Overview

Dataset statistics

Number of variables25
Number of observations500
Missing cells1666
Missing cells (%)13.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory106.1 KiB
Average record size in memory217.3 B

Variable types

Text6
Categorical6
Numeric12
Unsupported1

Dataset

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

Alerts

대장_구분_코드 has constant value ""Constant
대장_구분_코드_명 has constant value ""Constant
대장_종류_코드 has constant value ""Constant
대장_종류_코드_명 has constant value ""Constant
블록 has constant value ""Constant
새주소_지상지하_코드 has constant value ""Constant
대지_구분_코드 is highly imbalanced (97.9%)Imbalance
도로명_대지_위치 has 33 (6.6%) missing valuesMissing
건물_명 has 14 (2.8%) missing valuesMissing
특수지_명 has 497 (99.4%) missing valuesMissing
블록 has 499 (99.8%) missing valuesMissing
로트 has 500 (100.0%) missing valuesMissing
새주소_도로_코드 has 28 (5.6%) missing valuesMissing
새주소_법정동_코드 has 38 (7.6%) missing valuesMissing
새주소_본_번 has 30 (6.0%) missing valuesMissing
새주소_부_번 has 27 (5.4%) missing valuesMissing
관리_건축물대장_PK has unique valuesUnique
로트 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지 has 287 (57.4%) zerosZeros
외필지_수 has 406 (81.2%) zerosZeros
새주소_부_번 has 426 (85.2%) zerosZeros

Reproduction

Analysis started2023-12-10 15:03:13.035628
Analysis finished2023-12-10 15:03:14.156451
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리_건축물대장_PK
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:03:14.527371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length11.858
Min length10

Characters and Unicode

Total characters5929
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st row42720-34245
2nd row30200-75028
3rd row30140-83930
4th row11680-82814
5th row26350-60898
ValueCountFrequency (%)
42720-34245 1
 
0.2%
41630-50370 1
 
0.2%
43111-70541 1
 
0.2%
11710-171550 1
 
0.2%
45210-38634 1
 
0.2%
41550-50607 1
 
0.2%
27230-81400 1
 
0.2%
11680-160155 1
 
0.2%
47111-94179 1
 
0.2%
26470-38926 1
 
0.2%
Other values (490) 490
98.0%
2023-12-11T00:03:15.424246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1104
18.6%
0 838
14.1%
4 621
10.5%
2 551
9.3%
3 503
8.5%
- 500
8.4%
7 414
 
7.0%
5 409
 
6.9%
8 369
 
6.2%
6 328
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5429
91.6%
Dash Punctuation 500
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1104
20.3%
0 838
15.4%
4 621
11.4%
2 551
10.1%
3 503
9.3%
7 414
 
7.6%
5 409
 
7.5%
8 369
 
6.8%
6 328
 
6.0%
9 292
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5929
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1104
18.6%
0 838
14.1%
4 621
10.5%
2 551
9.3%
3 503
8.5%
- 500
8.4%
7 414
 
7.0%
5 409
 
6.9%
8 369
 
6.2%
6 328
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5929
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1104
18.6%
0 838
14.1%
4 621
10.5%
2 551
9.3%
3 503
8.5%
- 500
8.4%
7 414
 
7.0%
5 409
 
6.9%
8 369
 
6.2%
6 328
 
5.5%

대장_구분_코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 500
100.0%

Length

2023-12-11T00:03:15.732602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:03:15.931334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 500
100.0%

대장_구분_코드_명
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
집합 500
100.0%

Length

2023-12-11T00:03:16.130344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:03:16.344373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집합 500
100.0%

대장_종류_코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
4
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 500
100.0%

Length

2023-12-11T00:03:16.555113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:03:16.748582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 500
100.0%

대장_종류_코드_명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전유부 500
100.0%

Length

2023-12-11T00:03:16.961872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:03:17.227478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전유부 500
100.0%

대지_위치
Text

Distinct484
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:03:17.886135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length20.328
Min length15

Characters and Unicode

Total characters10164
Distinct characters241
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique469 ?
Unique (%)93.8%

Sample

1st row충청북도 청주시 흥덕구 비하동 362번지
2nd row서울특별시 용산구 한강로3가 91번지
3rd row광주광역시 광산구 비아동 152-5번지
4th row경기도 구리시 수택동 854번지
5th row경기도 안양시 동안구 호계동 713번지
ValueCountFrequency (%)
경기도 130
 
6.0%
서울특별시 84
 
3.9%
인천광역시 43
 
2.0%
경상남도 31
 
1.4%
부산광역시 27
 
1.2%
광주광역시 25
 
1.2%
대전광역시 21
 
1.0%
대구광역시 21
 
1.0%
충청남도 20
 
0.9%
경상북도 19
 
0.9%
Other values (1033) 1751
80.6%
2023-12-11T00:03:18.925543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1672
 
16.5%
지 514
 
5.1%
동 512
 
5.0%
번 499
 
4.9%
시 493
 
4.9%
구 387
 
3.8%
1 336
 
3.3%
도 284
 
2.8%
2 215
 
2.1%
광 200
 
2.0%
Other values (231) 5052
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6565
64.6%
Decimal Number 1741
 
