%
ValueCountFrequency (%)
313 1
 
0.2%
141 1
 
0.2%
135 1
 
0.2%
113 1
 
0.2%
109 1
 
0.2%
91 4
0.8%
86 1
 
0.2%
82 1
 
0.2%
74 2
0.4%
72 1
 
0.2%

부속_대장_구분_코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
455 
2
 
28
<NA>
 
17

Length

Max length4
Median length1
Mean length1.102
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 455
91.0%
2 28
 
5.6%
<NA> 17
 
3.4%

Length

2023-12-11T00:01:42.160635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:42.377935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 455
91.0%
2 28
 
5.6%
na 17
 
3.4%

부속_대장_구분_코드_명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
일반
459 
집합
 
30
<NA>
 
11

Length

Max length4
Median length2
Mean length2.044
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 459
91.8%
집합 30
 
6.0%
<NA> 11
 
2.2%

Length

2023-12-11T00:01:42.687363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:42.908966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 459
91.8%
집합 30
 
6.0%
na 11
 
2.2%

부속_시군구_코드
Real number (ℝ)

Distinct180
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40474.682
Minimum11140
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:43.129197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11140
5-th percentile26258.5
Q141171
median43114
Q346880
95-th percentile48730
Maximum50130
Range38990
Interquartile range (IQR)5709

Descriptive statistics

Standard deviation8876.5836
Coefficient of variation (CV)0.219312
Kurtosis2.4108373
Mean40474.682
Median Absolute Deviation (MAD)3766
Skewness-1.6371233
Sum20237341
Variance78793737
MonotonicityNot monotonic
2023-12-11T00:01:43.796485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41590 19
 
3.8%
31200 16
 
3.2%
47290 13
 
2.6%
30200 10
 
2.0%
31140 10
 
2.0%
46880 9
 
1.8%
41461 9
 
1.8%
50110 9
 
1.8%
31710 8
 
1.6%
48310 8
 
1.6%
Other values (170) 389
77.8%
ValueCountFrequency (%)
11140 1
 
0.2%
11200 2
0.4%
11215 2
0.4%
11230 1
 
0.2%
11290 2
0.4%
11350 2
0.4%
11380 3
0.6%
11410 1
 
0.2%
11440 1
 
0.2%
11470 2
0.4%
ValueCountFrequency (%)
50130 1
 
0.2%
50110 9
1.8%
48890 1
 
0.2%
48860 3
 
0.6%
48850 3
 
0.6%
48840 3
 
0.6%
48820 2
 
0.4%
48740 2
 
0.4%
48730 4
0.8%
48720 1
 
0.2%

부속_법정동_코드
Real number (ℝ)

Distinct191
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23440.076
Minimum10100
Maximum46037
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:44.048076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10100
5-th percentile10200
Q111175
median25034
Q334021
95-th percentile39022.05
Maximum46037
Range35937
Interquartile range (IQR)22846

Descriptive statistics

Standard deviation11007.464
Coefficient of variation (CV)0.46960019
Kurtosis-1.6023038
Mean23440.076
Median Absolute Deviation (MAD)11234
Skewness0.0045134337
Sum11720038
Variance1.2116427 × 108
MonotonicityNot monotonic
2023-12-11T00:01:44.324080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10100 18
 
3.6%
10300 17
 
3.4%
10700 17
 
3.4%
31021 15
 
3.0%
10200 14
 
2.8%
10400 14
 
2.8%
10500 11
 
2.2%
10800 10
 
2.0%
12000 9
 
1.8%
10600 8
 
1.6%
Other values (181) 367
73.4%
ValueCountFrequency (%)
10100 18
3.6%
10200 14
2.8%
10300 17
3.4%
10400 14
2.8%
10500 11
2.2%
10600 8
1.6%
10700 17
3.4%
10800 10
2.0%
10900 5
 
1.0%
11000 6
 
1.2%
ValueCountFrequency (%)
46037 1
0.2%
45032 1
0.2%
44050 1
0.2%
44024 1
0.2%
42029 1
0.2%
42027 1
0.2%
42023 1
0.2%
41030 1
0.2%
41026 2
0.4%
41024 1
0.2%

부속_대지_구분_코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
468 
1
 
25
<NA>
 
4
2
 
2
5
 
1

Length

Max length4
Median length1
Mean length1.024
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 468
93.6%
1 25
 
5.0%
<NA> 4
 
0.8%
2 2
 
0.4%
5 1
 
0.2%

Length

2023-12-11T00:01:44.681590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:44.912647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 468
93.6%
1 25
 
