Overview

Dataset statistics

Number of variables33
Number of observations500
Missing cells2582
Missing cells (%)15.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory138.3 KiB
Average record size in memory283.3 B

Variable types

Text10
Numeric13
Categorical9
Unsupported1

Dataset

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

Alerts

로트 has constant value ""Constant
새주소_지상지하_코드 has constant value ""Constant
대지_구분_코드 is highly imbalanced (96.3%)Imbalance
층_구분_코드 is highly imbalanced (63.4%)Imbalance
층_구분_코드_명 is highly imbalanced (70.3%)Imbalance
주_부속_구분_코드 is highly imbalanced (59.1%)Imbalance
주_부속_구분_코드_명 is highly imbalanced (73.8%)Imbalance
도로명_대지_위치 has 55 (11.0%) missing valuesMissing
건물_명 has 388 (77.6%) missing valuesMissing
특수지_명 has 498 (99.6%) missing valuesMissing
블록 has 500 (100.0%) missing valuesMissing
로트 has 499 (99.8%) missing valuesMissing
새주소_도로_코드 has 50 (10.0%) missing valuesMissing
새주소_법정동_코드 has 68 (13.6%) missing valuesMissing
새주소_본_번 has 75 (15.0%) missing valuesMissing
새주소_부_번 has 60 (12.0%) missing valuesMissing
동_명칭 has 383 (76.6%) missing valuesMissing
대지_위치 has unique valuesUnique
블록 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지 has 147 (29.4%) zerosZeros
새주소_본_번 has 8 (1.6%) zerosZeros
새주소_부_번 has 264 (52.8%) zerosZeros

Reproduction

Analysis started2023-12-10 15:04:50.490758
Analysis finished2023-12-10 15:04:52.125283
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리_건축물대장_PK
Text

Distinct499
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:04:52.492865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length11.582
Min length10

Characters and Unicode

Total characters5791
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

Unique498 ?
Unique (%)99.6%

Sample

1st row45740-1872
2nd row31710-9029
3rd row50130-18445
4th row28170-32588
5th row41410-8785
ValueCountFrequency (%)
43760-100184792 2
 
0.4%
43770-24382 1
 
0.2%
47280-8777 1
 
0.2%
48250-19525 1
 
0.2%
48170-11694 1
 
0.2%
31110-20292 1
 
0.2%
46800-12954 1
 
0.2%
48127-1000044849 1
 
0.2%
48840-7946 1
 
0.2%
46130-12706 1
 
0.2%
Other values (489) 489
97.8%
2023-12-11T00:04:53.384891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1034
17.9%
0 901
15.6%
4 646
11.2%
2 600
10.4%
- 500
8.6%
3 434
7.5%
7 403
 
7.0%
8 340
 
5.9%
5 327
 
5.6%
6 322
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5291
91.4%
Dash Punctuation 500
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1034
19.5%
0 901
17.0%
4 646
12.2%
2 600
11.3%
3 434
8.2%
7 403
 
7.6%
8 340
 
6.4%
5 327
 
6.2%
6 322
 
6.1%
9 284
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5791
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1034
17.9%
0 901
15.6%
4 646
11.2%
2 600
10.4%
- 500
8.6%
3 434
7.5%
7 403
 
7.0%
8 340
 
5.9%
5 327
 
5.6%
6 322
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5791
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1034
17.9%
0 901
15.6%
4 646
11.2%
2 600
10.4%
- 500
8.6%
3 434
7.5%
7 403
 
7.0%
8 340
 
5.9%
5 327
 
5.6%
6 322
 
5.6%

대지_위치
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:04:53.966022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length33
Mean length22.032
Min length16

Characters and Unicode

Total characters11016
Distinct characters266
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st row경상북도 의성군 의성읍 도서리 100-1번지
2nd row전라북도 진안군 성수면 중길리 82번지
3rd row대전광역시 유성구 덕명동 607번지
4th row경기도 포천시 창수면 가양리 338-5번지
5th row충청북도 괴산군 청천면 지촌리 278-1번지
ValueCountFrequency (%)
경기도 95
 
4.2%
서울특별시 74
 
3.3%
경상북도 51
 
2.3%
경상남도 46
 
2.0%
충청남도 28
 
1.2%
전라남도 26
 
1.1%
강원도 23
 
1.0%
대구광역시 22
 
1.0%
부산광역시 22
 
1.0%
전라북도 22
 
1.0%
Other values (1304) 1854
81.9%
2023-12-11T00:04:54.880276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1765
 
16.0%
지 513
 
4.7%
번 497
 
4.5%
1 426
 
3.9%
시 419
 
3.8%
동 392
 
3.6%
- 363
 
3.3%
도 343
 
3.1%
구 305
 
2.8%
2 244
 
2.2%
Other values (256) 5749
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6858
62.3%
Decimal Number 2027
 
18.4%
Space Separator 1765
 
16.0%
Dash Punctuation 363
 
3.3%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 513
 
7.5%
번 497
 
7.2%
시 419
 
6.1%
동 392
 
5.7%
도 343
 
5.0%
구 305
 
4.4%
경 208
 
3.0%
리 182
 
2.7%
남 165
 
2.4%
북 140
 
2.0%
Other values (241) 3694
53.9%
Decimal Number
ValueCountFrequency (%)
1 426
21.0%
2 244
12.0%
3 233
11.5%
4 217
10.7%
5 179
8.8%
7 166
 
8.2%
6 157
 
7.7%
0 144
 
7.1%
8 139
 
6.9%
9 122
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
B 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
1765
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 363
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6858
62.3%
Common 4155
37.7%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 513
 
7.5%
번 497
 
7.2%
시 419
 
6.1%
동 392
 
5.7%
도 343
 
5.0%
구 305
 
4.4%
경 208
 
3.0%
리 182
 
2.7%
남 165
 
2.4%
북 140
 
2.0%
Other values (241) 3694
53.9%
Common
ValueCountFrequency (%)
1765
42.5%
1 426
 
10.3%
- 363
 
8.7%
2 244
 
5.9%
3 233
 
5.6%
4 217
 
5.2%
5 179
 
4.3%
7 166
 
4.0%
6 157
 
3.8%
0 144
 
3.5%
Other values (2) 261
 
6.3%
Latin
ValueCountFrequency (%)
L 1
33.3%
B 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6858
62.3%
ASCII 4158
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1765
42.4%
1 426
 
10.2%
- 363
 
8.7%
2 244
 
5.9%
3 233
 
5.6%
4 217
 
5.2%
5 179
 
4.3%
7 166
 
4.0%
6 157
 
3.8%
0 144
 
3.5%
Other values (5) 264
 
6.3%
Hangul
ValueCountFrequency (%)
지 513
 
7.5%
번 497
 
7.2%
시 419
 
6.1%
동 392
 
5.7%
도 343
 
5.0%
구 305
 
4.4%
경 208
 
3.0%
리 182
 
2.7%
남 165
 
2.4%
북 140
 
2.0%
Other values (241) 3694
53.9%

도로명_대지_위치
Text

MISSING 

Distinct445
Distinct (%)100.0%
Missing55
Missing (%)11.0%
Memory size4.0 KiB
2023-12-11T00:04:55.484968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length19.058427
Min length14