17.1%
Space Separator 1672
 
16.5%
Dash Punctuation 184
 
1.8%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 514
 
7.8%
동 512
 
7.8%
번 499
 
7.6%
시 493
 
7.5%
구 387
 
5.9%
도 284
 
4.3%
광 200
 
3.0%
경 189
 
2.9%
역 154
 
2.3%
서 149
 
2.3%
Other values (217) 3184
48.5%
Decimal Number
ValueCountFrequency (%)
1 336
19.3%
2 215
12.3%
5 182
10.5%
3 178
10.2%
4 153
8.8%
8 147
8.4%
9 143
8.2%
0 131
 
7.5%
7 131
 
7.5%
6 125
 
7.2%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
N 1
50.0%
Space Separator
ValueCountFrequency (%)
1672
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6565
64.6%
Common 3597
35.4%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 514
 
7.8%
동 512
 
7.8%
번 499
 
7.6%
시 493
 
7.5%
구 387
 
5.9%
도 284
 
4.3%
광 200
 
3.0%
경 189
 
2.9%
역 154
 
2.3%
서 149
 
2.3%
Other values (217) 3184
48.5%
Common
ValueCountFrequency (%)
1672
46.5%
1 336
 
9.3%
2 215
 
6.0%
- 184
 
5.1%
5 182
 
5.1%
3 178
 
4.9%
4 153
 
4.3%
8 147
 
4.1%
9 143
 
4.0%
0 131
 
3.6%
Other values (2) 256
 
7.1%
Latin
ValueCountFrequency (%)
B 1
50.0%
N 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6565
64.6%
ASCII 3599
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1672
46.5%
1 336
 
9.3%
2 215
 
6.0%
- 184
 
5.1%
5 182
 
5.1%
3 178
 
4.9%
4 153
 
4.3%
8 147
 
4.1%
9 143
 
4.0%
0 131
 
3.6%
Other values (4) 258
 
7.2%
Hangul
ValueCountFrequency (%)
지 514
 
7.8%
동 512
 
7.8%
번 499
 
7.6%
시 493
 
7.5%
구 387
 
5.9%
도 284
 
4.3%
광 200
 
3.0%
경 189
 
2.9%
역 154
 
2.3%
서 149
 
2.3%
Other values (217) 3184
48.5%

도로명_대지_위치
Text

MISSING 

Distinct454
Distinct (%)97.2%
Missing33
Missing (%)6.6%
Memory size4.0 KiB
2023-12-11T00:03:19.700869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length18.479657
Min length10

Characters and Unicode

Total characters8630
Distinct characters272
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

Unique441 ?
Unique (%)94.4%

Sample

1st row울산광역시 중구 옥교동길 15
2nd row경기도 부천시 원미구 역곡로45번길 36
3rd row경기도 여주시 세종로 173-65
4th row충청북도 청주시 흥덕구 증안로 77
5th row서울특별시 영등포구 당산로4길 12
ValueCountFrequency (%)
경기도 116
 
5.9%
서울특별시 73
 
3.7%
부산광역시 49
 
2.5%
경상남도 30
 
1.5%
북구 27
 
1.4%
광주광역시 24
 
1.2%
대구광역시 23
 
1.2%
인천광역시 23
 
1.2%
경상북도 22
 
1.1%
대전광역시 20
 
1.0%
Other values (843) 1557
79.3%
2023-12-11T00:03:20.832002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1500
 
17.4%
시 465
 
5.4%
로 437
 
5.1%
구 356
 
4.1%
1 350
 
4.1%
도 247
 
2.9%
2 218
 
2.5%
광 195
 
2.3%
3 193
 
2.2%
길 184
 
2.1%
Other values (262) 4485
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5506
63.8%
Decimal Number 1574
 
18.2%
Space Separator 1500
 
17.4%
Dash Punctuation 50
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 465
 
8.4%
로 437
 
7.9%
구 356
 
6.5%
도 247
 
4.5%
광 195
 
3.5%
길 184
 
3.3%
경 179
 
3.3%
역 153
 
2.8%
서 132
 
2.4%
산 128
 
2.3%
Other values (250) 3030
55.0%
Decimal Number
ValueCountFrequency (%)
1 350
22.2%
2 218
13.9%
3 193
12.3%
5 136
 
8.6%
0 130
 
8.3%
4 130
 
8.3%
6 120
 
7.6%
9 108
 
6.9%
7 106
 
6.7%
8 83
 
5.3%
Space Separator
ValueCountFrequency (%)
1500
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5506
63.8%
Common 3124
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 465
 
8.4%
로 437
 
7.9%
구 356
 
6.5%
도 247
 
4.5%
광 195
 
3.5%
길 184
 
3.3%
경 179
 
3.3%
역 153
 
2.8%
서 132
 
2.4%
산 128
 
2.3%
Other values (250) 3030
55.0%
Common
ValueCountFrequency (%)
1500
48.0%
1 350
 
11.2%
2 218
 
7.0%
3 193
 
6.2%
5 136
 
4.4%
0 130
 
4.2%
4 130
 
4.2%
6 120
 
3.8%
9 108
 
3.5%
7 106
 
3.4%
Other values (2) 133
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5506
63.8%
ASCII 3124
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1500
48.0%
1 350
 