5.0%
na 4
 
0.8%
2 2
 
0.4%
5 1
 
0.2%

부속_번
Real number (ℝ)

ZEROS 

Distinct395
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean462.554
Minimum0
Maximum4296
Zeros6
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:45.220207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q1136
median365
Q3671.5
95-th percentile1179.4
Maximum4296
Range4296
Interquartile range (IQR)535.5

Descriptive statistics

Standard deviation458.64309
Coefficient of variation (CV)0.99154497
Kurtosis14.402501
Mean462.554
Median Absolute Deviation (MAD)253
Skewness2.6920825
Sum231277
Variance210353.49
MonotonicityNot monotonic
2023-12-11T00:01:45.680466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
1.2%
1 6
 
1.2%
2 4
 
0.8%
721 3
 
0.6%
4 3
 
0.6%
523 3
 
0.6%
117 3
 
0.6%
408 3
 
0.6%
124 3
 
0.6%
168 3
 
0.6%
Other values (385) 463
92.6%
ValueCountFrequency (%)
0 6
1.2%
1 6
1.2%
2 4
0.8%
3 1
 
0.2%
4 3
0.6%
5 2
 
0.4%
6 1
 
0.2%
8 1
 
0.2%
9 2
 
0.4%
12 2
 
0.4%
ValueCountFrequency (%)
4296 1
0.2%
3465 1
0.2%
2861 1
0.2%
2157 1
0.2%
2042 1
0.2%
1911 1
0.2%
1779 1
0.2%
1764 1
0.2%
1607 1
0.2%
1578 1
0.2%

부속_지
Real number (ℝ)

ZEROS 

Distinct63
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.994
Minimum0
Maximum1744
Zeros133
Zeros (%)26.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:45.962282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q38
95-th percentile57.05
Maximum1744
Range1744
Interquartile range (IQR)8

Descriptive statistics

Standard deviation110.80873
Coefficient of variation (CV)5.2781143
Kurtosis140.18756
Mean20.994
Median Absolute Deviation (MAD)2
Skewness10.783198
Sum10497
Variance12278.575
MonotonicityNot monotonic
2023-12-11T00:01:46.268529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 133
26.6%
1 67
13.4%
2 55
11.0%
3 36
 
7.2%
4 24
 
4.8%
5 23
 
4.6%
6 21
 
4.2%
8 13
 
2.6%
7 13
 
2.6%
11 11
 
2.2%
Other values (53) 104
20.8%
ValueCountFrequency (%)
0 133
26.6%
1 67
13.4%
2 55
11.0%
3 36
 
7.2%
4 24
 
4.8%
5 23
 
4.6%
6 21
 
4.2%
7 13
 
2.6%
8 13
 
2.6%
9 9
 
1.8%
ValueCountFrequency (%)
1744 1
0.2%
1083 1
0.2%
691 1
0.2%
656 1
0.2%
558 1
0.2%
527 1
0.2%
423 1
0.2%
343 1
0.2%
306 1
0.2%
210 1
0.2%

부속_특수지_명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

부속_블록
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing499
Missing (%)99.8%
Memory size4.0 KiB
2023-12-11T00:01:46.462242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories2 ?
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 row4B
ValueCountFrequency (%)
4b 1
100.0%
2023-12-11T00:01:46.980442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
50.0%
B 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
50.0%
Uppercase Letter 1
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
50.0%
Latin 1
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
50.0%
B 1
50.0%

부속_로트
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

부속_기타_지번_명
Text

MISSING 

Distinct24
Distinct (%)100.0%
Missing476
Missing (%)95.2%
Memory size4.0 KiB
2023-12-11T00:01:47.348907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.0416667
Min length2

Characters and Unicode

Total characters97
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row88-5
2nd row10-0
3rd row32
4th row737-3
5th row302
ValueCountFrequency (%)
88-5 1
 
4.2%
10-0 1
 
4.2%
636-4 1
 
4.2%
723 1
 
4.2%
산37 1
 
4.2%
792 1
 
4.2%
678-3 1
 
4.2%
33 1
 
4.2%
24-18 1
 
4.2%
687 1
 
4.2%
Other values (14) 14
58.3%
2023-12-11T00:01:48.089067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 16
16.5%
- 14
14.4%
2 11
11.3%
7 11
11.3%
6 10
10.3%
0 8
8.2%
8 7
7.2%
5 6
 