Characters and Unicode

Total characters8481
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

Unique445 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 서부로378번길 52-14
2nd row부산광역시 남구 용소로 45
3rd row경상남도 창원시 마산회원구 삼계8길 31
4th row경상북도 경주시 광산1길 11
5th row전라남도 해남군 선창길 10-7
ValueCountFrequency (%)
경기도 83
 
4.5%
서울특별시 80
 
4.3%
경상북도 48
 
2.6%
경상남도 38
 
2.1%
부산광역시 25
 
1.4%
인천광역시 25
 
1.4%
충청남도 20
 
1.1%
대구광역시 20
 
1.1%
충청북도 19
 
1.0%
전라남도 18
 
1.0%
Other values (934) 1474
79.7%
2023-12-11T00:04:56.430500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1405
 
16.6%
시 396
 
4.7%
1 372
 
4.4%
로 339
 
4.0%
길 301
 
3.5%
구 282
 
3.3%
도 277
 
3.3%
2 238
 
2.8%
3 197
 
2.3%
경 184
 
2.2%
Other values (262) 4490
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5261
62.0%
Decimal Number 1659
 
19.6%
Space Separator 1405
 
16.6%
Dash Punctuation 156
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 396
 
7.5%
로 339
 
6.4%
길 301
 
5.7%
구 282
 
5.4%
도 277
 
5.3%
경 184
 
3.5%
서 141
 
2.7%
남 140
 
2.7%
광 128
 
2.4%
북 113
 
2.1%
Other values (250) 2960
56.3%
Decimal Number
ValueCountFrequency (%)
1 372
22.4%
2 238
14.3%
3 197
11.9%
5 154
9.3%
4 142
 
8.6%
7 121
 
7.3%
0 116
 
7.0%
9 114
 
6.9%
6 113
 
6.8%
8 92
 
5.5%
Space Separator
ValueCountFrequency (%)
1405
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5261
62.0%
Common 3220
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 396
 
7.5%
로 339
 
6.4%
길 301
 
5.7%
구 282
 
5.4%
도 277
 
5.3%
경 184
 
3.5%
서 141
 
2.7%
남 140
 
2.7%
광 128
 
2.4%
북 113
 
2.1%
Other values (250) 2960
56.3%
Common
ValueCountFrequency (%)
1405
43.6%
1 372
 
11.6%
2 238
 
7.4%
3 197
 
6.1%
- 156
 
4.8%
5 154
 
4.8%
4 142
 
4.4%
7 121
 
3.8%
0 116
 
3.6%
9 114
 
3.5%
Other values (2) 205
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5261
62.0%
ASCII 3220
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1405
43.6%
1 372
 
11.6%
2 238
 
7.4%
3 197
 
6.1%
- 156
 
4.8%
5 154
 
4.8%
4 142
 
4.4%
7 121
 
3.8%
0 116
 
3.6%
9 114
 
3.5%
Other values (2) 205
 
6.4%
Hangul
ValueCountFrequency (%)
시 396
 
7.5%
로 339
 
6.4%
길 301
 
5.7%
구 282
 
5.4%
도 277
 
5.3%
경 184
 
3.5%
서 141
 
2.7%
남 140
 
2.7%
광 128
 
2.4%
북 113
 
2.1%
Other values (250) 2960
56.3%

건물_명
Text

MISSING 

Distinct111
Distinct (%)99.1%
Missing388
Missing (%)77.6%
Memory size4.0 KiB
2023-12-11T00:04:56.909626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length15
Mean length7.1428571
Min length2

Characters and Unicode

Total characters800
Distinct characters246
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

Unique110 ?
Unique (%)98.2%

Sample

1st row주택
2nd row삼호아파트
3rd row서울아트빌라
4th row혜정빌
5th row삼성아파트 1차
ValueCountFrequency (%)
단독주택 3
 
2.1%
주택 2
 
1.4%
2차 2
 
1.4%
아파트 2
 
1.4%
만경성당 1
 
0.7%
가제31호 1
 
0.7%
보성황실아파트 1
 
0.7%
케이디비생명보험(주 1
 
0.7%
태영아파트 1
 
0.7%
영도신도브래뉴 1
 
0.7%
Other values (127) 127
89.4%
2023-12-11T00:04:57.681020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
 
3.8%
아 28
 
3.5%
트 26
 
3.2%
파 25
 
3.1%
주 20
 
2.5%
빌 20
 
2.5%
이 16
 
2.0%
리 13
 
1.6%
1 13
 
1.6%
동 11
 
1.4%
Other values (236) 598
74.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 705
88.1%
Decimal Number 42
 
5.2%
Space Separator 30
 
3.8%
Dash Punctuation 7
 
0.9%
Close Punctuation 5
 
0.6%
Open Punctuation 5
 
0.6%
Uppercase Letter 4
 
0.5%
Lowercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 28
 
4.0%
트 26
 
3.7%
파 25
 
3.5%
주 20
 
2.8%
빌 20
 
2.8%
이 16
 
2.3%
리 13
 
1.8%
동 11
 
1.6%
스 11
 
1.6%
성 11
 
1.6%
Other values (219) 524
74.3%
Decimal Number
ValueCountFrequency (%)
1 13
31.0%
2 10
23.8%
3 4
 
9.5%
5 3
 
7.1%
0 3
 
7.1%
4 2
 
4.8%
8 2
 
4.8%
9 2
 
4.8%
6 2
 
4.8%
7 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
I 2
50.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 705
88.1%
Common 89
 
11.1%
Latin 6
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 28
 
4.0%
트 26
 
3.7%
파 25
 
3.5%
주 20
 
2.8%
빌 20
 
2.8%
이 16
 
2.3%
리 13
 
1.8%
동 11
 
1.6%
스 11
 
1.6%
성 11
 
1.6%
Other values (219) 524
74.3%
Common
ValueCountFrequency (%)
30
33.7%
1 13
14.6%
2 10
 
11.2%
- 7
 
7.9%
) 5
 
5.6%
( 5
 
5.6%
3 4
 
4.5%
5 3
 
3.4%
0 3
 
3.4%
4 2
 
2.2%
Other values (4) 7
 
7.9%
Latin
ValueCountFrequency (%)
T 2
33.3%
I 2
33.3%
e 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 705
88.1%
ASCII 95
 
11.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
31.6%
1 13
13.7%
2 10
 
10.5%
- 7
 
7.4%
) 5
 
5.3%
( 5
 
5.3%
3 4
 
4.2%
5 3
 
3.2%
0 3
 
3.2%
4 2
 
2.1%
Other values (7) 13
13.7%
Hangul
ValueCountFrequency (%)
아 28
 
4.0%
트 26
 
3.7%
파 25
 
3.5%
주 20
 
2.8%
빌 20
 
2.8%
이 16
 
2.3%
리 13
 
1.8%
동 11
 
1.6%
스 11
 
1.6%
성 11
 
1.6%
Other values (219) 524
74.3%

시군구_코드
Real number (ℝ)

Distinct198
Distinct (%)39.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35809.258
Minimum11110
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:04:57.931350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11288.5
Q127230
median41570
Q345190
95-th percentile48240.5
Maximum50130
Range39020
Interquartile range (IQR)17960

Descriptive statistics

Standard deviation12768.628
Coefficient of variation (CV)0.35657338
Kurtosis-0.56088893
Mean35809.258
Median Absolute Deviation (MAD)5715
Skewness-0.92096141
Sum17904629
Variance1.6303787 × 108
MonotonicityNot monotonic
2023-12-11T00:04:58.730823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42110 10
 