11.2%
2 218
 
7.0%
3 193
 
6.2%
5 136
 
4.4%
0 130
 
4.2%
4 130
 
4.2%
6 120
 
3.8%
9 108
 
3.5%
7 106
 
3.4%
Other values (2) 133
 
4.3%
Hangul
ValueCountFrequency (%)
시 465
 
8.4%
로 437
 
7.9%
구 356
 
6.5%
도 247
 
4.5%
광 195
 
3.5%
길 184
 
3.3%
경 179
 
3.3%
역 153
 
2.8%
서 132
 
2.4%
산 128
 
2.3%
Other values (250) 3030
55.0%

건물_명
Text

MISSING 

Distinct434
Distinct (%)89.3%
Missing14
Missing (%)2.8%
Memory size4.0 KiB
2023-12-11T00:03:21.314201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length7.8353909
Min length3

Characters and Unicode

Total characters3808
Distinct characters356
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique408 ?
Unique (%)84.0%

Sample

1st row양천아파트
2nd row푸른마을 10단지
3rd row동아청솔아파트
4th row비산롯데캐슬
5th row샘터마을
ValueCountFrequency (%)
주공아파트 18
 
2.8%
아파트 10
 
1.6%
현대아파트 9
 
1.4%
우성아파트 5
 
0.8%
부영아파트 5
 
0.8%
1단지 4
 
0.6%
삼성아파트 4
 
0.6%
2단지 4
 
0.6%
풍림아이원아파트 4
 
0.6%
상계주공아파트 4
 
0.6%
Other values (528) 570
89.5%
2023-12-11T00:03:22.088561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 364
 
9.6%
파 346
 
9.1%
트 341
 
9.0%
151
 
4.0%
동 97
 
2.5%
주 70
 
1.8%
대 70
 
1.8%
마 61
 
1.6%
지 61
 
1.6%
공 60
 
1.6%
Other values (346) 2187
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3485
91.5%
Space Separator 151
 
4.0%
Decimal Number 132
 
3.5%
Uppercase Letter 12
 
0.3%
Lowercase Letter 8
 
0.2%
Dash Punctuation 7
 
0.2%
Open Punctuation 6
 
0.2%
Close Punctuation 6
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 364
 
10.4%
파 346
 
9.9%
트 341
 
9.8%
동 97
 
2.8%
주 70
 
2.0%
대 70
 
2.0%
마 61
 
1.8%
지 61
 
1.8%
공 60
 
1.7%
을 54
 
1.5%
Other values (318) 1961
56.3%
Decimal Number
ValueCountFrequency (%)
1 38
28.8%
2 31
23.5%
0 19
14.4%
3 18
13.6%
6 9
 
6.8%
4 7
 
5.3%
5 4
 
3.0%
9 3
 
2.3%
8 2
 
1.5%
7 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
A 2
16.7%
T 2
16.7%
G 1
8.3%
E 1
8.3%
B 1
8.3%
S 1
8.3%
K 1
8.3%
D 1
8.3%
L 1
8.3%
P 1
8.3%
Lowercase Letter
ValueCountFrequency (%)
e 6
75.0%
h 1
 
12.5%
t 1
 
12.5%
Space Separator
ValueCountFrequency (%)
151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
？ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3485
91.5%
Common 303
 
8.0%
Latin 20
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 364
 
10.4%
파 346
 
9.9%
트 341
 
9.8%
동 97
 
2.8%
주 70
 
2.0%
대 70
 
2.0%
마 61
 
1.8%
지 61
 
1.8%
공 60
 
1.7%
을 54
 
1.5%
Other values (318) 1961
56.3%
Common
ValueCountFrequency (%)
151
49.8%
1 38
 
12.5%
2 31
 
10.2%
0 19
 
6.3%
3 18
 
5.9%
6 9
 
3.0%
4 7
 
2.3%
- 7
 
2.3%
( 6
 
2.0%
) 6
 
2.0%
Other values (5) 11
 
3.6%
Latin
ValueCountFrequency (%)
e 6
30.0%
A 2
 
10.0%
T 2
 
10.0%
h 1
 
5.0%
t 1
 
5.0%
G 1
 
5.0%
E 1
 
5.0%
B 1
 
5.0%
S 1
 
5.0%
K 1
 
5.0%
Other values (3) 3
15.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3483
91.5%
ASCII 322
 
8.5%
Compat Jamo 2
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 364
 
10.5%
파 346
 
9.9%
트 341
 
9.8%
동 97
 
2.8%
주 70
 
2.0%
대 70
 
2.0%
마 61
 
1.8%
지 61
 
1.8%
공 60
 
1.7%
을 54
 
1.6%
Other values (317) 1959
56.2%
ASCII
ValueCountFrequency (%)
151
46.9%
1 38
 
11.8%
2 31
 
9.6%
0 19
 
5.9%
3 18
 
5.6%
6 9
 
2.8%
4 7
 
2.2%
- 7
 
2.2%
e 6
 
1.9%
( 6
 
1.9%
Other values (17) 30
 
9.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
None
ValueCountFrequency (%)
？ 1
100.0%

시군구_코드
Real number (ℝ)

Distinct159
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33026.328
Minimum11110
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:22.350924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11304.25
Q126440
median41117
Q342115
95-th percentile48121
Maximum50130
Range39020
Interquartile range (IQR)15675

Descriptive statistics

Standard deviation12308.716
Coefficient of variation (CV)0.37269404
Kurtosis-0.89191367
Mean33026.328
Median Absolute Deviation (MAD)7032.5
Skewness-0.64686211
Sum16513164
Variance1.5150448 × 108
MonotonicityNot monotonic
2023-12-11T00:03:22.665045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41135 11
 