6.2%
4 5
 
5.2%
1 4
 
4.1%
Other values (2) 5
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
84.5%
Dash Punctuation 14
 
14.4%
Other Letter 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 16
19.5%
2 11
13.4%
7 11
13.4%
6 10
12.2%
0 8
9.8%
8 7
8.5%
5 6
 
7.3%
4 5
 
6.1%
1 4
 
4.9%
9 4
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Other Letter
ValueCountFrequency (%)
산 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
99.0%
Hangul 1
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 16
16.7%
- 14
14.6%
2 11
11.5%
7 11
11.5%
6 10
10.4%
0 8
8.3%
8 7
7.3%
5 6
 
6.2%
4 5
 
5.2%
1 4
 
4.2%
Hangul
ValueCountFrequency (%)
산 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
99.0%
Hangul 1
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 16
16.7%
- 14
14.6%
2 11
11.5%
7 11
11.5%
6 10
10.4%
0 8
8.3%
8 7
7.3%
5 6
 
6.2%
4 5
 
5.2%
1 4
 
4.2%
Hangul
ValueCountFrequency (%)
산 1
100.0%

생성_일자
Real number (ℝ)

Distinct294
Distinct (%)58.9%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean20132949
Minimum20090318
Maximum20160531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:48.388587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090318
5-th percentile20100708
Q120111229
median20140225
Q320150218
95-th percentile20160409
Maximum20160531
Range70213
Interquartile range (IQR)38989.5

Descriptive statistics

Standard deviation18919.118
Coefficient of variation (CV)0.00093970923
Kurtosis-0.80074224
Mean20132949
Median Absolute Deviation (MAD)10905
Skewness-0.33636655
Sum1.0046342 × 1010
Variance3.5793303 × 108
MonotonicityNot monotonic
2023-12-11T00:01:48.727857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110420 25
 
5.0%
20140902 14
 
2.8%
20140913 9
 
1.8%
20111021 8
 
1.6%
20110415 7
 
1.4%
20140601 7
 
1.4%
20130827 7
 
1.4%
20110418 7
 
1.4%
20111123 6
 
1.2%
20121121 6
 
1.2%
Other values (284) 403
80.6%
ValueCountFrequency (%)
20090318 5
1.0%
20090319 2
 