2.0%
45113 8
 
1.6%
11680 7
 
1.4%
41610 7
 
1.4%
11410 6
 
1.2%
47900 6
 
1.2%
11215 6
 
1.2%
11260 6
 
1.2%
45140 6
 
1.2%
11170 6
 
1.2%
Other values (188) 432
86.4%
ValueCountFrequency (%)
11110 1
 
0.2%
11140 1
 
0.2%
11170 6
1.2%
11200 3
0.6%
11215 6
1.2%
11230 2
 
0.4%
11260 6
1.2%
11290 4
0.8%
11305 2
 
0.4%
11320 2
 
0.4%
ValueCountFrequency (%)
50130 2
 
0.4%
50110 5
1.0%
48880 1
 
0.2%
48870 2
 
0.4%
48840 1
 
0.2%
48740 1
 
0.2%
48730 1
 
0.2%
48330 5
1.0%
48310 3
0.6%
48250 4
0.8%

법정동_코드
Real number (ℝ)

Distinct160
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18420.664
Minimum10100
Maximum46023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:04:59.071196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10100
5-th percentile10100
Q110500
median11550
Q325628.5
95-th percentile37028.05
Maximum46023
Range35923
Interquartile range (IQR)15128.5

Descriptive statistics

Standard deviation10460.839
Coefficient of variation (CV)0.56788609
Kurtosis-0.9235907
Mean18420.664
Median Absolute Deviation (MAD)1350
Skewness0.85875804
Sum9210332
Variance1.0942915 × 108
MonotonicityNot monotonic
2023-12-11T00:04:59.441811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10100 45
 
9.0%
10200 38
 
7.6%
10700 24
 
4.8%
10300 22
 
4.4%
11100 16
 
3.2%
10600 16
 
3.2%
10400 13
 
2.6%
10900 12
 
2.4%
11000 12
 
2.4%
10800 12
 
2.4%
Other values (150) 290
58.0%
ValueCountFrequency (%)
10100 45
9.0%
10200 38
7.6%
10300 22
4.4%
10400 13
 
2.6%
10500 9
 
1.8%
10600 16
 
3.2%
10700 24
4.8%
10800 12
 
2.4%
10900 12
 
2.4%
11000 12
 
2.4%
ValueCountFrequency (%)
46023 1
0.2%
43030 1
0.2%
43025 1
0.2%
42027 1
0.2%
41025 1
0.2%
41023 1
0.2%
41021 1
0.2%
40030 1
0.2%
40029 1
0.2%
39033 1
0.2%

대지_구분_코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
497 
1
 
2
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 (%)
0 497
99.4%
1 2
 
0.4%
2 1
 
0.2%

Length

2023-12-11T00:04:59.695015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:04:59.877455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 497
99.4%
1 2
 
0.4%
2 1
 
0.2%

번
Real number (ℝ)

Distinct410
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean556.896
Minimum0
Maximum4082
Zeros4
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:00.162455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile26.85
Q1178.75
median409
Q3773.25
95-th percentile1486.2
Maximum4082
Range4082
Interquartile range (IQR)594.5

Descriptive statistics

Standard deviation545.45506
Coefficient of variation (CV)0.97945589
Kurtosis7.9502069
Mean556.896
Median Absolute Deviation (MAD)287
Skewness2.2504161
Sum278448
Variance297521.23
MonotonicityNot monotonic
2023-12-11T00:05:00.477268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
0.8%
23 4
 
0.8%
360 3
 
0.6%
125 3
 
0.6%
56 3
 
0.6%
193 3
 
0.6%
33 3
 
0.6%
415 3
 
0.6%
166 3
 
0.6%
191 3
 
0.6%
Other values (400) 468
93.6%
ValueCountFrequency (%)
0 4
0.8%
1 2
0.4%
2 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
6 2
0.4%
7 1
 
0.2%
9 1
 
0.2%
10 2
0.4%
11 1
 
0.2%
ValueCountFrequency (%)
4082 1
0.2%
3322 1
0.2%
3153 1
0.2%
3141 1
0.2%
3014 1
0.2%
2823 1
0.2%
2779 1
0.2%
2680 1
0.2%
2468 1
0.2%
2220 1
0.2%

지
Real number (ℝ)

ZEROS 

Distinct68
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.164
Minimum0
Maximum765
Zeros147
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:00.771531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q313
95-th percentile71.3
Maximum765
Range765
Interquartile range (IQR)13

Descriptive statistics

Standard deviation62.519905
Coefficient of variation (CV)3.262362
Kurtosis60.610606
Mean19.164
Median Absolute Deviation (MAD)3
Skewness7.0117415
Sum9582
Variance3908.7386
MonotonicityNot monotonic
2023-12-11T00:05:01.108650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 147
29.4%
1 63
12.6%
2 34
 
6.8%
3 27
 
5.4%
5 17
 
3.4%
4 16
 
3.2%
6 15
 
3.0%
9 11
 
2.2%
17 10
 
2.0%
16 9
 
1.8%
Other values (58) 151
30.2%
ValueCountFrequency (%)
0 147
29.4%
1 63
12.6%
2 34
 
6.8%
3 27
 
5.4%
4 16
 
3.2%
5 17
 
3.4%
6 15
 
3.0%
7 9
 
1.8%
8 6
 
1.2%
9 11
 
2.2%
ValueCountFrequency (%)
765 1
0.2%
517 1
0.2%
422 1
0.2%
401 2
0.4%
385 1
0.2%
331 1
0.2%
301 1
0.2%
238 1
0.2%
210 1
0.2%
173 1
0.2%

특수지_명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing498
Missing (%)99.6%
Memory size4.0 KiB
2023-12-11T00:05:01.414804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7
Min length4

Characters and Unicode

Total characters14
Distinct characters11
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

Unique2 ?
Unique (%)100.0%

Sample

1st row2629-1 외 1
2nd row금포지구
ValueCountFrequency (%)
2629-1 1
25.0%
외 1
25.0%
1 1
25.0%
금포지구 1
25.0%
2023-12-11T00:05:01.956457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
14.3%
1 2
14.3%
2
14.3%
6 1
7.1%
9 1
7.1%
- 1
7.1%
외 1
7.1%
금 1
7.1%
포 1
7.1%
지 1
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
42.9%
Other Letter 5
35.7%
Space Separator 2
 
14.3%
Dash Punctuation 1
 
7.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
외 1
20.0%
금 1
20.0%
포 1
20.0%
지 1
20.0%
구 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
1 2
33.3%
6 1
16.7%
9 1
16.7%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9
64.3%
Hangul 5
35.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2
22.2%
1 2
22.2%
2
22.2%
6 1
11.1%
9 1
11.1%
- 1
11.1%
Hangul
ValueCountFrequency (%)
외 1
20.0%
금 1
20.0%
포 1
20.0%
지 1
20.0%
구 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
64.3%
Hangul 5
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
22.2%
1 2
22.2%
2
22.2%
6 1
11.1%
9 1
11.1%
- 1
11.1%
Hangul
ValueCountFrequency (%)
외 1
20.0%
금 1
20.0%
포 1
20.0%
지 1
20.0%
구 1
20.0%

블록
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

로트
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing499
Missing (%)99.8%
Memory size4.0 KiB
2023-12-11T00:05:02.179115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
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