2.2%
11710 10
 
2.0%
26350 9
 
1.8%
41463 9
 
1.8%
11290 9
 
1.8%
26230 8
 
1.6%
30170 8
 
1.6%
11350 8
 
1.6%
41173 7
 
1.4%
11320 7
 
1.4%
Other values (149) 414
82.8%
ValueCountFrequency (%)
11110 2
 
0.4%
11140 2
 
0.4%
11170 3
 
0.6%
11200 1
 
0.2%
11215 1
 
0.2%
11230 6
1.2%
11260 1
 
0.2%
11290 9
1.8%
11305 1
 
0.2%
11320 7
1.4%
ValueCountFrequency (%)
50130 1
 
0.2%
50110 2
 
0.4%
48330 4
0.8%
48310 2
 
0.4%
48250 3
0.6%
48220 1
 
0.2%
48170 1
 
0.2%
48129 1
 
0.2%
48127 2
 
0.4%
48125 5
1.0%

법정동_코드
Real number (ℝ)

Distinct79
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12996.834
Minimum10100
Maximum44031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:22.950616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10100
5-th percentile10100
Q110400
median10900
Q312325
95-th percentile25325.15
Maximum44031
Range33931
Interquartile range (IQR)1925

Descriptive statistics

Standard deviation5465.491
Coefficient of variation (CV)0.4205248
Kurtosis7.4604232
Mean12996.834
Median Absolute Deviation (MAD)600
Skewness2.7614172
Sum6498417
Variance29871591
MonotonicityNot monotonic
2023-12-11T00:03:23.591522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10200 42
 
8.4%
10100 36
 
7.2%
10300 35
 
7.0%
10700 32
 
6.4%
10600 29
 
5.8%
10800 28
 
5.6%
10900 27
 
5.4%
10500 25
 
5.0%
10400 22
 
4.4%
11400 16
 
3.2%
Other values (69) 208
41.6%
ValueCountFrequency (%)
10100 36
7.2%
10200 42
8.4%
10300 35
7.0%
10400 22
4.4%
10500 25
5.0%
10600 29
5.8%
10700 32
6.4%
10800 28
5.6%
10900 27
5.4%
11000 11
 
2.2%
ValueCountFrequency (%)
44031 1
0.2%
39032 1
0.2%
39021 1
0.2%
36027 1
0.2%
36022 1
0.2%
35024 1
0.2%
35022 1
0.2%
34025 1
0.2%
33027 1
0.2%
33022 1
0.2%

대지_구분_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
499 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 499
99.8%
2 1
 
0.2%

Length

2023-12-11T00:03:23.870921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:03:24.070341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 499
99.8%
2 1
 
0.2%

번
Real number (ℝ)

Distinct416
Distinct (%)83.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean636.496
Minimum0
Maximum4656
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:24.260113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile22.95
Q1219.5
median580
Q3928.25
95-th percentile1510.3
Maximum4656
Range4656
Interquartile range (IQR)708.75

Descriptive statistics

Standard deviation517.55596
Coefficient of variation (CV)0.8131331
Kurtosis7.5340516
Mean636.496
Median Absolute Deviation (MAD)353
Skewness1.6807421
Sum318248
Variance267864.17
MonotonicityNot monotonic
2023-12-11T00:03:24.523469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
154 4
 
0.8%
200 4
 
0.8%
120 3
 
0.6%
347 3
 
0.6%
765 3
 
0.6%
11 3
 
0.6%
5 3
 
0.6%
528 3
 
0.6%
2 3
 
0.6%
82 3
 
0.6%
Other values (406) 468
93.6%
ValueCountFrequency (%)
0 1
 
0.2%
2 3
0.6%
3 1
 
0.2%
4 1
 
0.2%
5 3
0.6%
7 1
 
0.2%
10 3
0.6%
11 3
0.6%
12 2
0.4%
13 2
0.4%
ValueCountFrequency (%)
4656 1
0.2%
2942 1
0.2%
2444 1
0.2%
2306 1
0.2%
2252 1
0.2%
2064 1
0.2%
2047 1
0.2%
2004 1
0.2%
1873 1
0.2%
1869 1
0.2%

지
Real number (ℝ)

ZEROS 

Distinct39
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.486
Minimum0
Maximum253
Zeros287
Zeros (%)57.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:24.746859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile23.05
Maximum253
Range253
Interquartile range (IQR)2

Descriptive statistics

Standard deviation23.441519
Coefficient of variation (CV)4.272971
Kurtosis73.915668
Mean5.486
Median Absolute Deviation (MAD)0
Skewness8.0168882
Sum2743
Variance549.50481
MonotonicityNot monotonic
2023-12-11T00:03:25.006600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 287
57.4%
1 70
 
14.0%
2 27
 
5.4%
3 22
 
4.4%
4 16
 
3.2%
5 11
 
2.2%
6 10
 
2.0%
9 6
 
1.2%
16 5
 
1.0%
10 4
 
0.8%
Other values (29) 42
 
8.4%
ValueCountFrequency (%)
0 287
57.4%
1 70
 
14.0%
2 27
 
5.4%
3 22
 
4.4%
4 16
 
3.2%
5 11
 
2.2%
6 10
 
2.0%
7 4
 
0.8%
8 1
 
0.2%
9 6
 
1.2%
ValueCountFrequency (%)
253 2
0.4%
242 1
0.2%
134 1
0.2%
123 1
0.2%
117 1
0.2%
101 1
0.2%
83 2
0.4%
71 1
0.2%
61 1
0.2%
59 1
0.2%