0.4%
20090320 3
0.6%
20090321 2
 
0.4%
20090325 1
 
0.2%
20090421 1
 
0.2%
20090730 1
 
0.2%
20090807 1
 
0.2%
20090917 1
 
0.2%
20091028 1
 
0.2%
ValueCountFrequency (%)
20160531 2
0.4%
20160526 2
0.4%
20160521 1
 
0.2%
20160520 1
 
0.2%
20160519 1
 
0.2%
20160518 1
 
0.2%
20160513 3
0.6%
20160511 1
 
0.2%
20160510 4
0.8%
20160506 1
 
0.2%

Sample

관리_건축물대장_PK대장_구분_코드대장_구분_코드_명대장_종류_코드대장_종류_코드_명대지_위치도로명_대지_위치건물_명시군구_코드법정동_코드대지_구분_코드번지특수지_명블록로트새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번부속_대장_구분_코드부속_대장_구분_코드_명부속_시군구_코드부속_법정동_코드부속_대지_구분_코드부속_번부속_지부속_특수지_명부속_블록부속_로트부속_기타_지번_명생성_일자
041287-2268711일반2일반건축물경상북도 청도군 운문면 마일리 125-1번지<NA>(주)중앙고속421301060003437<NA><NA><NA>312003172034<NA>040401일반317103402204288<NA><NA><NA><NA>20160108
148310-1002077541일반3일반건축물전라북도 임실군 임실읍 이도리 71-3번지<NA><NA>26230330280711<NA><NA><NA>41461440907810701061901일반413103804203097<NA><NA><NA>88-520111123
230200-154671일반2일반건축물경상북도 영덕군 영해면 괴시리 128번지경기도 포천시 시우동길 110-19<NA>4117325622012752<NA><NA><NA>41590443026833001025501일반113801200001551<NA><NA><NA><NA>20110811
341590-1002942931일반2일반건축물경기도 남양주시 퇴계원면 퇴계원리 218-202번지충청북도 음성군 행제길76번길 97-8학생군사학교27710112000280<NA><NA><NA><NA>253010001일반415002503415291083<NA><NA><NA><NA>20121220
441670-140111일반2일반건축물경상북도 김천시 구성면 송죽리 606번지경기도 화성시 초록로 594-29<NA>46170360300242<NA><NA><NA><NA>115030150<NA>1일반311701380009920<NA><NA><NA><NA>20160526
541220-545171일반2일반건축물부산광역시 해운대구 우동 588-4번지<NA>서남대학교479301310001550<NA><NA><NA><NA>32002013301일반302001020004631<NA><NA><NA><NA>20130205
642770-31031일반2일반건축물경상북도 영천시 금호읍 교대리 167-33번지충청남도 공주시 고마나루길 30<NA>27710114000130<NA><NA><NA>42780449011931001027<NA>1일반114401080009086<NA><NA><NA><NA>20150117
742150-271141일반3일반건축물울산광역시 남구 매암동 588-1번지<NA>학생군사학교4159010100011280<NA><NA><NA>451804611101104010232911일반43130102000993<NA><NA><NA><NA>20130312
847210-1002199702일반2일반건축물강원도 영월군 남면 연당리 647-1번지경상북도 칠곡군 3공단1로 62-6<NA>437601090012140<NA><NA><NA><NA>320020165<NA>1일반4711142027014658<NA><NA><NA><NA>20090319
944270-477321일반1일반건축물전라북도 부안군 보안면 하입석리 794-2번지경상북도 경산시 대학로 280신천초등학교(8동)47111250240670<NA><NA><NA>312003169028144010<NA><NA>1일반30200256320870<NA><NA><NA><NA>20121013
관리_건축물대장_PK대장_구분_코드대장_구분_코드_명대장_종류_코드대장_종류_코드_명대지_위치도로명_대지_위치건물_명시군구_코드법정동_코드대지_구분_코드번지특수지_명블록로트새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번부속_대장_구분_코드부속_대장_구분_코드_명부속_시군구_코드부속_법정동_코드부속_대지_구분_코드부속_번부속_지부속_특수지_명부속_블록부속_로트부속_기타_지번_명생성_일자
49047150-252871일반1표제부제주특별자치도 제주시 한림읍 협재리 2446-3번지<NA><NA>311401020003186<NA><NA><NA><NA>340010246<NA>1일반44131120000626<NA><NA><NA><NA>20141001
49141820-152591일반2일반건축물경상남도 의령군 화정면 상일리 894번지<NA><NA>448251400006870<NA><NA><NA>467904673399138020<NA><NA>1일반46880101000451<NA><NA><NA><NA>20160510
49230110-28201일반2일반건축물울산광역시 울주군 삼남면 가천리 818번지충청남도 홍성군 내포로 262<NA>4683025625161<NA><NA><NA>311703171011<NA>023<NA>1일반415903102104124<NA><NA><NA><NA>20151118
49346830-375141일반2일반건축물충청북도 청주시 청원구 오창읍 화산리(花山) 산 38-1번지<NA><NA>411171110001060<NA><NA><NA>3120031690283100106801일반4421011200050<NA><NA><NA><NA>20110415
49428237-61171일반2표제부충청남도 서천군 장항읍 창선1리 250-1번지경상북도 포항시 남구 철강로 119제일타운42130104000501<NA><NA><NA>472103309083250010319701일반471901090003666<NA><NA><NA><NA>20160331
49543750-202801일반2표제부서울특별시 은평구 신사동 29-93번지인천광역시 남구 독배로402번길 23-14<NA>26290104000695<NA><NA><NA>472504733824161010<NA>22일반482203702107213<NA><NA><NA><NA>20160331
49629200-3181일반2총괄표제부전라북도 익산시 팔봉동 304번지경상남도 함양군 수동내동안길 46<NA>415901240002253<NA><NA><NA>48250333507312403062081일반431131100002340<NA><NA><NA><NA>20131126
49748121-1001723061일반2일반건축물경기도 용인시 처인구 마평동 718-2번지울산광역시 동구 방어진순환도로 400서천근린공원438003102106392<NA><NA><NA>4519046134923500107801일반31710107000821<NA><NA><NA><NA>20120530
49831710-1001926191일반2일반건축물부산광역시 부산진구 가야동 467번지울산광역시 울주군 해맞이로 658-91교통센터415501190001712<NA><NA><NA><NA>25907064<NA>1일반4518025322013190<NA><NA><NA><NA>20100417
49928140-28131일반2일반건축물경기도 구리시 사노동 29번지울산광역시 북구 염포로 700<NA>421301150001100<NA><NA><NA>452103272068137010<NA>01일반47840460370940123<NA><NA><NA><NA>20150509