Unique1 ?
Unique (%)100.0%

Sample

1st row27롯트
ValueCountFrequency (%)
27롯트 1
100.0%
2023-12-11T00:05:02.642112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
25.0%
7 1
25.0%
롯 1
25.0%
트 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
50.0%
Other Letter 2
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
50.0%
7 1
50.0%
Other Letter
ValueCountFrequency (%)
롯 1
50.0%
트 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
50.0%
Hangul 2
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
50.0%
7 1
50.0%
Hangul
ValueCountFrequency (%)
롯 1
50.0%
트 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
50.0%
Hangul 2
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
50.0%
7 1
50.0%
Hangul
ValueCountFrequency (%)
롯 1
50.0%
트 1
50.0%

새주소_도로_코드
Real number (ℝ)

MISSING 

Distinct445
Distinct (%)98.9%
Missing50
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean3.6105167 × 1011
Minimum1.111041 × 1011
Maximum5.0130335 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:02.923863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111041 × 1011
5-th percentile1.1305351 × 1011
Q12.7710342 × 1011
median4.1281378 × 1011
Q34.5787964 × 1011
95-th percentile4.8310415 × 1011
Maximum5.0130335 × 1011
Range3.9019925 × 1011
Interquartile range (IQR)1.8077622 × 1011

Descriptive statistics

Standard deviation1.1993444 × 1011
Coefficient of variation (CV)0.33218083
Kurtosis-0.36884387
Mean3.6105167 × 1011
Median Absolute Deviation (MAD)6.5440974 × 1010
Skewness-0.90385823
Sum1.6247325 × 1014
Variance1.438427 × 1022
MonotonicityNot monotonic
2023-12-11T00:05:03.269823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
114403113005 3
 
0.6%
112154112143 2
 
0.4%
482504805624 2
 
0.4%
277103148058 2
 
0.4%
471304716143 1
 
0.2%
448103263012 1
 
0.2%
451404607995 1
 
0.2%
461703284033 1
 
0.2%
412203000117 1
 
0.2%
112004109428 1
 
0.2%
Other values (435) 435
87.0%
(Missing) 50
 
10.0%
ValueCountFrequency (%)
111104100162 1
0.2%
111104100202 1
0.2%
111403101001 1
0.2%
111404103152 1
0.2%
111404103396 1
0.2%
111703005022 1
0.2%
111704106002 1
0.2%
111704106245 1
0.2%
112003005011 1
0.2%
112004109284 1
0.2%
ValueCountFrequency (%)
501303350279 1
0.2%
501303349239 1
0.2%
501104848563 1
0.2%
501103349136 1
0.2%
501103349093 1
0.2%
488903019081 1
0.2%
488804841538 1
0.2%
488804841464 1
0.2%
488804841452 1
0.2%
488804841319 1
0.2%

새주소_법정동_코드
Real number (ℝ)

MISSING 

Distinct114
Distinct (%)26.4%
Missing68
Missing (%)13.6%
Infinite0
Infinite (%)0.0%
Mean17837.734
Minimum10101
Maximum46003
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:03.651708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10101
Q110501
median11501
Q325301
95-th percentile38001
Maximum46003
Range35902
Interquartile range (IQR)14800

Descriptive statistics

Standard deviation10424.002
Coefficient of variation (CV)0.58437927
Kurtosis-0.52355601
Mean17837.734
Median Absolute Deviation (MAD)1300
Skewness1.0488884
Sum7705901
Variance1.0865982 × 108
MonotonicityNot monotonic
2023-12-11T00:05:04.021534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10101 38
 
7.6%
25001 20
 
4.0%
10201 18
 
3.6%
10501 16
 
3.2%
10801 16
 
3.2%
10601 16
 
3.2%
10301 14
 
2.8%
33001 14
 
2.8%
31001 13
 
2.6%
35001 11
 
2.2%
Other values (104) 256
51.2%
(Missing) 68
 
13.6%
ValueCountFrequency (%)
10101 38
7.6%
10201 18
3.6%
10202 9
 
1.8%
10301 14
 
2.8%
10302 3
 
0.6%
10303 2
 
0.4%
10401 9
 
1.8%
10402 6
 
1.2%
10501 16
3.2%
10502 2
 
0.4%
ValueCountFrequency (%)
46003 1
 
0.2%
46001 1
 
0.2%
45001 1
 
0.2%
43001 1
 
0.2%
42001 1
 
0.2%
41001 2
 
0.4%
40002 1
 
0.2%
40001 6
1.2%
39003 1
 
0.2%
39001 5
1.0%

새주소_지상지하_코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-11T00:05:04.357246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:04.548383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

새주소_본_번
Real number (ℝ)

MISSING  ZEROS 

Distinct182
Distinct (%)42.8%
Missing75
Missing (%)15.0%
Infinite0
Infinite (%)0.0%
Mean139.2
Minimum0
Maximum6061
Zeros8
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:04.839248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q116
median40
Q397
95-th percentile609.2
Maximum6061
Range6061
Interquartile range (IQR)81

Descriptive statistics

Standard deviation389.01389
Coefficient of variation (CV)2.79464
Kurtosis130.07963
Mean139.2
Median Absolute Deviation (MAD)28
Skewness9.5922749
Sum59160
Variance151331.81
MonotonicityNot monotonic
2023-12-11T00:05:05.381742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 11
 
2.2%
7 10
 
2.0%
5 9
 
1.8%
0 8
 
1.6%
19 8
 
1.6%
3 8
 
1.6%
13 8
 
1.6%
8 8
 
1.6%
20 8
 
1.6%
12 7
 
1.4%
Other values (172) 340
68.0%
(Missing) 75
 
15.0%
ValueCountFrequency (%)
0 8
1.6%
1 4
 
0.8%
2 1
 
0.2%
3 8
1.6%
4 6
1.2%
5 9
1.8%
6 5
1.0%
7 10
2.0%
8 8
1.6%
9 5
1.0%
ValueCountFrequency (%)
6061 1
0.2%
1926 1
0.2%
1924 1
0.2%
1790 1
0.2%
1571 1
0.2%
1556 1
0.2%
1337 1
0.2%
1253 1
0.2%
1239 1
0.2%
1067 1
0.2%

새주소_부_번
Real number (ℝ)

MISSING  ZEROS 

Distinct43
Distinct (%)9.8%
Missing60
Missing (%)12.0%
Infinite0
Infinite (%)0.0%
Mean5.6295455
Minimum0
Maximum138
Zeros264
Zeros (%)52.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:05.756129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile30.05
Maximum138
Range138
Interquartile range (IQR)5

Descriptive statistics

Standard deviation14.566368
Coefficient of variation (CV)2.5874857
Kurtosis35.827859
Mean5.6295455
Median Absolute Deviation (MAD)0
Skewness5.2306063
Sum2477
Variance212.17908
MonotonicityNot monotonic
2023-12-11T00:05:06.105743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 264
52.8%
1 28
 