특수지_명
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing497
Missing (%)99.4%
Memory size4.0 KiB
2023-12-11T00:03:25.277766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.666667
Min length8

Characters and Unicode

Total characters32
Distinct characters20
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row126블럭 1-1놋트
2nd row15블록 8로트
3rd row동백지구 C9-1,2블럭
ValueCountFrequency (%)
126블럭 1
16.7%
1-1놋트 1
16.7%
15블록 1
16.7%
8로트 1
16.7%
동백지구 1
16.7%
c9-1,2블럭 1
16.7%
2023-12-11T00:03:25.809161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
15.6%
블 3
 
9.4%
3
 
9.4%
럭 2
 
6.2%
- 2
 
6.2%
트 2
 
6.2%
2 2
 
6.2%
동 1
 
3.1%
9 1
 
3.1%
C 1
 
3.1%
Other values (10) 10
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14
43.8%
Decimal Number 11
34.4%
Space Separator 3
 
9.4%
Dash Punctuation 2
 
6.2%
Uppercase Letter 1
 
3.1%
Other Punctuation 1
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
블 3
21.4%
럭 2
14.3%
트 2
14.3%
동 1
 
7.1%
구 1
 
7.1%
지 1
 
7.1%
백 1
 
7.1%
록 1
 
7.1%
로 1
 
7.1%
놋 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 5
45.5%
2 2
 
18.2%
9 1
 
9.1%
8 1
 
9.1%
5 1
 
9.1%
6 1
 
9.1%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17
53.1%
Hangul 14
43.8%
Latin 1
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
블 3
21.4%
럭 2
14.3%
트 2
14.3%
동 1
 
7.1%
구 1
 
7.1%
지 1
 
7.1%
백 1
 
7.1%
록 1
 
7.1%
로 1
 
7.1%
놋 1
 
7.1%
Common
ValueCountFrequency (%)
1 5
29.4%
3
17.6%
- 2
 
11.8%
2 2
 
11.8%
9 1
 
5.9%
8 1
 
5.9%
5 1
 
5.9%
6 1
 
5.9%
, 1
 
5.9%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
56.2%
Hangul 14
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
27.8%
3
16.7%
- 2
 
11.1%
2 2
 
11.1%
9 1
 
5.6%
C 1
 
5.6%
8 1
 
5.6%
5 1
 
5.6%
6 1
 
5.6%
, 1
 
5.6%
Hangul
ValueCountFrequency (%)
블 3
21.4%
럭 2
14.3%
트 2
14.3%
동 1
 
7.1%
구 1
 
7.1%
지 1
 
7.1%
백 1
 
7.1%
록 1
 
7.1%
로 1
 
7.1%
놋 1
 
7.1%

블록
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing499
Missing (%)99.8%
Memory size4.0 KiB
2023-12-11T00:03:26.006734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row18-1B
ValueCountFrequency (%)
18-1b 1
100.0%
2023-12-11T00:03:26.339416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
40.0%
8 1
20.0%
- 1
20.0%
B 1
20.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
66.7%
8 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
8 1
25.0%
- 1
25.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
40.0%
8 1
20.0%
- 1
20.0%
B 1
20.0%

로트
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

외필지_수
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.424
Minimum0
Maximum12
Zeros406
Zeros (%)81.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:26.582692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2535417
Coefficient of variation (CV)2.9564662
Kurtosis30.29569
Mean0.424
Median Absolute Deviation (MAD)0
Skewness4.815697
Sum212
Variance1.5713667
MonotonicityNot monotonic
2023-12-11T00:03:26.826761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 406
81.2%
1 51
 
10.2%
2 16
 
3.2%
3 11
 
2.2%
5 5
 
1.0%
4 4
 
0.8%
6 3
 
0.6%
7 2
 
0.4%
12 1
 
0.2%
11 1
 
0.2%
ValueCountFrequency (%)
0 406
81.2%
1 51
 
10.2%
2 16
 
3.2%
3 11
 
2.2%
4 4
 
0.8%
5 5
 
1.0%
6 3
 
0.6%
7 2
 
0.4%
11 1
 
0.2%
12 1
 
0.2%
ValueCountFrequency (%)
12 1
 
0.2%
11 1
 
0.2%
7 2
 
0.4%
6 3
 
0.6%
5 5
 
1.0%
4 4
 
0.8%
3 11
 
2.2%
2 16
 
3.2%
1 51
 
10.2%
0 406
81.2%

새주소_도로_코드
Real number (ℝ)

MISSING 

Distinct441
Distinct (%)93.4%
Missing28
Missing (%)5.6%
Infinite0
Infinite (%)0.0%
Mean3.4797562 × 1011
Minimum1.114031 × 1011
Maximum5.0110485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:27.121348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.114031 × 1011
5-th percentile1.1350413 × 1011
Q12.7260397 × 1011
median4.1210377 × 1011
Q34.3150452 × 1011
95-th percentile4.81704 × 1011
Maximum5.0110485 × 1011
Range3.8970175 × 1011
Interquartile range (IQR)1.5890055 × 1011

Descriptive statistics

Standard deviation1.2131487 × 1011
Coefficient of variation (CV)0.34863038
Kurtosis-0.57450534
Mean3.4797562 × 1011
Median Absolute Deviation (MAD)6.911028 × 1010
Skewness-0.82492099
Sum1.6424449 × 1014
Variance1.4717298 × 1022
MonotonicityNot monotonic
2023-12-11T00:03:27.501273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451803270051 2
 
0.4%
272904241565 2
 
0.4%
263204196396 2
 
0.4%
411994358161 2
 
0.4%
416702012002 2
 
0.4%
411504343094 2
 
0.4%
281853152021 2
 
0.4%
411173177018 2
 
0.4%
112603005028 2
 
0.4%
291403160042 2
 
0.4%
Other values (431) 452
90.4%
(Missing) 28
 
5.6%
ValueCountFrequency (%)
111403100021 1
0.2%
111404103057 1
0.2%
111703102011 1
0.2%
111704106052 1
0.2%
112003005011 1
0.2%
112004109148 1
0.2%
112303105011 1
0.2%
112304115342 1
0.2%
112304115646 1
0.2%
112603005028 2
0.4%
ValueCountFrequency (%)
501104847798 1
0.2%
501104847003 1
0.2%
501103349007 1
0.2%
488803347014 1
0.2%
487404823101 1
0.2%
487304820284 1
0.2%
487204817262 1
0.2%
483304814199 1
0.2%
483304814185 1
0.2%
483303338061 1
0.2%

새주소_법정동_코드
Real number (ℝ)

MISSING 

Distinct123
Distinct (%)26.6%
Missing38
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean13239.385
Minimum10101
Maximum41001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:27.925867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10101
Q110401
median10901
Q312301
95-th percentile25601
Maximum41001
Range30900
Interquartile range (IQR)1900

Descriptive statistics

Standard deviation5984.8605
Coefficient of variation (CV)0.45204973
Kurtosis6.3432075
Mean13239.385
Median Absolute Deviation (MAD)600
Skewness2.6283743
Sum6116596
Variance35818555
MonotonicityNot monotonic
2023-12-11T00:03:28.280013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10101 38
 
7.6%
25001 21
 
4.2%
10501 21
 
4.2%
10301 21
 
4.2%
10201 21
 
4.2%
10401 19
 
3.8%
10601 19
 
3.8%
10701 18
 
3.6%
10901 16
 
3.2%
10302 13
 
2.6%
Other values (113) 255
51.0%
(Missing) 38
 
7.6%
ValueCountFrequency (%)
10101 38
7.6%
10201 21
4.2%
10202 6
 
1.2%
10301 21
4.2%
10302 13
 
2.6%
10303 4
 
0.8%
10401 19
3.8%
10402 4
 
0.8%
10403 2
 
0.4%
10501 21
4.2%
ValueCountFrequency (%)
41001 1
0.2%
40001 2
0.4%
39002 1
0.2%
39001 1
0.2%
37008 1
0.2%
37001 1
0.2%
36001 1
0.2%
34005 1
0.2%
33002 1
0.2%
33001 2
0.4%

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

2023-12-11T00:03:28.600735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:03:28.800571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

새주소_본_번
Real number (ℝ)

MISSING 

Distinct211
Distinct (%)44.9%
Missing30
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean153.50851
Minimum0
Maximum3492
Zeros3
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:29.053017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q120
median49
Q3130
95-th percentile715.65
Maximum3492
Range3492
Interquartile range (IQR)110

Descriptive statistics

Standard deviation302.01643
Coefficient of variation (CV)1.9674246
Kurtosis38.108545
Mean153.50851
Median Absolute Deviation (MAD)36.5
Skewness5.0091058
Sum72149
Variance91213.922
MonotonicityNot monotonic
2023-12-11T00:03:29.423578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 14
 
2.8%
7 11
 
2.2%
20 10
 
2.0%
8 9
 
1.8%
10 9
 
1.8%
16 8
 
1.6%
36 8
 
1.6%
22 7
 
1.4%
71 7
 
1.4%
18 7
 
1.4%
Other values (201) 380
76.0%
(Missing) 30
 
6.0%
ValueCountFrequency (%)
0 3
 
0.6%
1 1
 
0.2%
2 2
 
0.4%
3 2
 
0.4%
4 2
 
0.4%
5 3
 
0.6%
6 5
1.0%
7 11
2.2%
8 9
1.8%
9 7
1.4%
ValueCountFrequency (%)
3492 1
0.2%
1871 1
0.2%
1832 1
0.2%
1472 1
0.2%
1348 1
0.2%
1340 2
0.4%
1220 1
0.2%
1218 1
0.2%
1144 1
0.2%
999 1
0.2%

새주소_부_번
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)5.7%
Missing27
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean1.602537
Minimum0
Maximum74
Zeros426
Zeros (%)85.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:29.778581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile9.4
Maximum74
Range74
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.9716856
Coefficient of variation (CV)4.3504054
Kurtosis42.659067
Mean1.602537
Median Absolute Deviation (MAD)0
Skewness6.0122694
Sum758
Variance48.6044
MonotonicityNot monotonic
2023-12-11T00:03:30.136903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 426
85.2%
7 5
 