5.6%
3 13
 
2.6%
2 13
 
2.6%
7 11
 
2.2%
9 11
 
2.2%
4 9
 
1.8%
11 8
 
1.6%
8 7
 
1.4%
12 7
 
1.4%
Other values (33) 69
 
13.8%
(Missing) 60
 
12.0%
ValueCountFrequency (%)
0 264
52.8%
1 28
 
5.6%
2 13
 
2.6%
3 13
 
2.6%
4 9
 
1.8%
5 6
 
1.2%
6 6
 
1.2%
7 11
 
2.2%
8 7
 
1.4%
9 11
 
2.2%
ValueCountFrequency (%)
138 1
 
0.2%
129 1
 
0.2%
104 1
 
0.2%
100 1
 
0.2%
67 1
 
0.2%
56 1
 
0.2%
48 1
 
0.2%
44 1
 
0.2%
43 3
0.6%
42 1
 
0.2%

동_명칭
Text

MISSING 

Distinct71
Distinct (%)60.7%
Missing383
Missing (%)76.6%
Memory size4.0 KiB
2023-12-11T00:05:06.575961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length3.6410256
Min length2

Characters and Unicode

Total characters426
Distinct characters65
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

Unique53 ?
Unique (%)45.3%

Sample

1st row3동
2nd rowB동
3rd row관리노인정
4th row105동
5th row가동
ValueCountFrequency (%)
가동 10
 
8.3%
나동 6
 
5.0%
2동 5
 
4.1%
주건축물제1동 4
 
3.3%
a동 4
 
3.3%
101동 4
 
3.3%
103동 4
 
3.3%
1동 4
 
3.3%
b동 3
 
2.5%
104동 3
 
2.5%
Other values (64) 74
61.2%
2023-12-11T00:05:07.364818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 101
23.7%
1 65
15.3%
0 51
12.0%
2 22
 
5.2%
3 18
 
4.2%
가 12
 
2.8%
5 11
 
2.6%
7 11
 
2.6%
제 10
 
2.3%
주 9
 
2.1%
Other values (55) 116
27.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 211
49.5%
Decimal Number 201
47.2%
Uppercase Letter 7
 
1.6%
Space Separator 4
 
0.9%
Other Punctuation 2
 
0.5%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 101
47.9%
가 12
 
5.7%
제 10
 
4.7%
주 9
 
4.3%
나 7
 
3.3%
건 5
 
2.4%
관 4
 
1.9%
축 4
 
1.9%
물 4
 
1.9%
인 3
 
1.4%
Other values (40) 52
24.6%
Decimal Number
ValueCountFrequency (%)
1 65
32.3%
0 51
25.4%
2 22
 
10.9%
3 18
 
9.0%
5 11
 
5.5%
7 11
 
5.5%
8 7
 
3.5%
4 7
 
3.5%
9 5
 
2.5%
6 4
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
A 4
57.1%
B 3
42.9%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 211
49.5%
Common 208
48.8%
Latin 7
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 101
47.9%
가 12
 
5.7%
제 10
 
4.7%
주 9
 
4.3%
나 7
 
3.3%
건 5
 
2.4%
관 4
 
1.9%
축 4
 
1.9%
물 4
 
1.9%
인 3
 
1.4%
Other values (40) 52
24.6%
Common
ValueCountFrequency (%)
1 65
31.2%
0 51
24.5%
2 22
 
10.6%
3 18
 
8.7%
5 11
 
5.3%
7 11
 
5.3%
8 7
 
3.4%
4 7
 
3.4%
9 5
 
2.4%
6 4
 
1.9%
Other values (3) 7
 
3.4%
Latin
ValueCountFrequency (%)
A 4
57.1%
B 3
42.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 215
50.5%
Hangul 211
49.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 101
47.9%
가 12
 
5.7%
제 10
 
4.7%
주 9
 
4.3%
나 7
 
3.3%
건 5
 
2.4%
관 4
 
1.9%
축 4
 
1.9%
물 4
 
1.9%
인 3
 
1.4%
Other values (40) 52
24.6%
ASCII
ValueCountFrequency (%)
1 65
30.2%
0 51
23.7%
2 22
 
10.2%
3 18
 
8.4%
5 11
 
5.1%
7 11
 
5.1%
8 7
 
3.3%
4 7
 
3.3%
9 5
 
2.3%
6 4
 
1.9%
Other values (5) 14
 
6.5%

층_구분_코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
20
445 
10
 
44
30
 
11

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
20 445
89.0%
10 44
 
8.8%
30 11
 
2.2%

Length

2023-12-11T00:05:07.641339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:07.825469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20 445
89.0%
10 44
 
8.8%
30 11
 
2.2%

층_구분_코드_명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
지상
445 
지하
 
43
옥탑
 
11
각층
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
지상 445
89.0%
지하 43
 
8.6%
옥탑 11
 
2.2%
각층 1
 
0.2%

Length

2023-12-11T00:05:08.031662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:08.212025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상 445
89.0%
지하 43
 
8.6%
옥탑 11
 
2.2%
각층 1
 
0.2%

층_번호
Real number (ℝ)

Distinct22
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5
Minimum0
Maximum36
Zeros3
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:08.392052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile10
Maximum36
Range36
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.7691395
Coefficient of variation (CV)1.5076558
Kurtosis23.724032
Mean2.5
Median Absolute Deviation (MAD)0
Skewness4.349301
Sum1250
Variance14.206413
MonotonicityNot monotonic
2023-12-11T00:05:08.603027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 306
61.2%
2 88
 
17.6%
3 29
 
5.8%
4 21
 
4.2%
6 8
 
1.6%
5 8
 
1.6%
9 4
 
0.8%
15 4
 
0.8%
7 4
 
0.8%
19 3
 
0.6%
Other values (12) 25
 
5.0%
ValueCountFrequency (%)
0 3
 
0.6%
1 306
61.2%
2 88
 
17.6%
3 29
 
5.8%
4 21
 
4.2%
5 8
 
1.6%
6 8
 
1.6%
7 4
 
0.8%
8 3
 
0.6%
9 4
 
0.8%
ValueCountFrequency (%)
36 1
 
0.2%
28 1
 
0.2%
23 2
0.4%
21 1
 
0.2%
19 3
0.6%
18 1
 
0.2%
15 4
0.8%
14 2
0.4%
13 3
0.6%
12 3
0.6%

층_번호_명
Categorical

Distinct48
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1층
262 
2층
56 
3층
40 
지1
28 
4층
 
11
Other values (43)
103 

Length

Max length11
Median length2
Mean length2.148
Min length1

Unique

Unique22 ?
Unique (%)4.4%

Sample

1st row1층
2nd row2층
3rd row1층
4th row3층
5th row3층

Common Values

ValueCountFrequency (%)
1층 262
52.4%
2층 56
 
11.2%
3층 40
 
8.0%
지1 28
 
5.6%
4층 11
 
2.2%
지1층 8
 
1.6%
1 7
 
1.4%
6층 6
 
1.2%
5층 5
 
1.0%
옥탑 5
 
1.0%
Other values (38) 72
 
14.4%

Length

2023-12-11T00:05:08.855589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1층 263
52.4%
2층 56
 
11.2%
3층 40
 
8.0%
지1 28
 
5.6%
4층 11
 
2.2%
지1층 8
 
1.6%
1 7
 
1.4%
6층 6
 
1.2%
옥탑 6
 
1.2%
12층 5
 
1.0%
Other values (38) 72
 
14.3%

구조_코드
Real number (ℝ)

Distinct11
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.168
Minimum11
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:09.033799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q112
median21
Q321
95-th percentile51
Maximum51
Range40
Interquartile range (IQR)9