1.0%
2 5
 
1.0%
1 4
 
0.8%
8 4
 
0.8%
19 3
 
0.6%
15 2
 
0.4%
21 2
 
0.4%
11 2
 
0.4%
10 2
 
0.4%
Other values (17) 18
 
3.6%
(Missing) 27
 
5.4%
ValueCountFrequency (%)
0 426
85.2%
1 4
 
0.8%
2 5
 
1.0%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
6 1
 
0.2%
7 5
 
1.0%
8 4
 
0.8%
9 1
 
0.2%
ValueCountFrequency (%)
74 1
0.2%
50 1
0.2%
49 1
0.2%
46 1
0.2%
40 2
0.4%
35 1
0.2%
33 1
0.2%
28 1
0.2%
26 1
0.2%
22 1
0.2%

기준_일자
Real number (ℝ)

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20124142
Minimum20080101
Maximum20160101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:30.440912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080101
5-th percentile20080101
Q120100101
median20120101
Q320150101
95-th percentile20160101
Maximum20160101
Range80000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation26386.423
Coefficient of variation (CV)0.0013111825
Kurtosis-1.2637177
Mean20124142
Median Absolute Deviation (MAD)20000
Skewness-0.14771025
Sum1.0062071 × 1010
Variance6.9624331 × 108
MonotonicityNot monotonic
2023-12-11T00:03:30.753771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
20160101 81
16.2%
20150101 65
13.0%
20140101 63
12.6%
20120101 62
12.4%
20100101 56
11.2%
20110101 52
10.4%
20080101 46
9.2%
20090101 42
8.4%
20130101 32
 
6.4%
20110601 1
 
0.2%
ValueCountFrequency (%)
20080101 46
9.2%
20090101 42
8.4%
20100101 56
11.2%
20110101 52
10.4%
20110601 1
 
0.2%
20120101 62
12.4%
20130101 32
 
6.4%
20140101 63
12.6%
20150101 65
13.0%
20160101 81
16.2%
ValueCountFrequency (%)
20160101 81
16.2%
20150101 65
13.0%
20140101 63
12.6%
20130101 32
 
6.4%
20120101 62
12.4%
20110601 1
 
0.2%
20110101 52
10.4%
20100101 56
11.2%
20090101 42
8.4%
20080101 46
9.2%

주택가격
Real number (ℝ)

Distinct259
Distinct (%)51.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.732344 × 108
Minimum7200000
Maximum2.168 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:31.150249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7200000
5-th percentile30000000
Q168750000
median1.3 × 108
Q32.16 × 108
95-th percentile4.206 × 108
Maximum2.168 × 109
Range2.1608 × 109
Interquartile range (IQR)1.4725 × 108

Descriptive statistics

Standard deviation1.7923512 × 108
Coefficient of variation (CV)1.0346393
Kurtosis41.953915
Mean1.732344 × 108
Median Absolute Deviation (MAD)67000000
Skewness4.9709839
Sum8.66172 × 1010
Variance3.2125229 × 1016
MonotonicityNot monotonic
2023-12-11T00:03:31.642680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160000000 8
 
1.6%
124000000 7
 
1.4%
42000000 7
 
1.4%
48000000 7
 
1.4%
36000000 6
 
1.2%
130000000 5
 
1.0%
68000000 5
 
1.0%
116000000 5
 
1.0%
46000000 5
 
1.0%
24000000 5
 
1.0%
Other values (249) 440
88.0%
ValueCountFrequency (%)
7200000 1
 
0.2%
11000000 1
 
0.2%
14000000 2
 
0.4%
16000000 1
 
0.2%
17000000 2
 
0.4%
19000000 3
0.6%
22000000 3
0.6%
23000000 1
 
0.2%
24000000 5
1.0%
26000000 1
 
0.2%
ValueCountFrequency (%)
2168000000 1
0.2%
1632000000 1
0.2%
1264000000 1
0.2%
848000000 1
0.2%
792000000 2
0.4%
741000000 1
0.2%
736000000 1
0.2%
733000000 1
0.2%
656000000 1
0.2%
532000000 1
0.2%

생성_일자
Real number (ℝ)

Distinct307
Distinct (%)61.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20123330
Minimum20090317
Maximum20160527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:03:32.019374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090317
5-th percentile20090319
Q120100725
median20121206
Q320141103
95-th percentile20160122
Maximum20160527
Range70210
Interquartile range (IQR)40377.75

Descriptive statistics

Standard deviation23109.659
Coefficient of variation (CV)0.0011484013
Kurtosis-1.3630689
Mean20123330
Median Absolute Deviation (MAD)20478.5
Skewness-0.048496069
Sum1.0061665 × 1010
Variance5.3405633 × 108
MonotonicityNot monotonic
2023-12-11T00:03:32.321902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090320 36
 
7.2%
20090319 14
 
2.8%
20100725 12
 
2.4%
20110420 12
 
2.4%
20140902 10
 
2.0%
20110417 9
 
1.8%
20090321 9
 
1.8%
20150725 8
 
1.6%
20090317 7
 
1.4%
20110416 6
 
1.2%
Other values (297) 377
75.4%
ValueCountFrequency (%)
20090317 7
 
1.4%
20090318 6
 
1.2%
20090319 14
 
2.8%
20090320 36
7.2%
20090321 9
 
1.8%
20090323 3
 
0.6%
20090325 1
 
0.2%
20090430 1
 
0.2%
20090507 2
 
0.4%
20090512 1
 
0.2%
ValueCountFrequency (%)
20160527 1
0.2%
20160513 2
0.4%
20160506 2
0.4%
20160429 2
0.4%
20160419 1
0.2%
20160416 1
0.2%
20160415 1
0.2%
20160407 1
0.2%
20160326 1
0.2%
20160315 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_명블록로트외필지_수새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번기준_일자주택가격생성_일자
042720-342452집합4전유부충청북도 청주시 흥덕구 비하동 362번지울산광역시 중구 옥교동길 15양천아파트4163011700016350<NA><NA><NA>430170316600912802090602009010149300000020090319
130200-750282집합4전유부서울특별시 용산구 한강로3가 91번지경기도 부천시 원미구 역곡로45번길 36푸른마을 10단지451131020004300<NA><NA><NA>02641042050791010109190201501017600000020121221
230140-839302집합4전유부광주광역시 광산구 비아동 152-5번지경기도 여주시 세종로 173-65동아청솔아파트4311312200025159<NA><NA><NA>0481213327035250010350201301013100000020090320
311680-828142집합4전유부경기도 구리시 수택동 854번지충청북도 청주시 흥덕구 증안로 77비산롯데캐슬41171102000149<NA><NA><NA>0301403165034107010584020100101126400000020140513
426350-608982집합4전유부경기도 안양시 동안구 호계동 713번지서울특별시 영등포구 당산로4길 12샘터마을112302532404940<NA><NA><NA>04136031970191040107082014010122500000020140611
511620-583662집합4전유부대구광역시 북구 노원동2가 319번지경기도 부천시 원미구 중동로 301마전3차풍림아이원아파트112301030003595<NA><NA><NA>12626020060121050101002014010110500000020090319
648330-465282집합4전유부부산광역시 북구 화명동 495-2번지전라남도 광양시 금영로 182코오롱 아파트301101170006140<NA><NA><NA>041480320606311801014902012010119300000020151230
741285-1565262집합4전유부서울특별시 광진구 화양동 234번지대전광역시 유성구 진잠로42번길 30석수e-편한세상아파트481251190009730<NA><NA><NA>04136031970431230103402008010116800000020151218
848250-1025152집합4전유부전라남도 목포시 용해동 973번지대전광역시 유성구 어은로 57미진5차강변아파트421902502602923<NA><NA><NA>0481703332034107010471<NA>2012010120100000020130810
930170-1330062집합4전유부전라북도 정읍시 상동 253-8번지서울특별시 종로구 새문안로3길 23쌍용스윗닷홈오창예가262601040003720126블럭 1-1놋트<NA><NA>028260426859339002074<NA>2010010122400000020120407
관리_건축물대장_PK대장_구분_코드대장_구분_코드_명대장_종류_코드대장_종류_코드_명대지_위치도로명_대지_위치건물_명시군구_코드법정동_코드대지_구분_코드번지특수지_명블록로트외필지_수새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번기준_일자주택가격생성_일자
49011200-301032집합4전유부경상북도 포항시 남구 오천읍 용덕리 322-60번지서울특별시 양천구 오목로 88주은아파트116201100001350<NA><NA><NA>0413904397266<NA>0200<NA>2013010113200000020090321
49141281-565712집합4전유부전라남도 광양시 광양읍 인서리 480번지<NA>신나무실주공아파트414631050006190<NA><NA><NA>14161044330631060104302016010112000000020140805
49230140-832432집합4전유부대구광역시 수성구 황금동 365번지경기도 의정부시 오목로 9강남아파트1165010200014760<NA><NA><NA>12729042415651060101102015010113000000020151001
49326320-982762집합4전유부서울특별시 강동구 둔촌동 555번지부산광역시 사하구 하신번영로 400늘푸른 벽산아파트112901060002030<NA><NA><NA>0501104847798101010134021201401019300000020100217
49444810-397522집합4전유부경기도 양주시 고암동 580번지영서로 2319월성주공5단지아파트281852502101204<NA><NA><NA>1481273330038106010670201301016300000020140422
49530140-542212집합4전유부경기도 용인시 기흥구 마북동 625번지전라북도 전주시 완산구 호암로 88낙양동명지아파트264101030008130<NA><NA><NA>04146144093351070104202009010112400000020130803
49641430-363692집합4전유부대전광역시 유성구 송강동 199번지강원도 원주시 행구로 287남양주양지e-편한세상 2단지2623010100070<NA><NA><NA>0413702012013103020206220130101720000020140515
49729170-1313532집합4전유부광주광역시 서구 동천동 502번지경기도 파주시 금신초교길 72경동하이츠타운361101090007130<NA><NA><NA>0414634412303111010400201201015800000020150601
49828245-589622집합4전유부경상남도 양산시 물금읍 범어리 549-1번지인천광역시 남구 낙섬동로 104무지개타운472501060002975<NA><NA><NA>04217044631591060101640201501019700000020100725
49942110-723612집합4전유부광주광역시 광산구 신가동 302-39번지경상남도 김해시 서부로 190신성아파트2635012800000<NA><NA><NA>0311403170015<NA>0187102016010110600000020100105