Descriptive statistics

Standard deviation11.557115
Coefficient of variation (CV)0.52134226
Kurtosis1.3690328
Mean22.168
Median Absolute Deviation (MAD)2
Skewness1.4414952
Sum11084
Variance133.56691
MonotonicityNot monotonic
2023-12-11T00:05:09.224424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
21 243
48.6%
11 105
21.0%
51 51
 
10.2%
12 46
 
9.2%
32 18
 
3.6%
31 15
 
3.0%
19 9
 
1.8%
33 6
 
1.2%
42 4
 
0.8%
41 2
 
0.4%
ValueCountFrequency (%)
11 105
21.0%
12 46
 
9.2%
13 1
 
0.2%
19 9
 
1.8%
21 243
48.6%
31 15
 
3.0%
32 18
 
3.6%
33 6
 
1.2%
41 2
 
0.4%
42 4
 
0.8%
ValueCountFrequency (%)
51 51
 
10.2%
42 4
 
0.8%
41 2
 
0.4%
33 6
 
1.2%
32 18
 
3.6%
31 15
 
3.0%
21 243
48.6%
19 9
 
1.8%
13 1
 
0.2%
12 46
 
9.2%

구조_코드_명
Categorical

Distinct15
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
철근콘크리트구조
210 
벽돌구조
111 
일반목구조
59 
블록구조
43 
경량철골구조
29 
Other values (10)
48 

Length

Max length11
Median length10
Mean length6.116
Min length3

Unique

Unique6 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 210
42.0%
벽돌구조 111
22.2%
일반목구조 59
 
11.8%
블록구조 43
 
8.6%
경량철골구조 29
 
5.8%
일반철골구조 21
 
4.2%
기타조적구조 14
 
2.8%
강파이프구조 5
 
1.0%
철골콘크리트구조 2
 
0.4%
기타구조 1
 
0.2%
Other values (5) 5
 
1.0%

Length

2023-12-11T00:05:09.482066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철근콘크리트구조 210
42.0%
벽돌구조 111
22.2%
일반목구조 59
 
11.8%
블록구조 43
 
8.6%
경량철골구조 29
 
5.8%
일반철골구조 21
 
4.2%
기타조적구조 14
 
2.8%
강파이프구조 5
 
1.0%
철골콘크리트구조 2
 
0.4%
기타구조 1
 
0.2%
Other values (5) 5
 
1.0%

기타_구조
Text

Distinct152
Distinct (%)30.5%
Missing2
Missing (%)0.4%
Memory size4.0 KiB
2023-12-11T00:05:09.931931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length14
Mean length6.3253012
Min length2

Characters and Unicode

Total characters3150
Distinct characters95
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)21.9%

Sample

1st row목조
2nd row철근콘크리트조
3rd row철근콘크리트구조
4th row목조
5th row철근콘크리트구조
ValueCountFrequency (%)
철근콘크리트구조 93
18.3%
철근콘크리트조 76
 
15.0%
연와조 30
 
5.9%
목조 24
 
4.7%
철근콘크리트 16
 
3.1%
벽돌조 14
 
2.8%
조적조 13
 
2.6%
경량철골구조 12
 
2.4%
시멘트벽돌조 12
 
2.4%
일반철골구조 12
 
2.4%
Other values (143) 206
40.6%
2023-12-11T00:05:11.200394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
조 477
15.1%
트 276
 
8.8%
철 272
 
8.6%
근 214
 
6.8%
크 212
 
6.7%
리 211
 
6.7%
콘 209
 
6.6%
구 153
 
4.9%
벽 78
 
2.5%
/ 70
 
2.2%
Other values (85) 978
31.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3011
95.6%
Other Punctuation 95
 
3.0%
Uppercase Letter 14
 
0.4%
Space Separator 10
 
0.3%
Close Punctuation 7
 
0.2%
Open Punctuation 7
 
0.2%
Decimal Number 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 477
15.8%
트 276
 
9.2%
철 272
 
9.0%
근 214
 
7.1%
크 212
 
7.0%
리 211
 
7.0%
콘 209
 
6.9%
구 153
 
5.1%
벽 78
 
2.6%
돌 63
 
2.1%
Other values (69) 846
28.1%
Decimal Number
ValueCountFrequency (%)
4 2
33.3%
6 1
16.7%
7 1
16.7%
5 1
16.7%
8 1
16.7%
Other Punctuation
ValueCountFrequency (%)
/ 70
73.7%
, 15
 
15.8%
. 9
 
9.5%
' 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
C 7
50.0%
R 5
35.7%
N 1
 
7.1%
O 1
 
7.1%
Space Separator
ValueCountFrequency (%)
10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3011
95.6%
Common 125
 
4.0%
Latin 14
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 477
15.8%
트 276
 
9.2%
철 272
 
9.0%
근 214
 
7.1%
크 212
 
7.0%
리 211
 
7.0%
콘 209
 
6.9%
구 153
 
5.1%
벽 78
 
2.6%
돌 63
 
2.1%
Other values (69) 846
28.1%
Common
ValueCountFrequency (%)
/ 70
56.0%
, 15
 
12.0%
10
 
8.0%
. 9
 
7.2%
) 7
 
5.6%
( 7
 
5.6%
4 2
 
1.6%
' 1
 
0.8%
6 1
 
0.8%
7 1
 
0.8%
Other values (2) 2
 
1.6%
Latin
ValueCountFrequency (%)
C 7
50.0%
R 5
35.7%
N 1
 
7.1%
O 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3011
95.6%
ASCII 139
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
조 477
15.8%
트 276
 
9.2%
철 272
 
9.0%
근 214
 
7.1%
크 212
 
7.0%
리 211
 
7.0%
콘 209
 
6.9%
구 153
 
5.1%
벽 78
 
2.6%
돌 63
 
2.1%
Other values (69) 846
28.1%
ASCII
ValueCountFrequency (%)
/ 70
50.4%
, 15
 
10.8%
10
 
7.2%
. 9
 
6.5%
) 7
 
5.0%
C 7
 
5.0%
( 7
 
5.0%
R 5
 
3.6%
4 2
 
1.4%
N 1
 
0.7%
Other values (6) 6
 
4.3%

주_용도_코드
Real number (ℝ)

Distinct59
Distinct (%)11.8%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean5034.8594
Minimum1001
Maximum23003
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:11.544945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001
5-th percentile1001
Q11001
median2001
Q34299
95-th percentile19001
Maximum23003
Range22002
Interquartile range (IQR)3298

Descriptive statistics

Standard deviation6512.8417
Coefficient of variation (CV)1.2935499
Kurtosis0.73112531
Mean5034.8594
Median Absolute Deviation (MAD)1000
Skewness1.5495486
Sum2507360
Variance42417108
MonotonicityNot monotonic
2023-12-11T00:05:11.876429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1001 169
33.8%
2001 53
 
10.6%
1003 42
 
8.4%
2003 34
 
6.8%
3001 25
 
5.0%
18001 21
 
4.2%
17100 19
 
3.8%
4001 14
 
2.8%
21101 12
 
2.4%
4999 9
 
1.8%
Other values (49) 100
20.0%
ValueCountFrequency (%)
1001 169
33.8%
1003 42
 
8.4%
2001 53
 
10.6%
2002 3
 
0.6%
2003 34
 
6.8%
2005 5
 
1.0%
2007 1
 
0.2%
3001 25
 
5.0%
3002 3
 
0.6%
3005 1
 
0.2%
ValueCountFrequency (%)
23003 1
 
0.2%
21999 6
 
1.2%
21101 12
2.4%
21004 1
 
0.2%
20999 1
 
0.2%
20001 2
 
0.4%
19999 1
 
0.2%
19001 4
 
0.8%
18999 4
 
0.8%
18001 21
4.2%

주_용도_코드_명
Text

Distinct69
Distinct (%)13.9%
Missing2
Missing (%)0.4%
Memory size4.0 KiB
2023-12-11T00:05:12.347761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.2128514
Min length2

Characters and Unicode

Total characters2098
Distinct characters120
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

Unique36 ?
Unique (%)7.2%

Sample

1st row사무소
2nd row아파트
3rd row단독주택
4th row단독주택
5th row아파트
ValueCountFrequency (%)
단독주택 147
29.4%
아파트 58
 
11.6%
다가구주택 52
 
10.4%
다세대주택 25
 
5.0%
소매점 24
 
4.8%
사무소 19
 
3.8%
창고 18
 
3.6%
일반음식점 18
 
3.6%
일반공장 17
 
3.4%
기타제1종근린생활시설 12
 
2.4%
Other values (60) 110
22.0%
2023-12-11T00:05:13.102407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 233
 
11.1%
택 231
 
11.0%
독 148
 
7.1%
단 147
 
7.0%
다 79
 
3.8%
파 59
 
2.8%
아 58
 
2.8%
트 58
 
2.8%
소 54
 
2.6%
구 53
 
2.5%
Other values (110) 978
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2074
98.9%
Decimal Number 18
 
0.9%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Space Separator 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 233
 
11.2%
택 231
 
11.1%
독 148
 
7.1%
단 147
 
7.1%
다 79
 
3.8%
파 59
 
2.8%
아 58
 
2.8%
트 58
 
2.8%
소 54
 
2.6%
구 53
 
2.6%
Other values (105) 954
46.0%
Decimal Number
ValueCountFrequency (%)
1 12
66.7%
2 6
33.3%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2074
98.9%
Common 24
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 233
 
11.2%
택 231
 
11.1%
독 148
 
7.1%
단 147
 
7.1%
다 79
 
3.8%
파 59
 
2.8%
아 58
 
2.8%
트 58
 
2.8%
소 54
 
2.6%
구 53
 
2.6%
Other values (105) 954
46.0%
Common
ValueCountFrequency (%)
1 12
50.0%
2 6
25.0%
( 2
 
8.3%
) 2
 
8.3%
2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2074
98.9%
ASCII 24
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 233
 
11.2%
택 231
 
11.1%
독 148
 
7.1%
단 147
 
7.1%
다 79
 
3.8%
파 59
 
2.8%
아 58
 
2.8%
트 58
 
2.8%
소 54
 
2.6%
구 53
 
2.6%
Other values (105) 954
46.0%
ASCII
ValueCountFrequency (%)
1 12
50.0%
2 6
25.0%
( 2
 
8.3%
) 2
 
8.3%
2
 
8.3%

기타_용도
Text

Distinct179
Distinct (%)35.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:05:13.502492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length30
Mean length5.22
Min length2

Characters and Unicode

Total characters2610
Distinct characters171
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)27.0%

Sample

1st row아파트
2nd row창고:50.01,위험물취급소:23.0,근린생활시설:46.7350.01
3rd row주택
4th row다세대주택
5th row급배기덕트
ValueCountFrequency (%)
주택 103
20.2%
아파트 40
 
7.9%
단독주택 35
 
6.9%
창고 25
 
4.9%
다세대주택 13
 
2.6%
공동주택(아파트 8
 
1.6%
소매점 8
 
1.6%
다세대주택(2세대 8
 
1.6%
축사 7
 
1.4%
사무실 7
 
1.4%
Other values (174) 255
50.1%
2023-12-11T00:05:14.310922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 237
 
9.1%
택 229
 
8.8%
( 126
 
4.8%
) 126
 
4.8%
시 69
 
2.6%
단 66
 
2.5%
실 66
 
2.5%
설 64
 
2.5%
사 56
 
2.1%
대 54
 
2.1%
Other values (161) 1517
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2190
83.9%
Open Punctuation 127
 
4.9%
Close Punctuation 127
 
4.9%
Decimal Number 96
 
3.7%
Other Punctuation 35
 
1.3%
Uppercase Letter 25
 
1.0%
Space Separator 10
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 237
 
10.8%
택 229
 
10.5%
시 69
 
3.2%
단 66
 
3.0%
실 66
 
3.0%
설 64
 
2.9%
사 56
 
2.6%
대 54
 
2.5%
아 50
 
2.3%
파 50
 
2.3%
Other values (133) 1249
57.0%
Decimal Number
ValueCountFrequency (%)
2 38
39.6%
1 25
26.0%
9 7
 
7.3%
6 6
 
6.2%
0 6
 
6.2%
5 4
 
4.2%
3 3
 
3.1%
4 3
 
3.1%
8 2
 
2.1%
7 2
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
E 7
28.0%
L 4
16.0%
O 4
16.0%
V 3
12.0%
R 2
 
8.0%
B 2
 
8.0%
W 1
 
4.0%
M 1
 
4.0%
H 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 15
42.9%
. 14
40.0%
: 4
 
11.4%
/ 2
 
5.7%
Open Punctuation
ValueCountFrequency (%)
( 126
99.2%
[ 1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 126
99.2%
] 1
 
0.8%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2190
83.9%
Common 395
 
15.1%
Latin 25
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 237
 
10.8%
택 229
 
10.5%
시 69
 
3.2%
단 66
 
3.0%
실 66
 
3.0%
설 64
 
2.9%
사 56
 
2.6%
대 54
 
2.5%
아 50
 
2.3%
파 50
 
2.3%
Other values (133) 1249
57.0%
Common
ValueCountFrequency (%)
( 126
31.9%
) 126
31.9%
2 38
 
9.6%
1 25
 
6.3%
, 15
 
3.8%
. 14
 
3.5%
10
 
2.5%
9 7
 
1.8%
6 6
 
1.5%
0 6
 
1.5%
Other values (9) 22
 
5.6%
Latin
ValueCountFrequency (%)
E 7
28.0%
L 4
16.0%
O 4
16.0%
V 3
12.0%
R 2
 
8.0%
B 2
 
8.0%
W 1
 
4.0%
M 1
 
4.0%
H 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2190
83.9%
ASCII 420
 
16.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 237
 
10.8%
택 229
 
10.5%
시 69
 
3.2%
단 66
 
3.0%
실 66
 
3.0%
설 64
 
2.9%
사 56
 
2.6%
대 54
 
2.5%
아 50
 
2.3%
파 50
 
2.3%
Other values (133) 1249
57.0%
ASCII
ValueCountFrequency (%)
( 126
30.0%
) 126
30.0%
2 38
 
9.0%
1 25
 
6.0%
, 15
 
3.6%
. 14
 
3.3%
10
 
2.4%
9 7
 
1.7%
E 7
 
1.7%
6 6
 
1.4%
Other values (18) 46
 
11.0%

면적(㎡)
Real number (ℝ)

Distinct471
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.45971
Minimum0
Maximum2903.74
Zeros2
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:14.613071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.153
Q134.9
median84.43
Q3161.16
95-th percentile596.5371
Maximum2903.74
Range2903.74
Interquartile range (IQR)126.26

Descriptive statistics

Standard deviation287.25047
Coefficient of variation (CV)1.7051583
Kurtosis34.49651
Mean168.45971
Median Absolute Deviation (MAD)55.43
Skewness5.0295591
Sum84229.854
Variance82512.832
MonotonicityNot monotonic
2023-12-11T00:05:14.957353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.06 3
 
0.6%
3.0 3
 
0.6%
1.0 3
 
0.6%
99.0 3
 
0.6%
19.83 3
 
0.6%
44.05 2
 
0.4%
44.0 2
 
0.4%
9.9 2
 
0.4%
18.0 2
 
0.4%
0.0 2
 
0.4%
Other values (461) 475
95.0%
ValueCountFrequency (%)
0.0 2
0.4%
1.0 3
0.6%
1.2 1
 
0.2%
1.44 2
0.4%
2.0 2
0.4%
2.6 1
 
0.2%
3.0 3
0.6%
3.9 1
 
0.2%
4.0 1
 
0.2%
4.13 1
 
0.2%
ValueCountFrequency (%)
2903.74 1
0.2%
2584.4 1
0.2%
2145.64 1
0.2%
1709.61 1
0.2%
1682.43 1
0.2%
1547.6 1
0.2%
1378.56 1
0.2%
1074.14 1
0.2%
967.08 1
0.2%
954.89 1
0.2%

주_부속_구분_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
459 
1
 
41

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 459
91.8%
1 41
 
8.2%

Length

2023-12-11T00:05:15.232187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:15.420689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 459
91.8%
1 41
 
8.2%

주_부속_구분_코드_명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
주건축물
460 
부속건축물
 
39
<NA>
 
1

Length

Max length5
Median length4
Mean length4.078
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
주건축물 460
92.0%
부속건축물 39
 
7.8%
<NA> 1
 
0.2%

Length

2023-12-11T00:05:15.653084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:15.841914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주건축물 460
92.0%
부속건축물 39
 
7.8%
na 1
 
0.2%

면적_제외_여부
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
375 
0
122 
1
 
3

Length

Max length4
Median length4
Mean length3.25
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 375
75.0%
0 122
 
24.4%
1 3
 
0.6%

Length

2023-12-11T00:05:16.104455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:05:16.366082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 375
75.0%
0 122
 
24.4%
1 3
 
0.6%

생성_일자
Real number (ℝ)

Distinct247
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20124037
Minimum20090317
Maximum20160513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:05:16.612961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090317
5-th percentile20100105
Q120110420
median20120512
Q320140710
95-th percentile20151208
Maximum20160513
Range70196
Interquartile range (IQR)30290

Descriptive statistics

Standard deviation18466.515
Coefficient of variation (CV)0.00091763473
Kurtosis-1.0092163
Mean20124037
Median Absolute Deviation (MAD)10098
Skewness0.31810757
Sum1.0062018 × 1010
Variance3.4101218 × 108
MonotonicityNot monotonic
2023-12-11T00:05:17.089019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110420 29
 
5.8%
20111117 29
 
5.8%
20111123 23
 
4.6%
20110415 23
 
4.6%
20111124 19
 
3.8%
20111125 12
 
2.4%
20110418 10
 
2.0%
20100105 8
 
1.6%
20110417 7
 
1.4%
20160513 6
 
1.2%
Other values (237) 334
66.8%
ValueCountFrequency (%)
20090317 1
 
0.2%
20090318 3
0.6%
20090319 3
0.6%
20090320 3
0.6%
20090321 2
0.4%
20090809 1
 
0.2%
20090902 1
 
0.2%
20091015 1
 
0.2%
20091021 1
 
0.2%
20091030 1
 
0.2%
ValueCountFrequency (%)
20160513 6
1.2%
20160510 3
0.6%
20160506 1
 
0.2%
20160426 1
 
0.2%
20160423 1
 
0.2%
20160422 1
 
0.2%
20160420 1
 
0.2%
20160409 1
 
0.2%
20160407 1
 
0.2%
20160301 1
 
0.2%

Sample

관리_건축물대장_PK대지_위치도로명_대지_위치건물_명시군구_코드법정동_코드대지_구분_코드번지특수지_명블록로트새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번동_명칭층_구분_코드층_구분_코드_명층_번호층_번호_명구조_코드구조_코드_명기타_구조주_용도_코드주_용도_코드_명기타_용도면적(㎡)주_부속_구분_코드주_부속_구분_코드_명면적_제외_여부생성_일자
045740-1872경상북도 의성군 의성읍 도서리 100-1번지경상남도 김해시 서부로378번길 52-14<NA>442002562703730<NA><NA><NA><NA>134010<NA>313동20지상41층21벽돌구조목조19001사무소아파트41.630주건축물020141017
131710-9029전라북도 진안군 성수면 중길리 82번지<NA>주택2920010600057967<NA><NA><NA>27140314200910601080<NA>20지상52층21벽돌구조철근콘크리트조3001아파트창고:50.01,위험물취급소:23.0,근린생활시설:46.7350.01279.010부속건축물<NA>20110902
250130-18445대전광역시 유성구 덕명동 607번지부산광역시 남구 용소로 45<NA>42820106000609<NA><NA><NA>2826042685382591104510<NA>20지상21층21철근콘크리트구조철근콘크리트구조4001단독주택주택137.171주건축물<NA>20150523
328170-32588경기도 포천시 창수면 가양리 338-5번지경상남도 창원시 마산회원구 삼계8길 31<NA>412203402407184<NA><NA><NA>301104292206127010410B동20지상13층21철근콘크리트구조목조1003단독주택다세대주택235.60주건축물<NA>20151119
441410-8785충청북도 괴산군 청천면 지촌리 278-1번지경상북도 경주시 광산1길 11삼호아파트44790134000370<NA><NA><NA>112604118082101010<NA><NA><NA>20지상13층12철근콘크리트구조철근콘크리트구조1001아파트급배기덕트84.880주건축물<NA>20140731
541310-100172676경상남도 거제시 옥포동 1076번지전라남도 해남군 선창길 10-7서울아트빌라46880107000350<NA><NA><NA>114104136454129030226<NA>20지상22층12철근콘크리트구조경량철골조1001다세대주택사무실4.130주건축물020111117
643760-8619경상북도 울진군 후포면 삼율리 276-2번지경기도 안양시 만안구 장내로100번길 15<NA>302002532402525<NA><NA><NA>3017031660511320103000관리노인정20지상123층21벽돌구조라멘조1001여관단독주택(단독주택(주차장))(연면적제외)567.040주건축물<NA>20130928
742110-19298경기도 평택시 안중읍 용성리 80-9번지<NA><NA>1147010200015181<NA><NA><NA>461304646826101010717<NA>20옥탑2지121경량철골구조철근콘크리트구조4999단독주택공동주택(계단실,ELEV.)139.410주건축물020110417
811650-8951충청남도 금산군 금산읍 계진리 100-1번지경상북도 안동시 연곡큰들길 39-12혜정빌41360132000165951<NA><NA><NA>477204742290<NA>0250<NA>10지상41층21철근콘크리트구조철근콘크리트조1001다가구주택계단실(연면적제외)92.890주건축물<NA>20150513
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